Journal of Clinical Outcomes Management

A new, highly contagious subvariant of Omicron has emerged, which some have begun calling “son of Omicron,” but public health officials say it’s too soon to tell what kind of real threat, if any, this new strain will present.

In the meantime, it’s worth watching BA.2, the World Health Organization said. The subvariant has been identified across at least 40 countries, including three cases reported in Houston and several in Washington state.

BA.2 accounts for only a small minority of reported cases so far, including 5% in India, 4% of those in the United Kingdom, and 2% each of cases in Sweden and Singapore.

The one exception is Denmark, a country with robust genetic sequencing abilities, where estimates range from 50% to 81% of cases.

The news throws a little more uncertainty into an already uncertain situation, including how close the world might be to a less life-altering infectious disease.

For example, the world is at an ideal point for a new variant to emerge, WHO Director General Tedros Adhanom Ghebreyesus, PhD, said during a Jan. 24 meeting of the WHO executive board. He also said it’s too early to call an “end game” to the pandemic.

Similarly, Anthony S. Fauci, MD, said on Jan. 19 that it remained “an open question” whether the Omicron variant could hasten endemic COVID-19, a situation where the virus still circulates but is much less disruptive to everyday life.
 

No Pi for you

This could be the first time a coronavirus subvariant rises to the level of a household name, or – if previous variants of the moment have shown us – it could recede from the spotlight.

For example, a lot of focus on the potential of the Mu variant to wreak havoc fizzled out a few weeks after the WHO listed it as a variant of interest on Aug. 30.

Subvariants can feature mutations and other small differences but are not distinct enough from an existing strain to be called a variant on their own and be named after the next letter in the Greek alphabet. That’s why BA.2 is not called the “Pi variant.”

Predicting what’s next for the coronavirus has puzzled many experts throughout the pandemic. That is why many public health officials wait for the WHO to officially designate a strain as a variant of interest or variant of concern before taking action.

At the moment with BA.2, it seems close monitoring is warranted.

Because it’s too early to call, expert predictions about BA.2 vary widely, from worry to cautious optimism.

For example, early data indicates that BA.2 could be more worrisome than original Omicron, Eric Feigl-Ding, ScD, an epidemiologist and health economist, said on Twitter.

Information from Denmark seems to show BA.2 either has “much faster transmission or it evades immunity even more,” he said.

The same day, Jan. 23, Dr. Feigl-Ding tweeted that other data shows the subvariant can spread twice as fast as Omicron, which was already much more contagious than previous versions of the virus.

At the same time, other experts appear less concerned. Robert Garry, PhD, a virologist at Tulane University, New Orleans, told the Washington Post that there is no reason to think BA.2 will be any worse than the original Omicron strain.

So which expert predictions will come closer to BA.2’s potential? For now, it’s just a watch-and-see situation.

For updated information, the website outbreak.info tracks BA.2’s average daily and cumulative prevalence in the United States and in other locations.

Also, if and when WHO experts decide to elevate BA.2 to a variant of interest or a variant of concern, it will be noted on its coronavirus variant tracking website.

A version of this article first appeared on WebMD.com.

A new, highly contagious subvariant of Omicron has emerged, which some have begun calling “son of Omicron,” but public health officials say it’s too soon to tell what kind of real threat, if any, this new strain will present.

In the meantime, it’s worth watching BA.2, the World Health Organization said. The subvariant has been identified across at least 40 countries, including three cases reported in Houston and several in Washington state.

BA.2 accounts for only a small minority of reported cases so far, including 5% in India, 4% of those in the United Kingdom, and 2% each of cases in Sweden and Singapore.

The one exception is Denmark, a country with robust genetic sequencing abilities, where estimates range from 50% to 81% of cases.

The news throws a little more uncertainty into an already uncertain situation, including how close the world might be to a less life-altering infectious disease.

For example, the world is at an ideal point for a new variant to emerge, WHO Director General Tedros Adhanom Ghebreyesus, PhD, said during a Jan. 24 meeting of the WHO executive board. He also said it’s too early to call an “end game” to the pandemic.

Similarly, Anthony S. Fauci, MD, said on Jan. 19 that it remained “an open question” whether the Omicron variant could hasten endemic COVID-19, a situation where the virus still circulates but is much less disruptive to everyday life.
 

No Pi for you

This could be the first time a coronavirus subvariant rises to the level of a household name, or – if previous variants of the moment have shown us – it could recede from the spotlight.

For example, a lot of focus on the potential of the Mu variant to wreak havoc fizzled out a few weeks after the WHO listed it as a variant of interest on Aug. 30.

Subvariants can feature mutations and other small differences but are not distinct enough from an existing strain to be called a variant on their own and be named after the next letter in the Greek alphabet. That’s why BA.2 is not called the “Pi variant.”

Predicting what’s next for the coronavirus has puzzled many experts throughout the pandemic. That is why many public health officials wait for the WHO to officially designate a strain as a variant of interest or variant of concern before taking action.

At the moment with BA.2, it seems close monitoring is warranted.

Because it’s too early to call, expert predictions about BA.2 vary widely, from worry to cautious optimism.

For example, early data indicates that BA.2 could be more worrisome than original Omicron, Eric Feigl-Ding, ScD, an epidemiologist and health economist, said on Twitter.

Information from Denmark seems to show BA.2 either has “much faster transmission or it evades immunity even more,” he said.

The same day, Jan. 23, Dr. Feigl-Ding tweeted that other data shows the subvariant can spread twice as fast as Omicron, which was already much more contagious than previous versions of the virus.

At the same time, other experts appear less concerned. Robert Garry, PhD, a virologist at Tulane University, New Orleans, told the Washington Post that there is no reason to think BA.2 will be any worse than the original Omicron strain.

So which expert predictions will come closer to BA.2’s potential? For now, it’s just a watch-and-see situation.

For updated information, the website outbreak.info tracks BA.2’s average daily and cumulative prevalence in the United States and in other locations.

Also, if and when WHO experts decide to elevate BA.2 to a variant of interest or a variant of concern, it will be noted on its coronavirus variant tracking website.

A version of this article first appeared on WebMD.com.

A new, highly contagious subvariant of Omicron has emerged, which some have begun calling “son of Omicron,” but public health officials say it’s too soon to tell what kind of real threat, if any, this new strain will present.

In the meantime, it’s worth watching BA.2, the World Health Organization said. The subvariant has been identified across at least 40 countries, including three cases reported in Houston and several in Washington state.

BA.2 accounts for only a small minority of reported cases so far, including 5% in India, 4% of those in the United Kingdom, and 2% each of cases in Sweden and Singapore.

The one exception is Denmark, a country with robust genetic sequencing abilities, where estimates range from 50% to 81% of cases.

The news throws a little more uncertainty into an already uncertain situation, including how close the world might be to a less life-altering infectious disease.

For example, the world is at an ideal point for a new variant to emerge, WHO Director General Tedros Adhanom Ghebreyesus, PhD, said during a Jan. 24 meeting of the WHO executive board. He also said it’s too early to call an “end game” to the pandemic.

Similarly, Anthony S. Fauci, MD, said on Jan. 19 that it remained “an open question” whether the Omicron variant could hasten endemic COVID-19, a situation where the virus still circulates but is much less disruptive to everyday life.
 

No Pi for you

This could be the first time a coronavirus subvariant rises to the level of a household name, or – if previous variants of the moment have shown us – it could recede from the spotlight.

For example, a lot of focus on the potential of the Mu variant to wreak havoc fizzled out a few weeks after the WHO listed it as a variant of interest on Aug. 30.

Subvariants can feature mutations and other small differences but are not distinct enough from an existing strain to be called a variant on their own and be named after the next letter in the Greek alphabet. That’s why BA.2 is not called the “Pi variant.”

Predicting what’s next for the coronavirus has puzzled many experts throughout the pandemic. That is why many public health officials wait for the WHO to officially designate a strain as a variant of interest or variant of concern before taking action.

At the moment with BA.2, it seems close monitoring is warranted.

Because it’s too early to call, expert predictions about BA.2 vary widely, from worry to cautious optimism.

For example, early data indicates that BA.2 could be more worrisome than original Omicron, Eric Feigl-Ding, ScD, an epidemiologist and health economist, said on Twitter.

Information from Denmark seems to show BA.2 either has “much faster transmission or it evades immunity even more,” he said.

The same day, Jan. 23, Dr. Feigl-Ding tweeted that other data shows the subvariant can spread twice as fast as Omicron, which was already much more contagious than previous versions of the virus.

At the same time, other experts appear less concerned. Robert Garry, PhD, a virologist at Tulane University, New Orleans, told the Washington Post that there is no reason to think BA.2 will be any worse than the original Omicron strain.

So which expert predictions will come closer to BA.2’s potential? For now, it’s just a watch-and-see situation.

For updated information, the website outbreak.info tracks BA.2’s average daily and cumulative prevalence in the United States and in other locations.

Also, if and when WHO experts decide to elevate BA.2 to a variant of interest or a variant of concern, it will be noted on its coronavirus variant tracking website.

A version of this article first appeared on WebMD.com.

Greater access to next-generation sequencing (NGS) testing enabled by the national coverage determination (NCD) issued by Medicare in 2018 has not narrowed racial and ethnic disparities in uptake, according to an analysis of data from patients with advanced non–small cell lung cancer (aNSCLC), metastatic colorectal cancer, metastatic breast cancer, or advanced melanoma. The finding was reported in JAMA Network Open.

Biomarker testing has become an essential tool in cancer care over the last decade. In 2011, for example, less than 1% of patients with aNSCLC, metastatic colorectal cancer, metastatic breast cancer, and advanced melanoma underwent NGS testing, but by 2019, 40% of patients with these cancers received the testing.

“Next-generation sequencing testing has become increasingly important because it enables identification of multiple biomarkers simultaneously and efficiently while minimizing the number of biopsies required,” wrote the authors, led by William B. Wong, PharmD, of Genentech.

