Covid ICYMI

A history of liver transplant conveyed no increased risk of death from COVID-19 infections, according to data from a multicenter cohort study of 151 transplant recipients who became infected.

Although current data suggest a possible increased risk of adverse outcomes if liver transplant patients develop COVID-19 infections, the effects remain unclear, wrote Gwilym J. Webb, PhD, of the University of Oxford (England) and colleagues.

In a study published in the Lancet Gastroenterology & Hepatology, the researchers identified adults from 18 countries who had laboratory-confirmed COVID-19 infections between March 25, 2020, and June 26, 2020. The average age of the patients was 60 years, and 68% were men. A contemporaneous group of 627 consecutive adults with confirmed COVID-19 infections who had not undergone liver transplants served as controls.

Overall, 28 of the liver transplant patients and 167 of the controls died (19% vs. 27%; P = .046).

In addition, no differences appeared between infected transplant patients and infected controls in terms of hospitalization (82% vs. 76%) and the need for intensive care (31% vs. 30%), although the transplant patients were significantly more likely to require invasive ventilation (20% vs. 5%).

However, in a multivariate analysis, older age, serum creatinine concentration, and the presence of nonliver cancers were independently associated with increased risk of death in the liver transplant patients, with odds ratios of 1.06 for each year increase in age, 1.57 for each mg/dL increase in serum creatinine concentration, and 18.30 with the presence of a nonliver cancer.

The study findings were limited by several factors including the potential overreporting of severe COVID-19 cases because of reporting bias in the transplant registry, as well as the inability of the sample size to rule out mortality differences, the differences in comorbidities between the transplant patients and controls, and the impact of unmeasured confounding variables such as diet, physical activity, or fibrosis or cirrhosis in recipient grafts, the researchers noted. However, the results suggest that a history of liver transplantation does not increase the risk of death following COVID-19 infection, they wrote.

“Thus, traditional risk factors for adverse outcomes from COVID-19 should be preferentially considered when considering the risks and benefits of hospital attendance, immunosuppression, and social-distancing requirements for liver transplant recipients during the ongoing COVID-19 pandemic,” they concluded.

Focus on comorbidities and combined transplants

“Given that age and presence of comorbidities were significantly associated with risk of death in the cohorts of patients who had and had not undergone liver transplantation, greater emphasis should be placed on other coexisting comorbidities, rather than transplantation status per se, when risk-stratifying liver transplant recipients,” the researchers noted. “Indirectly, these findings suggest that liver transplantation, where indicated, should not be delayed during the COVID-19 pandemic, and that supportive care should not be limited for patients with existing liver transplants with COVID-19,” they suggested.

Given the high prevalence of COVID-19 in many countries, “it is inevitable that liver transplant patients will become infected,” said Wajahat Mehal, MD, of Yale University, New Haven, Conn., in an interview.

Going forward, “it is important to know the natural history of COVID in the immunocompromised population,” he emphasized.

One of the study limitations was the lack of data on how patients’ immunosuppression regimens were changed, if at all, while they were infected. “Since some other immunocompromised patients have had a higher rate of complications [in the wake of COVID-19 infections], I was pleasantly surprised that liver transplant recipients did so well,” Dr. Mehal said.

Dr. Mehal noted that additional research is needed to promote safety in patients with liver disease in the context of COVID-19. “It would be important to evaluate combined transplants, particularly combined liver/kidney transplants,” he said.

The study was supported by the European Association for the Study of the Liver, the National Institutes of Health, and the United Kingdom National Institute for Health Research. Lead author Dr. Webb had no financial conflicts to disclose. One coauthor disclosed unrelated fees from AbbVie and grants from the Fondation du Centre Hospitalier de l’Université de Montréal. Dr. Mehal had no financial conflicts to disclose.

SOURCE: Webb GJ et al. Lancet Gastroenterol Hepatol. 2020 Aug 28. doi: 10.1016/ S2468-1253(20)30271-5.

A history of liver transplant conveyed no increased risk of death from COVID-19 infections, according to data from a multicenter cohort study of 151 transplant recipients who became infected.

Although current data suggest a possible increased risk of adverse outcomes if liver transplant patients develop COVID-19 infections, the effects remain unclear, wrote Gwilym J. Webb, PhD, of the University of Oxford (England) and colleagues.

In a study published in the Lancet Gastroenterology & Hepatology, the researchers identified adults from 18 countries who had laboratory-confirmed COVID-19 infections between March 25, 2020, and June 26, 2020. The average age of the patients was 60 years, and 68% were men. A contemporaneous group of 627 consecutive adults with confirmed COVID-19 infections who had not undergone liver transplants served as controls.

Overall, 28 of the liver transplant patients and 167 of the controls died (19% vs. 27%; P = .046).

In addition, no differences appeared between infected transplant patients and infected controls in terms of hospitalization (82% vs. 76%) and the need for intensive care (31% vs. 30%), although the transplant patients were significantly more likely to require invasive ventilation (20% vs. 5%).

However, in a multivariate analysis, older age, serum creatinine concentration, and the presence of nonliver cancers were independently associated with increased risk of death in the liver transplant patients, with odds ratios of 1.06 for each year increase in age, 1.57 for each mg/dL increase in serum creatinine concentration, and 18.30 with the presence of a nonliver cancer.

The study findings were limited by several factors including the potential overreporting of severe COVID-19 cases because of reporting bias in the transplant registry, as well as the inability of the sample size to rule out mortality differences, the differences in comorbidities between the transplant patients and controls, and the impact of unmeasured confounding variables such as diet, physical activity, or fibrosis or cirrhosis in recipient grafts, the researchers noted. However, the results suggest that a history of liver transplantation does not increase the risk of death following COVID-19 infection, they wrote.

“Thus, traditional risk factors for adverse outcomes from COVID-19 should be preferentially considered when considering the risks and benefits of hospital attendance, immunosuppression, and social-distancing requirements for liver transplant recipients during the ongoing COVID-19 pandemic,” they concluded.

Focus on comorbidities and combined transplants

“Given that age and presence of comorbidities were significantly associated with risk of death in the cohorts of patients who had and had not undergone liver transplantation, greater emphasis should be placed on other coexisting comorbidities, rather than transplantation status per se, when risk-stratifying liver transplant recipients,” the researchers noted. “Indirectly, these findings suggest that liver transplantation, where indicated, should not be delayed during the COVID-19 pandemic, and that supportive care should not be limited for patients with existing liver transplants with COVID-19,” they suggested.

Given the high prevalence of COVID-19 in many countries, “it is inevitable that liver transplant patients will become infected,” said Wajahat Mehal, MD, of Yale University, New Haven, Conn., in an interview.

Going forward, “it is important to know the natural history of COVID in the immunocompromised population,” he emphasized.

One of the study limitations was the lack of data on how patients’ immunosuppression regimens were changed, if at all, while they were infected. “Since some other immunocompromised patients have had a higher rate of complications [in the wake of COVID-19 infections], I was pleasantly surprised that liver transplant recipients did so well,” Dr. Mehal said.

Dr. Mehal noted that additional research is needed to promote safety in patients with liver disease in the context of COVID-19. “It would be important to evaluate combined transplants, particularly combined liver/kidney transplants,” he said.

The study was supported by the European Association for the Study of the Liver, the National Institutes of Health, and the United Kingdom National Institute for Health Research. Lead author Dr. Webb had no financial conflicts to disclose. One coauthor disclosed unrelated fees from AbbVie and grants from the Fondation du Centre Hospitalier de l’Université de Montréal. Dr. Mehal had no financial conflicts to disclose.

SOURCE: Webb GJ et al. Lancet Gastroenterol Hepatol. 2020 Aug 28. doi: 10.1016/ S2468-1253(20)30271-5.

A history of liver transplant conveyed no increased risk of death from COVID-19 infections, according to data from a multicenter cohort study of 151 transplant recipients who became infected.

Although current data suggest a possible increased risk of adverse outcomes if liver transplant patients develop COVID-19 infections, the effects remain unclear, wrote Gwilym J. Webb, PhD, of the University of Oxford (England) and colleagues.

In a study published in the Lancet Gastroenterology & Hepatology, the researchers identified adults from 18 countries who had laboratory-confirmed COVID-19 infections between March 25, 2020, and June 26, 2020. The average age of the patients was 60 years, and 68% were men. A contemporaneous group of 627 consecutive adults with confirmed COVID-19 infections who had not undergone liver transplants served as controls.

Overall, 28 of the liver transplant patients and 167 of the controls died (19% vs. 27%; P = .046).

In addition, no differences appeared between infected transplant patients and infected controls in terms of hospitalization (82% vs. 76%) and the need for intensive care (31% vs. 30%), although the transplant patients were significantly more likely to require invasive ventilation (20% vs. 5%).

However, in a multivariate analysis, older age, serum creatinine concentration, and the presence of nonliver cancers were independently associated with increased risk of death in the liver transplant patients, with odds ratios of 1.06 for each year increase in age, 1.57 for each mg/dL increase in serum creatinine concentration, and 18.30 with the presence of a nonliver cancer.

The study findings were limited by several factors including the potential overreporting of severe COVID-19 cases because of reporting bias in the transplant registry, as well as the inability of the sample size to rule out mortality differences, the differences in comorbidities between the transplant patients and controls, and the impact of unmeasured confounding variables such as diet, physical activity, or fibrosis or cirrhosis in recipient grafts, the researchers noted. However, the results suggest that a history of liver transplantation does not increase the risk of death following COVID-19 infection, they wrote.

“Thus, traditional risk factors for adverse outcomes from COVID-19 should be preferentially considered when considering the risks and benefits of hospital attendance, immunosuppression, and social-distancing requirements for liver transplant recipients during the ongoing COVID-19 pandemic,” they concluded.

Focus on comorbidities and combined transplants

“Given that age and presence of comorbidities were significantly associated with risk of death in the cohorts of patients who had and had not undergone liver transplantation, greater emphasis should be placed on other coexisting comorbidities, rather than transplantation status per se, when risk-stratifying liver transplant recipients,” the researchers noted. “Indirectly, these findings suggest that liver transplantation, where indicated, should not be delayed during the COVID-19 pandemic, and that supportive care should not be limited for patients with existing liver transplants with COVID-19,” they suggested.

Given the high prevalence of COVID-19 in many countries, “it is inevitable that liver transplant patients will become infected,” said Wajahat Mehal, MD, of Yale University, New Haven, Conn., in an interview.

Going forward, “it is important to know the natural history of COVID in the immunocompromised population,” he emphasized.

One of the study limitations was the lack of data on how patients’ immunosuppression regimens were changed, if at all, while they were infected. “Since some other immunocompromised patients have had a higher rate of complications [in the wake of COVID-19 infections], I was pleasantly surprised that liver transplant recipients did so well,” Dr. Mehal said.

Dr. Mehal noted that additional research is needed to promote safety in patients with liver disease in the context of COVID-19. “It would be important to evaluate combined transplants, particularly combined liver/kidney transplants,” he said.

The study was supported by the European Association for the Study of the Liver, the National Institutes of Health, and the United Kingdom National Institute for Health Research. Lead author Dr. Webb had no financial conflicts to disclose. One coauthor disclosed unrelated fees from AbbVie and grants from the Fondation du Centre Hospitalier de l’Université de Montréal. Dr. Mehal had no financial conflicts to disclose.

SOURCE: Webb GJ et al. Lancet Gastroenterol Hepatol. 2020 Aug 28. doi: 10.1016/ S2468-1253(20)30271-5.

One of every 10 pregnant or recently pregnant women in hospital was diagnosed with COVID-19, yet up to three-quarters were asymptomatic at the time of diagnosis, according to a living systematic review from the PregCOV-19 Living Systematic Review Consortium.

dimarik/iStock/Getty Images

The study, published in BMJ, shows an increased risk of preterm delivery, as well as the need for invasive ventilation in these women, wrote John Allotey, PhD, of the University of Birmingham (England) and colleagues. The findings “will produce a strong evidence base for living guidelines on COVID-19 and pregnancy,” they noted.

The systematic review included 77 studies, one-third each from the United States and China, with the remaining studies from Belgium, Brazil, Denmark, France, Israel, Italy, Japan, Mexico, the Netherlands Portugal, Spain, and the United Kingdom.

The studies included women with COVID-19, of whom 13,118 were either pregnant or in the postpartum or postabortion period and 83,486 were of reproductive age but not pregnant. Some studies also included healthy pregnant women for comparison.

In the pregnant and recently pregnant women, the most common COVID-19 symptoms were fever (40%) and cough (39%), with lymphopenia (35%) and raised C reactive protein levels (49%) being the most common laboratory findings. Pregnant and recently pregnant women with COVID-19 were less likely to have fever (odds ratio, 0.43) and myalgia (OR, 0.48), compared with nonpregnant women of reproductive age with COVID-19, reported the authors.

The overall preterm and spontaneous preterm birth rates in the COVID-19–positive women were 17% and 6% respectively. Dr. Allotey and authors noted that “these preterm births could be medically indicated, as the overall rates of spontaneous preterm births in pregnant women with COVID-19 was broadly similar to those observed in the pre-pandemic period.” There were 18 stillbirths and 6 neonatal deaths in the COVID-19 cohort.

Overall, 73 (0.1%) of pregnant women with confirmed COVID-19 died from any cause, and severe COVID-19 infection was diagnosed in 13%. Maternal risk factors associated with severe infection included older age (OR, 1.78), high body mass index (OR, 2.3), chronic hypertension (OR, 2.0), and preexisting diabetes (OR, 2.51). Compared with nonpregnant women with COVID-19, pregnant or recently pregnant women with the infection were at increased risk of admission to intensive care (OR, 1.62) and needing invasive ventilation (OR, 1.88).

The report included studies published between December 1, 2019, and June 26, 2020, but the living systematic review will involve weekly search updates, with analysis performed every 2-4 weeks and reported through a dedicated website.
 

The value of a living meta-analysis

Asked to comment on the findings, Torri Metz, MD, a maternal-fetal medicine subspecialist at the University of Utah, Salt Lake City, expressed surprise at the 10% rate of infection in the pregnant or recently pregnant population. “This is higher than currently observed at many hospitals in the United States,” she said in an interview. “This may overestimate the actual risk as many of these studies were published early in the pandemic and did not universally sample women who were pregnant for SARS-CoV-2.”

She noted the value of a living meta-analysis in that it will be updated on a regular basis as new evidence emerges. “During this time of rapidly accumulating publications about COVID-19 infection, clinicians will find it useful to have a resource in which the available data can be combined in one source.”

And there are still some outstanding questions that new studies hopefully will shed light on, she added. “The authors found that many of the risk factors for severe disease, like diabetes, obesity and high blood pressure, in nonpregnant adults are the same in the pregnant population. What remains unknown is if pregnant patients with COVID-19 infection are at higher risk than those who are not pregnant. The authors note that this information is still limited and largely influenced in this published analysis by a CDC [Centers for Disease Control and Prevention] study in which the majority of patients had unknown pregnancy status. We also do not know if COVID-19 infection is associated with any birth defects since the majority of women with COVID-19 infection in the first trimester have not yet delivered.”

Malavika Prabhu, MD, an obstetetrician/gyneologist at Weill Cornell Medicine in New York City added that “this systematic review and meta analysis, which is a compilation of other studies done around the globe, confirms that pregnant women with preexisting medical conditions such as diabetes, hypertension, and obesity, are at increased risk of severe COVID-19 and that pregnant women with COVID-19 are at increased risk of invasive ventilation, compared to nonpregnant women with COVID-19, particularly if they have a preexisting medical condition.”

She said the preterm delivery rate of COVID-positive women is “challenging to interpret given that the total preterm birth rate potentially included many medically indicated preterm deliveries – which is to be expected – and there is no comparison group for spontaneous preterm birth presented”.

Other outstanding questions about COVID-19 pregnancies include whether they are associated with preeclampsia or smaller/growth restricted infants and why the cesarean delivery rate is high, she said. “But some of these questions are tough to answer with this data because it primarily reflects a COVID infection close to the delivery, not one that occurred several months prior to a delivery.”

Deborah Money, MD, professor of obstetrics and gynecology, medicine, and the school of population and public health, University of British Columbia, Vancouver, commented that “this is a group that have been doing ongoing living systematic reviews of the literature scanning for pregnancy outcomes. They post their information in real time on their website, so many of us in this area follow these postings as their methodology is robust and they work hard to only include high-quality literature and avoid duplication of cases in multiple papers. There has been a problem of re-reporting the same severe cases of COVID-19 in the literature.”

This “amplifies the importance of collecting Canadian-specific data to ensure that we understand if these kind of outcomes will also be found in Canada. The data presented in this paper represent outcomes from a broad range of countries with different methods of collecting information on pregnancy and highly variable prenatal care systems. This makes our pan-Canadian study of outcomes of COVID-19 for pregnant women and their infants, CANCOVID-Preg, even more important,” she said.

“Globally, we all must continue to monitor outcomes of COVID-19 in pregnancy to minimize adverse impact on women and their infants,” said Dr. Money, who was not involved in the study.

The study was partially funded by the World Health Organization and supported by Katie’s Team, a dedicated patient and public involvement group in Women’s Health. Dr. Metz is principal investigator for the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Maternal-Fetal Medicine Units Network COVID-19 study; the study is funded by NICHD and enrollment is ongoing. Dr. Prabhu had no relevant financial disclosures. Dr. Money received funding from the Canadian Institutes for Health Research and the Public Health Agency of Canada and received a small grant from theBC Women’s Foundation for COVID-19 in pregnancy research.

SOURCE: Allotey J et al. BMJ. 2020;370:m3320.

One of every 10 pregnant or recently pregnant women in hospital was diagnosed with COVID-19, yet up to three-quarters were asymptomatic at the time of diagnosis, according to a living systematic review from the PregCOV-19 Living Systematic Review Consortium.

dimarik/iStock/Getty Images

The study, published in BMJ, shows an increased risk of preterm delivery, as well as the need for invasive ventilation in these women, wrote John Allotey, PhD, of the University of Birmingham (England) and colleagues. The findings “will produce a strong evidence base for living guidelines on COVID-19 and pregnancy,” they noted.

The systematic review included 77 studies, one-third each from the United States and China, with the remaining studies from Belgium, Brazil, Denmark, France, Israel, Italy, Japan, Mexico, the Netherlands Portugal, Spain, and the United Kingdom.

The studies included women with COVID-19, of whom 13,118 were either pregnant or in the postpartum or postabortion period and 83,486 were of reproductive age but not pregnant. Some studies also included healthy pregnant women for comparison.

In the pregnant and recently pregnant women, the most common COVID-19 symptoms were fever (40%) and cough (39%), with lymphopenia (35%) and raised C reactive protein levels (49%) being the most common laboratory findings. Pregnant and recently pregnant women with COVID-19 were less likely to have fever (odds ratio, 0.43) and myalgia (OR, 0.48), compared with nonpregnant women of reproductive age with COVID-19, reported the authors.

The overall preterm and spontaneous preterm birth rates in the COVID-19–positive women were 17% and 6% respectively. Dr. Allotey and authors noted that “these preterm births could be medically indicated, as the overall rates of spontaneous preterm births in pregnant women with COVID-19 was broadly similar to those observed in the pre-pandemic period.” There were 18 stillbirths and 6 neonatal deaths in the COVID-19 cohort.

Overall, 73 (0.1%) of pregnant women with confirmed COVID-19 died from any cause, and severe COVID-19 infection was diagnosed in 13%. Maternal risk factors associated with severe infection included older age (OR, 1.78), high body mass index (OR, 2.3), chronic hypertension (OR, 2.0), and preexisting diabetes (OR, 2.51). Compared with nonpregnant women with COVID-19, pregnant or recently pregnant women with the infection were at increased risk of admission to intensive care (OR, 1.62) and needing invasive ventilation (OR, 1.88).

The report included studies published between December 1, 2019, and June 26, 2020, but the living systematic review will involve weekly search updates, with analysis performed every 2-4 weeks and reported through a dedicated website.
 

The value of a living meta-analysis

Asked to comment on the findings, Torri Metz, MD, a maternal-fetal medicine subspecialist at the University of Utah, Salt Lake City, expressed surprise at the 10% rate of infection in the pregnant or recently pregnant population. “This is higher than currently observed at many hospitals in the United States,” she said in an interview. “This may overestimate the actual risk as many of these studies were published early in the pandemic and did not universally sample women who were pregnant for SARS-CoV-2.”

She noted the value of a living meta-analysis in that it will be updated on a regular basis as new evidence emerges. “During this time of rapidly accumulating publications about COVID-19 infection, clinicians will find it useful to have a resource in which the available data can be combined in one source.”

And there are still some outstanding questions that new studies hopefully will shed light on, she added. “The authors found that many of the risk factors for severe disease, like diabetes, obesity and high blood pressure, in nonpregnant adults are the same in the pregnant population. What remains unknown is if pregnant patients with COVID-19 infection are at higher risk than those who are not pregnant. The authors note that this information is still limited and largely influenced in this published analysis by a CDC [Centers for Disease Control and Prevention] study in which the majority of patients had unknown pregnancy status. We also do not know if COVID-19 infection is associated with any birth defects since the majority of women with COVID-19 infection in the first trimester have not yet delivered.”

Malavika Prabhu, MD, an obstetetrician/gyneologist at Weill Cornell Medicine in New York City added that “this systematic review and meta analysis, which is a compilation of other studies done around the globe, confirms that pregnant women with preexisting medical conditions such as diabetes, hypertension, and obesity, are at increased risk of severe COVID-19 and that pregnant women with COVID-19 are at increased risk of invasive ventilation, compared to nonpregnant women with COVID-19, particularly if they have a preexisting medical condition.”

She said the preterm delivery rate of COVID-positive women is “challenging to interpret given that the total preterm birth rate potentially included many medically indicated preterm deliveries – which is to be expected – and there is no comparison group for spontaneous preterm birth presented”.

Other outstanding questions about COVID-19 pregnancies include whether they are associated with preeclampsia or smaller/growth restricted infants and why the cesarean delivery rate is high, she said. “But some of these questions are tough to answer with this data because it primarily reflects a COVID infection close to the delivery, not one that occurred several months prior to a delivery.”

Deborah Money, MD, professor of obstetrics and gynecology, medicine, and the school of population and public health, University of British Columbia, Vancouver, commented that “this is a group that have been doing ongoing living systematic reviews of the literature scanning for pregnancy outcomes. They post their information in real time on their website, so many of us in this area follow these postings as their methodology is robust and they work hard to only include high-quality literature and avoid duplication of cases in multiple papers. There has been a problem of re-reporting the same severe cases of COVID-19 in the literature.”

This “amplifies the importance of collecting Canadian-specific data to ensure that we understand if these kind of outcomes will also be found in Canada. The data presented in this paper represent outcomes from a broad range of countries with different methods of collecting information on pregnancy and highly variable prenatal care systems. This makes our pan-Canadian study of outcomes of COVID-19 for pregnant women and their infants, CANCOVID-Preg, even more important,” she said.

“Globally, we all must continue to monitor outcomes of COVID-19 in pregnancy to minimize adverse impact on women and their infants,” said Dr. Money, who was not involved in the study.

The study was partially funded by the World Health Organization and supported by Katie’s Team, a dedicated patient and public involvement group in Women’s Health. Dr. Metz is principal investigator for the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Maternal-Fetal Medicine Units Network COVID-19 study; the study is funded by NICHD and enrollment is ongoing. Dr. Prabhu had no relevant financial disclosures. Dr. Money received funding from the Canadian Institutes for Health Research and the Public Health Agency of Canada and received a small grant from theBC Women’s Foundation for COVID-19 in pregnancy research.

SOURCE: Allotey J et al. BMJ. 2020;370:m3320.

One of every 10 pregnant or recently pregnant women in hospital was diagnosed with COVID-19, yet up to three-quarters were asymptomatic at the time of diagnosis, according to a living systematic review from the PregCOV-19 Living Systematic Review Consortium.

dimarik/iStock/Getty Images

The study, published in BMJ, shows an increased risk of preterm delivery, as well as the need for invasive ventilation in these women, wrote John Allotey, PhD, of the University of Birmingham (England) and colleagues. The findings “will produce a strong evidence base for living guidelines on COVID-19 and pregnancy,” they noted.

The systematic review included 77 studies, one-third each from the United States and China, with the remaining studies from Belgium, Brazil, Denmark, France, Israel, Italy, Japan, Mexico, the Netherlands Portugal, Spain, and the United Kingdom.

The studies included women with COVID-19, of whom 13,118 were either pregnant or in the postpartum or postabortion period and 83,486 were of reproductive age but not pregnant. Some studies also included healthy pregnant women for comparison.

In the pregnant and recently pregnant women, the most common COVID-19 symptoms were fever (40%) and cough (39%), with lymphopenia (35%) and raised C reactive protein levels (49%) being the most common laboratory findings. Pregnant and recently pregnant women with COVID-19 were less likely to have fever (odds ratio, 0.43) and myalgia (OR, 0.48), compared with nonpregnant women of reproductive age with COVID-19, reported the authors.

The overall preterm and spontaneous preterm birth rates in the COVID-19–positive women were 17% and 6% respectively. Dr. Allotey and authors noted that “these preterm births could be medically indicated, as the overall rates of spontaneous preterm births in pregnant women with COVID-19 was broadly similar to those observed in the pre-pandemic period.” There were 18 stillbirths and 6 neonatal deaths in the COVID-19 cohort.

Overall, 73 (0.1%) of pregnant women with confirmed COVID-19 died from any cause, and severe COVID-19 infection was diagnosed in 13%. Maternal risk factors associated with severe infection included older age (OR, 1.78), high body mass index (OR, 2.3), chronic hypertension (OR, 2.0), and preexisting diabetes (OR, 2.51). Compared with nonpregnant women with COVID-19, pregnant or recently pregnant women with the infection were at increased risk of admission to intensive care (OR, 1.62) and needing invasive ventilation (OR, 1.88).

The report included studies published between December 1, 2019, and June 26, 2020, but the living systematic review will involve weekly search updates, with analysis performed every 2-4 weeks and reported through a dedicated website.
 

The value of a living meta-analysis

Asked to comment on the findings, Torri Metz, MD, a maternal-fetal medicine subspecialist at the University of Utah, Salt Lake City, expressed surprise at the 10% rate of infection in the pregnant or recently pregnant population. “This is higher than currently observed at many hospitals in the United States,” she said in an interview. “This may overestimate the actual risk as many of these studies were published early in the pandemic and did not universally sample women who were pregnant for SARS-CoV-2.”

She noted the value of a living meta-analysis in that it will be updated on a regular basis as new evidence emerges. “During this time of rapidly accumulating publications about COVID-19 infection, clinicians will find it useful to have a resource in which the available data can be combined in one source.”

And there are still some outstanding questions that new studies hopefully will shed light on, she added. “The authors found that many of the risk factors for severe disease, like diabetes, obesity and high blood pressure, in nonpregnant adults are the same in the pregnant population. What remains unknown is if pregnant patients with COVID-19 infection are at higher risk than those who are not pregnant. The authors note that this information is still limited and largely influenced in this published analysis by a CDC [Centers for Disease Control and Prevention] study in which the majority of patients had unknown pregnancy status. We also do not know if COVID-19 infection is associated with any birth defects since the majority of women with COVID-19 infection in the first trimester have not yet delivered.”

Malavika Prabhu, MD, an obstetetrician/gyneologist at Weill Cornell Medicine in New York City added that “this systematic review and meta analysis, which is a compilation of other studies done around the globe, confirms that pregnant women with preexisting medical conditions such as diabetes, hypertension, and obesity, are at increased risk of severe COVID-19 and that pregnant women with COVID-19 are at increased risk of invasive ventilation, compared to nonpregnant women with COVID-19, particularly if they have a preexisting medical condition.”

She said the preterm delivery rate of COVID-positive women is “challenging to interpret given that the total preterm birth rate potentially included many medically indicated preterm deliveries – which is to be expected – and there is no comparison group for spontaneous preterm birth presented”.

Other outstanding questions about COVID-19 pregnancies include whether they are associated with preeclampsia or smaller/growth restricted infants and why the cesarean delivery rate is high, she said. “But some of these questions are tough to answer with this data because it primarily reflects a COVID infection close to the delivery, not one that occurred several months prior to a delivery.”

Deborah Money, MD, professor of obstetrics and gynecology, medicine, and the school of population and public health, University of British Columbia, Vancouver, commented that “this is a group that have been doing ongoing living systematic reviews of the literature scanning for pregnancy outcomes. They post their information in real time on their website, so many of us in this area follow these postings as their methodology is robust and they work hard to only include high-quality literature and avoid duplication of cases in multiple papers. There has been a problem of re-reporting the same severe cases of COVID-19 in the literature.”

This “amplifies the importance of collecting Canadian-specific data to ensure that we understand if these kind of outcomes will also be found in Canada. The data presented in this paper represent outcomes from a broad range of countries with different methods of collecting information on pregnancy and highly variable prenatal care systems. This makes our pan-Canadian study of outcomes of COVID-19 for pregnant women and their infants, CANCOVID-Preg, even more important,” she said.

“Globally, we all must continue to monitor outcomes of COVID-19 in pregnancy to minimize adverse impact on women and their infants,” said Dr. Money, who was not involved in the study.

The study was partially funded by the World Health Organization and supported by Katie’s Team, a dedicated patient and public involvement group in Women’s Health. Dr. Metz is principal investigator for the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Maternal-Fetal Medicine Units Network COVID-19 study; the study is funded by NICHD and enrollment is ongoing. Dr. Prabhu had no relevant financial disclosures. Dr. Money received funding from the Canadian Institutes for Health Research and the Public Health Agency of Canada and received a small grant from theBC Women’s Foundation for COVID-19 in pregnancy research.

SOURCE: Allotey J et al. BMJ. 2020;370:m3320.

Like most family medicine residencies, our teaching nursing home was struck with a COVID-19 outbreak. Within 10 days, I was the sole physician responsible for 15 patients with varying degrees of illness, quarantined behind the fire doors of a wing of a Memory Support Unit. My daily work there over the course of the next month prompted me to reflect on some of the core principles of family medicine, and health care, that are vital to effective patient care during a pandemic. My experience provided the following reminders:

Work as a team. Gowned, gloved, and masked behind the fire doors, our world shrank to our patients and a 4-person team comprised of a nurse, 2 nursing assistants, and me. For the first time in the 10+ years I’ve worked at that facility, I actually asked for and memorized the names of everyone I was working with that day. Without an intercom or other telecommunications system, it became important for me to be able to call for my team members by name for immediate help. We had to depend on one another to make sure all patients were hydrated and fed, to avert falls whenever possible, to intervene early when dementia-­associated behaviors were escalating, and to recognize when patients were crashing.

I began asking for the names of everyone I was working with that day and I observed, first-hand, the great finesse that nurses display in their efforts to de-escalate disruptive behaviors.

We also had to depend on each other to ensure that our personal protective equipment remained properly placed, to combat the psychological sense of isolation that quarantine environments engender, and to placate a gnawing undercurrent of unease while working around a potentially deadly pathogen.

Develop clinical routines. Having listened to other medical directors whose nursing homes were affected by the pandemic earlier than we were, and hearing about potentially avoidable complications, we developed clinical routines. This began with identifying any patients with diabetes whose poor appetites while acutely ill could send them into hypoglycemia. We devised a daily clinical report sheet that included vital signs, date of positive COVID-19 test, global clinical status, and advance directives. Unlike the usual mode of working almost in parallel, I began my workday with a “sign-out” from the nurse, then started examining each patient.

Under the strain of this unusual environment and novel circumstances, we communicated more and more often. This allowed us to quickly recognize and communicate emerging changes in the clinical status of a patient by sharing our observations of subtle, nonspecific “sub-threshold” indicators.

Clarify the goals of care. Since most of the patients in the COVID-19 unit were under the long-term care of other attending physicians, it was important for me to understand the wishes of the patient or surrogate decision maker, should life-threatening complications occur. While all affected patients were long-term residents of a memory support unit, some had full-code advance directives. I quickly realized that what was first necessary was to develop rapport and trust with the families who didn’t know me, then discuss goals of care, and finally assure that the advance directives were in congruence with their stated goals. What helped families gain trust in me was knowing that I was seeing their loved one daily, that I was committed to helping the patient survive this infection, and that I was willing to come back to the facility if a crisis occurred—even at night, if necessary.

Appreciate the daily work of team members. One of my greatest worries was dehydration. When elders were acutely ill and eating and drinking poorly, I would assist with feeding and offering liquids. I quickly came to appreciate how complex and subtle this seemingly mundane task can be. Learning the proper pace and portion size, even choosing the right conversation topic and tone, could make the difference between a patient “shutting down” and refusing all nourishment and successfully drinking a 360-cc cup of a high-nutrient shake.

Continue to: In the disrupted routines...

In the disrupted routines and altered physical environments of the COVID-19 unit, the psychological and behavioral complications of dementia intensified for some patients. I observed first-hand the great patience, kindness, and finesse that nurses and nursing assistants display in their efforts to de-escalate and prevent disruptive behaviors.

Empathize with (and appreciate) families. Families tearfully reminded me that they had been suffering from the absence of contact with their loved ones for months; COVID-19 added to that trauma for many of them. They talked about the missed graduations, birthdays, and other precious times together that were lost because of the quarantine.

Families also prevented me from making mistakes. When I ordered nitrofurantoin for a patient with a urinary tract infection, her son called me and respectfully requested I “just check and make sure” it would not cause a problem, given her G6PD deficiency. He prevented me from prescribing an antibiotic contraindicated in that condition.

Bring forward the lessons learned. The COVID-19 outbreak has passed through our nursing home—at least for now. I perceive a subtle shift in how we continue to interact with one another. Behind the masks, we make a little more eye contact; we more often address each other by name; and we acknowledge a greater mutual respect.

The shared experience of COVID-19 has brought us all a little closer together, and in the end, our patients have benefitted.

Like most family medicine residencies, our teaching nursing home was struck with a COVID-19 outbreak. Within 10 days, I was the sole physician responsible for 15 patients with varying degrees of illness, quarantined behind the fire doors of a wing of a Memory Support Unit. My daily work there over the course of the next month prompted me to reflect on some of the core principles of family medicine, and health care, that are vital to effective patient care during a pandemic. My experience provided the following reminders:

Work as a team. Gowned, gloved, and masked behind the fire doors, our world shrank to our patients and a 4-person team comprised of a nurse, 2 nursing assistants, and me. For the first time in the 10+ years I’ve worked at that facility, I actually asked for and memorized the names of everyone I was working with that day. Without an intercom or other telecommunications system, it became important for me to be able to call for my team members by name for immediate help. We had to depend on one another to make sure all patients were hydrated and fed, to avert falls whenever possible, to intervene early when dementia-­associated behaviors were escalating, and to recognize when patients were crashing.

I began asking for the names of everyone I was working with that day and I observed, first-hand, the great finesse that nurses display in their efforts to de-escalate disruptive behaviors.

We also had to depend on each other to ensure that our personal protective equipment remained properly placed, to combat the psychological sense of isolation that quarantine environments engender, and to placate a gnawing undercurrent of unease while working around a potentially deadly pathogen.

Develop clinical routines. Having listened to other medical directors whose nursing homes were affected by the pandemic earlier than we were, and hearing about potentially avoidable complications, we developed clinical routines. This began with identifying any patients with diabetes whose poor appetites while acutely ill could send them into hypoglycemia. We devised a daily clinical report sheet that included vital signs, date of positive COVID-19 test, global clinical status, and advance directives. Unlike the usual mode of working almost in parallel, I began my workday with a “sign-out” from the nurse, then started examining each patient.

Under the strain of this unusual environment and novel circumstances, we communicated more and more often. This allowed us to quickly recognize and communicate emerging changes in the clinical status of a patient by sharing our observations of subtle, nonspecific “sub-threshold” indicators.

Clarify the goals of care. Since most of the patients in the COVID-19 unit were under the long-term care of other attending physicians, it was important for me to understand the wishes of the patient or surrogate decision maker, should life-threatening complications occur. While all affected patients were long-term residents of a memory support unit, some had full-code advance directives. I quickly realized that what was first necessary was to develop rapport and trust with the families who didn’t know me, then discuss goals of care, and finally assure that the advance directives were in congruence with their stated goals. What helped families gain trust in me was knowing that I was seeing their loved one daily, that I was committed to helping the patient survive this infection, and that I was willing to come back to the facility if a crisis occurred—even at night, if necessary.

Appreciate the daily work of team members. One of my greatest worries was dehydration. When elders were acutely ill and eating and drinking poorly, I would assist with feeding and offering liquids. I quickly came to appreciate how complex and subtle this seemingly mundane task can be. Learning the proper pace and portion size, even choosing the right conversation topic and tone, could make the difference between a patient “shutting down” and refusing all nourishment and successfully drinking a 360-cc cup of a high-nutrient shake.

Continue to: In the disrupted routines...

In the disrupted routines and altered physical environments of the COVID-19 unit, the psychological and behavioral complications of dementia intensified for some patients. I observed first-hand the great patience, kindness, and finesse that nurses and nursing assistants display in their efforts to de-escalate and prevent disruptive behaviors.

Empathize with (and appreciate) families. Families tearfully reminded me that they had been suffering from the absence of contact with their loved ones for months; COVID-19 added to that trauma for many of them. They talked about the missed graduations, birthdays, and other precious times together that were lost because of the quarantine.

Families also prevented me from making mistakes. When I ordered nitrofurantoin for a patient with a urinary tract infection, her son called me and respectfully requested I “just check and make sure” it would not cause a problem, given her G6PD deficiency. He prevented me from prescribing an antibiotic contraindicated in that condition.

Bring forward the lessons learned. The COVID-19 outbreak has passed through our nursing home—at least for now. I perceive a subtle shift in how we continue to interact with one another. Behind the masks, we make a little more eye contact; we more often address each other by name; and we acknowledge a greater mutual respect.

The shared experience of COVID-19 has brought us all a little closer together, and in the end, our patients have benefitted.

Like most family medicine residencies, our teaching nursing home was struck with a COVID-19 outbreak. Within 10 days, I was the sole physician responsible for 15 patients with varying degrees of illness, quarantined behind the fire doors of a wing of a Memory Support Unit. My daily work there over the course of the next month prompted me to reflect on some of the core principles of family medicine, and health care, that are vital to effective patient care during a pandemic. My experience provided the following reminders:

Work as a team. Gowned, gloved, and masked behind the fire doors, our world shrank to our patients and a 4-person team comprised of a nurse, 2 nursing assistants, and me. For the first time in the 10+ years I’ve worked at that facility, I actually asked for and memorized the names of everyone I was working with that day. Without an intercom or other telecommunications system, it became important for me to be able to call for my team members by name for immediate help. We had to depend on one another to make sure all patients were hydrated and fed, to avert falls whenever possible, to intervene early when dementia-­associated behaviors were escalating, and to recognize when patients were crashing.

I began asking for the names of everyone I was working with that day and I observed, first-hand, the great finesse that nurses display in their efforts to de-escalate disruptive behaviors.

We also had to depend on each other to ensure that our personal protective equipment remained properly placed, to combat the psychological sense of isolation that quarantine environments engender, and to placate a gnawing undercurrent of unease while working around a potentially deadly pathogen.

Develop clinical routines. Having listened to other medical directors whose nursing homes were affected by the pandemic earlier than we were, and hearing about potentially avoidable complications, we developed clinical routines. This began with identifying any patients with diabetes whose poor appetites while acutely ill could send them into hypoglycemia. We devised a daily clinical report sheet that included vital signs, date of positive COVID-19 test, global clinical status, and advance directives. Unlike the usual mode of working almost in parallel, I began my workday with a “sign-out” from the nurse, then started examining each patient.

Under the strain of this unusual environment and novel circumstances, we communicated more and more often. This allowed us to quickly recognize and communicate emerging changes in the clinical status of a patient by sharing our observations of subtle, nonspecific “sub-threshold” indicators.

Clarify the goals of care. Since most of the patients in the COVID-19 unit were under the long-term care of other attending physicians, it was important for me to understand the wishes of the patient or surrogate decision maker, should life-threatening complications occur. While all affected patients were long-term residents of a memory support unit, some had full-code advance directives. I quickly realized that what was first necessary was to develop rapport and trust with the families who didn’t know me, then discuss goals of care, and finally assure that the advance directives were in congruence with their stated goals. What helped families gain trust in me was knowing that I was seeing their loved one daily, that I was committed to helping the patient survive this infection, and that I was willing to come back to the facility if a crisis occurred—even at night, if necessary.

Appreciate the daily work of team members. One of my greatest worries was dehydration. When elders were acutely ill and eating and drinking poorly, I would assist with feeding and offering liquids. I quickly came to appreciate how complex and subtle this seemingly mundane task can be. Learning the proper pace and portion size, even choosing the right conversation topic and tone, could make the difference between a patient “shutting down” and refusing all nourishment and successfully drinking a 360-cc cup of a high-nutrient shake.

Continue to: In the disrupted routines...

In the disrupted routines and altered physical environments of the COVID-19 unit, the psychological and behavioral complications of dementia intensified for some patients. I observed first-hand the great patience, kindness, and finesse that nurses and nursing assistants display in their efforts to de-escalate and prevent disruptive behaviors.

Empathize with (and appreciate) families. Families tearfully reminded me that they had been suffering from the absence of contact with their loved ones for months; COVID-19 added to that trauma for many of them. They talked about the missed graduations, birthdays, and other precious times together that were lost because of the quarantine.

Families also prevented me from making mistakes. When I ordered nitrofurantoin for a patient with a urinary tract infection, her son called me and respectfully requested I “just check and make sure” it would not cause a problem, given her G6PD deficiency. He prevented me from prescribing an antibiotic contraindicated in that condition.

Bring forward the lessons learned. The COVID-19 outbreak has passed through our nursing home—at least for now. I perceive a subtle shift in how we continue to interact with one another. Behind the masks, we make a little more eye contact; we more often address each other by name; and we acknowledge a greater mutual respect.

The shared experience of COVID-19 has brought us all a little closer together, and in the end, our patients have benefitted.

The novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARSCoV- 2), which causes the respiratory disease coronavirus disease-19 (COVID- 19), was first identified as a cluster of cases of pneumonia in Wuhan, Hubei Province of China on December 31, 2019.1 Within a month, the disease had spread significantly, leading the World Health Organization (WHO) to designate COVID-19 a public health emergency of international concern. On March 11, 2020, the WHO declared COVID-19 a global pandemic.² As of August 18, 2020, the virus has infected > 21 million people, with > 750,000 deaths worldwide.3 The spread of COVID-19 has had a dramatic impact on social, economic, and health care issues throughout the world, which has been discussed elsewhere.⁴

Prior to the this century, members of the coronavirus family had minimal impact on human health.5 However, in the past 20 years, outbreaks have highlighted an emerging importance of coronaviruses in morbidity and mortality on a global scale. Although less prevalent than COVID-19, severe acute respiratory syndrome (SARS) in 2002 to 2003 and Middle East respiratory syndrome (MERS) in 2012 likely had higher mortality rates than the current pandemic.⁵ Based on this recent history, it is reasonable to assume that we will continue to see novel diseases with similar significant health and societal implications. The challenges presented to health care providers (HCPs) by such novel viral pathogens are numerous, including methods for rapid diagnosis, prevention, and treatment. In the current study, we focus on diagnosis issues, which were evident with COVID-19 with the time required to develop rapid and effective diagnostic modalities.