It has been unknown whether for Medicare beneficiaries and the overall population, if the NCD affected health equity issues, the authors wrote. While increased use of appropriate targeted therapies facilitated by NGS testing is associated with improved survival rates in patients with advanced or metastatic cancer, variability in health care coverage policies has posed a significant barrier to obtaining NGS testing for cancer patients, specifically through policy coverage limitations. It has remained unclear if the NCD has influenced NGS testing coverage in insurance types (for example, Medicaid) encompassing a larger population of minority racial and ethnic groups often experiencing poorer care and outcomes.

The retrospective cohort analysis compared EHR data from 280 U.S. cancer clinics in the (800 sites of care) pre- versus post-NCD period for patients with aNSCLC, metastatic colorectal cancer, metastatic breast cancer, or advanced melanoma (January 2011–March 2020). Nearly 70% of all patients in the study were Medicare recipients who needed NCD approval to cover the cost of testing.

Among 92,687 patients (mean age, 66.6 years; 55.7% women), compared with Medicare beneficiaries, changes in pre- to post-NCD NGS testing trends were similar in commercially insured patients (odds ratio, 1.03; 95% CI, 0.98-1.08; P = .25). Pre- to post-NCD NGS testing trends increased at a slower rate among patients in assistance programs (OR, 0.93; 95% CI, 0.87-0.99; P = .03), compared with Medicare beneficiaries. The rate of increase for patients receiving Medicaid was not significantly different statistically compared with those receiving Medicare (OR, 0.92; 95% CI, 0.84-1.01; P = .07). Also, the NCD was not associated with racial and ethnic groups within Medicare beneficiaries alone or across all insurance types.

Compared with non-Hispanic White individuals, increases in average NGS use from the pre-NCD to post-NCD period were 14% lower (OR, 0.86; 95% CI, 0.74-0.99; P = .04) among African American and 23% lower (OR, 0.77; 95% CI, 0.62-0.96; P = .02) among Hispanic/Latino individuals; increases were similar, however, among Asian individuals and other races and ethnicities.

The authors observed that the post-NCD trend of increasing NGS testing seen in Medicare beneficiaries was similarly observed in those with commercial insurance. Testing rate differences, however, widened or were maintained after versus before the NCD in PAP (personal assistance program) and Medicaid beneficiaries relative to Medicare beneficiaries, suggesting that access to NGS testing did not improve equally across insurance types. Since Medicare coverage is determined at the state level, the authors urged research examining individual state coverage policies to further elucidate factors slowing uptake among Medicaid beneficiaries. “Additional efforts beyond coverage policies,” the authors concluded, “are needed to ensure equitable access to the benefits of precision medicine.”

The study was supported by Genentech.

Greater access to next-generation sequencing (NGS) testing enabled by the national coverage determination (NCD) issued by Medicare in 2018 has not narrowed racial and ethnic disparities in uptake, according to an analysis of data from patients with advanced non–small cell lung cancer (aNSCLC), metastatic colorectal cancer, metastatic breast cancer, or advanced melanoma. The finding was reported in JAMA Network Open.

Biomarker testing has become an essential tool in cancer care over the last decade. In 2011, for example, less than 1% of patients with aNSCLC, metastatic colorectal cancer, metastatic breast cancer, and advanced melanoma underwent NGS testing, but by 2019, 40% of patients with these cancers received the testing.

“Next-generation sequencing testing has become increasingly important because it enables identification of multiple biomarkers simultaneously and efficiently while minimizing the number of biopsies required,” wrote the authors, led by William B. Wong, PharmD, of Genentech.

It has been unknown whether for Medicare beneficiaries and the overall population, if the NCD affected health equity issues, the authors wrote. While increased use of appropriate targeted therapies facilitated by NGS testing is associated with improved survival rates in patients with advanced or metastatic cancer, variability in health care coverage policies has posed a significant barrier to obtaining NGS testing for cancer patients, specifically through policy coverage limitations. It has remained unclear if the NCD has influenced NGS testing coverage in insurance types (for example, Medicaid) encompassing a larger population of minority racial and ethnic groups often experiencing poorer care and outcomes.

The retrospective cohort analysis compared EHR data from 280 U.S. cancer clinics in the (800 sites of care) pre- versus post-NCD period for patients with aNSCLC, metastatic colorectal cancer, metastatic breast cancer, or advanced melanoma (January 2011–March 2020). Nearly 70% of all patients in the study were Medicare recipients who needed NCD approval to cover the cost of testing.

Among 92,687 patients (mean age, 66.6 years; 55.7% women), compared with Medicare beneficiaries, changes in pre- to post-NCD NGS testing trends were similar in commercially insured patients (odds ratio, 1.03; 95% CI, 0.98-1.08; P = .25). Pre- to post-NCD NGS testing trends increased at a slower rate among patients in assistance programs (OR, 0.93; 95% CI, 0.87-0.99; P = .03), compared with Medicare beneficiaries. The rate of increase for patients receiving Medicaid was not significantly different statistically compared with those receiving Medicare (OR, 0.92; 95% CI, 0.84-1.01; P = .07). Also, the NCD was not associated with racial and ethnic groups within Medicare beneficiaries alone or across all insurance types.

Compared with non-Hispanic White individuals, increases in average NGS use from the pre-NCD to post-NCD period were 14% lower (OR, 0.86; 95% CI, 0.74-0.99; P = .04) among African American and 23% lower (OR, 0.77; 95% CI, 0.62-0.96; P = .02) among Hispanic/Latino individuals; increases were similar, however, among Asian individuals and other races and ethnicities.

The authors observed that the post-NCD trend of increasing NGS testing seen in Medicare beneficiaries was similarly observed in those with commercial insurance. Testing rate differences, however, widened or were maintained after versus before the NCD in PAP (personal assistance program) and Medicaid beneficiaries relative to Medicare beneficiaries, suggesting that access to NGS testing did not improve equally across insurance types. Since Medicare coverage is determined at the state level, the authors urged research examining individual state coverage policies to further elucidate factors slowing uptake among Medicaid beneficiaries. “Additional efforts beyond coverage policies,” the authors concluded, “are needed to ensure equitable access to the benefits of precision medicine.”

The study was supported by Genentech.

Greater access to next-generation sequencing (NGS) testing enabled by the national coverage determination (NCD) issued by Medicare in 2018 has not narrowed racial and ethnic disparities in uptake, according to an analysis of data from patients with advanced non–small cell lung cancer (aNSCLC), metastatic colorectal cancer, metastatic breast cancer, or advanced melanoma. The finding was reported in JAMA Network Open.

Biomarker testing has become an essential tool in cancer care over the last decade. In 2011, for example, less than 1% of patients with aNSCLC, metastatic colorectal cancer, metastatic breast cancer, and advanced melanoma underwent NGS testing, but by 2019, 40% of patients with these cancers received the testing.

“Next-generation sequencing testing has become increasingly important because it enables identification of multiple biomarkers simultaneously and efficiently while minimizing the number of biopsies required,” wrote the authors, led by William B. Wong, PharmD, of Genentech.

It has been unknown whether for Medicare beneficiaries and the overall population, if the NCD affected health equity issues, the authors wrote. While increased use of appropriate targeted therapies facilitated by NGS testing is associated with improved survival rates in patients with advanced or metastatic cancer, variability in health care coverage policies has posed a significant barrier to obtaining NGS testing for cancer patients, specifically through policy coverage limitations. It has remained unclear if the NCD has influenced NGS testing coverage in insurance types (for example, Medicaid) encompassing a larger population of minority racial and ethnic groups often experiencing poorer care and outcomes.

The retrospective cohort analysis compared EHR data from 280 U.S. cancer clinics in the (800 sites of care) pre- versus post-NCD period for patients with aNSCLC, metastatic colorectal cancer, metastatic breast cancer, or advanced melanoma (January 2011–March 2020). Nearly 70% of all patients in the study were Medicare recipients who needed NCD approval to cover the cost of testing.

Among 92,687 patients (mean age, 66.6 years; 55.7% women), compared with Medicare beneficiaries, changes in pre- to post-NCD NGS testing trends were similar in commercially insured patients (odds ratio, 1.03; 95% CI, 0.98-1.08; P = .25). Pre- to post-NCD NGS testing trends increased at a slower rate among patients in assistance programs (OR, 0.93; 95% CI, 0.87-0.99; P = .03), compared with Medicare beneficiaries. The rate of increase for patients receiving Medicaid was not significantly different statistically compared with those receiving Medicare (OR, 0.92; 95% CI, 0.84-1.01; P = .07). Also, the NCD was not associated with racial and ethnic groups within Medicare beneficiaries alone or across all insurance types.

Compared with non-Hispanic White individuals, increases in average NGS use from the pre-NCD to post-NCD period were 14% lower (OR, 0.86; 95% CI, 0.74-0.99; P = .04) among African American and 23% lower (OR, 0.77; 95% CI, 0.62-0.96; P = .02) among Hispanic/Latino individuals; increases were similar, however, among Asian individuals and other races and ethnicities.

The authors observed that the post-NCD trend of increasing NGS testing seen in Medicare beneficiaries was similarly observed in those with commercial insurance. Testing rate differences, however, widened or were maintained after versus before the NCD in PAP (personal assistance program) and Medicaid beneficiaries relative to Medicare beneficiaries, suggesting that access to NGS testing did not improve equally across insurance types. Since Medicare coverage is determined at the state level, the authors urged research examining individual state coverage policies to further elucidate factors slowing uptake among Medicaid beneficiaries. “Additional efforts beyond coverage policies,” the authors concluded, “are needed to ensure equitable access to the benefits of precision medicine.”

The study was supported by Genentech.

A digital algorithm using 24 patient characteristics identifies far more women who are likely to develop a postpartum hemorrhage than currently used tools to predict the risk for bleeding after delivery, according to a study published in the Journal of the American Medical Informatics Association.

About 1 in 10 of the roughly 700 pregnancy-related deaths in the United States are caused by postpartum hemorrhage, according to the U.S. Centers for Disease Control and Prevention. These deaths disproportionately occur among Black women, for whom studies show the risk of dying from a postpartum hemorrhage is fivefold greater than that of White women.

“Postpartum hemorrhage is a preventable medical emergency but remains the leading cause of maternal mortality globally,” the study’s senior author Li Li, MD, senior vice president of clinical informatics at Sema4, a company that uses artificial intelligence and machine learning to develop data-based clinical tools, told this news organization. “Early intervention is critical for reducing postpartum hemorrhage morbidity and mortality.”
 