We have previously reported the utility of using artificial intelligence (AI) in the histopathologic diagnosis of cancer.^6-8 AI was first described in 1956 and involves the field of computer science in which machines are trained to learn from experience.⁹ Machine learning (ML) is a subset of AI and is achieved by using mathematic models to compute sample datasets.¹⁰ Current ML employs deep learning with neural network algorithms, which can recognize patterns and achieve complex computational tasks often far quicker and with increased precision than can humans.^11-13 In addition to applications in pathology, ML algorithms have both prognostic and diagnostic applications in multiple medical specialties, such as radiology, dermatology, ophthalmology, and cardiology.6 It is predicted that AI will impact almost every aspect of health care in the future.¹⁴

In this article, we examine the potential for AI to diagnose patients with COVID-19 pneumonia using chest radiographs (CXR) alone. This is done using Microsoft CustomVision (www.customvision.ai), a readily available, automated ML platform. Employing AI to both screen and diagnose emerging health emergencies such as COVID-19 has the potential to dramatically change how we approach medical care in the future. In addition, we describe the creation of a publicly available website (interknowlogy-covid-19 .azurewebsites.net) that could augment COVID-19 pneumonia CXR diagnosis.

Methods

For the training dataset, 103 CXR images of COVID-19 were downloaded from GitHub covid-chest-xray dataset^.15 Five hundred images of non-COVID-19 pneumonia and 500 images of the normal lung were downloaded from the Kaggle RSNA Pneumonia Detection Challenge dataset.¹⁶ To balance the dataset, we expanded the COVID-19 dataset to 500 images by slight rotation (probability = 1, max rotation = 5) and zooming (probability = 0.5, percentage area = 0.9) of the original images using the Augmentor Python package.¹⁷

Validation Dataset

For the validation dataset 30 random CXR images were obtained from the US Department of Veterans Affairs (VA) PACS (picture archiving and communication system). This dataset included 10 CXR images from hospitalized patients with COVID-19, 10 CXR pneumonia images from patients without COVID-19, and 10 normal CXRs. COVID-19 diagnoses were confirmed with a positive test result from the Xpert Xpress SARS-CoV-2 polymerase chain reaction (PCR) platform.¹⁸

Microsoft Custom

Vision Microsoft CustomVision is an automated image classification and object detection system that is a part of Microsoft Azure Cognitive Services (azure.microsoft.com). It has a pay-as-you-go model with fees depending on the computing needs and usage. It offers a free trial to users for 2 initial projects. The service is online with an easy-to-follow graphical user interface. No coding skills are necessary.

We created a new classification project in CustomVision and chose a compact general domain for small size and easy export to TensorFlow. js model format. TensorFlow.js is a JavaScript library that enables dynamic download and execution of ML models. After the project was created, we proceeded to upload our image dataset. Each class was uploaded separately and tagged with the appropriate label (covid pneumonia, non-covid pneumonia, or normal lung). The system rejected 16 COVID-19 images as duplicates. The final CustomVision training dataset consisted of 484 images of COVID-19 pneumonia, 500 images of non-COVID-19 pneumonia, and 500 images of normal lungs. Once uploaded, CustomVision self-trains using the dataset upon initiating the program (Figure 1).

Website Creation

CustomVision was used to train the model. It can be used to execute the model continuously, or the model can be compacted and decoupled from CustomVision. In this case, the model was compacted and decoupled for use in an online application. An Angular online application was created with TensorFlow.js. Within a user’s web browser, the model is executed when an image of a CXR is submitted. Confidence values for each classification are returned. In this design, after the initial webpage and model is downloaded, the webpage no longer needs to access any server components and performs all operations in the browser. Although the solution works well on mobile phone browsers and in low bandwidth situations, the quality of predictions may depend on the browser and device used. At no time does an image get submitted to the cloud.

Result

Overall, our trained model showed 92.9% precision and recall. Precision and recall results for each label were 98.9% and 94.8%, respectively for COVID-19 pneumonia; 91.8% and 89%, respectively, for non- COVID-19 pneumonia; and 88.8% and 95%, respectively, for normal lung (Figure 2). Next, we proceeded to validate the training model on the VA data by making individual predictions on 30 images from the VA dataset. Our model performed well with 100% sensitivity (recall), 95% specificity, 97% accuracy, 91% positive predictive value (precision), and 100% negative predictive value (Table).

Discussion

We successfully demonstrated the potential of using AI algorithms in assessing CXRs for COVID-19. We first trained the CustomVision automated image classification and object detection system to differentiate cases of COVID-19 from pneumonia from other etiologies as well as normal lung CXRs. We then tested our model against known patients from the James A. Haley Veterans’ Hospital in Tampa, Florida. The program achieved 100% sensitivity (recall), 95% specificity, 97% accuracy, 91% positive predictive value (precision), and 100% negative predictive value in differentiating the 3 scenarios. Using the trained ML model, we proceeded to create a website that could augment COVID-19 CXR diagnosis.¹⁹ The website works on mobile as well as desktop platforms. A health care provider can take a CXR photo with a mobile phone or upload the image file. The ML algorithm would provide the probability of COVID-19 pneumonia, non-COVID-19 pneumonia, or normal lung diagnosis (Figure 3).

Emerging diseases such as COVID-19 present numerous challenges to HCPs, governments, and businesses, as well as to individual members of society. As evidenced with COVID-19, the time from first recognition of an emerging pathogen to the development of methods for reliable diagnosis and treatment can be months, even with a concerted international effort. The gold standard for diagnosis of COVID-19 is by reverse transcriptase PCR (RT-PCR) technologies; however, early RT-PCR testing produced less than optimal results.^20-22 Even after the development of reliable tests for detection, making test kits readily available to health care providers on an adequate scale presents an additional challenge as evident with COVID-19.

Use of X-ray vs Computed Tomography

The lack of availability of diagnostic RTPCR with COVID-19 initially placed increased reliability on presumptive diagnoses via imaging in some situations.²³ Most of the literature evaluating radiographs of patients with COVID-19 focuses on chest computed tomography (CT) findings, with initial results suggesting CT was more accurate than early RT-PCR methodologies.21,22,24 The Radiological Society of North America Expert consensus statement on chest CT for COVID-19 states that CT findings can even precede positivity on RT-PCR in some cases.²² However, currently it does not recommend the use of CT scanning as a screening tool. Furthermore, the actual sensitivity and specificity of CT interpretation by radiologists for COVID-19 are unknown.²²

Characteristic CT findings include ground-glass opacities (GGOs) and consolidation most commonly in the lung periphery, though a diffuse distribution was found in a minority of patients.^21,23,25-27 Lomoro and colleagues recently summarized the CT findings from several reports that described abnormalities as most often bilateral and peripheral, subpleural, and affecting the lower lobes.26 Not surprisingly, CT appears more sensitive at detecting changes with COVID-19 than does CXR, with reports that a minority of patients exhibited CT changes before changes were visible on CXR.^23,26

We focused our study on the potential of AI in the examination of CXRs in patients with COVID-19, as there are several limitations to the routine use of CT scans with conditions such as COVID-19. Aside from the more considerable time required to obtain CTs, there are issues with contamination of CT suites, sometimes requiring a dedicated COVID-19 CT scanner.^23,28 The time constraints of decontamination or limited utilization of CT suites can delay or disrupt services for patients with and without COVID-19. Because of these factors, CXR may be a better resource to minimize the risk of infection to other patients. Also, accurate assessment of abnormalities on CXR for COVID-19 may identify patients in whom the CXR was performed for other purposes.²³ CXR is more readily available than CT, especially in more remote or underdeveloped areas.²⁸ Finally, as with CT, CXR abnormalities are reported to have appeared before RT-PCR tests became positive for a minority of patients.²³

CXR findings described in patients with COVID-19 are similar to those of CT and include GGOs, consolidation, and hazy increased opacities.^{23,25,26,28,29} Like CT, the majority of patients who received CXR demonstrated greater involvement in the lower zones and peripherally.^{23,25,26,28,29} Most patients showed bilateral involvement. However, while these findings are common in patients with COVID-19, they are not specific and can be seen in other conditions, such as other viral pneumonia, bacterial pneumonia, injury from drug toxicity, inhalation injury, connective tissue disease, and idiopathic conditions.

Application of AI for COVID-19

Applications of AI in interpreting radiographs of various types are numerous, and extensive literature has been written on the topic.³⁰ Using deep learning algorithms, AI has multiple possible roles to augment traditional radiograph interpretation. These include the potential for screening, triaging, and increasing the speed to render diagnoses. It also can provide a rapid “second opinion” to the radiologist to support the final interpretation. In areas with critical shortages of radiologists, AI potentially can be used to render the definitive diagnosis. In COVID- 19, imaging studies have been shown to correlate with disease severity and mortality, and AI could assist in monitoring the course of the disease as it progresses and potentially identify patients at greatest risk.²⁷ Furthermore, early results from PCR have been considered suboptimal, and it is known that patients with COVID-19 can test negative initially even by reliable testing methodologies. As AI technology progresses, interpretation can detect and guide triage and treatment of patients with high suspicions of COVID-19 but negative initial PCR results, or in situations where test availability is limited or results are delayed. There are numerous potential benefits should a rapid diagnostic test as simple as a CXR be able to reliably impact containment and prevention of the spread of contagions such as COVID- 19 early in its course.

Few studies have assessed using AI in the radiologic diagnosis of COVID-19, most of which use CT scanning. Bai and colleagues demonstrated increased accuracy, sensitivity, and specificity in distinguishing chest CTs of COVID-19 patients from other types of pneumonia.^21,31 A separate study demonstrated the utility of using AI to differentiate COVID-19 from community-acquired pneumonia with CT.32 However, the effective utility of AI for CXR interpretation also has been demonstrated.^14,33 Implementation of convolutional neural network layers has allowed for reliable differentiation of viral and bacterial pneumonia with CXR imaging.³⁴ Evidence suggests that there is great potential in the application of AI in the interpretation of radiographs of all types.

Finally, we have developed a publicly available website based on our studies.¹⁸ This website is for research use only as it is based on data from our preliminary investigation. To appear within the website, images must have protected health information removed before uploading. The information on the website, including text, graphics, images, or other material, is for research and may not be appropriate for all circumstances. The website does not provide medical, professional, or licensed advice and is not a substitute for consultation with a HCP. Medical advice should be sought from a qualified HCP for any questions, and the website should not be used for medical diagnosis or treatment.

Limitations

In our preliminary study, we have demonstrated the potential impact AI can have in multiple aspects of patient care for emerging pathogens such as COVID-19 using a test as readily available as a CXR. However, several limitations to this investigation should be mentioned. The study is retrospective in nature with limited sample size and with X-rays from patients with various stages of COVID-19 pneumonia. Also, cases of non-COVID-19 pneumonia are not stratified into different types or etiologies. We intend to demonstrate the potential of AI in differentiating COVID-19 pneumonia from non-COVID-19 pneumonia of any etiology, though future studies should address comparison of COVID-19 cases to more specific types of pneumonias, such as of bacterial or viral origin. Furthermore, the present study does not address any potential effects of additional radiographic findings from coexistent conditions, such as pulmonary edema as seen in congestive heart failure, pleural effusions (which can be seen with COVID-19 pneumonia, though rarely), interstitial lung disease, etc. Future studies are required to address these issues. Ultimately, prospective studies to assess AI-assisted radiographic interpretation in conditions such as COVID-19 are required to demonstrate the impact on diagnosis, treatment, outcome, and patient safety as these technologies are implemented.

Conclusions

We have used a readily available, commercial platform to demonstrate the potential of AI to assist in the successful diagnosis of COVID-19 pneumonia on CXR images. While this technology has numerous applications in radiology, we have focused on the potential impact on future world health crises such as COVID-19. The findings have implications for screening and triage, initial diagnosis, monitoring disease progression, and identifying patients at increased risk of morbidity and mortality. Based on the data, a website was created to demonstrate how such technologies could be shared and distributed to others to combat entities such as COVID-19 moving forward. Our study offers a small window into the potential for how AI will likely dramatically change the practice of medicine in the future.

The novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARSCoV- 2), which causes the respiratory disease coronavirus disease-19 (COVID- 19), was first identified as a cluster of cases of pneumonia in Wuhan, Hubei Province of China on December 31, 2019.1 Within a month, the disease had spread significantly, leading the World Health Organization (WHO) to designate COVID-19 a public health emergency of international concern. On March 11, 2020, the WHO declared COVID-19 a global pandemic.² As of August 18, 2020, the virus has infected > 21 million people, with > 750,000 deaths worldwide.3 The spread of COVID-19 has had a dramatic impact on social, economic, and health care issues throughout the world, which has been discussed elsewhere.⁴

Prior to the this century, members of the coronavirus family had minimal impact on human health.5 However, in the past 20 years, outbreaks have highlighted an emerging importance of coronaviruses in morbidity and mortality on a global scale. Although less prevalent than COVID-19, severe acute respiratory syndrome (SARS) in 2002 to 2003 and Middle East respiratory syndrome (MERS) in 2012 likely had higher mortality rates than the current pandemic.⁵ Based on this recent history, it is reasonable to assume that we will continue to see novel diseases with similar significant health and societal implications. The challenges presented to health care providers (HCPs) by such novel viral pathogens are numerous, including methods for rapid diagnosis, prevention, and treatment. In the current study, we focus on diagnosis issues, which were evident with COVID-19 with the time required to develop rapid and effective diagnostic modalities.

We have previously reported the utility of using artificial intelligence (AI) in the histopathologic diagnosis of cancer.^6-8 AI was first described in 1956 and involves the field of computer science in which machines are trained to learn from experience.⁹ Machine learning (ML) is a subset of AI and is achieved by using mathematic models to compute sample datasets.¹⁰ Current ML employs deep learning with neural network algorithms, which can recognize patterns and achieve complex computational tasks often far quicker and with increased precision than can humans.^11-13 In addition to applications in pathology, ML algorithms have both prognostic and diagnostic applications in multiple medical specialties, such as radiology, dermatology, ophthalmology, and cardiology.6 It is predicted that AI will impact almost every aspect of health care in the future.¹⁴

In this article, we examine the potential for AI to diagnose patients with COVID-19 pneumonia using chest radiographs (CXR) alone. This is done using Microsoft CustomVision (www.customvision.ai), a readily available, automated ML platform. Employing AI to both screen and diagnose emerging health emergencies such as COVID-19 has the potential to dramatically change how we approach medical care in the future. In addition, we describe the creation of a publicly available website (interknowlogy-covid-19 .azurewebsites.net) that could augment COVID-19 pneumonia CXR diagnosis.

Methods

For the training dataset, 103 CXR images of COVID-19 were downloaded from GitHub covid-chest-xray dataset^.15 Five hundred images of non-COVID-19 pneumonia and 500 images of the normal lung were downloaded from the Kaggle RSNA Pneumonia Detection Challenge dataset.¹⁶ To balance the dataset, we expanded the COVID-19 dataset to 500 images by slight rotation (probability = 1, max rotation = 5) and zooming (probability = 0.5, percentage area = 0.9) of the original images using the Augmentor Python package.¹⁷

Validation Dataset

For the validation dataset 30 random CXR images were obtained from the US Department of Veterans Affairs (VA) PACS (picture archiving and communication system). This dataset included 10 CXR images from hospitalized patients with COVID-19, 10 CXR pneumonia images from patients without COVID-19, and 10 normal CXRs. COVID-19 diagnoses were confirmed with a positive test result from the Xpert Xpress SARS-CoV-2 polymerase chain reaction (PCR) platform.¹⁸

Microsoft Custom

Vision Microsoft CustomVision is an automated image classification and object detection system that is a part of Microsoft Azure Cognitive Services (azure.microsoft.com). It has a pay-as-you-go model with fees depending on the computing needs and usage. It offers a free trial to users for 2 initial projects. The service is online with an easy-to-follow graphical user interface. No coding skills are necessary.

We created a new classification project in CustomVision and chose a compact general domain for small size and easy export to TensorFlow. js model format. TensorFlow.js is a JavaScript library that enables dynamic download and execution of ML models. After the project was created, we proceeded to upload our image dataset. Each class was uploaded separately and tagged with the appropriate label (covid pneumonia, non-covid pneumonia, or normal lung). The system rejected 16 COVID-19 images as duplicates. The final CustomVision training dataset consisted of 484 images of COVID-19 pneumonia, 500 images of non-COVID-19 pneumonia, and 500 images of normal lungs. Once uploaded, CustomVision self-trains using the dataset upon initiating the program (Figure 1).

Website Creation

CustomVision was used to train the model. It can be used to execute the model continuously, or the model can be compacted and decoupled from CustomVision. In this case, the model was compacted and decoupled for use in an online application. An Angular online application was created with TensorFlow.js. Within a user’s web browser, the model is executed when an image of a CXR is submitted. Confidence values for each classification are returned. In this design, after the initial webpage and model is downloaded, the webpage no longer needs to access any server components and performs all operations in the browser. Although the solution works well on mobile phone browsers and in low bandwidth situations, the quality of predictions may depend on the browser and device used. At no time does an image get submitted to the cloud.

Result

Overall, our trained model showed 92.9% precision and recall. Precision and recall results for each label were 98.9% and 94.8%, respectively for COVID-19 pneumonia; 91.8% and 89%, respectively, for non- COVID-19 pneumonia; and 88.8% and 95%, respectively, for normal lung (Figure 2). Next, we proceeded to validate the training model on the VA data by making individual predictions on 30 images from the VA dataset. Our model performed well with 100% sensitivity (recall), 95% specificity, 97% accuracy, 91% positive predictive value (precision), and 100% negative predictive value (Table).

Discussion

We successfully demonstrated the potential of using AI algorithms in assessing CXRs for COVID-19. We first trained the CustomVision automated image classification and object detection system to differentiate cases of COVID-19 from pneumonia from other etiologies as well as normal lung CXRs. We then tested our model against known patients from the James A. Haley Veterans’ Hospital in Tampa, Florida. The program achieved 100% sensitivity (recall), 95% specificity, 97% accuracy, 91% positive predictive value (precision), and 100% negative predictive value in differentiating the 3 scenarios. Using the trained ML model, we proceeded to create a website that could augment COVID-19 CXR diagnosis.¹⁹ The website works on mobile as well as desktop platforms. A health care provider can take a CXR photo with a mobile phone or upload the image file. The ML algorithm would provide the probability of COVID-19 pneumonia, non-COVID-19 pneumonia, or normal lung diagnosis (Figure 3).

Emerging diseases such as COVID-19 present numerous challenges to HCPs, governments, and businesses, as well as to individual members of society. As evidenced with COVID-19, the time from first recognition of an emerging pathogen to the development of methods for reliable diagnosis and treatment can be months, even with a concerted international effort. The gold standard for diagnosis of COVID-19 is by reverse transcriptase PCR (RT-PCR) technologies; however, early RT-PCR testing produced less than optimal results.^20-22 Even after the development of reliable tests for detection, making test kits readily available to health care providers on an adequate scale presents an additional challenge as evident with COVID-19.

Use of X-ray vs Computed Tomography

The lack of availability of diagnostic RTPCR with COVID-19 initially placed increased reliability on presumptive diagnoses via imaging in some situations.²³ Most of the literature evaluating radiographs of patients with COVID-19 focuses on chest computed tomography (CT) findings, with initial results suggesting CT was more accurate than early RT-PCR methodologies.21,22,24 The Radiological Society of North America Expert consensus statement on chest CT for COVID-19 states that CT findings can even precede positivity on RT-PCR in some cases.²² However, currently it does not recommend the use of CT scanning as a screening tool. Furthermore, the actual sensitivity and specificity of CT interpretation by radiologists for COVID-19 are unknown.²²

Characteristic CT findings include ground-glass opacities (GGOs) and consolidation most commonly in the lung periphery, though a diffuse distribution was found in a minority of patients.^21,23,25-27 Lomoro and colleagues recently summarized the CT findings from several reports that described abnormalities as most often bilateral and peripheral, subpleural, and affecting the lower lobes.26 Not surprisingly, CT appears more sensitive at detecting changes with COVID-19 than does CXR, with reports that a minority of patients exhibited CT changes before changes were visible on CXR.^23,26

We focused our study on the potential of AI in the examination of CXRs in patients with COVID-19, as there are several limitations to the routine use of CT scans with conditions such as COVID-19. Aside from the more considerable time required to obtain CTs, there are issues with contamination of CT suites, sometimes requiring a dedicated COVID-19 CT scanner.^23,28 The time constraints of decontamination or limited utilization of CT suites can delay or disrupt services for patients with and without COVID-19. Because of these factors, CXR may be a better resource to minimize the risk of infection to other patients. Also, accurate assessment of abnormalities on CXR for COVID-19 may identify patients in whom the CXR was performed for other purposes.²³ CXR is more readily available than CT, especially in more remote or underdeveloped areas.²⁸ Finally, as with CT, CXR abnormalities are reported to have appeared before RT-PCR tests became positive for a minority of patients.²³

CXR findings described in patients with COVID-19 are similar to those of CT and include GGOs, consolidation, and hazy increased opacities.^{23,25,26,28,29} Like CT, the majority of patients who received CXR demonstrated greater involvement in the lower zones and peripherally.^{23,25,26,28,29} Most patients showed bilateral involvement. However, while these findings are common in patients with COVID-19, they are not specific and can be seen in other conditions, such as other viral pneumonia, bacterial pneumonia, injury from drug toxicity, inhalation injury, connective tissue disease, and idiopathic conditions.

Application of AI for COVID-19

Applications of AI in interpreting radiographs of various types are numerous, and extensive literature has been written on the topic.³⁰ Using deep learning algorithms, AI has multiple possible roles to augment traditional radiograph interpretation. These include the potential for screening, triaging, and increasing the speed to render diagnoses. It also can provide a rapid “second opinion” to the radiologist to support the final interpretation. In areas with critical shortages of radiologists, AI potentially can be used to render the definitive diagnosis. In COVID- 19, imaging studies have been shown to correlate with disease severity and mortality, and AI could assist in monitoring the course of the disease as it progresses and potentially identify patients at greatest risk.²⁷ Furthermore, early results from PCR have been considered suboptimal, and it is known that patients with COVID-19 can test negative initially even by reliable testing methodologies. As AI technology progresses, interpretation can detect and guide triage and treatment of patients with high suspicions of COVID-19 but negative initial PCR results, or in situations where test availability is limited or results are delayed. There are numerous potential benefits should a rapid diagnostic test as simple as a CXR be able to reliably impact containment and prevention of the spread of contagions such as COVID- 19 early in its course.