Porous predictors

Existing tools for risk prediction are not particularly effective, Dr. Li said. For example, the American College of Obstetricians and Gynecologists’ (ACOG) Safe Motherhood Initiative offers checklists of clinical characteristics to classify women as low, medium, or high risk. However, 40% of the women classified as low risk based on this type of tool experience a hemorrhage.

ACOG also recommends quantifying blood loss during delivery or immediately after to identify women who are hemorrhaging, because imprecise estimates from clinicians may delay urgently needed care. Yet many hospitals have not implemented methods for measuring bleeding, said Dr. Li, who also is an assistant professor of genetics and genomic sciences at the Icahn School of Medicine at Mount Sinai, New York.

To develop a more precise way of identifying women at risk, Dr. Li and colleagues turned to artificial intelligence technology to create a “digital phenotype” based on approximately 72,000 births in the Mount Sinai Health System.

The digital tool retrospectively identified about 6,600 cases of postpartum hemorrhage, about 3.8 times the roughly 1,700 cases that would have been predicted based on methods that estimate blood loss. A blinded physician review of a subset of 45 patient charts – including 26 patients who experienced a hemorrhage, 11 who didn’t, and 6 with unclear outcomes – found that the digital approach was 89% percent accurate at identifying cases, whereas blood loss–based methods were accurate 67% of the time.

Several of the 24 characteristics included in the model appear in other risk predictors, including whether a woman has had a previous cesarean delivery or prior postdelivery bleeding and whether she has anemia or related blood disorders. Among the rest were risk factors that have been identified in the literature, including maternal blood pressure, time from admission to delivery, and average pulse during hospitalization. Five more features were new: red blood cell count and distribution width, mean corpuscular hemoglobin, absolute neutrophil count, and white blood cell count.

“These [new] values are easily obtainable from standard blood draws in the hospital but are not currently used in clinical practice to estimate postpartum hemorrhage risk,” Dr. Li said.

In a related retrospective study, Dr. Li and her colleagues used the new tool to classify women into high, low, or medium risk categories. They found that 28% of the women the algorithm classified as high risk experienced a postpartum hemorrhage compared with 15% to 19% of the women classified as high risk by standard predictive tools. They also identified potential “inflection points” where changes in vital signs may suggest a substantial increase in risk. For example, women whose median blood pressure during labor and delivery was above 132 mm Hg had an 11% average increase in their risk for bleeding. 

By more precisely identifying women at risk, the new method “could be used to pre-emptively allocate resources that can ultimately reduce postpartum hemorrhage morbidity and mortality,” Dr. Li said. Sema4 is launching a prospective clinical trial to further assess the algorithm, she added.  
 

Finding the continuum of risk

Holly Ende, MD, an obstetric anesthesiologist at Vanderbilt University Medical Center, Nashville, Tenn., said approaches that leverage electronic health records to identify women at risk for hemorrhage have many advantages over currently used tools.

“Machine learning models or statistical models are able to take into account many more risk factors and weigh each of those risk factors based on how much they contribute to risk,” Dr. Ende, who was not involved in the new studies, told this news organization. “We can stratify women more on a continuum.”

But digital approaches have potential downsides.

“Machine learning algorithms can be developed in such a way that perpetuates racial bias, and it’s important to be aware of potential biases in coded algorithms,” Dr. Li said. To help reduce such bias, they used a database that included a racially and ethnically diverse patient population, but she acknowledged that additional research is needed.

Dr. Ende, the coauthor of a commentary in Obstetrics & Gynecology on risk assessment for postpartum hemorrhage, said algorithm developers must be sensitive to pre-existing disparities in health care that may affect the data they use to build the software.

She pointed to uterine atony – a known risk factor for hemorrhage – as an example. In her own research, she and her colleagues identified women with atony by searching their medical records for medications used to treat the condition. But when they ran their model, Black women were less likely to develop uterine atony, which the team knew wasn’t true in the real world. They traced the problem to an existing disparity in obstetric care: Black women with uterine atony were less likely than women of other races to receive medications for the condition.

“People need to be cognizant as they are developing these types of prediction models and be extremely careful to avoid perpetuating any disparities in care,” Dr. Ende cautioned. On the other hand, if carefully developed, these tools might also help reduce disparities in health care by standardizing risk stratification and clinical practices, she said.

In addition to independent validation of data-based risk prediction tools, Dr. Ende said ensuring that clinicians are properly trained to use these tools is crucial.

“Implementation may be the biggest limitation,” she said.

Dr. Ende and Dr. Li have disclosed no relevant financial relationships.

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

A digital algorithm using 24 patient characteristics identifies far more women who are likely to develop a postpartum hemorrhage than currently used tools to predict the risk for bleeding after delivery, according to a study published in the Journal of the American Medical Informatics Association.

About 1 in 10 of the roughly 700 pregnancy-related deaths in the United States are caused by postpartum hemorrhage, according to the U.S. Centers for Disease Control and Prevention. These deaths disproportionately occur among Black women, for whom studies show the risk of dying from a postpartum hemorrhage is fivefold greater than that of White women.

“Postpartum hemorrhage is a preventable medical emergency but remains the leading cause of maternal mortality globally,” the study’s senior author Li Li, MD, senior vice president of clinical informatics at Sema4, a company that uses artificial intelligence and machine learning to develop data-based clinical tools, told this news organization. “Early intervention is critical for reducing postpartum hemorrhage morbidity and mortality.”
 

Porous predictors

Existing tools for risk prediction are not particularly effective, Dr. Li said. For example, the American College of Obstetricians and Gynecologists’ (ACOG) Safe Motherhood Initiative offers checklists of clinical characteristics to classify women as low, medium, or high risk. However, 40% of the women classified as low risk based on this type of tool experience a hemorrhage.

ACOG also recommends quantifying blood loss during delivery or immediately after to identify women who are hemorrhaging, because imprecise estimates from clinicians may delay urgently needed care. Yet many hospitals have not implemented methods for measuring bleeding, said Dr. Li, who also is an assistant professor of genetics and genomic sciences at the Icahn School of Medicine at Mount Sinai, New York.

To develop a more precise way of identifying women at risk, Dr. Li and colleagues turned to artificial intelligence technology to create a “digital phenotype” based on approximately 72,000 births in the Mount Sinai Health System.

The digital tool retrospectively identified about 6,600 cases of postpartum hemorrhage, about 3.8 times the roughly 1,700 cases that would have been predicted based on methods that estimate blood loss. A blinded physician review of a subset of 45 patient charts – including 26 patients who experienced a hemorrhage, 11 who didn’t, and 6 with unclear outcomes – found that the digital approach was 89% percent accurate at identifying cases, whereas blood loss–based methods were accurate 67% of the time.

Several of the 24 characteristics included in the model appear in other risk predictors, including whether a woman has had a previous cesarean delivery or prior postdelivery bleeding and whether she has anemia or related blood disorders. Among the rest were risk factors that have been identified in the literature, including maternal blood pressure, time from admission to delivery, and average pulse during hospitalization. Five more features were new: red blood cell count and distribution width, mean corpuscular hemoglobin, absolute neutrophil count, and white blood cell count.

“These [new] values are easily obtainable from standard blood draws in the hospital but are not currently used in clinical practice to estimate postpartum hemorrhage risk,” Dr. Li said.

In a related retrospective study, Dr. Li and her colleagues used the new tool to classify women into high, low, or medium risk categories. They found that 28% of the women the algorithm classified as high risk experienced a postpartum hemorrhage compared with 15% to 19% of the women classified as high risk by standard predictive tools. They also identified potential “inflection points” where changes in vital signs may suggest a substantial increase in risk. For example, women whose median blood pressure during labor and delivery was above 132 mm Hg had an 11% average increase in their risk for bleeding. 

By more precisely identifying women at risk, the new method “could be used to pre-emptively allocate resources that can ultimately reduce postpartum hemorrhage morbidity and mortality,” Dr. Li said. Sema4 is launching a prospective clinical trial to further assess the algorithm, she added.  
 

Finding the continuum of risk

Holly Ende, MD, an obstetric anesthesiologist at Vanderbilt University Medical Center, Nashville, Tenn., said approaches that leverage electronic health records to identify women at risk for hemorrhage have many advantages over currently used tools.

“Machine learning models or statistical models are able to take into account many more risk factors and weigh each of those risk factors based on how much they contribute to risk,” Dr. Ende, who was not involved in the new studies, told this news organization. “We can stratify women more on a continuum.”

But digital approaches have potential downsides.

“Machine learning algorithms can be developed in such a way that perpetuates racial bias, and it’s important to be aware of potential biases in coded algorithms,” Dr. Li said. To help reduce such bias, they used a database that included a racially and ethnically diverse patient population, but she acknowledged that additional research is needed.

Dr. Ende, the coauthor of a commentary in Obstetrics & Gynecology on risk assessment for postpartum hemorrhage, said algorithm developers must be sensitive to pre-existing disparities in health care that may affect the data they use to build the software.

She pointed to uterine atony – a known risk factor for hemorrhage – as an example. In her own research, she and her colleagues identified women with atony by searching their medical records for medications used to treat the condition. But when they ran their model, Black women were less likely to develop uterine atony, which the team knew wasn’t true in the real world. They traced the problem to an existing disparity in obstetric care: Black women with uterine atony were less likely than women of other races to receive medications for the condition.

“People need to be cognizant as they are developing these types of prediction models and be extremely careful to avoid perpetuating any disparities in care,” Dr. Ende cautioned. On the other hand, if carefully developed, these tools might also help reduce disparities in health care by standardizing risk stratification and clinical practices, she said.

In addition to independent validation of data-based risk prediction tools, Dr. Ende said ensuring that clinicians are properly trained to use these tools is crucial.

“Implementation may be the biggest limitation,” she said.

Dr. Ende and Dr. Li have disclosed no relevant financial relationships.

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

A digital algorithm using 24 patient characteristics identifies far more women who are likely to develop a postpartum hemorrhage than currently used tools to predict the risk for bleeding after delivery, according to a study published in the Journal of the American Medical Informatics Association.