Few studies have assessed using AI in the radiologic diagnosis of COVID-19, most of which use CT scanning. Bai and colleagues demonstrated increased accuracy, sensitivity, and specificity in distinguishing chest CTs of COVID-19 patients from other types of pneumonia.^21,31 A separate study demonstrated the utility of using AI to differentiate COVID-19 from community-acquired pneumonia with CT.32 However, the effective utility of AI for CXR interpretation also has been demonstrated.^14,33 Implementation of convolutional neural network layers has allowed for reliable differentiation of viral and bacterial pneumonia with CXR imaging.³⁴ Evidence suggests that there is great potential in the application of AI in the interpretation of radiographs of all types.

Finally, we have developed a publicly available website based on our studies.¹⁸ This website is for research use only as it is based on data from our preliminary investigation. To appear within the website, images must have protected health information removed before uploading. The information on the website, including text, graphics, images, or other material, is for research and may not be appropriate for all circumstances. The website does not provide medical, professional, or licensed advice and is not a substitute for consultation with a HCP. Medical advice should be sought from a qualified HCP for any questions, and the website should not be used for medical diagnosis or treatment.

Limitations

In our preliminary study, we have demonstrated the potential impact AI can have in multiple aspects of patient care for emerging pathogens such as COVID-19 using a test as readily available as a CXR. However, several limitations to this investigation should be mentioned. The study is retrospective in nature with limited sample size and with X-rays from patients with various stages of COVID-19 pneumonia. Also, cases of non-COVID-19 pneumonia are not stratified into different types or etiologies. We intend to demonstrate the potential of AI in differentiating COVID-19 pneumonia from non-COVID-19 pneumonia of any etiology, though future studies should address comparison of COVID-19 cases to more specific types of pneumonias, such as of bacterial or viral origin. Furthermore, the present study does not address any potential effects of additional radiographic findings from coexistent conditions, such as pulmonary edema as seen in congestive heart failure, pleural effusions (which can be seen with COVID-19 pneumonia, though rarely), interstitial lung disease, etc. Future studies are required to address these issues. Ultimately, prospective studies to assess AI-assisted radiographic interpretation in conditions such as COVID-19 are required to demonstrate the impact on diagnosis, treatment, outcome, and patient safety as these technologies are implemented.

Conclusions

We have used a readily available, commercial platform to demonstrate the potential of AI to assist in the successful diagnosis of COVID-19 pneumonia on CXR images. While this technology has numerous applications in radiology, we have focused on the potential impact on future world health crises such as COVID-19. The findings have implications for screening and triage, initial diagnosis, monitoring disease progression, and identifying patients at increased risk of morbidity and mortality. Based on the data, a website was created to demonstrate how such technologies could be shared and distributed to others to combat entities such as COVID-19 moving forward. Our study offers a small window into the potential for how AI will likely dramatically change the practice of medicine in the future.

The novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARSCoV- 2), which causes the respiratory disease coronavirus disease-19 (COVID- 19), was first identified as a cluster of cases of pneumonia in Wuhan, Hubei Province of China on December 31, 2019.1 Within a month, the disease had spread significantly, leading the World Health Organization (WHO) to designate COVID-19 a public health emergency of international concern. On March 11, 2020, the WHO declared COVID-19 a global pandemic.² As of August 18, 2020, the virus has infected > 21 million people, with > 750,000 deaths worldwide.3 The spread of COVID-19 has had a dramatic impact on social, economic, and health care issues throughout the world, which has been discussed elsewhere.⁴

Prior to the this century, members of the coronavirus family had minimal impact on human health.5 However, in the past 20 years, outbreaks have highlighted an emerging importance of coronaviruses in morbidity and mortality on a global scale. Although less prevalent than COVID-19, severe acute respiratory syndrome (SARS) in 2002 to 2003 and Middle East respiratory syndrome (MERS) in 2012 likely had higher mortality rates than the current pandemic.⁵ Based on this recent history, it is reasonable to assume that we will continue to see novel diseases with similar significant health and societal implications. The challenges presented to health care providers (HCPs) by such novel viral pathogens are numerous, including methods for rapid diagnosis, prevention, and treatment. In the current study, we focus on diagnosis issues, which were evident with COVID-19 with the time required to develop rapid and effective diagnostic modalities.

We have previously reported the utility of using artificial intelligence (AI) in the histopathologic diagnosis of cancer.^6-8 AI was first described in 1956 and involves the field of computer science in which machines are trained to learn from experience.⁹ Machine learning (ML) is a subset of AI and is achieved by using mathematic models to compute sample datasets.¹⁰ Current ML employs deep learning with neural network algorithms, which can recognize patterns and achieve complex computational tasks often far quicker and with increased precision than can humans.^11-13 In addition to applications in pathology, ML algorithms have both prognostic and diagnostic applications in multiple medical specialties, such as radiology, dermatology, ophthalmology, and cardiology.6 It is predicted that AI will impact almost every aspect of health care in the future.¹⁴

In this article, we examine the potential for AI to diagnose patients with COVID-19 pneumonia using chest radiographs (CXR) alone. This is done using Microsoft CustomVision (www.customvision.ai), a readily available, automated ML platform. Employing AI to both screen and diagnose emerging health emergencies such as COVID-19 has the potential to dramatically change how we approach medical care in the future. In addition, we describe the creation of a publicly available website (interknowlogy-covid-19 .azurewebsites.net) that could augment COVID-19 pneumonia CXR diagnosis.

Methods

For the training dataset, 103 CXR images of COVID-19 were downloaded from GitHub covid-chest-xray dataset^.15 Five hundred images of non-COVID-19 pneumonia and 500 images of the normal lung were downloaded from the Kaggle RSNA Pneumonia Detection Challenge dataset.¹⁶ To balance the dataset, we expanded the COVID-19 dataset to 500 images by slight rotation (probability = 1, max rotation = 5) and zooming (probability = 0.5, percentage area = 0.9) of the original images using the Augmentor Python package.¹⁷

Validation Dataset

For the validation dataset 30 random CXR images were obtained from the US Department of Veterans Affairs (VA) PACS (picture archiving and communication system). This dataset included 10 CXR images from hospitalized patients with COVID-19, 10 CXR pneumonia images from patients without COVID-19, and 10 normal CXRs. COVID-19 diagnoses were confirmed with a positive test result from the Xpert Xpress SARS-CoV-2 polymerase chain reaction (PCR) platform.¹⁸

Microsoft Custom

Vision Microsoft CustomVision is an automated image classification and object detection system that is a part of Microsoft Azure Cognitive Services (azure.microsoft.com). It has a pay-as-you-go model with fees depending on the computing needs and usage. It offers a free trial to users for 2 initial projects. The service is online with an easy-to-follow graphical user interface. No coding skills are necessary.

We created a new classification project in CustomVision and chose a compact general domain for small size and easy export to TensorFlow. js model format. TensorFlow.js is a JavaScript library that enables dynamic download and execution of ML models. After the project was created, we proceeded to upload our image dataset. Each class was uploaded separately and tagged with the appropriate label (covid pneumonia, non-covid pneumonia, or normal lung). The system rejected 16 COVID-19 images as duplicates. The final CustomVision training dataset consisted of 484 images of COVID-19 pneumonia, 500 images of non-COVID-19 pneumonia, and 500 images of normal lungs. Once uploaded, CustomVision self-trains using the dataset upon initiating the program (Figure 1).

Website Creation

CustomVision was used to train the model. It can be used to execute the model continuously, or the model can be compacted and decoupled from CustomVision. In this case, the model was compacted and decoupled for use in an online application. An Angular online application was created with TensorFlow.js. Within a user’s web browser, the model is executed when an image of a CXR is submitted. Confidence values for each classification are returned. In this design, after the initial webpage and model is downloaded, the webpage no longer needs to access any server components and performs all operations in the browser. Although the solution works well on mobile phone browsers and in low bandwidth situations, the quality of predictions may depend on the browser and device used. At no time does an image get submitted to the cloud.

Result

Overall, our trained model showed 92.9% precision and recall. Precision and recall results for each label were 98.9% and 94.8%, respectively for COVID-19 pneumonia; 91.8% and 89%, respectively, for non- COVID-19 pneumonia; and 88.8% and 95%, respectively, for normal lung (Figure 2). Next, we proceeded to validate the training model on the VA data by making individual predictions on 30 images from the VA dataset. Our model performed well with 100% sensitivity (recall), 95% specificity, 97% accuracy, 91% positive predictive value (precision), and 100% negative predictive value (Table).

Discussion

We successfully demonstrated the potential of using AI algorithms in assessing CXRs for COVID-19. We first trained the CustomVision automated image classification and object detection system to differentiate cases of COVID-19 from pneumonia from other etiologies as well as normal lung CXRs. We then tested our model against known patients from the James A. Haley Veterans’ Hospital in Tampa, Florida. The program achieved 100% sensitivity (recall), 95% specificity, 97% accuracy, 91% positive predictive value (precision), and 100% negative predictive value in differentiating the 3 scenarios. Using the trained ML model, we proceeded to create a website that could augment COVID-19 CXR diagnosis.¹⁹ The website works on mobile as well as desktop platforms. A health care provider can take a CXR photo with a mobile phone or upload the image file. The ML algorithm would provide the probability of COVID-19 pneumonia, non-COVID-19 pneumonia, or normal lung diagnosis (Figure 3).

Emerging diseases such as COVID-19 present numerous challenges to HCPs, governments, and businesses, as well as to individual members of society. As evidenced with COVID-19, the time from first recognition of an emerging pathogen to the development of methods for reliable diagnosis and treatment can be months, even with a concerted international effort. The gold standard for diagnosis of COVID-19 is by reverse transcriptase PCR (RT-PCR) technologies; however, early RT-PCR testing produced less than optimal results.^20-22 Even after the development of reliable tests for detection, making test kits readily available to health care providers on an adequate scale presents an additional challenge as evident with COVID-19.

Use of X-ray vs Computed Tomography

The lack of availability of diagnostic RTPCR with COVID-19 initially placed increased reliability on presumptive diagnoses via imaging in some situations.²³ Most of the literature evaluating radiographs of patients with COVID-19 focuses on chest computed tomography (CT) findings, with initial results suggesting CT was more accurate than early RT-PCR methodologies.21,22,24 The Radiological Society of North America Expert consensus statement on chest CT for COVID-19 states that CT findings can even precede positivity on RT-PCR in some cases.²² However, currently it does not recommend the use of CT scanning as a screening tool. Furthermore, the actual sensitivity and specificity of CT interpretation by radiologists for COVID-19 are unknown.²²

Characteristic CT findings include ground-glass opacities (GGOs) and consolidation most commonly in the lung periphery, though a diffuse distribution was found in a minority of patients.^21,23,25-27 Lomoro and colleagues recently summarized the CT findings from several reports that described abnormalities as most often bilateral and peripheral, subpleural, and affecting the lower lobes.26 Not surprisingly, CT appears more sensitive at detecting changes with COVID-19 than does CXR, with reports that a minority of patients exhibited CT changes before changes were visible on CXR.^23,26

We focused our study on the potential of AI in the examination of CXRs in patients with COVID-19, as there are several limitations to the routine use of CT scans with conditions such as COVID-19. Aside from the more considerable time required to obtain CTs, there are issues with contamination of CT suites, sometimes requiring a dedicated COVID-19 CT scanner.^23,28 The time constraints of decontamination or limited utilization of CT suites can delay or disrupt services for patients with and without COVID-19. Because of these factors, CXR may be a better resource to minimize the risk of infection to other patients. Also, accurate assessment of abnormalities on CXR for COVID-19 may identify patients in whom the CXR was performed for other purposes.²³ CXR is more readily available than CT, especially in more remote or underdeveloped areas.²⁸ Finally, as with CT, CXR abnormalities are reported to have appeared before RT-PCR tests became positive for a minority of patients.²³

CXR findings described in patients with COVID-19 are similar to those of CT and include GGOs, consolidation, and hazy increased opacities.^{23,25,26,28,29} Like CT, the majority of patients who received CXR demonstrated greater involvement in the lower zones and peripherally.^{23,25,26,28,29} Most patients showed bilateral involvement. However, while these findings are common in patients with COVID-19, they are not specific and can be seen in other conditions, such as other viral pneumonia, bacterial pneumonia, injury from drug toxicity, inhalation injury, connective tissue disease, and idiopathic conditions.

Application of AI for COVID-19

Applications of AI in interpreting radiographs of various types are numerous, and extensive literature has been written on the topic.³⁰ Using deep learning algorithms, AI has multiple possible roles to augment traditional radiograph interpretation. These include the potential for screening, triaging, and increasing the speed to render diagnoses. It also can provide a rapid “second opinion” to the radiologist to support the final interpretation. In areas with critical shortages of radiologists, AI potentially can be used to render the definitive diagnosis. In COVID- 19, imaging studies have been shown to correlate with disease severity and mortality, and AI could assist in monitoring the course of the disease as it progresses and potentially identify patients at greatest risk.²⁷ Furthermore, early results from PCR have been considered suboptimal, and it is known that patients with COVID-19 can test negative initially even by reliable testing methodologies. As AI technology progresses, interpretation can detect and guide triage and treatment of patients with high suspicions of COVID-19 but negative initial PCR results, or in situations where test availability is limited or results are delayed. There are numerous potential benefits should a rapid diagnostic test as simple as a CXR be able to reliably impact containment and prevention of the spread of contagions such as COVID- 19 early in its course.

Few studies have assessed using AI in the radiologic diagnosis of COVID-19, most of which use CT scanning. Bai and colleagues demonstrated increased accuracy, sensitivity, and specificity in distinguishing chest CTs of COVID-19 patients from other types of pneumonia.^21,31 A separate study demonstrated the utility of using AI to differentiate COVID-19 from community-acquired pneumonia with CT.32 However, the effective utility of AI for CXR interpretation also has been demonstrated.^14,33 Implementation of convolutional neural network layers has allowed for reliable differentiation of viral and bacterial pneumonia with CXR imaging.³⁴ Evidence suggests that there is great potential in the application of AI in the interpretation of radiographs of all types.

Finally, we have developed a publicly available website based on our studies.¹⁸ This website is for research use only as it is based on data from our preliminary investigation. To appear within the website, images must have protected health information removed before uploading. The information on the website, including text, graphics, images, or other material, is for research and may not be appropriate for all circumstances. The website does not provide medical, professional, or licensed advice and is not a substitute for consultation with a HCP. Medical advice should be sought from a qualified HCP for any questions, and the website should not be used for medical diagnosis or treatment.

Limitations

In our preliminary study, we have demonstrated the potential impact AI can have in multiple aspects of patient care for emerging pathogens such as COVID-19 using a test as readily available as a CXR. However, several limitations to this investigation should be mentioned. The study is retrospective in nature with limited sample size and with X-rays from patients with various stages of COVID-19 pneumonia. Also, cases of non-COVID-19 pneumonia are not stratified into different types or etiologies. We intend to demonstrate the potential of AI in differentiating COVID-19 pneumonia from non-COVID-19 pneumonia of any etiology, though future studies should address comparison of COVID-19 cases to more specific types of pneumonias, such as of bacterial or viral origin. Furthermore, the present study does not address any potential effects of additional radiographic findings from coexistent conditions, such as pulmonary edema as seen in congestive heart failure, pleural effusions (which can be seen with COVID-19 pneumonia, though rarely), interstitial lung disease, etc. Future studies are required to address these issues. Ultimately, prospective studies to assess AI-assisted radiographic interpretation in conditions such as COVID-19 are required to demonstrate the impact on diagnosis, treatment, outcome, and patient safety as these technologies are implemented.

Conclusions

We have used a readily available, commercial platform to demonstrate the potential of AI to assist in the successful diagnosis of COVID-19 pneumonia on CXR images. While this technology has numerous applications in radiology, we have focused on the potential impact on future world health crises such as COVID-19. The findings have implications for screening and triage, initial diagnosis, monitoring disease progression, and identifying patients at increased risk of morbidity and mortality. Based on the data, a website was created to demonstrate how such technologies could be shared and distributed to others to combat entities such as COVID-19 moving forward. Our study offers a small window into the potential for how AI will likely dramatically change the practice of medicine in the future.

About 22% of children with COVID-19 infections were asymptomatic, and 66% of the symptomatic children had unrecognized symptoms at the time of diagnosis, based on data from a case series of 91 confirmed cases.

South_agency/Getty Images

Although recent reports suggest that COVID-19 infections in children are generally mild, data on the full spectrum of illness and duration of viral RNA in children are limited, wrote Mi Seon Han, MD, PhD, of Seoul (South Korea) Metropolitan Government–Seoul National University Boramae Medical Center, and colleagues.

To examine the full clinical course and duration of COVID-19 RNA detectability in children with confirmed infections, the researchers reviewed data from 91 individuals with confirmed infections. The children ranged in age from 27 days to 18 years, and 58% were male. The children were monitored at 20 hospitals and 2 isolation facilities for a mean 21.9 days. The findings were published in JAMA Pediatrics.

Overall, COVID-19 viral RNA was present in the study population for a mean 17.6 days, with testing done at a median interval of 3 days. A total of 20 children (22%) were asymptomatic throughout the study period. In these children, viral RNA was detected for a mean 14 days.

“The major hurdle implicated in this study in diagnosing and treating children with COVID-19 is that a considerable number of children are asymptomatic, and even if symptoms are present, they are unrecognized and overlooked before COVID-19 is diagnosed,” the researchers noted.

Of the 71 symptomatic children, 47 (66%) had unrecognized symptoms prior to diagnosis, 18 (25%) developed symptoms after diagnosis, and 6 (9%) were diagnosed at the time of symptom onset. The symptomatic children were symptomatic for a median of 11 days; 43 (61%) remained symptomatic at 7 days’ follow-up after the study period, 27 (38%) were symptomatic at 14 days, and 7 (10%) were symptomatic at 21 days.

A total of 41 children had upper respiratory infections (58%) and 22 children (24%) had lower respiratory tract infections. No difference in the duration of virus RNA was detected between children with upper respiratory tract infections and lower respiratory tract infections (average, 18.7 days vs. 19.9 days).

Among the symptomatic children, 46 (65%) had mild cases and 20 (28%) had moderate cases.

For treatment, 14 children (15%) received lopinavir-ritonavir and/or hydroxychloroquine. Two patients had severe illness and received oxygen via nasal prong, without the need for mechanical ventilation. All the children in the case series recovered from their infections with no fatalities.

The study’s main limitation was the inability to analyze the transmission potential of the children because of the quarantine and isolation policies in Korea, the researchers noted. In addition, the researchers did not perform follow-up testing at consistent intervals, so the duration of COVID-19 RNA detection may be inexact.

However, the results suggest “that suspecting and diagnosing COVID-19 in children based on their symptoms without epidemiologic information and virus testing is very challenging,” the researchers emphasized.

“Most of the children with COVID-19 have silent disease, but SARS-CoV-2 RNA can still be detected in the respiratory tract for a prolonged period,” they wrote. More research is needed to explore the potential for disease transmission by children in the community, and increased surveillance with laboratory screening can help identify children with unrecognized infections.

The study is the first known to focus on the frequency of asymptomatic infection in children and the duration of symptoms in both asymptomatic and symptomatic children, Roberta L. DeBiasi, MD, and Meghan Delaney, DO, both affiliated with Children’s National Hospital and Research Institute, Washington, and George Washington University, Washington, wrote in an accompanying editorial. The structure of the Korean public health system “allowed for the sequential observation, testing (median testing interval of every 3 days), and comparison of 91 asymptomatic, presymptomatic, and symptomatic children with mild to moderate upper and lower respiratory tract infection, identified primarily by contact tracing from laboratory-proven cases.”

Two take-home points from the study are that not all infected children are symptomatic, and the duration of symptoms in those who are varies widely, they noted. “Interestingly, this study aligns with adult data in which up to 40% of adults may remain asymptomatic in the face of infection.”

However, “The third and most important take-home point from this study relates to the duration of viral shedding in infected pediatric patients,” Dr. DeBiasi and Dr. Delaney said (JAMA Pediatr. 2020 Aug 28. doi: 10.1001/jamapediatrics.2020.3996).

“Fully half of symptomatic children with both upper and lower tract disease were still shedding virus at 21 days. These are striking data, particularly since 86 of 88 diagnosed children (98%) either had no symptoms or mild or moderate disease,” they explained. The results highlight the need for improvements in qualitative molecular testing and formal studies to identify differences in results from different testing scenarios, such as hospital entry, preprocedure screening, and symptomatic testing. In addition, “these findings are highly relevant to the development of public health strategies to mitigate and contain spread within communities, particularly as affected communities begin their recovery phases.”

The study is important because “schools are opening, and we don’t know what is going to happen,” Michael E. Pichichero, MD, of Rochester General Hospital, N.Y., said in an interview.

“Clinicians, parents, students, school administrators and politicians are worried,” he said. “This study adds to others recently published, bringing into focus the challenges to several suppositions that existed when the COVID-19 pandemic began and over the summer.”

“This study of 91 Korean children tells us that taking a child’s temperature as a screening tool to decide if they may enter school will not be a highly successful strategy,” he said. “Many children are without fever and asymptomatic when infected and contagious. The notion that children shed less virus or shed it for shorter lengths of time we keep learning from this type of research is not true. In another recent study the authors found that children shed as much of the SARS-CoV-2 virus as an adult in the ICU on a ventilator.”

Dr. Pichichero said he was not surprised by the study findings. “A similar paper was published last week in the Journal of Pediatrics from Massachusetts General Hospital, so the findings in the JAMA paper are similar to what has been reported in the United States.”

“Availability of testing will continue to be a challenge in some communities,” said Dr. Pichichero. “Here in the Rochester, New York, area we will use a screening questionnaire based on the CDC [Centers for Disease Control and Prevention] symptom criteria of SARS-CoV-2 infections to decide whom to test.”