About 1 in 10 of the roughly 700 pregnancy-related deaths in the United States are caused by postpartum hemorrhage, according to the U.S. Centers for Disease Control and Prevention. These deaths disproportionately occur among Black women, for whom studies show the risk of dying from a postpartum hemorrhage is fivefold greater than that of White women.

“Postpartum hemorrhage is a preventable medical emergency but remains the leading cause of maternal mortality globally,” the study’s senior author Li Li, MD, senior vice president of clinical informatics at Sema4, a company that uses artificial intelligence and machine learning to develop data-based clinical tools, told this news organization. “Early intervention is critical for reducing postpartum hemorrhage morbidity and mortality.”
 

Porous predictors

Existing tools for risk prediction are not particularly effective, Dr. Li said. For example, the American College of Obstetricians and Gynecologists’ (ACOG) Safe Motherhood Initiative offers checklists of clinical characteristics to classify women as low, medium, or high risk. However, 40% of the women classified as low risk based on this type of tool experience a hemorrhage.

ACOG also recommends quantifying blood loss during delivery or immediately after to identify women who are hemorrhaging, because imprecise estimates from clinicians may delay urgently needed care. Yet many hospitals have not implemented methods for measuring bleeding, said Dr. Li, who also is an assistant professor of genetics and genomic sciences at the Icahn School of Medicine at Mount Sinai, New York.

To develop a more precise way of identifying women at risk, Dr. Li and colleagues turned to artificial intelligence technology to create a “digital phenotype” based on approximately 72,000 births in the Mount Sinai Health System.

The digital tool retrospectively identified about 6,600 cases of postpartum hemorrhage, about 3.8 times the roughly 1,700 cases that would have been predicted based on methods that estimate blood loss. A blinded physician review of a subset of 45 patient charts – including 26 patients who experienced a hemorrhage, 11 who didn’t, and 6 with unclear outcomes – found that the digital approach was 89% percent accurate at identifying cases, whereas blood loss–based methods were accurate 67% of the time.

Several of the 24 characteristics included in the model appear in other risk predictors, including whether a woman has had a previous cesarean delivery or prior postdelivery bleeding and whether she has anemia or related blood disorders. Among the rest were risk factors that have been identified in the literature, including maternal blood pressure, time from admission to delivery, and average pulse during hospitalization. Five more features were new: red blood cell count and distribution width, mean corpuscular hemoglobin, absolute neutrophil count, and white blood cell count.

“These [new] values are easily obtainable from standard blood draws in the hospital but are not currently used in clinical practice to estimate postpartum hemorrhage risk,” Dr. Li said.

In a related retrospective study, Dr. Li and her colleagues used the new tool to classify women into high, low, or medium risk categories. They found that 28% of the women the algorithm classified as high risk experienced a postpartum hemorrhage compared with 15% to 19% of the women classified as high risk by standard predictive tools. They also identified potential “inflection points” where changes in vital signs may suggest a substantial increase in risk. For example, women whose median blood pressure during labor and delivery was above 132 mm Hg had an 11% average increase in their risk for bleeding. 

By more precisely identifying women at risk, the new method “could be used to pre-emptively allocate resources that can ultimately reduce postpartum hemorrhage morbidity and mortality,” Dr. Li said. Sema4 is launching a prospective clinical trial to further assess the algorithm, she added.  
 

Finding the continuum of risk

Holly Ende, MD, an obstetric anesthesiologist at Vanderbilt University Medical Center, Nashville, Tenn., said approaches that leverage electronic health records to identify women at risk for hemorrhage have many advantages over currently used tools.

“Machine learning models or statistical models are able to take into account many more risk factors and weigh each of those risk factors based on how much they contribute to risk,” Dr. Ende, who was not involved in the new studies, told this news organization. “We can stratify women more on a continuum.”

But digital approaches have potential downsides.

“Machine learning algorithms can be developed in such a way that perpetuates racial bias, and it’s important to be aware of potential biases in coded algorithms,” Dr. Li said. To help reduce such bias, they used a database that included a racially and ethnically diverse patient population, but she acknowledged that additional research is needed.

Dr. Ende, the coauthor of a commentary in Obstetrics & Gynecology on risk assessment for postpartum hemorrhage, said algorithm developers must be sensitive to pre-existing disparities in health care that may affect the data they use to build the software.

She pointed to uterine atony – a known risk factor for hemorrhage – as an example. In her own research, she and her colleagues identified women with atony by searching their medical records for medications used to treat the condition. But when they ran their model, Black women were less likely to develop uterine atony, which the team knew wasn’t true in the real world. They traced the problem to an existing disparity in obstetric care: Black women with uterine atony were less likely than women of other races to receive medications for the condition.

“People need to be cognizant as they are developing these types of prediction models and be extremely careful to avoid perpetuating any disparities in care,” Dr. Ende cautioned. On the other hand, if carefully developed, these tools might also help reduce disparities in health care by standardizing risk stratification and clinical practices, she said.

In addition to independent validation of data-based risk prediction tools, Dr. Ende said ensuring that clinicians are properly trained to use these tools is crucial.

“Implementation may be the biggest limitation,” she said.

Dr. Ende and Dr. Li have disclosed no relevant financial relationships.

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

Two years ago, I argued that independent care from nurse practitioners (NPs) and physician assistants (PAs) would not have ill effects on health outcomes. To the surprise of no one, NPs and PAs embraced the argument; physicians clobbered it.

My case had three pegs: One was that medicine isn’t rocket science and clinicians control a lot less than we think we do. The second peg was that technology levels the playing field of clinical care. High-sensitivity troponin assays, for instance, make missing MI a lot less likely. The third peg was empirical: Studies have found little difference in MD versus non–MD-led care. Looking back, I now see empiricism as the weakest part of the argument because the studies had so many limitations.

I update this viewpoint now because health care is increasingly delivered by NPs and PAs. And there are two concerning trends regarding NP education and experience. First is that nurses are turning to advanced practitioner training earlier in their careers – without gathering much bedside experience. And these training programs are increasingly likely to be online, with minimal hands-on clinical tutoring. 

Education and experience pop in my head often. Not every day, but many days I think back to my lucky 7 years in Indiana learning under the supervision of master clinicians – at a time when trainees were allowed the leeway to make decisions ... and mistakes. Then, when I joined private practice, I continued to learn from experienced practitioners.

It would be foolish to argue that training and experience aren’t important.

But here’s the thing: I still don’t see average health outcomes declining as a result of the rise in NPs and PAs. And even if I did, it wouldn’t matter. The rise in nonphysician care will not be undone, at least any time soon.

I will make three points: First, I will bolster two of my old arguments as to why we shouldn’t be worried about non-MD clinicians, then I will propose some ideas to increase confidence in NP and PA care.
 

Health care does not equal health

On the matter of how much clinicians affect outcomes, a recently published randomized controlled trial performed in India found that subsidizing insurance care led to increased utilization of hospital services but had no significant effect on health outcomes. This follows the RAND and Oregon Health Insurance studies in the United States, which largely reported similar results.

It’s about the delta

Logos trumps pathos. Sure, my physician colleagues can tell scary anecdotes of bad outcomes caused by an inexperienced NP or PA. I would counter that by saying I have sat on our hospital’s peer review committee for 2 decades, including the era before NPs or PAs were practicing, and I have plenty of stories of physician errors. These include, of course, my own errors.

Logos: We must consider the difference between non–MD-led care and MD-led care.

My arguments from 2020 remain relevant today. Most medical problems are not engineering puzzles. Many, perhaps most, patients fall into an easy protocol – say, chest pain, dyspnea, or atrial fibrillation. With basic training, a motivated serious person quickly gains skill in recognizing and treating everyday problems.

And just 2 years on, technology further levels the playing field. Consider radiology in 2022 – it’s easy to take for granted the speed of the CT scan, the fidelity of the MRI, and the easy access to both in the U.S. hospital system. Less experienced clinicians have never had more tools to assist with diagnostics and therapeutics.

The expansion of team-based care has also mitigated the effects of inexperience. It took Americans longer than Canadians to figure out how helpful pharmacists could be. Pharmacists in my hospital now help us dose complicated medicines and protect us against prescribing errors.

Then there is the immediate access to online information. Gone are the days when you had to memorize long-QT syndromes. Book knowledge – that I spent years acquiring – now comes in seconds. The other day an NP corrected me. I asked, Are you sure? Boom, she took out her phone and showed me the evidence.

In sum, if it were even possible to measure the clinical competence of care from NP and PA versus physicians, there would be two bell-shaped curves with a tremendous amount of overlap. And that overlap would steadily increase as a given NP or PA gathered experience. (The NP in our electrophysiology division has more than 25 years’ experience in heart rhythm care, and it is common for colleagues to call her before one of us docs. Rightly so.)
 

Three basic proposals regarding NP and PA care

To ensure quality of care, I have three proposals.

It has always seemed strange to me that an NP or PA can flip from one field to another without a period of training. I can’t just change practice from electrophysiology to dermatology without doing a residency. But NPs and PAs can.

My first proposal would be that NPs and PAs spend a substantial period of training in a field before practice – a legit apprenticeship. The duration of this period is a matter of debate, but it ought to be standardized.

My second proposal is that, if physicians are required to pass certification exams, so should NPs. (PAs have an exam every 10 years.) The exam should be the same as (or very similar to) the physician exam, and it should be specific to their field of practice.

While I have argued (and still feel) that the American Board of Internal Medicine brand of certification is dubious, the fact remains that physicians must maintain proficiency in their field. Requiring NPs and PAs to do the same would help foster specialization. And while I can’t cite empirical evidence, specialization seems super-important. We have NPs at my hospital who have been in the same area for years, and they exude clinical competence.

Finally, I have come to believe that the best way for nearly any clinician to practice medicine is as part of a team. (The exception being primary care in rural areas where there are clinician shortages.)

On the matter of team care, I’ve practiced for a long time, but nearly every day I run situations by a colleague; often this person is an NP. The economist Friedrich Hayek proposed that dispersed knowledge always outpaces the wisdom of any individual. That notion pertains well to the increasing complexities and specialization of modern medical practice.