As for additional research, “We have so much more to learn about SARS-CoV-2 in children,” he emphasized. “The focus has been on adults because the morbidity and mortality has been greatest in adults, especially the elderly and those with compromised health.”

“The National Institutes of Health has issued a call for more research in children to characterize the spectrum of SARS-CoV-2 illness, including the multisystem inflammatory syndrome in children [MIS-C] and try to identify biomarkers and/or biosignatures for a prognostic algorithm to predict the longitudinal risk of disease severity after a child is exposed to and may be infected with SARS-CoV-2,” said Dr. Pichichero. “NIH has asked researchers to answer the following questions.”

• Why do children have milder illness?
• Are there differences in childhood biology (e.g., gender, puberty, etc.) that contribute to illness severity?
• Are there genetic host differences associated with different disease severity phenotypes, including MIS-C?
• Are there innate mucosal, humoral, cellular and other adaptive immune profiles that are associated with reduced or increased risk of progressive disease, including previous coronavirus infections?
• Will SARS-CoV-2 reinfection cause worse disease as seen with antibody-dependent enhancement (ADE) in other viral infections (e.g., dengue)? Will future vaccines carry a risk of the ADE phenomenon?
• Does substance use (e.g., nicotine, marijuana) exacerbate or trigger MIS-C through immune activation?

“We have no knowledge yet about SARS-CoV-2 vaccination of children, especially young children,” Dr. Pichichero emphasized. “There are different types of vaccines – messenger RNA, adenovirus vector and purified spike proteins of the virus – among others, but questions remain: Will the vaccines work in children? What about side effects? Will the antibodies and cellular immunity protect partially or completely?”

The researchers and editorialists had no financial conflicts to disclose. Dr. Pichichero had no financial conflicts to disclose.

SOURCE: Han MS et al. JAMA Pediatr. 2020 Aug 28. doi:10.1001/jamapediatrics.2020.3988.

About 22% of children with COVID-19 infections were asymptomatic, and 66% of the symptomatic children had unrecognized symptoms at the time of diagnosis, based on data from a case series of 91 confirmed cases.

South_agency/Getty Images

Although recent reports suggest that COVID-19 infections in children are generally mild, data on the full spectrum of illness and duration of viral RNA in children are limited, wrote Mi Seon Han, MD, PhD, of Seoul (South Korea) Metropolitan Government–Seoul National University Boramae Medical Center, and colleagues.

To examine the full clinical course and duration of COVID-19 RNA detectability in children with confirmed infections, the researchers reviewed data from 91 individuals with confirmed infections. The children ranged in age from 27 days to 18 years, and 58% were male. The children were monitored at 20 hospitals and 2 isolation facilities for a mean 21.9 days. The findings were published in JAMA Pediatrics.

Overall, COVID-19 viral RNA was present in the study population for a mean 17.6 days, with testing done at a median interval of 3 days. A total of 20 children (22%) were asymptomatic throughout the study period. In these children, viral RNA was detected for a mean 14 days.

“The major hurdle implicated in this study in diagnosing and treating children with COVID-19 is that a considerable number of children are asymptomatic, and even if symptoms are present, they are unrecognized and overlooked before COVID-19 is diagnosed,” the researchers noted.

Of the 71 symptomatic children, 47 (66%) had unrecognized symptoms prior to diagnosis, 18 (25%) developed symptoms after diagnosis, and 6 (9%) were diagnosed at the time of symptom onset. The symptomatic children were symptomatic for a median of 11 days; 43 (61%) remained symptomatic at 7 days’ follow-up after the study period, 27 (38%) were symptomatic at 14 days, and 7 (10%) were symptomatic at 21 days.

A total of 41 children had upper respiratory infections (58%) and 22 children (24%) had lower respiratory tract infections. No difference in the duration of virus RNA was detected between children with upper respiratory tract infections and lower respiratory tract infections (average, 18.7 days vs. 19.9 days).

Among the symptomatic children, 46 (65%) had mild cases and 20 (28%) had moderate cases.

For treatment, 14 children (15%) received lopinavir-ritonavir and/or hydroxychloroquine. Two patients had severe illness and received oxygen via nasal prong, without the need for mechanical ventilation. All the children in the case series recovered from their infections with no fatalities.

The study’s main limitation was the inability to analyze the transmission potential of the children because of the quarantine and isolation policies in Korea, the researchers noted. In addition, the researchers did not perform follow-up testing at consistent intervals, so the duration of COVID-19 RNA detection may be inexact.

However, the results suggest “that suspecting and diagnosing COVID-19 in children based on their symptoms without epidemiologic information and virus testing is very challenging,” the researchers emphasized.

“Most of the children with COVID-19 have silent disease, but SARS-CoV-2 RNA can still be detected in the respiratory tract for a prolonged period,” they wrote. More research is needed to explore the potential for disease transmission by children in the community, and increased surveillance with laboratory screening can help identify children with unrecognized infections.

The study is the first known to focus on the frequency of asymptomatic infection in children and the duration of symptoms in both asymptomatic and symptomatic children, Roberta L. DeBiasi, MD, and Meghan Delaney, DO, both affiliated with Children’s National Hospital and Research Institute, Washington, and George Washington University, Washington, wrote in an accompanying editorial. The structure of the Korean public health system “allowed for the sequential observation, testing (median testing interval of every 3 days), and comparison of 91 asymptomatic, presymptomatic, and symptomatic children with mild to moderate upper and lower respiratory tract infection, identified primarily by contact tracing from laboratory-proven cases.”

Two take-home points from the study are that not all infected children are symptomatic, and the duration of symptoms in those who are varies widely, they noted. “Interestingly, this study aligns with adult data in which up to 40% of adults may remain asymptomatic in the face of infection.”

However, “The third and most important take-home point from this study relates to the duration of viral shedding in infected pediatric patients,” Dr. DeBiasi and Dr. Delaney said (JAMA Pediatr. 2020 Aug 28. doi: 10.1001/jamapediatrics.2020.3996).

“Fully half of symptomatic children with both upper and lower tract disease were still shedding virus at 21 days. These are striking data, particularly since 86 of 88 diagnosed children (98%) either had no symptoms or mild or moderate disease,” they explained. The results highlight the need for improvements in qualitative molecular testing and formal studies to identify differences in results from different testing scenarios, such as hospital entry, preprocedure screening, and symptomatic testing. In addition, “these findings are highly relevant to the development of public health strategies to mitigate and contain spread within communities, particularly as affected communities begin their recovery phases.”

The study is important because “schools are opening, and we don’t know what is going to happen,” Michael E. Pichichero, MD, of Rochester General Hospital, N.Y., said in an interview.

“Clinicians, parents, students, school administrators and politicians are worried,” he said. “This study adds to others recently published, bringing into focus the challenges to several suppositions that existed when the COVID-19 pandemic began and over the summer.”

“This study of 91 Korean children tells us that taking a child’s temperature as a screening tool to decide if they may enter school will not be a highly successful strategy,” he said. “Many children are without fever and asymptomatic when infected and contagious. The notion that children shed less virus or shed it for shorter lengths of time we keep learning from this type of research is not true. In another recent study the authors found that children shed as much of the SARS-CoV-2 virus as an adult in the ICU on a ventilator.”

Dr. Pichichero said he was not surprised by the study findings. “A similar paper was published last week in the Journal of Pediatrics from Massachusetts General Hospital, so the findings in the JAMA paper are similar to what has been reported in the United States.”

“Availability of testing will continue to be a challenge in some communities,” said Dr. Pichichero. “Here in the Rochester, New York, area we will use a screening questionnaire based on the CDC [Centers for Disease Control and Prevention] symptom criteria of SARS-CoV-2 infections to decide whom to test.”

As for additional research, “We have so much more to learn about SARS-CoV-2 in children,” he emphasized. “The focus has been on adults because the morbidity and mortality has been greatest in adults, especially the elderly and those with compromised health.”

“The National Institutes of Health has issued a call for more research in children to characterize the spectrum of SARS-CoV-2 illness, including the multisystem inflammatory syndrome in children [MIS-C] and try to identify biomarkers and/or biosignatures for a prognostic algorithm to predict the longitudinal risk of disease severity after a child is exposed to and may be infected with SARS-CoV-2,” said Dr. Pichichero. “NIH has asked researchers to answer the following questions.”

• Why do children have milder illness?
• Are there differences in childhood biology (e.g., gender, puberty, etc.) that contribute to illness severity?
• Are there genetic host differences associated with different disease severity phenotypes, including MIS-C?
• Are there innate mucosal, humoral, cellular and other adaptive immune profiles that are associated with reduced or increased risk of progressive disease, including previous coronavirus infections?
• Will SARS-CoV-2 reinfection cause worse disease as seen with antibody-dependent enhancement (ADE) in other viral infections (e.g., dengue)? Will future vaccines carry a risk of the ADE phenomenon?
• Does substance use (e.g., nicotine, marijuana) exacerbate or trigger MIS-C through immune activation?

“We have no knowledge yet about SARS-CoV-2 vaccination of children, especially young children,” Dr. Pichichero emphasized. “There are different types of vaccines – messenger RNA, adenovirus vector and purified spike proteins of the virus – among others, but questions remain: Will the vaccines work in children? What about side effects? Will the antibodies and cellular immunity protect partially or completely?”

The researchers and editorialists had no financial conflicts to disclose. Dr. Pichichero had no financial conflicts to disclose.

SOURCE: Han MS et al. JAMA Pediatr. 2020 Aug 28. doi:10.1001/jamapediatrics.2020.3988.

About 22% of children with COVID-19 infections were asymptomatic, and 66% of the symptomatic children had unrecognized symptoms at the time of diagnosis, based on data from a case series of 91 confirmed cases.

South_agency/Getty Images

Although recent reports suggest that COVID-19 infections in children are generally mild, data on the full spectrum of illness and duration of viral RNA in children are limited, wrote Mi Seon Han, MD, PhD, of Seoul (South Korea) Metropolitan Government–Seoul National University Boramae Medical Center, and colleagues.

To examine the full clinical course and duration of COVID-19 RNA detectability in children with confirmed infections, the researchers reviewed data from 91 individuals with confirmed infections. The children ranged in age from 27 days to 18 years, and 58% were male. The children were monitored at 20 hospitals and 2 isolation facilities for a mean 21.9 days. The findings were published in JAMA Pediatrics.

Overall, COVID-19 viral RNA was present in the study population for a mean 17.6 days, with testing done at a median interval of 3 days. A total of 20 children (22%) were asymptomatic throughout the study period. In these children, viral RNA was detected for a mean 14 days.

“The major hurdle implicated in this study in diagnosing and treating children with COVID-19 is that a considerable number of children are asymptomatic, and even if symptoms are present, they are unrecognized and overlooked before COVID-19 is diagnosed,” the researchers noted.

Of the 71 symptomatic children, 47 (66%) had unrecognized symptoms prior to diagnosis, 18 (25%) developed symptoms after diagnosis, and 6 (9%) were diagnosed at the time of symptom onset. The symptomatic children were symptomatic for a median of 11 days; 43 (61%) remained symptomatic at 7 days’ follow-up after the study period, 27 (38%) were symptomatic at 14 days, and 7 (10%) were symptomatic at 21 days.

A total of 41 children had upper respiratory infections (58%) and 22 children (24%) had lower respiratory tract infections. No difference in the duration of virus RNA was detected between children with upper respiratory tract infections and lower respiratory tract infections (average, 18.7 days vs. 19.9 days).

Among the symptomatic children, 46 (65%) had mild cases and 20 (28%) had moderate cases.

For treatment, 14 children (15%) received lopinavir-ritonavir and/or hydroxychloroquine. Two patients had severe illness and received oxygen via nasal prong, without the need for mechanical ventilation. All the children in the case series recovered from their infections with no fatalities.

The study’s main limitation was the inability to analyze the transmission potential of the children because of the quarantine and isolation policies in Korea, the researchers noted. In addition, the researchers did not perform follow-up testing at consistent intervals, so the duration of COVID-19 RNA detection may be inexact.

However, the results suggest “that suspecting and diagnosing COVID-19 in children based on their symptoms without epidemiologic information and virus testing is very challenging,” the researchers emphasized.

“Most of the children with COVID-19 have silent disease, but SARS-CoV-2 RNA can still be detected in the respiratory tract for a prolonged period,” they wrote. More research is needed to explore the potential for disease transmission by children in the community, and increased surveillance with laboratory screening can help identify children with unrecognized infections.

The study is the first known to focus on the frequency of asymptomatic infection in children and the duration of symptoms in both asymptomatic and symptomatic children, Roberta L. DeBiasi, MD, and Meghan Delaney, DO, both affiliated with Children’s National Hospital and Research Institute, Washington, and George Washington University, Washington, wrote in an accompanying editorial. The structure of the Korean public health system “allowed for the sequential observation, testing (median testing interval of every 3 days), and comparison of 91 asymptomatic, presymptomatic, and symptomatic children with mild to moderate upper and lower respiratory tract infection, identified primarily by contact tracing from laboratory-proven cases.”

Two take-home points from the study are that not all infected children are symptomatic, and the duration of symptoms in those who are varies widely, they noted. “Interestingly, this study aligns with adult data in which up to 40% of adults may remain asymptomatic in the face of infection.”

However, “The third and most important take-home point from this study relates to the duration of viral shedding in infected pediatric patients,” Dr. DeBiasi and Dr. Delaney said (JAMA Pediatr. 2020 Aug 28. doi: 10.1001/jamapediatrics.2020.3996).

“Fully half of symptomatic children with both upper and lower tract disease were still shedding virus at 21 days. These are striking data, particularly since 86 of 88 diagnosed children (98%) either had no symptoms or mild or moderate disease,” they explained. The results highlight the need for improvements in qualitative molecular testing and formal studies to identify differences in results from different testing scenarios, such as hospital entry, preprocedure screening, and symptomatic testing. In addition, “these findings are highly relevant to the development of public health strategies to mitigate and contain spread within communities, particularly as affected communities begin their recovery phases.”

The study is important because “schools are opening, and we don’t know what is going to happen,” Michael E. Pichichero, MD, of Rochester General Hospital, N.Y., said in an interview.

“Clinicians, parents, students, school administrators and politicians are worried,” he said. “This study adds to others recently published, bringing into focus the challenges to several suppositions that existed when the COVID-19 pandemic began and over the summer.”

“This study of 91 Korean children tells us that taking a child’s temperature as a screening tool to decide if they may enter school will not be a highly successful strategy,” he said. “Many children are without fever and asymptomatic when infected and contagious. The notion that children shed less virus or shed it for shorter lengths of time we keep learning from this type of research is not true. In another recent study the authors found that children shed as much of the SARS-CoV-2 virus as an adult in the ICU on a ventilator.”

Dr. Pichichero said he was not surprised by the study findings. “A similar paper was published last week in the Journal of Pediatrics from Massachusetts General Hospital, so the findings in the JAMA paper are similar to what has been reported in the United States.”

“Availability of testing will continue to be a challenge in some communities,” said Dr. Pichichero. “Here in the Rochester, New York, area we will use a screening questionnaire based on the CDC [Centers for Disease Control and Prevention] symptom criteria of SARS-CoV-2 infections to decide whom to test.”

As for additional research, “We have so much more to learn about SARS-CoV-2 in children,” he emphasized. “The focus has been on adults because the morbidity and mortality has been greatest in adults, especially the elderly and those with compromised health.”

“The National Institutes of Health has issued a call for more research in children to characterize the spectrum of SARS-CoV-2 illness, including the multisystem inflammatory syndrome in children [MIS-C] and try to identify biomarkers and/or biosignatures for a prognostic algorithm to predict the longitudinal risk of disease severity after a child is exposed to and may be infected with SARS-CoV-2,” said Dr. Pichichero. “NIH has asked researchers to answer the following questions.”

• Why do children have milder illness?
• Are there differences in childhood biology (e.g., gender, puberty, etc.) that contribute to illness severity?
• Are there genetic host differences associated with different disease severity phenotypes, including MIS-C?
• Are there innate mucosal, humoral, cellular and other adaptive immune profiles that are associated with reduced or increased risk of progressive disease, including previous coronavirus infections?
• Will SARS-CoV-2 reinfection cause worse disease as seen with antibody-dependent enhancement (ADE) in other viral infections (e.g., dengue)? Will future vaccines carry a risk of the ADE phenomenon?
• Does substance use (e.g., nicotine, marijuana) exacerbate or trigger MIS-C through immune activation?

“We have no knowledge yet about SARS-CoV-2 vaccination of children, especially young children,” Dr. Pichichero emphasized. “There are different types of vaccines – messenger RNA, adenovirus vector and purified spike proteins of the virus – among others, but questions remain: Will the vaccines work in children? What about side effects? Will the antibodies and cellular immunity protect partially or completely?”

The researchers and editorialists had no financial conflicts to disclose. Dr. Pichichero had no financial conflicts to disclose.

SOURCE: Han MS et al. JAMA Pediatr. 2020 Aug 28. doi:10.1001/jamapediatrics.2020.3988.

Treatment with statins was associated with a reduced risk of a severe or fatal course of COVID-19 by 30%, a meta-analysis of four published studies has shown.

RogerAshford/Thinkstock

In the analysis that included almost 9,000 COVID-19 patients, there was a significantly reduced risk for fatal or severe COVID-19 among patients who were users of statins, compared with nonusers (pooled hazard ratio, 0.70; 95% confidence interval, 0.53-0.94).

Based on the findings, “it may be time we shift our focus to statins as the potential therapeutic options in COVID-19 patients,” authors Syed Shahzad Hasan, PhD, University of Huddersfield (England), and Chia Siang Kow, MPharm, International Medical University, Kuala Lumpur, Malaysia, said in an interview.

The study was published online August 11 in The American Journal of Cardiology.
 

Moderate- to good-quality data

The analysis included four studies published up to July 27 of this year. Eligible studies included those with a cohort or case-control designs, enrolled patients with confirmed COVID-19, and had data available allowing comparison of the risk of severe illness and/or mortality among statin users versus nonusers in adjusted analyses, the authors noted.

The four studies – one of “moderate” quality and three of “good” quality – included a total of 8,990 COVID-19 patients.

In the pooled analysis, there was a significantly reduced risk for fatal or severe COVID-19 with use of statins, compared with non-use of statins (pooled HR, 0.70; 95% CI, 0.53-0.94).

Their findings also “discredited the suggestion of harms with the use of statins in COVID-19 patients,” the authors concluded.

“Since our meta-analysis included a fairly large total number of COVID-19 patients from four studies in which three are large-scale studies that adjusted extensively for multiple potential confounding factors, the findings can be considered reliable,” Dr. Hasan and Mr. Kow wrote in their article.

Based on the results, “moderate- to high-intensity statin therapy is likely to be beneficial” in patients with COVID-19, they said.

However, they cautioned that more data from prospective studies are needed to substantiate the findings and to determine the appropriate regimen for a statin in COVID-19 patients.

Yibin Wang, PhD, of the University of California, Los Angeles, said that “this is a very simple meta-analysis from four published studies which consistently reported a protective or neutral effect of statin usage on mortality or severe complications in COVID-19 patients.”

Although the scope of this meta-analysis was “quite limited, the conclusion was not unexpected, as most of the clinical analysis so far reported supports the benefits or safety of statin usage in COVID-19 patients,” Dr. Wang said in an interview.
 

Nonetheless, questions remain

While there is “almost no dispute” about the safety of continuing statin therapy in COVID-19 patients, it remains to be determined if statin therapy can be implemented as an adjuvant or independent therapy and a part of the standard care for COVID-19 patients regardless of their hyperlipidemia status, said Dr. Wang, who was not associated with Dr. Hasan’s and Mr. Kow’s research.

“While statin usage is associated with several beneficial effects such as anti-inflammation and cytoprotection, these effects are usually observed from long-term usage rather than short-term/acute administration. Therefore, prospective studies and randomized trials should be conducted to test the efficacy of stain usage for COVID-19 patients with mild to severe symptoms,” he noted.

“Considering the excellent record of statins as a safe and cheap drug, it is certainly a worthwhile effort to consider its broad-based usage for COVID-19 in order to lower the overall death and severe complications,” Dr. Wang concluded.

Guillermo Rodriguez-Nava, MD, department of internal medicine, AMITA Health Saint Francis Hospital, Evanston, Ill., is first author on one of the studies included in this meta-analysis.

The retrospective, single-center study found slower progression to death associated with atorvastatin in older patients with COVID-19 admitted to the ICU. 

“Currently, there are hundreds of clinical trials evaluating a wide variety of pharmacological therapies for COVID-19. Unfortunately, these trials take time, and we are getting results in dribs and drabs,” Dr. Rodriguez-Nava said in an interview.

“In the meantime, the best available evidence is observational, and COVID-19 treatment regiments will continue to evolve. Whether atorvastatin is effective against COVID-19 is still under investigation. Nevertheless, clinicians should consider at least continuing them in patients with COVID-19,” he advised.

The study had no specific funding. Dr. Hasan, Mr. Kow, Dr. Wang, and Dr. Rodriguez-Nava disclosed no relationships relevant to this research.

A version of this article originally appeared on Medscape.com.

Treatment with statins was associated with a reduced risk of a severe or fatal course of COVID-19 by 30%, a meta-analysis of four published studies has shown.

RogerAshford/Thinkstock

In the analysis that included almost 9,000 COVID-19 patients, there was a significantly reduced risk for fatal or severe COVID-19 among patients who were users of statins, compared with nonusers (pooled hazard ratio, 0.70; 95% confidence interval, 0.53-0.94).

Based on the findings, “it may be time we shift our focus to statins as the potential therapeutic options in COVID-19 patients,” authors Syed Shahzad Hasan, PhD, University of Huddersfield (England), and Chia Siang Kow, MPharm, International Medical University, Kuala Lumpur, Malaysia, said in an interview.

The study was published online August 11 in The American Journal of Cardiology.
 

Moderate- to good-quality data

The analysis included four studies published up to July 27 of this year. Eligible studies included those with a cohort or case-control designs, enrolled patients with confirmed COVID-19, and had data available allowing comparison of the risk of severe illness and/or mortality among statin users versus nonusers in adjusted analyses, the authors noted.

The four studies – one of “moderate” quality and three of “good” quality – included a total of 8,990 COVID-19 patients.

In the pooled analysis, there was a significantly reduced risk for fatal or severe COVID-19 with use of statins, compared with non-use of statins (pooled HR, 0.70; 95% CI, 0.53-0.94).

Their findings also “discredited the suggestion of harms with the use of statins in COVID-19 patients,” the authors concluded.

“Since our meta-analysis included a fairly large total number of COVID-19 patients from four studies in which three are large-scale studies that adjusted extensively for multiple potential confounding factors, the findings can be considered reliable,” Dr. Hasan and Mr. Kow wrote in their article.

Based on the results, “moderate- to high-intensity statin therapy is likely to be beneficial” in patients with COVID-19, they said.

However, they cautioned that more data from prospective studies are needed to substantiate the findings and to determine the appropriate regimen for a statin in COVID-19 patients.

Yibin Wang, PhD, of the University of California, Los Angeles, said that “this is a very simple meta-analysis from four published studies which consistently reported a protective or neutral effect of statin usage on mortality or severe complications in COVID-19 patients.”

Although the scope of this meta-analysis was “quite limited, the conclusion was not unexpected, as most of the clinical analysis so far reported supports the benefits or safety of statin usage in COVID-19 patients,” Dr. Wang said in an interview.
 

Nonetheless, questions remain

While there is “almost no dispute” about the safety of continuing statin therapy in COVID-19 patients, it remains to be determined if statin therapy can be implemented as an adjuvant or independent therapy and a part of the standard care for COVID-19 patients regardless of their hyperlipidemia status, said Dr. Wang, who was not associated with Dr. Hasan’s and Mr. Kow’s research.

“While statin usage is associated with several beneficial effects such as anti-inflammation and cytoprotection, these effects are usually observed from long-term usage rather than short-term/acute administration. Therefore, prospective studies and randomized trials should be conducted to test the efficacy of stain usage for COVID-19 patients with mild to severe symptoms,” he noted.

“Considering the excellent record of statins as a safe and cheap drug, it is certainly a worthwhile effort to consider its broad-based usage for COVID-19 in order to lower the overall death and severe complications,” Dr. Wang concluded.

Guillermo Rodriguez-Nava, MD, department of internal medicine, AMITA Health Saint Francis Hospital, Evanston, Ill., is first author on one of the studies included in this meta-analysis.

The retrospective, single-center study found slower progression to death associated with atorvastatin in older patients with COVID-19 admitted to the ICU. 

“Currently, there are hundreds of clinical trials evaluating a wide variety of pharmacological therapies for COVID-19. Unfortunately, these trials take time, and we are getting results in dribs and drabs,” Dr. Rodriguez-Nava said in an interview.

“In the meantime, the best available evidence is observational, and COVID-19 treatment regiments will continue to evolve. Whether atorvastatin is effective against COVID-19 is still under investigation. Nevertheless, clinicians should consider at least continuing them in patients with COVID-19,” he advised.

The study had no specific funding. Dr. Hasan, Mr. Kow, Dr. Wang, and Dr. Rodriguez-Nava disclosed no relationships relevant to this research.

A version of this article originally appeared on Medscape.com.

Treatment with statins was associated with a reduced risk of a severe or fatal course of COVID-19 by 30%, a meta-analysis of four published studies has shown.

RogerAshford/Thinkstock

In the analysis that included almost 9,000 COVID-19 patients, there was a significantly reduced risk for fatal or severe COVID-19 among patients who were users of statins, compared with nonusers (pooled hazard ratio, 0.70; 95% confidence interval, 0.53-0.94).

Based on the findings, “it may be time we shift our focus to statins as the potential therapeutic options in COVID-19 patients,” authors Syed Shahzad Hasan, PhD, University of Huddersfield (England), and Chia Siang Kow, MPharm, International Medical University, Kuala Lumpur, Malaysia, said in an interview.

The study was published online August 11 in The American Journal of Cardiology.
 

Moderate- to good-quality data

The analysis included four studies published up to July 27 of this year. Eligible studies included those with a cohort or case-control designs, enrolled patients with confirmed COVID-19, and had data available allowing comparison of the risk of severe illness and/or mortality among statin users versus nonusers in adjusted analyses, the authors noted.

The four studies – one of “moderate” quality and three of “good” quality – included a total of 8,990 COVID-19 patients.

In the pooled analysis, there was a significantly reduced risk for fatal or severe COVID-19 with use of statins, compared with non-use of statins (pooled HR, 0.70; 95% CI, 0.53-0.94).

Their findings also “discredited the suggestion of harms with the use of statins in COVID-19 patients,” the authors concluded.

“Since our meta-analysis included a fairly large total number of COVID-19 patients from four studies in which three are large-scale studies that adjusted extensively for multiple potential confounding factors, the findings can be considered reliable,” Dr. Hasan and Mr. Kow wrote in their article.

Based on the results, “moderate- to high-intensity statin therapy is likely to be beneficial” in patients with COVID-19, they said.

However, they cautioned that more data from prospective studies are needed to substantiate the findings and to determine the appropriate regimen for a statin in COVID-19 patients.

Yibin Wang, PhD, of the University of California, Los Angeles, said that “this is a very simple meta-analysis from four published studies which consistently reported a protective or neutral effect of statin usage on mortality or severe complications in COVID-19 patients.”

Although the scope of this meta-analysis was “quite limited, the conclusion was not unexpected, as most of the clinical analysis so far reported supports the benefits or safety of statin usage in COVID-19 patients,” Dr. Wang said in an interview.
 

Nonetheless, questions remain

While there is “almost no dispute” about the safety of continuing statin therapy in COVID-19 patients, it remains to be determined if statin therapy can be implemented as an adjuvant or independent therapy and a part of the standard care for COVID-19 patients regardless of their hyperlipidemia status, said Dr. Wang, who was not associated with Dr. Hasan’s and Mr. Kow’s research.

“While statin usage is associated with several beneficial effects such as anti-inflammation and cytoprotection, these effects are usually observed from long-term usage rather than short-term/acute administration. Therefore, prospective studies and randomized trials should be conducted to test the efficacy of stain usage for COVID-19 patients with mild to severe symptoms,” he noted.

“Considering the excellent record of statins as a safe and cheap drug, it is certainly a worthwhile effort to consider its broad-based usage for COVID-19 in order to lower the overall death and severe complications,” Dr. Wang concluded.

Guillermo Rodriguez-Nava, MD, department of internal medicine, AMITA Health Saint Francis Hospital, Evanston, Ill., is first author on one of the studies included in this meta-analysis.

The retrospective, single-center study found slower progression to death associated with atorvastatin in older patients with COVID-19 admitted to the ICU. 

“Currently, there are hundreds of clinical trials evaluating a wide variety of pharmacological therapies for COVID-19. Unfortunately, these trials take time, and we are getting results in dribs and drabs,” Dr. Rodriguez-Nava said in an interview.

“In the meantime, the best available evidence is observational, and COVID-19 treatment regiments will continue to evolve. Whether atorvastatin is effective against COVID-19 is still under investigation. Nevertheless, clinicians should consider at least continuing them in patients with COVID-19,” he advised.

The study had no specific funding. Dr. Hasan, Mr. Kow, Dr. Wang, and Dr. Rodriguez-Nava disclosed no relationships relevant to this research.

A version of this article originally appeared on Medscape.com.

Factors including older age and certain comorbidities have been linked to more serious COVID-19 outcomes in previous research, and now a large dataset collected from hundreds of hospitals nationwide provides more detailed data regarding risk for mechanical ventilation and death.

Comorbidities such as cardiovascular disease, chronic kidney disease, and obesity also were associated with more severe COVID-19 outcomes in this observational study of 11,721 adults. History of pulmonary disease or smoking, interestingly, were not.

One expert urges caution when interpreting the results, however. Although the study found a number of risk factors for ventilation and mortality, she says the dataset lacks information on race and disease severity, and the sample may not be nationally representative. 

The investigators hope their level of granularity will further assist researchers searching for effective treatments and clinicians seeking to triage patients during the COVID-19 pandemic.

The study was published online August 28 in Clinical Infectious Diseases.
 

COVID-19 and comorbidities

“What I found most illuminating was this whole concept of comorbid conditions. This provides suggestive data about who we need to worry about most and who we may need to worry about less,” study author Robert S. Brown Jr, MD, MPH, told Medscape Medical News.

Comorbid conditions included hypertension in 47% of patients, diabetes in 28%, and cardiovascular disease in 19%. Another 16% were obese and 12% had chronic kidney disease. People with comorbid obesity, chronic kidney disease, and cardiovascular disease were more likely to receive mechanical ventilation compared to those without a history of these conditions in an adjusted, multivariable logistic analysis.

With the exception of obesity, the same factors were associated with risk for death during hospitalization.

In contrast, hypertension, history of smoking, and history of pulmonary disease were associated with a lower risk of needing mechanical ventilation and/or lower risk for mortality.

Furthermore, people with liver disease, gastrointestinal diseases, and even autoimmune diseases – which are likely associated with immunosuppression – “are not at that much of an increased risk that we noticed it in our data,” Brown said.

“As I tell many of my patients who have mild liver disease, for example, I would rather have mild liver disease and be on immunosuppressant therapy than be an older, obese male,” he added.

Assessing data for people in 38 U.S. states, and not limiting outcomes to patients in a particular COVID-19 hot spot, was a unique aspect of the research, said Brown, clinical chief of the Division of Gastroenterology and Hepatology at Weill Cornell Medicine in New York City.

Brown, lead author Michael W. Fried, MD, from TARGET PharmaSolutions in Durham, North Carolina, and colleagues studied adults from a commercially available Target Real-World Evidence (RWE) dataset of nearly 70,000 patients. They examined hospital chargemaster data and ICD-10 codes for COVID-19 inpatients between February 15 and April 20.

This population tended to be older, with 60% older than 60 years. A little more than half of participants, 53%, were men.
 

Key findings

A total of 21% of patients died after a median hospital length of stay of 8 days.

Older patients were significantly more likely to die, particularly those older than 60 years (P < .0001).

“This confirms some of the things we know about age and its impact on outcome,” Brown said.

The risk for mortality among patients older than 60 years was 7.2 times that of patients between 18 and 40 years in an adjusted multivariate analysis. The risk for death for those between 41 and 60 years of age was lower (odds ratio [OR], 2.6), compared with the youngest cohort.  

Men were more likely to die than women (OR, 1.5).

When asked if he was surprised by the high mortality rates, Brown said, “Having worked here in New York? No, I was not.”
 

Mechanical ventilation and mortality

Male sex, age older than 40 years, obesity, and presence of cardiovascular or chronic kidney disease were risk factors for mechanical ventilation.

Among the nearly 2,000 hospitalized adults requiring mechanical ventilation in the current report, only 27% were discharged alive. “The outcomes of people who are mechanically ventilated are really quite sobering,” Brown said.

People who ever required mechanical ventilation were 32 times more likely to die compared with others whose highest level of oxygenation was low-flow, high-flow, or no-oxygen therapy in an analysis that controlled for demographics and comorbidities.

Furthermore, patients placed on mechanical ventilation earlier – within 24 hours of admission – tended to experience better outcomes.
 

COVID-19 therapies?

Brown and colleagues also evaluated outcomes in patients who were taking either remdesivir or hydroxychloroquine. A total of 48 people were treated with remdesivir.

The four individuals receiving remdesivir who died were among 11 who were taking remdesivir and also on mechanical ventilation.

“The data for remdesivir is very encouraging,” Brown said.

Many more participants were treated with hydroxychloroquine, more than 4,200 or 36% of the total study population.

A higher proportion of people treated with hydroxychloroquine received mechanical ventilation, at 25%, versus 12% not treated with hydroxychloroquine.

The unadjusted mortality rate was also higher among those treated with the agent, at 25%, compared to 20% not receiving hydroxychloroquine.

The data with hydroxychloroquine can lead to two conclusions, Brown said: “One, it doesn’t work. Or two, it doesn’t work in the way that we use it.”

The researchers cautioned that their hydroxychloroquine findings must be interpreted carefully because those treated with the agent were also more likely to have comorbidities and greater COVID-19 disease severity.

“This study greatly contributes to understanding the natural course of COVID-19 infection by describing characteristics and outcomes of patients with COVID-19 hospitalized throughout the US,” the investigators note. “It identified categories of patients at greatest risk for poor outcomes, which should be used to prioritize prevention and treatment strategies in the future.”
 

Some limitations

“The findings that patients with hypertension and who were smokers had lower ventilation rates, and patients with hypertension, pulmonary disease, who were smokers had lower mortality risks was very surprising,” Ninez A. Ponce, PhD, MPP, told Medscape Medical News when asked to comment on the study.

Although the study identified multiple risk factors for ventilation and mortality, “unfortunately the dataset did not have race available or disease severity,” said Ponce, director of the UCLA Center for Health Policy Research and professor in the Department of Health Policy and Management at the UCLA Fielding School of Public Health.

“These omitted variables could have a considerable effect on the significance, magnitude, and direction of point estimates provided, so I would be cautious in interpreting the results as a picture of a nationally representative sample,” she said.

On a positive note, the study and dataset could illuminate the utility of medications used to treat COVID-19, Ponce said. In addition, as the authors note, “the data will expand over time.” 

Brown has reported receiving grants and consulting for Gilead. Ponce has disclosed no relevant financial relationships.
 

This article first appeared on Medscape.com.

Factors including older age and certain comorbidities have been linked to more serious COVID-19 outcomes in previous research, and now a large dataset collected from hundreds of hospitals nationwide provides more detailed data regarding risk for mechanical ventilation and death.

Comorbidities such as cardiovascular disease, chronic kidney disease, and obesity also were associated with more severe COVID-19 outcomes in this observational study of 11,721 adults. History of pulmonary disease or smoking, interestingly, were not.

One expert urges caution when interpreting the results, however. Although the study found a number of risk factors for ventilation and mortality, she says the dataset lacks information on race and disease severity, and the sample may not be nationally representative. 

The investigators hope their level of granularity will further assist researchers searching for effective treatments and clinicians seeking to triage patients during the COVID-19 pandemic.

The study was published online August 28 in Clinical Infectious Diseases.
 

COVID-19 and comorbidities

“What I found most illuminating was this whole concept of comorbid conditions. This provides suggestive data about who we need to worry about most and who we may need to worry about less,” study author Robert S. Brown Jr, MD, MPH, told Medscape Medical News.

Comorbid conditions included hypertension in 47% of patients, diabetes in 28%, and cardiovascular disease in 19%. Another 16% were obese and 12% had chronic kidney disease. People with comorbid obesity, chronic kidney disease, and cardiovascular disease were more likely to receive mechanical ventilation compared to those without a history of these conditions in an adjusted, multivariable logistic analysis.

With the exception of obesity, the same factors were associated with risk for death during hospitalization.

In contrast, hypertension, history of smoking, and history of pulmonary disease were associated with a lower risk of needing mechanical ventilation and/or lower risk for mortality.

Furthermore, people with liver disease, gastrointestinal diseases, and even autoimmune diseases – which are likely associated with immunosuppression – “are not at that much of an increased risk that we noticed it in our data,” Brown said.

“As I tell many of my patients who have mild liver disease, for example, I would rather have mild liver disease and be on immunosuppressant therapy than be an older, obese male,” he added.

Assessing data for people in 38 U.S. states, and not limiting outcomes to patients in a particular COVID-19 hot spot, was a unique aspect of the research, said Brown, clinical chief of the Division of Gastroenterology and Hepatology at Weill Cornell Medicine in New York City.

Brown, lead author Michael W. Fried, MD, from TARGET PharmaSolutions in Durham, North Carolina, and colleagues studied adults from a commercially available Target Real-World Evidence (RWE) dataset of nearly 70,000 patients. They examined hospital chargemaster data and ICD-10 codes for COVID-19 inpatients between February 15 and April 20.

This population tended to be older, with 60% older than 60 years. A little more than half of participants, 53%, were men.
 

Key findings

A total of 21% of patients died after a median hospital length of stay of 8 days.

Older patients were significantly more likely to die, particularly those older than 60 years (P < .0001).

“This confirms some of the things we know about age and its impact on outcome,” Brown said.

The risk for mortality among patients older than 60 years was 7.2 times that of patients between 18 and 40 years in an adjusted multivariate analysis. The risk for death for those between 41 and 60 years of age was lower (odds ratio [OR], 2.6), compared with the youngest cohort.  

Men were more likely to die than women (OR, 1.5).

When asked if he was surprised by the high mortality rates, Brown said, “Having worked here in New York? No, I was not.”
 

Mechanical ventilation and mortality

Male sex, age older than 40 years, obesity, and presence of cardiovascular or chronic kidney disease were risk factors for mechanical ventilation.

Among the nearly 2,000 hospitalized adults requiring mechanical ventilation in the current report, only 27% were discharged alive. “The outcomes of people who are mechanically ventilated are really quite sobering,” Brown said.

People who ever required mechanical ventilation were 32 times more likely to die compared with others whose highest level of oxygenation was low-flow, high-flow, or no-oxygen therapy in an analysis that controlled for demographics and comorbidities.

Furthermore, patients placed on mechanical ventilation earlier – within 24 hours of admission – tended to experience better outcomes.
 

COVID-19 therapies?

Brown and colleagues also evaluated outcomes in patients who were taking either remdesivir or hydroxychloroquine. A total of 48 people were treated with remdesivir.

The four individuals receiving remdesivir who died were among 11 who were taking remdesivir and also on mechanical ventilation.

“The data for remdesivir is very encouraging,” Brown said.

Many more participants were treated with hydroxychloroquine, more than 4,200 or 36% of the total study population.

A higher proportion of people treated with hydroxychloroquine received mechanical ventilation, at 25%, versus 12% not treated with hydroxychloroquine.

The unadjusted mortality rate was also higher among those treated with the agent, at 25%, compared to 20% not receiving hydroxychloroquine.

The data with hydroxychloroquine can lead to two conclusions, Brown said: “One, it doesn’t work. Or two, it doesn’t work in the way that we use it.”

The researchers cautioned that their hydroxychloroquine findings must be interpreted carefully because those treated with the agent were also more likely to have comorbidities and greater COVID-19 disease severity.

“This study greatly contributes to understanding the natural course of COVID-19 infection by describing characteristics and outcomes of patients with COVID-19 hospitalized throughout the US,” the investigators note. “It identified categories of patients at greatest risk for poor outcomes, which should be used to prioritize prevention and treatment strategies in the future.”
 

Some limitations

“The findings that patients with hypertension and who were smokers had lower ventilation rates, and patients with hypertension, pulmonary disease, who were smokers had lower mortality risks was very surprising,” Ninez A. Ponce, PhD, MPP, told Medscape Medical News when asked to comment on the study.

Although the study identified multiple risk factors for ventilation and mortality, “unfortunately the dataset did not have race available or disease severity,” said Ponce, director of the UCLA Center for Health Policy Research and professor in the Department of Health Policy and Management at the UCLA Fielding School of Public Health.

“These omitted variables could have a considerable effect on the significance, magnitude, and direction of point estimates provided, so I would be cautious in interpreting the results as a picture of a nationally representative sample,” she said.

On a positive note, the study and dataset could illuminate the utility of medications used to treat COVID-19, Ponce said. In addition, as the authors note, “the data will expand over time.” 

Brown has reported receiving grants and consulting for Gilead. Ponce has disclosed no relevant financial relationships.
 

This article first appeared on Medscape.com.

Factors including older age and certain comorbidities have been linked to more serious COVID-19 outcomes in previous research, and now a large dataset collected from hundreds of hospitals nationwide provides more detailed data regarding risk for mechanical ventilation and death.

Comorbidities such as cardiovascular disease, chronic kidney disease, and obesity also were associated with more severe COVID-19 outcomes in this observational study of 11,721 adults. History of pulmonary disease or smoking, interestingly, were not.

One expert urges caution when interpreting the results, however. Although the study found a number of risk factors for ventilation and mortality, she says the dataset lacks information on race and disease severity, and the sample may not be nationally representative. 

The investigators hope their level of granularity will further assist researchers searching for effective treatments and clinicians seeking to triage patients during the COVID-19 pandemic.

The study was published online August 28 in Clinical Infectious Diseases.
 

COVID-19 and comorbidities

“What I found most illuminating was this whole concept of comorbid conditions. This provides suggestive data about who we need to worry about most and who we may need to worry about less,” study author Robert S. Brown Jr, MD, MPH, told Medscape Medical News.

Comorbid conditions included hypertension in 47% of patients, diabetes in 28%, and cardiovascular disease in 19%. Another 16% were obese and 12% had chronic kidney disease. People with comorbid obesity, chronic kidney disease, and cardiovascular disease were more likely to receive mechanical ventilation compared to those without a history of these conditions in an adjusted, multivariable logistic analysis.

With the exception of obesity, the same factors were associated with risk for death during hospitalization.

In contrast, hypertension, history of smoking, and history of pulmonary disease were associated with a lower risk of needing mechanical ventilation and/or lower risk for mortality.

Furthermore, people with liver disease, gastrointestinal diseases, and even autoimmune diseases – which are likely associated with immunosuppression – “are not at that much of an increased risk that we noticed it in our data,” Brown said.

“As I tell many of my patients who have mild liver disease, for example, I would rather have mild liver disease and be on immunosuppressant therapy than be an older, obese male,” he added.

Assessing data for people in 38 U.S. states, and not limiting outcomes to patients in a particular COVID-19 hot spot, was a unique aspect of the research, said Brown, clinical chief of the Division of Gastroenterology and Hepatology at Weill Cornell Medicine in New York City.

Brown, lead author Michael W. Fried, MD, from TARGET PharmaSolutions in Durham, North Carolina, and colleagues studied adults from a commercially available Target Real-World Evidence (RWE) dataset of nearly 70,000 patients. They examined hospital chargemaster data and ICD-10 codes for COVID-19 inpatients between February 15 and April 20.