A person who commits to learning one area of medicine, enjoys helping people, asks often for help, and has the support of colleagues is set up to be a successful clinician – whether the letters after their name are APRN, PA, DO, or MD.

Dr. Mandrola practices cardiac electrophysiology in Louisville, Ky. He did not report any relevant financial disclosures. A version of this article first appeared on Medscape.com.

Two years ago, I argued that independent care from nurse practitioners (NPs) and physician assistants (PAs) would not have ill effects on health outcomes. To the surprise of no one, NPs and PAs embraced the argument; physicians clobbered it.

My case had three pegs: One was that medicine isn’t rocket science and clinicians control a lot less than we think we do. The second peg was that technology levels the playing field of clinical care. High-sensitivity troponin assays, for instance, make missing MI a lot less likely. The third peg was empirical: Studies have found little difference in MD versus non–MD-led care. Looking back, I now see empiricism as the weakest part of the argument because the studies had so many limitations.

I update this viewpoint now because health care is increasingly delivered by NPs and PAs. And there are two concerning trends regarding NP education and experience. First is that nurses are turning to advanced practitioner training earlier in their careers – without gathering much bedside experience. And these training programs are increasingly likely to be online, with minimal hands-on clinical tutoring. 

Education and experience pop in my head often. Not every day, but many days I think back to my lucky 7 years in Indiana learning under the supervision of master clinicians – at a time when trainees were allowed the leeway to make decisions ... and mistakes. Then, when I joined private practice, I continued to learn from experienced practitioners.

It would be foolish to argue that training and experience aren’t important.

But here’s the thing: I still don’t see average health outcomes declining as a result of the rise in NPs and PAs. And even if I did, it wouldn’t matter. The rise in nonphysician care will not be undone, at least any time soon.

I will make three points: First, I will bolster two of my old arguments as to why we shouldn’t be worried about non-MD clinicians, then I will propose some ideas to increase confidence in NP and PA care.
 

Health care does not equal health

On the matter of how much clinicians affect outcomes, a recently published randomized controlled trial performed in India found that subsidizing insurance care led to increased utilization of hospital services but had no significant effect on health outcomes. This follows the RAND and Oregon Health Insurance studies in the United States, which largely reported similar results.

It’s about the delta

Logos trumps pathos. Sure, my physician colleagues can tell scary anecdotes of bad outcomes caused by an inexperienced NP or PA. I would counter that by saying I have sat on our hospital’s peer review committee for 2 decades, including the era before NPs or PAs were practicing, and I have plenty of stories of physician errors. These include, of course, my own errors.

Logos: We must consider the difference between non–MD-led care and MD-led care.

My arguments from 2020 remain relevant today. Most medical problems are not engineering puzzles. Many, perhaps most, patients fall into an easy protocol – say, chest pain, dyspnea, or atrial fibrillation. With basic training, a motivated serious person quickly gains skill in recognizing and treating everyday problems.

And just 2 years on, technology further levels the playing field. Consider radiology in 2022 – it’s easy to take for granted the speed of the CT scan, the fidelity of the MRI, and the easy access to both in the U.S. hospital system. Less experienced clinicians have never had more tools to assist with diagnostics and therapeutics.

The expansion of team-based care has also mitigated the effects of inexperience. It took Americans longer than Canadians to figure out how helpful pharmacists could be. Pharmacists in my hospital now help us dose complicated medicines and protect us against prescribing errors.

Then there is the immediate access to online information. Gone are the days when you had to memorize long-QT syndromes. Book knowledge – that I spent years acquiring – now comes in seconds. The other day an NP corrected me. I asked, Are you sure? Boom, she took out her phone and showed me the evidence.

In sum, if it were even possible to measure the clinical competence of care from NP and PA versus physicians, there would be two bell-shaped curves with a tremendous amount of overlap. And that overlap would steadily increase as a given NP or PA gathered experience. (The NP in our electrophysiology division has more than 25 years’ experience in heart rhythm care, and it is common for colleagues to call her before one of us docs. Rightly so.)
 

Three basic proposals regarding NP and PA care

To ensure quality of care, I have three proposals.

It has always seemed strange to me that an NP or PA can flip from one field to another without a period of training. I can’t just change practice from electrophysiology to dermatology without doing a residency. But NPs and PAs can.

My first proposal would be that NPs and PAs spend a substantial period of training in a field before practice – a legit apprenticeship. The duration of this period is a matter of debate, but it ought to be standardized.

My second proposal is that, if physicians are required to pass certification exams, so should NPs. (PAs have an exam every 10 years.) The exam should be the same as (or very similar to) the physician exam, and it should be specific to their field of practice.

While I have argued (and still feel) that the American Board of Internal Medicine brand of certification is dubious, the fact remains that physicians must maintain proficiency in their field. Requiring NPs and PAs to do the same would help foster specialization. And while I can’t cite empirical evidence, specialization seems super-important. We have NPs at my hospital who have been in the same area for years, and they exude clinical competence.

Finally, I have come to believe that the best way for nearly any clinician to practice medicine is as part of a team. (The exception being primary care in rural areas where there are clinician shortages.)

On the matter of team care, I’ve practiced for a long time, but nearly every day I run situations by a colleague; often this person is an NP. The economist Friedrich Hayek proposed that dispersed knowledge always outpaces the wisdom of any individual. That notion pertains well to the increasing complexities and specialization of modern medical practice.

A person who commits to learning one area of medicine, enjoys helping people, asks often for help, and has the support of colleagues is set up to be a successful clinician – whether the letters after their name are APRN, PA, DO, or MD.

Dr. Mandrola practices cardiac electrophysiology in Louisville, Ky. He did not report any relevant financial disclosures. A version of this article first appeared on Medscape.com.

Two years ago, I argued that independent care from nurse practitioners (NPs) and physician assistants (PAs) would not have ill effects on health outcomes. To the surprise of no one, NPs and PAs embraced the argument; physicians clobbered it.

My case had three pegs: One was that medicine isn’t rocket science and clinicians control a lot less than we think we do. The second peg was that technology levels the playing field of clinical care. High-sensitivity troponin assays, for instance, make missing MI a lot less likely. The third peg was empirical: Studies have found little difference in MD versus non–MD-led care. Looking back, I now see empiricism as the weakest part of the argument because the studies had so many limitations.

I update this viewpoint now because health care is increasingly delivered by NPs and PAs. And there are two concerning trends regarding NP education and experience. First is that nurses are turning to advanced practitioner training earlier in their careers – without gathering much bedside experience. And these training programs are increasingly likely to be online, with minimal hands-on clinical tutoring. 

Education and experience pop in my head often. Not every day, but many days I think back to my lucky 7 years in Indiana learning under the supervision of master clinicians – at a time when trainees were allowed the leeway to make decisions ... and mistakes. Then, when I joined private practice, I continued to learn from experienced practitioners.

It would be foolish to argue that training and experience aren’t important.

But here’s the thing: I still don’t see average health outcomes declining as a result of the rise in NPs and PAs. And even if I did, it wouldn’t matter. The rise in nonphysician care will not be undone, at least any time soon.

I will make three points: First, I will bolster two of my old arguments as to why we shouldn’t be worried about non-MD clinicians, then I will propose some ideas to increase confidence in NP and PA care.
 

Health care does not equal health

On the matter of how much clinicians affect outcomes, a recently published randomized controlled trial performed in India found that subsidizing insurance care led to increased utilization of hospital services but had no significant effect on health outcomes. This follows the RAND and Oregon Health Insurance studies in the United States, which largely reported similar results.

It’s about the delta

Logos trumps pathos. Sure, my physician colleagues can tell scary anecdotes of bad outcomes caused by an inexperienced NP or PA. I would counter that by saying I have sat on our hospital’s peer review committee for 2 decades, including the era before NPs or PAs were practicing, and I have plenty of stories of physician errors. These include, of course, my own errors.

Logos: We must consider the difference between non–MD-led care and MD-led care.

My arguments from 2020 remain relevant today. Most medical problems are not engineering puzzles. Many, perhaps most, patients fall into an easy protocol – say, chest pain, dyspnea, or atrial fibrillation. With basic training, a motivated serious person quickly gains skill in recognizing and treating everyday problems.

And just 2 years on, technology further levels the playing field. Consider radiology in 2022 – it’s easy to take for granted the speed of the CT scan, the fidelity of the MRI, and the easy access to both in the U.S. hospital system. Less experienced clinicians have never had more tools to assist with diagnostics and therapeutics.

The expansion of team-based care has also mitigated the effects of inexperience. It took Americans longer than Canadians to figure out how helpful pharmacists could be. Pharmacists in my hospital now help us dose complicated medicines and protect us against prescribing errors.

Then there is the immediate access to online information. Gone are the days when you had to memorize long-QT syndromes. Book knowledge – that I spent years acquiring – now comes in seconds. The other day an NP corrected me. I asked, Are you sure? Boom, she took out her phone and showed me the evidence.

In sum, if it were even possible to measure the clinical competence of care from NP and PA versus physicians, there would be two bell-shaped curves with a tremendous amount of overlap. And that overlap would steadily increase as a given NP or PA gathered experience. (The NP in our electrophysiology division has more than 25 years’ experience in heart rhythm care, and it is common for colleagues to call her before one of us docs. Rightly so.)
 

Three basic proposals regarding NP and PA care

To ensure quality of care, I have three proposals.

It has always seemed strange to me that an NP or PA can flip from one field to another without a period of training. I can’t just change practice from electrophysiology to dermatology without doing a residency. But NPs and PAs can.

My first proposal would be that NPs and PAs spend a substantial period of training in a field before practice – a legit apprenticeship. The duration of this period is a matter of debate, but it ought to be standardized.

My second proposal is that, if physicians are required to pass certification exams, so should NPs. (PAs have an exam every 10 years.) The exam should be the same as (or very similar to) the physician exam, and it should be specific to their field of practice.

While I have argued (and still feel) that the American Board of Internal Medicine brand of certification is dubious, the fact remains that physicians must maintain proficiency in their field. Requiring NPs and PAs to do the same would help foster specialization. And while I can’t cite empirical evidence, specialization seems super-important. We have NPs at my hospital who have been in the same area for years, and they exude clinical competence.

Finally, I have come to believe that the best way for nearly any clinician to practice medicine is as part of a team. (The exception being primary care in rural areas where there are clinician shortages.)

On the matter of team care, I’ve practiced for a long time, but nearly every day I run situations by a colleague; often this person is an NP. The economist Friedrich Hayek proposed that dispersed knowledge always outpaces the wisdom of any individual. That notion pertains well to the increasing complexities and specialization of modern medical practice.

A person who commits to learning one area of medicine, enjoys helping people, asks often for help, and has the support of colleagues is set up to be a successful clinician – whether the letters after their name are APRN, PA, DO, or MD.

Dr. Mandrola practices cardiac electrophysiology in Louisville, Ky. He did not report any relevant financial disclosures. A version of this article first appeared on Medscape.com.

Two new studies from different parts of the world have identified an increase in the incidence of type 1 diabetes in children since the COVID-19 pandemic began, but the reasons still aren’t clear.

The findings from the two studies, in Germany and the United States, align closely, endocrinologist Jane J. Kim, MD, professor of pediatrics and principal investigator of the U.S. study, told this news organization. “I think that the general conclusion based on their data and our data is that there appears to be an increased rate of new type 1 diabetes diagnoses in children since the onset of the pandemic.”

Dr. Kim noted that because her group’s data pertain to just a single center, she is “heartened to see that the [German team’s] general conclusions are the same as ours.” Moreover, she pointed out that other studies examining this question came from Europe early in the pandemic, whereas “now both they [the German group] and we have had the opportunity to look at what’s happening over a longer period of time.”

But the reason for the association remains unclear. Some answers may be forthcoming from a database designed in mid-2020 specifically to examine the relationship between COVID-19 and new-onset diabetes. Called CoviDiab, the registry aims “to establish the extent and characteristics of new-onset, COVID-19–related diabetes and to investigate its pathogenesis, management, and outcomes,” according to the website.

The first new study, a multicenter German diabetes registry study, was published online Jan. 17 in Diabetes Care by Clemens Kamrath, MD, of Justus Liebig University, Giessen, Germany, and colleagues.

The other, from Rady Children’s Hospital of San Diego, was published online Jan. 24 in JAMA Pediatrics by Bethany L. Gottesman, MD, and colleagues, all with the University of California, San Diego.
 

Mechanisms likely to differ for type 1 versus type 2 diabetes

Neither the German nor the U.S. investigators were able to directly correlate current or prior SARS-CoV-2 infection in children with the subsequent development of type 1 diabetes.

Earlier this month, a study from the U.S. Centers for Disease Control and Prevention did examine that issue, but it also included youth with type 2 diabetes and did not separate out the two groups.

Dr. Kim said her institution has also seen an increase in type 2 diabetes among youth since the COVID-19 pandemic began but did not include that in their current article.

“When we started looking at our data, diabetes and COVID-19 in adults had been relatively well established. To see an increase in type 2 [diabetes] was not so surprising to our group. But we had the sense we were seeing more patients with type 1, and when we looked at our hospital that was very much the case. I think that was a surprise to people,” said Dr. Kim.

Although a direct effect of SARS-CoV-2 on pancreatic beta cells has been proposed, in both the German and San Diego datasets the diagnosis of type 1 diabetes was confirmed with autoantibodies that are typically present years prior to the onset of clinical symptoms.

The German group suggests possible other explanations for the link, including the lack of immune system exposure to other common pediatric infections during pandemic-necessitated social distancing – the so-called hygiene hypothesis – as well as the possible role of psychological stress, which several studies have linked to type 1 diabetes.

But as of now, Dr. Kim said, “Nobody really knows.” 
 

Is the effect direct or indirect?

Using data from the multicenter German Diabetes Prospective Follow-up Registry, Dr. Kamrath and colleagues compared the incidence of type 1 diabetes in children and adolescents from Jan. 1, 2020 through June 30, 2021 with the incidence in 2011-2019.

During the pandemic period, a total of 5,162 youth were newly diagnosed with type 1 diabetes at 236 German centers. That incidence, 24.4 per 100,000 patient-years, was significantly higher than the 21.2 per 100,000 patient-years expected based on the prior decade, with an incidence rate ratio of 1.15 (P < .001). The increase was similar in both males and females.

There was a difference by age, however, as the phenomenon appeared to be limited to the preadolescent age groups. The incidence rate ratios (IRRs) for ages below 6 years and 6-11 years were 1.23 and 1.18 (both P < .001), respectively, compared to a nonsignificant IRR of 1.06 (P = .13) in those aged 12-17 years.

Compared with the expected monthly incidence, the observed incidence was significantly higher in June 2020 (IRR, 1.43; P = .003), July 2020 (IRR, 1.48; P < 0.001), March 2021 (IRR, 1.29; P = .028), and June 2021 (IRR, 1.39; P = .01).

Among the 3,851 patients for whom data on type 1 diabetes-associated autoantibodies were available, the adjusted rates of autoantibody negativity did not differ from 2018-2019 during the entire pandemic period or during the year 2020 or the first half of 2021.  

“Therefore, the increase in the incidence of type 1 diabetes in children appears to be due to immune-mediated type 1 diabetes. However, because autoimmunity and progressive beta-cell destruction typically begin long before the clinical diagnosis of type 1 diabetes, we were surprised to see the incidence of type 1 diabetes followed the peak incidence of COVID-19 and also the pandemic containment measures by only approximately 3 months,” Dr. Kamrath and colleagues write.

Taken together, they say, the data suggest that “the impact on type 1 diabetes incidence is not due to infection with SARS-CoV-2 but rather a consequence of environmental changes resulting from the pandemic itself or pandemic containment measures.”
 

Similar findings at a U.S. children’s hospital

In the cross-sectional study in San Diego, Dr. Gottesman and colleagues looked at the electronic medical records (EMRs) at Rady Children’s Hospital for patients aged younger than 19 years with at least one positive type 1 diabetes antibody titer.

During March 19, 2020 to March 18, 2021, a total of 187 children were admitted for new-onset type 1 diabetes, compared with just 119 the previous year, a 57% increase.

From July 2020 through February 2021, the number of new type 1 diabetes diagnoses significantly exceeded the number expected based on a quarterly moving average of each of the preceding 5 years.

Only four of the 187 patients (2.1%) diagnosed during the pandemic period had a COVID-19 infection at the time of presentation. Antibody testing to assess prior infection wasn’t feasible, and now that children are receiving the vaccine – and therefore most will have antibodies – “we’ve lost our window of opportunity to look at that question,” Dr. Kim noted.   

As has been previously shown, there was an increase in the percentage of patients presenting with diabetic ketoacidosis during the pandemic compared with the prior 5 years (49.7% vs. 40.7% requiring insulin infusion). However, there was no difference in mean age at presentation, body mass index, A1c, or percentage requiring admission to intensive care.

Because these data only go through March 2021, Dr. Kim noted, “We need to see what’s happening with these different variants. We’ll have a chance to look in a month or two to see the effects of Omicron on the rates of diabetes in the hospital.”
 

Will CoviDiab answer the question?

Data from CoviDiab will include diabetes type in adults and children, registry coprincipal investigator Francesco Rubino, MD, of King’s College London, told this news organization.

“We aimed at having as many as possible cases of new-onset diabetes for which we can have also a minimum set of clinical data including type of diabetes and A1c. By looking at this information we can infer whether a role of COVID-19 in triggering diabetes is clinically plausible – or not – and what type of diabetes is most frequently associated with COVID-19 as this also speaks about mechanisms of action.”

Dr. Rubino said that the CoviDiab team is approaching the data with the assumption that, at least in adults diagnosed with type 2 diabetes, the explanation might be that the person already had undiagnosed diabetes or that the hyperglycemia may be stress-induced and temporary.

“We’re looking at this question with a skeptical eye ... Is it just an association, or does the virus have a role in inducing diabetes from scratch, or can the virus advance pathophysiology in a way that it ends up in full-blown diabetes in predisposed individuals?”

While no single study will prove that SARS-CoV-2 causes diabetes, “combining observations from various studies and approaches we may get a higher degree of certainty,” Dr. Rubino said, noting that the CoviDiab team plans to publish data from the first 800 cases “soon.”

Dr. Kim has reported no relevant financial relationships. Dr. Rubino has reported receiving grants from Ethicon and Medtronic, personal fees from GI Dynamic, Keyron, Novo Nordisk, Ethicon, and Medtronic.

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

Two new studies from different parts of the world have identified an increase in the incidence of type 1 diabetes in children since the COVID-19 pandemic began, but the reasons still aren’t clear.

The findings from the two studies, in Germany and the United States, align closely, endocrinologist Jane J. Kim, MD, professor of pediatrics and principal investigator of the U.S. study, told this news organization. “I think that the general conclusion based on their data and our data is that there appears to be an increased rate of new type 1 diabetes diagnoses in children since the onset of the pandemic.”

Dr. Kim noted that because her group’s data pertain to just a single center, she is “heartened to see that the [German team’s] general conclusions are the same as ours.” Moreover, she pointed out that other studies examining this question came from Europe early in the pandemic, whereas “now both they [the German group] and we have had the opportunity to look at what’s happening over a longer period of time.”

But the reason for the association remains unclear. Some answers may be forthcoming from a database designed in mid-2020 specifically to examine the relationship between COVID-19 and new-onset diabetes. Called CoviDiab, the registry aims “to establish the extent and characteristics of new-onset, COVID-19–related diabetes and to investigate its pathogenesis, management, and outcomes,” according to the website.

The first new study, a multicenter German diabetes registry study, was published online Jan. 17 in Diabetes Care by Clemens Kamrath, MD, of Justus Liebig University, Giessen, Germany, and colleagues.

The other, from Rady Children’s Hospital of San Diego, was published online Jan. 24 in JAMA Pediatrics by Bethany L. Gottesman, MD, and colleagues, all with the University of California, San Diego.
 

Mechanisms likely to differ for type 1 versus type 2 diabetes

Neither the German nor the U.S. investigators were able to directly correlate current or prior SARS-CoV-2 infection in children with the subsequent development of type 1 diabetes.

Earlier this month, a study from the U.S. Centers for Disease Control and Prevention did examine that issue, but it also included youth with type 2 diabetes and did not separate out the two groups.