This population tended to be older, with 60% older than 60 years. A little more than half of participants, 53%, were men.
 

Key findings

A total of 21% of patients died after a median hospital length of stay of 8 days.

Older patients were significantly more likely to die, particularly those older than 60 years (P < .0001).

“This confirms some of the things we know about age and its impact on outcome,” Brown said.

The risk for mortality among patients older than 60 years was 7.2 times that of patients between 18 and 40 years in an adjusted multivariate analysis. The risk for death for those between 41 and 60 years of age was lower (odds ratio [OR], 2.6), compared with the youngest cohort.  

Men were more likely to die than women (OR, 1.5).

When asked if he was surprised by the high mortality rates, Brown said, “Having worked here in New York? No, I was not.”
 

Mechanical ventilation and mortality

Male sex, age older than 40 years, obesity, and presence of cardiovascular or chronic kidney disease were risk factors for mechanical ventilation.

Among the nearly 2,000 hospitalized adults requiring mechanical ventilation in the current report, only 27% were discharged alive. “The outcomes of people who are mechanically ventilated are really quite sobering,” Brown said.

People who ever required mechanical ventilation were 32 times more likely to die compared with others whose highest level of oxygenation was low-flow, high-flow, or no-oxygen therapy in an analysis that controlled for demographics and comorbidities.

Furthermore, patients placed on mechanical ventilation earlier – within 24 hours of admission – tended to experience better outcomes.
 

COVID-19 therapies?

Brown and colleagues also evaluated outcomes in patients who were taking either remdesivir or hydroxychloroquine. A total of 48 people were treated with remdesivir.

The four individuals receiving remdesivir who died were among 11 who were taking remdesivir and also on mechanical ventilation.

“The data for remdesivir is very encouraging,” Brown said.

Many more participants were treated with hydroxychloroquine, more than 4,200 or 36% of the total study population.

A higher proportion of people treated with hydroxychloroquine received mechanical ventilation, at 25%, versus 12% not treated with hydroxychloroquine.

The unadjusted mortality rate was also higher among those treated with the agent, at 25%, compared to 20% not receiving hydroxychloroquine.

The data with hydroxychloroquine can lead to two conclusions, Brown said: “One, it doesn’t work. Or two, it doesn’t work in the way that we use it.”

The researchers cautioned that their hydroxychloroquine findings must be interpreted carefully because those treated with the agent were also more likely to have comorbidities and greater COVID-19 disease severity.

“This study greatly contributes to understanding the natural course of COVID-19 infection by describing characteristics and outcomes of patients with COVID-19 hospitalized throughout the US,” the investigators note. “It identified categories of patients at greatest risk for poor outcomes, which should be used to prioritize prevention and treatment strategies in the future.”
 

Some limitations

“The findings that patients with hypertension and who were smokers had lower ventilation rates, and patients with hypertension, pulmonary disease, who were smokers had lower mortality risks was very surprising,” Ninez A. Ponce, PhD, MPP, told Medscape Medical News when asked to comment on the study.

Although the study identified multiple risk factors for ventilation and mortality, “unfortunately the dataset did not have race available or disease severity,” said Ponce, director of the UCLA Center for Health Policy Research and professor in the Department of Health Policy and Management at the UCLA Fielding School of Public Health.

“These omitted variables could have a considerable effect on the significance, magnitude, and direction of point estimates provided, so I would be cautious in interpreting the results as a picture of a nationally representative sample,” she said.

On a positive note, the study and dataset could illuminate the utility of medications used to treat COVID-19, Ponce said. In addition, as the authors note, “the data will expand over time.” 

Brown has reported receiving grants and consulting for Gilead. Ponce has disclosed no relevant financial relationships.
 

This article first appeared on Medscape.com.

A study of more than 60,000 prostate cancer patients suggests it is safe to delay radiation therapy (RT) for at least 6 months for localized higher-risk disease being treated with androgen deprivation therapy.

These findings are relevant to oncology care in the COVID-19 era, as the pandemic has complicated delivery of radiation therapy (RT) in several ways, the study authors wrote in JAMA Oncology.

“Daily hospital trips for RT create many possible points of COVID-19 transmission, and patients with cancer are at high risk of COVID-19 mortality,” Edward Christopher Dee, a research fellow at Dana-Farber Cancer Institute in Boston, and colleagues wrote.

To assess the safety of delaying RT, the investigators analyzed National Cancer Database data for 63,858 men with localized but unfavorable intermediate-risk, high-risk, or very-high-risk prostate cancer diagnosed during 2004-2014 and managed with external beam RT and androgen deprivation therapy (ADT).

Only 5.6% of patients (n = 3,572) initiated their RT 0-60 days before starting ADT. Another 36.3% (n = 23,207) initiated RT 1-60 days after starting ADT, 47.4% (n = 30,285) initiated RT 61-120 days after starting ADT, and 10.6% (n = 6,794) initiated RT 121-180 days after starting ADT.

The investigators found that 10-year overall survival rates were similar regardless of when patients started RT.

Multivariate analysis in the unfavorable intermediate-risk group showed that, relative to peers who started RT before ADT, men initiating RT later did not have significantly poorer overall survival, regardless of whether RT was initiated 1-60 days after starting ADT (hazard ratio for death, 1.03; P = .64), 61-120 days after (HR, 0.95; P = .42), or 121-180 days after (HR, 0.99; P = .90).

Findings were similar in the combined high-risk and very-high-risk group, with no significant elevation of mortality risk for patients initiating RT 1-60 days after starting ADT (HR, 1.07; P = .12), 61-120 days after (HR, 1.04; P = .36), or 121-180 days after (HR, 1.07; P = .17).

“These results validate the findings of two prior randomized trials and possibly justify the delay of prostate RT for patients currently receiving ADT until COVID-19 infection rates in the community and hospitals are lower,” the authors wrote.

Despite the fairly short follow-up period and other study limitations, “if COVID-19 outbreaks continue to occur sporadically during the coming months to years, these data could allow future flexibility about the timing of RT initiation,” the authors concluded.
 

Experts weigh in

“Overall, this study is asking a good question given the COVID situation and the fact that many providers are delaying RT due to COVID concerns of patients and providers,” Colleen A. Lawton, MD, of the Medical College of Wisconsin, Milwaukee, commented in an interview.

At the same time, Dr. Lawton cautioned about oversimplifying the issue, noting that results of the Radiation Therapy Oncology Group (RTOG) 9413 trial suggest important interactions between the anatomic extent of RT and the timing of ADT on outcomes (Int J Radiat Oncol Biol Phys. 2007 Nov 1;69[3]:646-55).

“I have certainly delayed some of my own patients with ADT during the COVID pandemic,” she reported. “No one knows what the maximum acceptable delay should be. A few months is likely not a problem, and a year is probably too much, but scientifically, we just don’t know.”

The interplay of volume irradiated and ADT timing is relevant here, agreed Mack Roach III, MD, of University of California, San Francisco.

In addition, the study did not address why ADT was given when it was, the duration of this therapy, and endpoints other than overall survival (such as prostate-specific antigen failure rate) that may better reflect the effectiveness of cancer treatment.

“Yes, delays are safe for patients on ADT, but not for the reasons stated. A more appropriate source of data is RTOG 9910, which compared 28 versus 8 weeks of ADT prior to RT for mostly intermediate-risk prostate cancer patients with comparable results,” Dr. Roach noted (J Clin Oncol. 2015 Feb 1;33[4]:332-9).

“Delay duration should be based on the risk of disease, but 6 months is probably safe, especially if on ADT,” he said.

Michael J. Zelefsky, MD, of Memorial Sloan Kettering Cancer Center in New York, said he agreed with the investigators’ main conclusions. “Once ADT suppression is achieved, maintaining patients on this regimen for 6 months would not likely lead to the development of a castrate-resistant state where radiotherapy would be less effective,” he elaborated.

However, limitations of the database used preclude conclusions about the safety of longer delays or the impact on other outcomes, he cautioned.

“This study provides further support to the accepted notion that delays of up to 6 months prior to initiation of planned prostate radiation would be safe and appropriate, especially where concerns of COVID outbreaks may present significant logistic challenges and concerns for the patient, who needs to commit to a course of daily radiation treatments, which could span for 5-8 weeks,” Dr. Zelefsky said.

“We have, in fact, adopted this approach in our clinics during the COVID outbreaks in New York,” he reported. “Most of our patients with unfavorable intermediate- or high-risk disease were initiated on ADT planned for at least 4-6 months before the radiotherapy was initiated. In addition, for these reasons, our preference has been to also offer such patients, if feasible, an ultrahypofractionated treatment course where the radiotherapy course is completed in five fractions over 1-2 weeks.”

This research was funded by the National Institutes of Health. The authors disclosed various grants and personal fees outside the submitted work. Dr. Lawton disclosed that she was a coauthor on RTOG 9413. Dr. Roach and Dr. Zelefsky disclosed no relevant conflicts of interest.

SOURCE: Dee EC et al. JAMA Oncol. 2020 Aug 13. doi: 10.1001/jamaoncol.2020.3545.

A study of more than 60,000 prostate cancer patients suggests it is safe to delay radiation therapy (RT) for at least 6 months for localized higher-risk disease being treated with androgen deprivation therapy.

These findings are relevant to oncology care in the COVID-19 era, as the pandemic has complicated delivery of radiation therapy (RT) in several ways, the study authors wrote in JAMA Oncology.

“Daily hospital trips for RT create many possible points of COVID-19 transmission, and patients with cancer are at high risk of COVID-19 mortality,” Edward Christopher Dee, a research fellow at Dana-Farber Cancer Institute in Boston, and colleagues wrote.

To assess the safety of delaying RT, the investigators analyzed National Cancer Database data for 63,858 men with localized but unfavorable intermediate-risk, high-risk, or very-high-risk prostate cancer diagnosed during 2004-2014 and managed with external beam RT and androgen deprivation therapy (ADT).

Only 5.6% of patients (n = 3,572) initiated their RT 0-60 days before starting ADT. Another 36.3% (n = 23,207) initiated RT 1-60 days after starting ADT, 47.4% (n = 30,285) initiated RT 61-120 days after starting ADT, and 10.6% (n = 6,794) initiated RT 121-180 days after starting ADT.

The investigators found that 10-year overall survival rates were similar regardless of when patients started RT.

Multivariate analysis in the unfavorable intermediate-risk group showed that, relative to peers who started RT before ADT, men initiating RT later did not have significantly poorer overall survival, regardless of whether RT was initiated 1-60 days after starting ADT (hazard ratio for death, 1.03; P = .64), 61-120 days after (HR, 0.95; P = .42), or 121-180 days after (HR, 0.99; P = .90).

Findings were similar in the combined high-risk and very-high-risk group, with no significant elevation of mortality risk for patients initiating RT 1-60 days after starting ADT (HR, 1.07; P = .12), 61-120 days after (HR, 1.04; P = .36), or 121-180 days after (HR, 1.07; P = .17).

“These results validate the findings of two prior randomized trials and possibly justify the delay of prostate RT for patients currently receiving ADT until COVID-19 infection rates in the community and hospitals are lower,” the authors wrote.

Despite the fairly short follow-up period and other study limitations, “if COVID-19 outbreaks continue to occur sporadically during the coming months to years, these data could allow future flexibility about the timing of RT initiation,” the authors concluded.
 

Experts weigh in

“Overall, this study is asking a good question given the COVID situation and the fact that many providers are delaying RT due to COVID concerns of patients and providers,” Colleen A. Lawton, MD, of the Medical College of Wisconsin, Milwaukee, commented in an interview.

At the same time, Dr. Lawton cautioned about oversimplifying the issue, noting that results of the Radiation Therapy Oncology Group (RTOG) 9413 trial suggest important interactions between the anatomic extent of RT and the timing of ADT on outcomes (Int J Radiat Oncol Biol Phys. 2007 Nov 1;69[3]:646-55).

“I have certainly delayed some of my own patients with ADT during the COVID pandemic,” she reported. “No one knows what the maximum acceptable delay should be. A few months is likely not a problem, and a year is probably too much, but scientifically, we just don’t know.”

The interplay of volume irradiated and ADT timing is relevant here, agreed Mack Roach III, MD, of University of California, San Francisco.

In addition, the study did not address why ADT was given when it was, the duration of this therapy, and endpoints other than overall survival (such as prostate-specific antigen failure rate) that may better reflect the effectiveness of cancer treatment.

“Yes, delays are safe for patients on ADT, but not for the reasons stated. A more appropriate source of data is RTOG 9910, which compared 28 versus 8 weeks of ADT prior to RT for mostly intermediate-risk prostate cancer patients with comparable results,” Dr. Roach noted (J Clin Oncol. 2015 Feb 1;33[4]:332-9).

“Delay duration should be based on the risk of disease, but 6 months is probably safe, especially if on ADT,” he said.

Michael J. Zelefsky, MD, of Memorial Sloan Kettering Cancer Center in New York, said he agreed with the investigators’ main conclusions. “Once ADT suppression is achieved, maintaining patients on this regimen for 6 months would not likely lead to the development of a castrate-resistant state where radiotherapy would be less effective,” he elaborated.

However, limitations of the database used preclude conclusions about the safety of longer delays or the impact on other outcomes, he cautioned.

“This study provides further support to the accepted notion that delays of up to 6 months prior to initiation of planned prostate radiation would be safe and appropriate, especially where concerns of COVID outbreaks may present significant logistic challenges and concerns for the patient, who needs to commit to a course of daily radiation treatments, which could span for 5-8 weeks,” Dr. Zelefsky said.

“We have, in fact, adopted this approach in our clinics during the COVID outbreaks in New York,” he reported. “Most of our patients with unfavorable intermediate- or high-risk disease were initiated on ADT planned for at least 4-6 months before the radiotherapy was initiated. In addition, for these reasons, our preference has been to also offer such patients, if feasible, an ultrahypofractionated treatment course where the radiotherapy course is completed in five fractions over 1-2 weeks.”

This research was funded by the National Institutes of Health. The authors disclosed various grants and personal fees outside the submitted work. Dr. Lawton disclosed that she was a coauthor on RTOG 9413. Dr. Roach and Dr. Zelefsky disclosed no relevant conflicts of interest.

SOURCE: Dee EC et al. JAMA Oncol. 2020 Aug 13. doi: 10.1001/jamaoncol.2020.3545.

A study of more than 60,000 prostate cancer patients suggests it is safe to delay radiation therapy (RT) for at least 6 months for localized higher-risk disease being treated with androgen deprivation therapy.

These findings are relevant to oncology care in the COVID-19 era, as the pandemic has complicated delivery of radiation therapy (RT) in several ways, the study authors wrote in JAMA Oncology.

“Daily hospital trips for RT create many possible points of COVID-19 transmission, and patients with cancer are at high risk of COVID-19 mortality,” Edward Christopher Dee, a research fellow at Dana-Farber Cancer Institute in Boston, and colleagues wrote.

To assess the safety of delaying RT, the investigators analyzed National Cancer Database data for 63,858 men with localized but unfavorable intermediate-risk, high-risk, or very-high-risk prostate cancer diagnosed during 2004-2014 and managed with external beam RT and androgen deprivation therapy (ADT).

Only 5.6% of patients (n = 3,572) initiated their RT 0-60 days before starting ADT. Another 36.3% (n = 23,207) initiated RT 1-60 days after starting ADT, 47.4% (n = 30,285) initiated RT 61-120 days after starting ADT, and 10.6% (n = 6,794) initiated RT 121-180 days after starting ADT.

The investigators found that 10-year overall survival rates were similar regardless of when patients started RT.

Multivariate analysis in the unfavorable intermediate-risk group showed that, relative to peers who started RT before ADT, men initiating RT later did not have significantly poorer overall survival, regardless of whether RT was initiated 1-60 days after starting ADT (hazard ratio for death, 1.03; P = .64), 61-120 days after (HR, 0.95; P = .42), or 121-180 days after (HR, 0.99; P = .90).

Findings were similar in the combined high-risk and very-high-risk group, with no significant elevation of mortality risk for patients initiating RT 1-60 days after starting ADT (HR, 1.07; P = .12), 61-120 days after (HR, 1.04; P = .36), or 121-180 days after (HR, 1.07; P = .17).

“These results validate the findings of two prior randomized trials and possibly justify the delay of prostate RT for patients currently receiving ADT until COVID-19 infection rates in the community and hospitals are lower,” the authors wrote.

Despite the fairly short follow-up period and other study limitations, “if COVID-19 outbreaks continue to occur sporadically during the coming months to years, these data could allow future flexibility about the timing of RT initiation,” the authors concluded.
 

Experts weigh in

“Overall, this study is asking a good question given the COVID situation and the fact that many providers are delaying RT due to COVID concerns of patients and providers,” Colleen A. Lawton, MD, of the Medical College of Wisconsin, Milwaukee, commented in an interview.

At the same time, Dr. Lawton cautioned about oversimplifying the issue, noting that results of the Radiation Therapy Oncology Group (RTOG) 9413 trial suggest important interactions between the anatomic extent of RT and the timing of ADT on outcomes (Int J Radiat Oncol Biol Phys. 2007 Nov 1;69[3]:646-55).

“I have certainly delayed some of my own patients with ADT during the COVID pandemic,” she reported. “No one knows what the maximum acceptable delay should be. A few months is likely not a problem, and a year is probably too much, but scientifically, we just don’t know.”

The interplay of volume irradiated and ADT timing is relevant here, agreed Mack Roach III, MD, of University of California, San Francisco.

In addition, the study did not address why ADT was given when it was, the duration of this therapy, and endpoints other than overall survival (such as prostate-specific antigen failure rate) that may better reflect the effectiveness of cancer treatment.

“Yes, delays are safe for patients on ADT, but not for the reasons stated. A more appropriate source of data is RTOG 9910, which compared 28 versus 8 weeks of ADT prior to RT for mostly intermediate-risk prostate cancer patients with comparable results,” Dr. Roach noted (J Clin Oncol. 2015 Feb 1;33[4]:332-9).

“Delay duration should be based on the risk of disease, but 6 months is probably safe, especially if on ADT,” he said.

Michael J. Zelefsky, MD, of Memorial Sloan Kettering Cancer Center in New York, said he agreed with the investigators’ main conclusions. “Once ADT suppression is achieved, maintaining patients on this regimen for 6 months would not likely lead to the development of a castrate-resistant state where radiotherapy would be less effective,” he elaborated.

However, limitations of the database used preclude conclusions about the safety of longer delays or the impact on other outcomes, he cautioned.

“This study provides further support to the accepted notion that delays of up to 6 months prior to initiation of planned prostate radiation would be safe and appropriate, especially where concerns of COVID outbreaks may present significant logistic challenges and concerns for the patient, who needs to commit to a course of daily radiation treatments, which could span for 5-8 weeks,” Dr. Zelefsky said.

“We have, in fact, adopted this approach in our clinics during the COVID outbreaks in New York,” he reported. “Most of our patients with unfavorable intermediate- or high-risk disease were initiated on ADT planned for at least 4-6 months before the radiotherapy was initiated. In addition, for these reasons, our preference has been to also offer such patients, if feasible, an ultrahypofractionated treatment course where the radiotherapy course is completed in five fractions over 1-2 weeks.”

This research was funded by the National Institutes of Health. The authors disclosed various grants and personal fees outside the submitted work. Dr. Lawton disclosed that she was a coauthor on RTOG 9413. Dr. Roach and Dr. Zelefsky disclosed no relevant conflicts of interest.

SOURCE: Dee EC et al. JAMA Oncol. 2020 Aug 13. doi: 10.1001/jamaoncol.2020.3545.

Child cases moved up to 9.5% of the cumulative COVID-19 population as the United States added almost 44,000 pediatric cases for the week ending Aug. 27, according to a report from the American Academy of Pediatrics and the Children’s Hospital Association.

The new cases bring the cumulative number of infected children to over 476,000, and that figure represents 9.5% of the over 5 million COVID-19 cases reported among all ages, the AAP and the CHA said in their weekly report. The cumulative number of children covers 49 states (New York is not reporting age distribution), the District of Columbia, New York City, Puerto Rico, and Guam.

From lowest to highest, the states occupying opposite ends of the cumulative proportion spectrum are New Jersey at 3.4% – New York City was lower with a 3.2% figure but is not a state – and Wyoming at 18.3%, the report showed.

Children represent more than 15% of all reported COVID-19 cases in five other states: Tennessee (17.1%), North Dakota (16.0%), Alaska (15.9%), New Mexico (15.7%), and Minnesota (15.1%). The states just above New Jersey are Florida (5.8%), Connecticut (5.9%), and Massachusetts (6.7%). Texas has a rate of 5.6% but has reported age for only 8% of confirmed cases, the AAP and CHA noted.

Children make up a much lower share of COVID-19 hospitalizations – 1.7% of the cumulative number for all ages – although that figure has been slowly rising over the course of the pandemic: it was 1.2% on July 9 and 0.9% on May 8. Arizona (4.1%) is the highest of the 22 states reporting age for hospitalizations and Hawaii (0.6%) is the lowest, based on the AAP/CHA data.

Mortality figures for children continue to be even lower. Nationwide, 0.07% of all COVID-19 deaths occurred in children, and 19 of the 43 states reporting age distributions have had no deaths yet. Pediatric deaths totaled 101 as of Aug. 27, the two groups reported.

rfranki@mdedge.com

Child cases moved up to 9.5% of the cumulative COVID-19 population as the United States added almost 44,000 pediatric cases for the week ending Aug. 27, according to a report from the American Academy of Pediatrics and the Children’s Hospital Association.

The new cases bring the cumulative number of infected children to over 476,000, and that figure represents 9.5% of the over 5 million COVID-19 cases reported among all ages, the AAP and the CHA said in their weekly report. The cumulative number of children covers 49 states (New York is not reporting age distribution), the District of Columbia, New York City, Puerto Rico, and Guam.

From lowest to highest, the states occupying opposite ends of the cumulative proportion spectrum are New Jersey at 3.4% – New York City was lower with a 3.2% figure but is not a state – and Wyoming at 18.3%, the report showed.