Dr. Kim said her institution has also seen an increase in type 2 diabetes among youth since the COVID-19 pandemic began but did not include that in their current article.

“When we started looking at our data, diabetes and COVID-19 in adults had been relatively well established. To see an increase in type 2 [diabetes] was not so surprising to our group. But we had the sense we were seeing more patients with type 1, and when we looked at our hospital that was very much the case. I think that was a surprise to people,” said Dr. Kim.

Although a direct effect of SARS-CoV-2 on pancreatic beta cells has been proposed, in both the German and San Diego datasets the diagnosis of type 1 diabetes was confirmed with autoantibodies that are typically present years prior to the onset of clinical symptoms.

The German group suggests possible other explanations for the link, including the lack of immune system exposure to other common pediatric infections during pandemic-necessitated social distancing – the so-called hygiene hypothesis – as well as the possible role of psychological stress, which several studies have linked to type 1 diabetes.

But as of now, Dr. Kim said, “Nobody really knows.” 
 

Is the effect direct or indirect?

Using data from the multicenter German Diabetes Prospective Follow-up Registry, Dr. Kamrath and colleagues compared the incidence of type 1 diabetes in children and adolescents from Jan. 1, 2020 through June 30, 2021 with the incidence in 2011-2019.

During the pandemic period, a total of 5,162 youth were newly diagnosed with type 1 diabetes at 236 German centers. That incidence, 24.4 per 100,000 patient-years, was significantly higher than the 21.2 per 100,000 patient-years expected based on the prior decade, with an incidence rate ratio of 1.15 (P < .001). The increase was similar in both males and females.

There was a difference by age, however, as the phenomenon appeared to be limited to the preadolescent age groups. The incidence rate ratios (IRRs) for ages below 6 years and 6-11 years were 1.23 and 1.18 (both P < .001), respectively, compared to a nonsignificant IRR of 1.06 (P = .13) in those aged 12-17 years.

Compared with the expected monthly incidence, the observed incidence was significantly higher in June 2020 (IRR, 1.43; P = .003), July 2020 (IRR, 1.48; P < 0.001), March 2021 (IRR, 1.29; P = .028), and June 2021 (IRR, 1.39; P = .01).

Among the 3,851 patients for whom data on type 1 diabetes-associated autoantibodies were available, the adjusted rates of autoantibody negativity did not differ from 2018-2019 during the entire pandemic period or during the year 2020 or the first half of 2021.  

“Therefore, the increase in the incidence of type 1 diabetes in children appears to be due to immune-mediated type 1 diabetes. However, because autoimmunity and progressive beta-cell destruction typically begin long before the clinical diagnosis of type 1 diabetes, we were surprised to see the incidence of type 1 diabetes followed the peak incidence of COVID-19 and also the pandemic containment measures by only approximately 3 months,” Dr. Kamrath and colleagues write.

Taken together, they say, the data suggest that “the impact on type 1 diabetes incidence is not due to infection with SARS-CoV-2 but rather a consequence of environmental changes resulting from the pandemic itself or pandemic containment measures.”
 

Similar findings at a U.S. children’s hospital

In the cross-sectional study in San Diego, Dr. Gottesman and colleagues looked at the electronic medical records (EMRs) at Rady Children’s Hospital for patients aged younger than 19 years with at least one positive type 1 diabetes antibody titer.

During March 19, 2020 to March 18, 2021, a total of 187 children were admitted for new-onset type 1 diabetes, compared with just 119 the previous year, a 57% increase.

From July 2020 through February 2021, the number of new type 1 diabetes diagnoses significantly exceeded the number expected based on a quarterly moving average of each of the preceding 5 years.

Only four of the 187 patients (2.1%) diagnosed during the pandemic period had a COVID-19 infection at the time of presentation. Antibody testing to assess prior infection wasn’t feasible, and now that children are receiving the vaccine – and therefore most will have antibodies – “we’ve lost our window of opportunity to look at that question,” Dr. Kim noted.   

As has been previously shown, there was an increase in the percentage of patients presenting with diabetic ketoacidosis during the pandemic compared with the prior 5 years (49.7% vs. 40.7% requiring insulin infusion). However, there was no difference in mean age at presentation, body mass index, A1c, or percentage requiring admission to intensive care.

Because these data only go through March 2021, Dr. Kim noted, “We need to see what’s happening with these different variants. We’ll have a chance to look in a month or two to see the effects of Omicron on the rates of diabetes in the hospital.”
 

Will CoviDiab answer the question?

Data from CoviDiab will include diabetes type in adults and children, registry coprincipal investigator Francesco Rubino, MD, of King’s College London, told this news organization.

“We aimed at having as many as possible cases of new-onset diabetes for which we can have also a minimum set of clinical data including type of diabetes and A1c. By looking at this information we can infer whether a role of COVID-19 in triggering diabetes is clinically plausible – or not – and what type of diabetes is most frequently associated with COVID-19 as this also speaks about mechanisms of action.”

Dr. Rubino said that the CoviDiab team is approaching the data with the assumption that, at least in adults diagnosed with type 2 diabetes, the explanation might be that the person already had undiagnosed diabetes or that the hyperglycemia may be stress-induced and temporary.

“We’re looking at this question with a skeptical eye ... Is it just an association, or does the virus have a role in inducing diabetes from scratch, or can the virus advance pathophysiology in a way that it ends up in full-blown diabetes in predisposed individuals?”

While no single study will prove that SARS-CoV-2 causes diabetes, “combining observations from various studies and approaches we may get a higher degree of certainty,” Dr. Rubino said, noting that the CoviDiab team plans to publish data from the first 800 cases “soon.”

Dr. Kim has reported no relevant financial relationships. Dr. Rubino has reported receiving grants from Ethicon and Medtronic, personal fees from GI Dynamic, Keyron, Novo Nordisk, Ethicon, and Medtronic.

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

Two new studies from different parts of the world have identified an increase in the incidence of type 1 diabetes in children since the COVID-19 pandemic began, but the reasons still aren’t clear.

The findings from the two studies, in Germany and the United States, align closely, endocrinologist Jane J. Kim, MD, professor of pediatrics and principal investigator of the U.S. study, told this news organization. “I think that the general conclusion based on their data and our data is that there appears to be an increased rate of new type 1 diabetes diagnoses in children since the onset of the pandemic.”

Dr. Kim noted that because her group’s data pertain to just a single center, she is “heartened to see that the [German team’s] general conclusions are the same as ours.” Moreover, she pointed out that other studies examining this question came from Europe early in the pandemic, whereas “now both they [the German group] and we have had the opportunity to look at what’s happening over a longer period of time.”

But the reason for the association remains unclear. Some answers may be forthcoming from a database designed in mid-2020 specifically to examine the relationship between COVID-19 and new-onset diabetes. Called CoviDiab, the registry aims “to establish the extent and characteristics of new-onset, COVID-19–related diabetes and to investigate its pathogenesis, management, and outcomes,” according to the website.

The first new study, a multicenter German diabetes registry study, was published online Jan. 17 in Diabetes Care by Clemens Kamrath, MD, of Justus Liebig University, Giessen, Germany, and colleagues.

The other, from Rady Children’s Hospital of San Diego, was published online Jan. 24 in JAMA Pediatrics by Bethany L. Gottesman, MD, and colleagues, all with the University of California, San Diego.
 

Mechanisms likely to differ for type 1 versus type 2 diabetes

Neither the German nor the U.S. investigators were able to directly correlate current or prior SARS-CoV-2 infection in children with the subsequent development of type 1 diabetes.

Earlier this month, a study from the U.S. Centers for Disease Control and Prevention did examine that issue, but it also included youth with type 2 diabetes and did not separate out the two groups.

Dr. Kim said her institution has also seen an increase in type 2 diabetes among youth since the COVID-19 pandemic began but did not include that in their current article.

“When we started looking at our data, diabetes and COVID-19 in adults had been relatively well established. To see an increase in type 2 [diabetes] was not so surprising to our group. But we had the sense we were seeing more patients with type 1, and when we looked at our hospital that was very much the case. I think that was a surprise to people,” said Dr. Kim.

Although a direct effect of SARS-CoV-2 on pancreatic beta cells has been proposed, in both the German and San Diego datasets the diagnosis of type 1 diabetes was confirmed with autoantibodies that are typically present years prior to the onset of clinical symptoms.

The German group suggests possible other explanations for the link, including the lack of immune system exposure to other common pediatric infections during pandemic-necessitated social distancing – the so-called hygiene hypothesis – as well as the possible role of psychological stress, which several studies have linked to type 1 diabetes.

But as of now, Dr. Kim said, “Nobody really knows.” 
 

Is the effect direct or indirect?

Using data from the multicenter German Diabetes Prospective Follow-up Registry, Dr. Kamrath and colleagues compared the incidence of type 1 diabetes in children and adolescents from Jan. 1, 2020 through June 30, 2021 with the incidence in 2011-2019.

During the pandemic period, a total of 5,162 youth were newly diagnosed with type 1 diabetes at 236 German centers. That incidence, 24.4 per 100,000 patient-years, was significantly higher than the 21.2 per 100,000 patient-years expected based on the prior decade, with an incidence rate ratio of 1.15 (P < .001). The increase was similar in both males and females.

There was a difference by age, however, as the phenomenon appeared to be limited to the preadolescent age groups. The incidence rate ratios (IRRs) for ages below 6 years and 6-11 years were 1.23 and 1.18 (both P < .001), respectively, compared to a nonsignificant IRR of 1.06 (P = .13) in those aged 12-17 years.

Compared with the expected monthly incidence, the observed incidence was significantly higher in June 2020 (IRR, 1.43; P = .003), July 2020 (IRR, 1.48; P < 0.001), March 2021 (IRR, 1.29; P = .028), and June 2021 (IRR, 1.39; P = .01).

Among the 3,851 patients for whom data on type 1 diabetes-associated autoantibodies were available, the adjusted rates of autoantibody negativity did not differ from 2018-2019 during the entire pandemic period or during the year 2020 or the first half of 2021.  