Children represent more than 15% of all reported COVID-19 cases in five other states: Tennessee (17.1%), North Dakota (16.0%), Alaska (15.9%), New Mexico (15.7%), and Minnesota (15.1%). The states just above New Jersey are Florida (5.8%), Connecticut (5.9%), and Massachusetts (6.7%). Texas has a rate of 5.6% but has reported age for only 8% of confirmed cases, the AAP and CHA noted.

Children make up a much lower share of COVID-19 hospitalizations – 1.7% of the cumulative number for all ages – although that figure has been slowly rising over the course of the pandemic: it was 1.2% on July 9 and 0.9% on May 8. Arizona (4.1%) is the highest of the 22 states reporting age for hospitalizations and Hawaii (0.6%) is the lowest, based on the AAP/CHA data.

Mortality figures for children continue to be even lower. Nationwide, 0.07% of all COVID-19 deaths occurred in children, and 19 of the 43 states reporting age distributions have had no deaths yet. Pediatric deaths totaled 101 as of Aug. 27, the two groups reported.

rfranki@mdedge.com

Child cases moved up to 9.5% of the cumulative COVID-19 population as the United States added almost 44,000 pediatric cases for the week ending Aug. 27, according to a report from the American Academy of Pediatrics and the Children’s Hospital Association.

The new cases bring the cumulative number of infected children to over 476,000, and that figure represents 9.5% of the over 5 million COVID-19 cases reported among all ages, the AAP and the CHA said in their weekly report. The cumulative number of children covers 49 states (New York is not reporting age distribution), the District of Columbia, New York City, Puerto Rico, and Guam.

From lowest to highest, the states occupying opposite ends of the cumulative proportion spectrum are New Jersey at 3.4% – New York City was lower with a 3.2% figure but is not a state – and Wyoming at 18.3%, the report showed.

Children represent more than 15% of all reported COVID-19 cases in five other states: Tennessee (17.1%), North Dakota (16.0%), Alaska (15.9%), New Mexico (15.7%), and Minnesota (15.1%). The states just above New Jersey are Florida (5.8%), Connecticut (5.9%), and Massachusetts (6.7%). Texas has a rate of 5.6% but has reported age for only 8% of confirmed cases, the AAP and CHA noted.

Children make up a much lower share of COVID-19 hospitalizations – 1.7% of the cumulative number for all ages – although that figure has been slowly rising over the course of the pandemic: it was 1.2% on July 9 and 0.9% on May 8. Arizona (4.1%) is the highest of the 22 states reporting age for hospitalizations and Hawaii (0.6%) is the lowest, based on the AAP/CHA data.

Mortality figures for children continue to be even lower. Nationwide, 0.07% of all COVID-19 deaths occurred in children, and 19 of the 43 states reporting age distributions have had no deaths yet. Pediatric deaths totaled 101 as of Aug. 27, the two groups reported.

rfranki@mdedge.com

The first randomized study to compare continuing versus stopping ACE inhibitors or angiotensin receptor blockers (ARBs) for patients with COVID-19 has shown no difference in key outcomes between the two approaches.

European Society of Cardiology

The BRACE CORONA trial – conducted in patients had been taking an ACE inhibitor or an ARB on a long-term basis and who were subsequently hospitalized with COVID-19 – showed no difference in the primary endpoint of number of days alive and out of hospital among those whose medication was suspended for 30 days and those who continued undergoing treatment with these agents.

“Because these data indicate that there is no clinical benefit from routinely interrupting these medications in hospitalized patients with mild to moderate COVID-19, they should generally be continued for those with an indication,” principal investigator Renato Lopes, MD, of Duke Clinical Research Institute, Durham, N.C., concluded.

The BRACE CORONA trial was presented at the European Society of Cardiology Congress 2020 on Sept. 1.

Dr. Lopes explained that there are two conflicting hypotheses about the role of ACE inhibitors and ARBs in COVID-19.

One hypothesis suggests that use of these drugs could be harmful by increasing the expression of ACE2 receptors (which the SARS-CoV-2 virus uses to gain entry into cells), thus potentially enhancing viral binding and viral entry. The other suggests that ACE inhibitors and ARBs could be protective by reducing production of angiotensin II and enhancing the generation of angiotensin 1-7, which attenuates inflammation and fibrosis and therefore could attenuate lung injury.

The BRACE CORONA trial was an academic-led randomized study that tested two strategies: temporarily stopping the ACE inhibitor/ARB for 30 days or continuing these drugs for patients who had been taking these medications on a long-term basis and were hospitalized with a confirmed diagnosis of COVID-19.

The primary outcome was the number of days alive and out of hospital at 30 days. Patients who were using more than three antihypertensive drugs or sacubitril/valsartan or who were hemodynamically unstable at presentation were excluded from the study.

The trial enrolled 659 patients from 29 sites in Brazil. The mean age of patients was 56 years, 40% were women, and 52% were obese. ACE inhibitors were being taken by 15% of the trial participants; ARBs were being taken by 85%. The median duration of ACE inhibitor/ARB treatment was 5 years.

Patients were a median of 6 days from COVID-19 symptom onset. For 30% of the patients, oxygen saturation was below 94% at entry. In terms of COVID-19 symptoms, 57% were classified as mild, and 43% as moderate.

Those with severe COVID-19 symptoms who needed intubation or vasoactive drugs were excluded. Antihypertensive therapy would generally be discontinued in these patients anyway, Dr. Lopes said.

Results showed that the average number of days alive and out of hospital was 21.9 days for patients who stopped taking ACE inhibitors/ARBs and 22.9 days for patients who continued taking these medications. The average difference between groups was –1.1 days.

The average ratio of days alive and out of hospital between the suspending and continuing groups was 0.95 (95% CI, 0.90-1.01; P = .09).

The proportion of patients alive and out of hospital by the end of 30 days in the suspending ACE inhibitor/ARB group was 91.8% versus 95% in the continuing group.

A similar 30-day mortality rate was seen for patients who continued and those who suspended ACE inhibitor/ARB therapy, at 2.8% and 2.7%, respectively (hazard ratio, 0.97). The median number of days that patients were alive and out of hospital was 25 in both groups.

Dr. Lopes said that there was no difference between the two groups with regard to many other secondary outcomes. These included COVID-19 disease progression (need for intubation, ventilation, need for vasoactive drugs, or imaging results) and cardiovascular endpoints (MI, stroke, thromboembolic events, worsening heart failure, myocarditis, or hypertensive crisis).

“Our results endorse with reliable and more definitive data what most medical and cardiovascular societies are recommending – that patients do not stop ACE inhibitor or ARB medication. This has been based on observational data so far, but BRACE CORONA now provides randomized data to support this recommendation,” Dr. Lopes concluded.

Dr. Lopes noted that several subgroups had been prespecified for analysis. Factors included age, obesity, difference between ACE inhibitors/ARBs, difference in oxygen saturation at presentation, time since COVID-19 symptom onset, degree of lung involvement on CT, and symptom severity on presentation.

“We saw very consistent effects of our main findings across all these subgroups, and we plan to report more details of these in the near future,” he said.
 

Protective for older patients?

The discussant of the study at the ESC Hotline session, Gianfranco Parati, MD, University of Milan-Bicocca and San Luca Hospital, Milan, congratulated Lopes and his team for conducting this important trial at such a difficult time.

He pointed out that patients in the BRACE CORONA trial were quite young (average age, 56 years) and that observational data so far suggest that ACE inhibitors and ARBs have a stronger protective effect in older COVID-19 patients.

He also noted that the percentage of patients alive and out of hospital at 30 days was higher for the patients who continued on treatment in this study (95% vs. 91.8%), which suggested an advantage in maintaining the medication.

Dr. Lopes replied that one-quarter of the population in the BRACE CORONA trial was older than 65 years, which he said was a “reasonable number.”

“Subgroup analysis by age did not show a significant interaction, but the effect of continuing treatment does seem to be more favorable in older patients and also in those who were sicker and had more comorbidities,” he added.

Dr. Parati also suggested that it would have been difficult to discern differences between ACE inhibitors and ARBs in the BRACE CORONA trial, because so few patents were taking ACE inhibitors; the follow-up period of 30 days was relatively short, inasmuch as these drugs may have long-term effects; and it would have been difficult to show differences in the main outcomes used in the study – mortality and time out of hospital – in these patients with mild to moderate disease.

Franz H. Messerli, MD, and Christoph Gräni, MD, University of Bern (Switzerland), said in a joint statement: “The BRACE CORONA trial provides answers to what we know from retrospective studies: if you have already COVID, don’t stop renin-angiotensin system blocker medication.”

But they added that the study does not answer the question about the risk/benefit of ACE inhibitors or ARBs with regard to possible enhanced viral entry through the ACE2 receptor. “What about all those on these drugs who are not infected with COVID? Do they need to stop them? We simply don’t know yet,” they said.

Dr. Messerli and Dr. Gräni added that they would like to see a study that compared patients before SARS-CoV-2 infection who were without hypertension, patients with hypertension who were taking ACE inhibitors or ARBs, and patients with hypertension taking other antihypertensive drugs.

The BRACE CORONA trial was sponsored by D’Or Institute for Research and Education and the Brazilian Clinical Research Institute. Dr. Lopes has disclosed no relevant financial relationships.

A version of this article originally appeared on Medscape.com.

The first randomized study to compare continuing versus stopping ACE inhibitors or angiotensin receptor blockers (ARBs) for patients with COVID-19 has shown no difference in key outcomes between the two approaches.

European Society of Cardiology

The BRACE CORONA trial – conducted in patients had been taking an ACE inhibitor or an ARB on a long-term basis and who were subsequently hospitalized with COVID-19 – showed no difference in the primary endpoint of number of days alive and out of hospital among those whose medication was suspended for 30 days and those who continued undergoing treatment with these agents.

“Because these data indicate that there is no clinical benefit from routinely interrupting these medications in hospitalized patients with mild to moderate COVID-19, they should generally be continued for those with an indication,” principal investigator Renato Lopes, MD, of Duke Clinical Research Institute, Durham, N.C., concluded.

The BRACE CORONA trial was presented at the European Society of Cardiology Congress 2020 on Sept. 1.

Dr. Lopes explained that there are two conflicting hypotheses about the role of ACE inhibitors and ARBs in COVID-19.

One hypothesis suggests that use of these drugs could be harmful by increasing the expression of ACE2 receptors (which the SARS-CoV-2 virus uses to gain entry into cells), thus potentially enhancing viral binding and viral entry. The other suggests that ACE inhibitors and ARBs could be protective by reducing production of angiotensin II and enhancing the generation of angiotensin 1-7, which attenuates inflammation and fibrosis and therefore could attenuate lung injury.

The BRACE CORONA trial was an academic-led randomized study that tested two strategies: temporarily stopping the ACE inhibitor/ARB for 30 days or continuing these drugs for patients who had been taking these medications on a long-term basis and were hospitalized with a confirmed diagnosis of COVID-19.

The primary outcome was the number of days alive and out of hospital at 30 days. Patients who were using more than three antihypertensive drugs or sacubitril/valsartan or who were hemodynamically unstable at presentation were excluded from the study.

The trial enrolled 659 patients from 29 sites in Brazil. The mean age of patients was 56 years, 40% were women, and 52% were obese. ACE inhibitors were being taken by 15% of the trial participants; ARBs were being taken by 85%. The median duration of ACE inhibitor/ARB treatment was 5 years.

Patients were a median of 6 days from COVID-19 symptom onset. For 30% of the patients, oxygen saturation was below 94% at entry. In terms of COVID-19 symptoms, 57% were classified as mild, and 43% as moderate.

Those with severe COVID-19 symptoms who needed intubation or vasoactive drugs were excluded. Antihypertensive therapy would generally be discontinued in these patients anyway, Dr. Lopes said.

Results showed that the average number of days alive and out of hospital was 21.9 days for patients who stopped taking ACE inhibitors/ARBs and 22.9 days for patients who continued taking these medications. The average difference between groups was –1.1 days.

The average ratio of days alive and out of hospital between the suspending and continuing groups was 0.95 (95% CI, 0.90-1.01; P = .09).

The proportion of patients alive and out of hospital by the end of 30 days in the suspending ACE inhibitor/ARB group was 91.8% versus 95% in the continuing group.

A similar 30-day mortality rate was seen for patients who continued and those who suspended ACE inhibitor/ARB therapy, at 2.8% and 2.7%, respectively (hazard ratio, 0.97). The median number of days that patients were alive and out of hospital was 25 in both groups.

Dr. Lopes said that there was no difference between the two groups with regard to many other secondary outcomes. These included COVID-19 disease progression (need for intubation, ventilation, need for vasoactive drugs, or imaging results) and cardiovascular endpoints (MI, stroke, thromboembolic events, worsening heart failure, myocarditis, or hypertensive crisis).

“Our results endorse with reliable and more definitive data what most medical and cardiovascular societies are recommending – that patients do not stop ACE inhibitor or ARB medication. This has been based on observational data so far, but BRACE CORONA now provides randomized data to support this recommendation,” Dr. Lopes concluded.

Dr. Lopes noted that several subgroups had been prespecified for analysis. Factors included age, obesity, difference between ACE inhibitors/ARBs, difference in oxygen saturation at presentation, time since COVID-19 symptom onset, degree of lung involvement on CT, and symptom severity on presentation.

“We saw very consistent effects of our main findings across all these subgroups, and we plan to report more details of these in the near future,” he said.
 

Protective for older patients?

The discussant of the study at the ESC Hotline session, Gianfranco Parati, MD, University of Milan-Bicocca and San Luca Hospital, Milan, congratulated Lopes and his team for conducting this important trial at such a difficult time.

He pointed out that patients in the BRACE CORONA trial were quite young (average age, 56 years) and that observational data so far suggest that ACE inhibitors and ARBs have a stronger protective effect in older COVID-19 patients.

He also noted that the percentage of patients alive and out of hospital at 30 days was higher for the patients who continued on treatment in this study (95% vs. 91.8%), which suggested an advantage in maintaining the medication.

Dr. Lopes replied that one-quarter of the population in the BRACE CORONA trial was older than 65 years, which he said was a “reasonable number.”

“Subgroup analysis by age did not show a significant interaction, but the effect of continuing treatment does seem to be more favorable in older patients and also in those who were sicker and had more comorbidities,” he added.

Dr. Parati also suggested that it would have been difficult to discern differences between ACE inhibitors and ARBs in the BRACE CORONA trial, because so few patents were taking ACE inhibitors; the follow-up period of 30 days was relatively short, inasmuch as these drugs may have long-term effects; and it would have been difficult to show differences in the main outcomes used in the study – mortality and time out of hospital – in these patients with mild to moderate disease.

Franz H. Messerli, MD, and Christoph Gräni, MD, University of Bern (Switzerland), said in a joint statement: “The BRACE CORONA trial provides answers to what we know from retrospective studies: if you have already COVID, don’t stop renin-angiotensin system blocker medication.”

But they added that the study does not answer the question about the risk/benefit of ACE inhibitors or ARBs with regard to possible enhanced viral entry through the ACE2 receptor. “What about all those on these drugs who are not infected with COVID? Do they need to stop them? We simply don’t know yet,” they said.

Dr. Messerli and Dr. Gräni added that they would like to see a study that compared patients before SARS-CoV-2 infection who were without hypertension, patients with hypertension who were taking ACE inhibitors or ARBs, and patients with hypertension taking other antihypertensive drugs.

The BRACE CORONA trial was sponsored by D’Or Institute for Research and Education and the Brazilian Clinical Research Institute. Dr. Lopes has disclosed no relevant financial relationships.

A version of this article originally appeared on Medscape.com.

The first randomized study to compare continuing versus stopping ACE inhibitors or angiotensin receptor blockers (ARBs) for patients with COVID-19 has shown no difference in key outcomes between the two approaches.

European Society of Cardiology

The BRACE CORONA trial – conducted in patients had been taking an ACE inhibitor or an ARB on a long-term basis and who were subsequently hospitalized with COVID-19 – showed no difference in the primary endpoint of number of days alive and out of hospital among those whose medication was suspended for 30 days and those who continued undergoing treatment with these agents.

“Because these data indicate that there is no clinical benefit from routinely interrupting these medications in hospitalized patients with mild to moderate COVID-19, they should generally be continued for those with an indication,” principal investigator Renato Lopes, MD, of Duke Clinical Research Institute, Durham, N.C., concluded.

The BRACE CORONA trial was presented at the European Society of Cardiology Congress 2020 on Sept. 1.

Dr. Lopes explained that there are two conflicting hypotheses about the role of ACE inhibitors and ARBs in COVID-19.

One hypothesis suggests that use of these drugs could be harmful by increasing the expression of ACE2 receptors (which the SARS-CoV-2 virus uses to gain entry into cells), thus potentially enhancing viral binding and viral entry. The other suggests that ACE inhibitors and ARBs could be protective by reducing production of angiotensin II and enhancing the generation of angiotensin 1-7, which attenuates inflammation and fibrosis and therefore could attenuate lung injury.

The BRACE CORONA trial was an academic-led randomized study that tested two strategies: temporarily stopping the ACE inhibitor/ARB for 30 days or continuing these drugs for patients who had been taking these medications on a long-term basis and were hospitalized with a confirmed diagnosis of COVID-19.

The primary outcome was the number of days alive and out of hospital at 30 days. Patients who were using more than three antihypertensive drugs or sacubitril/valsartan or who were hemodynamically unstable at presentation were excluded from the study.

The trial enrolled 659 patients from 29 sites in Brazil. The mean age of patients was 56 years, 40% were women, and 52% were obese. ACE inhibitors were being taken by 15% of the trial participants; ARBs were being taken by 85%. The median duration of ACE inhibitor/ARB treatment was 5 years.

Patients were a median of 6 days from COVID-19 symptom onset. For 30% of the patients, oxygen saturation was below 94% at entry. In terms of COVID-19 symptoms, 57% were classified as mild, and 43% as moderate.

Those with severe COVID-19 symptoms who needed intubation or vasoactive drugs were excluded. Antihypertensive therapy would generally be discontinued in these patients anyway, Dr. Lopes said.

Results showed that the average number of days alive and out of hospital was 21.9 days for patients who stopped taking ACE inhibitors/ARBs and 22.9 days for patients who continued taking these medications. The average difference between groups was –1.1 days.

The average ratio of days alive and out of hospital between the suspending and continuing groups was 0.95 (95% CI, 0.90-1.01; P = .09).

The proportion of patients alive and out of hospital by the end of 30 days in the suspending ACE inhibitor/ARB group was 91.8% versus 95% in the continuing group.

A similar 30-day mortality rate was seen for patients who continued and those who suspended ACE inhibitor/ARB therapy, at 2.8% and 2.7%, respectively (hazard ratio, 0.97). The median number of days that patients were alive and out of hospital was 25 in both groups.

Dr. Lopes said that there was no difference between the two groups with regard to many other secondary outcomes. These included COVID-19 disease progression (need for intubation, ventilation, need for vasoactive drugs, or imaging results) and cardiovascular endpoints (MI, stroke, thromboembolic events, worsening heart failure, myocarditis, or hypertensive crisis).

“Our results endorse with reliable and more definitive data what most medical and cardiovascular societies are recommending – that patients do not stop ACE inhibitor or ARB medication. This has been based on observational data so far, but BRACE CORONA now provides randomized data to support this recommendation,” Dr. Lopes concluded.

Dr. Lopes noted that several subgroups had been prespecified for analysis. Factors included age, obesity, difference between ACE inhibitors/ARBs, difference in oxygen saturation at presentation, time since COVID-19 symptom onset, degree of lung involvement on CT, and symptom severity on presentation.

“We saw very consistent effects of our main findings across all these subgroups, and we plan to report more details of these in the near future,” he said.
 

Protective for older patients?

The discussant of the study at the ESC Hotline session, Gianfranco Parati, MD, University of Milan-Bicocca and San Luca Hospital, Milan, congratulated Lopes and his team for conducting this important trial at such a difficult time.

He pointed out that patients in the BRACE CORONA trial were quite young (average age, 56 years) and that observational data so far suggest that ACE inhibitors and ARBs have a stronger protective effect in older COVID-19 patients.

He also noted that the percentage of patients alive and out of hospital at 30 days was higher for the patients who continued on treatment in this study (95% vs. 91.8%), which suggested an advantage in maintaining the medication.

Dr. Lopes replied that one-quarter of the population in the BRACE CORONA trial was older than 65 years, which he said was a “reasonable number.”

“Subgroup analysis by age did not show a significant interaction, but the effect of continuing treatment does seem to be more favorable in older patients and also in those who were sicker and had more comorbidities,” he added.

Dr. Parati also suggested that it would have been difficult to discern differences between ACE inhibitors and ARBs in the BRACE CORONA trial, because so few patents were taking ACE inhibitors; the follow-up period of 30 days was relatively short, inasmuch as these drugs may have long-term effects; and it would have been difficult to show differences in the main outcomes used in the study – mortality and time out of hospital – in these patients with mild to moderate disease.

Franz H. Messerli, MD, and Christoph Gräni, MD, University of Bern (Switzerland), said in a joint statement: “The BRACE CORONA trial provides answers to what we know from retrospective studies: if you have already COVID, don’t stop renin-angiotensin system blocker medication.”

But they added that the study does not answer the question about the risk/benefit of ACE inhibitors or ARBs with regard to possible enhanced viral entry through the ACE2 receptor. “What about all those on these drugs who are not infected with COVID? Do they need to stop them? We simply don’t know yet,” they said.

Dr. Messerli and Dr. Gräni added that they would like to see a study that compared patients before SARS-CoV-2 infection who were without hypertension, patients with hypertension who were taking ACE inhibitors or ARBs, and patients with hypertension taking other antihypertensive drugs.

The BRACE CORONA trial was sponsored by D’Or Institute for Research and Education and the Brazilian Clinical Research Institute. Dr. Lopes has disclosed no relevant financial relationships.

A version of this article originally appeared on Medscape.com.