“Therefore, the increase in the incidence of type 1 diabetes in children appears to be due to immune-mediated type 1 diabetes. However, because autoimmunity and progressive beta-cell destruction typically begin long before the clinical diagnosis of type 1 diabetes, we were surprised to see the incidence of type 1 diabetes followed the peak incidence of COVID-19 and also the pandemic containment measures by only approximately 3 months,” Dr. Kamrath and colleagues write.

Taken together, they say, the data suggest that “the impact on type 1 diabetes incidence is not due to infection with SARS-CoV-2 but rather a consequence of environmental changes resulting from the pandemic itself or pandemic containment measures.”
 

Similar findings at a U.S. children’s hospital

In the cross-sectional study in San Diego, Dr. Gottesman and colleagues looked at the electronic medical records (EMRs) at Rady Children’s Hospital for patients aged younger than 19 years with at least one positive type 1 diabetes antibody titer.

During March 19, 2020 to March 18, 2021, a total of 187 children were admitted for new-onset type 1 diabetes, compared with just 119 the previous year, a 57% increase.

From July 2020 through February 2021, the number of new type 1 diabetes diagnoses significantly exceeded the number expected based on a quarterly moving average of each of the preceding 5 years.

Only four of the 187 patients (2.1%) diagnosed during the pandemic period had a COVID-19 infection at the time of presentation. Antibody testing to assess prior infection wasn’t feasible, and now that children are receiving the vaccine – and therefore most will have antibodies – “we’ve lost our window of opportunity to look at that question,” Dr. Kim noted.   

As has been previously shown, there was an increase in the percentage of patients presenting with diabetic ketoacidosis during the pandemic compared with the prior 5 years (49.7% vs. 40.7% requiring insulin infusion). However, there was no difference in mean age at presentation, body mass index, A1c, or percentage requiring admission to intensive care.

Because these data only go through March 2021, Dr. Kim noted, “We need to see what’s happening with these different variants. We’ll have a chance to look in a month or two to see the effects of Omicron on the rates of diabetes in the hospital.”
 

Will CoviDiab answer the question?

Data from CoviDiab will include diabetes type in adults and children, registry coprincipal investigator Francesco Rubino, MD, of King’s College London, told this news organization.

“We aimed at having as many as possible cases of new-onset diabetes for which we can have also a minimum set of clinical data including type of diabetes and A1c. By looking at this information we can infer whether a role of COVID-19 in triggering diabetes is clinically plausible – or not – and what type of diabetes is most frequently associated with COVID-19 as this also speaks about mechanisms of action.”

Dr. Rubino said that the CoviDiab team is approaching the data with the assumption that, at least in adults diagnosed with type 2 diabetes, the explanation might be that the person already had undiagnosed diabetes or that the hyperglycemia may be stress-induced and temporary.

“We’re looking at this question with a skeptical eye ... Is it just an association, or does the virus have a role in inducing diabetes from scratch, or can the virus advance pathophysiology in a way that it ends up in full-blown diabetes in predisposed individuals?”

While no single study will prove that SARS-CoV-2 causes diabetes, “combining observations from various studies and approaches we may get a higher degree of certainty,” Dr. Rubino said, noting that the CoviDiab team plans to publish data from the first 800 cases “soon.”

Dr. Kim has reported no relevant financial relationships. Dr. Rubino has reported receiving grants from Ethicon and Medtronic, personal fees from GI Dynamic, Keyron, Novo Nordisk, Ethicon, and Medtronic.

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

The widely held notion that consuming small to moderate amounts of alcohol is good for cardiovascular health is not supported by the data, the World Heart Federation says in a new policy brief.

In fact, the evidence is clear that any level of drinking can contribute to loss of a healthy life, the organization says.

“Over the past several decades, the prevalence of cardiovascular disease has nearly doubled, and alcohol has played a major role in the incidence of much of it,” the WHF said in the brief.

“The portrayal of alcohol as necessary for a vibrant social life has diverted attention from the harms of alcohol use, as have the frequent and widely publicized claims that moderate drinking, such as a glass of red wine a day, can offer protection against cardiovascular disease,” Monika Arora, PhD, member of the WHF advocacy committee and coauthor of the brief, said in a news release.

“These claims are at best misinformed and at worst an attempt by the alcohol industry to mislead the public about the danger of their product,” Dr. Arora added.

The WHF conclusions follow a report in the Lancet based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), which found that there is no safe level of alcohol consumption.

In 2019, nearly 2.4 million deaths were attributed to alcohol, accounting for 4.3% of all deaths globally and 12.6% of deaths in men 15 to 49 years of age.

Even small amounts of alcohol have been shown to raise the risk for cardiovascular disease, including coronary disease, stroke, heart failure, hypertensive heart disease, cardiomyopathy, atrial fibrillation, and aneurysm, the WHF notes.

Studies that claim otherwise are largely based on purely observational research, which fails to account for relevant cofactors, the organization writes.

Based on their summary of the evidence to date, there is no reliable correlation between moderate alcohol consumption and a lower risk for cardiovascular disease.

Alcohol use is also a “major avoidable risk factor” for cancer, digestive diseases, intentional and unintentional injuries, and several infectious diseases, the WHF says.

Alcohol use also has significant economic and social costs, which include costs to individuals and health systems, productivity losses, as well as the increased risk for violence, homelessness, and criminal activity.

The WHF policy brief calls for “urgent and decisive action” to tackle the unprecedented rise in alcohol-related death and disability worldwide.

Recommended actions include boosting restrictions on alcohol availability; advancing and enforcing drinking and driving countermeasures; increasing access to screening, brief interventions, and treatment for alcohol use disorder; enforcing bans on alcohol advertising; establishing a uniform minimum legal drinking age; and mandating health warnings on alcohol products.

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

The widely held notion that consuming small to moderate amounts of alcohol is good for cardiovascular health is not supported by the data, the World Heart Federation says in a new policy brief.

In fact, the evidence is clear that any level of drinking can contribute to loss of a healthy life, the organization says.

“Over the past several decades, the prevalence of cardiovascular disease has nearly doubled, and alcohol has played a major role in the incidence of much of it,” the WHF said in the brief.

“The portrayal of alcohol as necessary for a vibrant social life has diverted attention from the harms of alcohol use, as have the frequent and widely publicized claims that moderate drinking, such as a glass of red wine a day, can offer protection against cardiovascular disease,” Monika Arora, PhD, member of the WHF advocacy committee and coauthor of the brief, said in a news release.

“These claims are at best misinformed and at worst an attempt by the alcohol industry to mislead the public about the danger of their product,” Dr. Arora added.

The WHF conclusions follow a report in the Lancet based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), which found that there is no safe level of alcohol consumption.

In 2019, nearly 2.4 million deaths were attributed to alcohol, accounting for 4.3% of all deaths globally and 12.6% of deaths in men 15 to 49 years of age.

Even small amounts of alcohol have been shown to raise the risk for cardiovascular disease, including coronary disease, stroke, heart failure, hypertensive heart disease, cardiomyopathy, atrial fibrillation, and aneurysm, the WHF notes.

Studies that claim otherwise are largely based on purely observational research, which fails to account for relevant cofactors, the organization writes.

Based on their summary of the evidence to date, there is no reliable correlation between moderate alcohol consumption and a lower risk for cardiovascular disease.

Alcohol use is also a “major avoidable risk factor” for cancer, digestive diseases, intentional and unintentional injuries, and several infectious diseases, the WHF says.

Alcohol use also has significant economic and social costs, which include costs to individuals and health systems, productivity losses, as well as the increased risk for violence, homelessness, and criminal activity.

The WHF policy brief calls for “urgent and decisive action” to tackle the unprecedented rise in alcohol-related death and disability worldwide.

Recommended actions include boosting restrictions on alcohol availability; advancing and enforcing drinking and driving countermeasures; increasing access to screening, brief interventions, and treatment for alcohol use disorder; enforcing bans on alcohol advertising; establishing a uniform minimum legal drinking age; and mandating health warnings on alcohol products.

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

The widely held notion that consuming small to moderate amounts of alcohol is good for cardiovascular health is not supported by the data, the World Heart Federation says in a new policy brief.

In fact, the evidence is clear that any level of drinking can contribute to loss of a healthy life, the organization says.

“Over the past several decades, the prevalence of cardiovascular disease has nearly doubled, and alcohol has played a major role in the incidence of much of it,” the WHF said in the brief.

“The portrayal of alcohol as necessary for a vibrant social life has diverted attention from the harms of alcohol use, as have the frequent and widely publicized claims that moderate drinking, such as a glass of red wine a day, can offer protection against cardiovascular disease,” Monika Arora, PhD, member of the WHF advocacy committee and coauthor of the brief, said in a news release.

“These claims are at best misinformed and at worst an attempt by the alcohol industry to mislead the public about the danger of their product,” Dr. Arora added.

The WHF conclusions follow a report in the Lancet based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), which found that there is no safe level of alcohol consumption.

In 2019, nearly 2.4 million deaths were attributed to alcohol, accounting for 4.3% of all deaths globally and 12.6% of deaths in men 15 to 49 years of age.

Even small amounts of alcohol have been shown to raise the risk for cardiovascular disease, including coronary disease, stroke, heart failure, hypertensive heart disease, cardiomyopathy, atrial fibrillation, and aneurysm, the WHF notes.

Studies that claim otherwise are largely based on purely observational research, which fails to account for relevant cofactors, the organization writes.

Based on their summary of the evidence to date, there is no reliable correlation between moderate alcohol consumption and a lower risk for cardiovascular disease.

Alcohol use is also a “major avoidable risk factor” for cancer, digestive diseases, intentional and unintentional injuries, and several infectious diseases, the WHF says.

Alcohol use also has significant economic and social costs, which include costs to individuals and health systems, productivity losses, as well as the increased risk for violence, homelessness, and criminal activity.

The WHF policy brief calls for “urgent and decisive action” to tackle the unprecedented rise in alcohol-related death and disability worldwide.

Recommended actions include boosting restrictions on alcohol availability; advancing and enforcing drinking and driving countermeasures; increasing access to screening, brief interventions, and treatment for alcohol use disorder; enforcing bans on alcohol advertising; establishing a uniform minimum legal drinking age; and mandating health warnings on alcohol products.

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

Disruption of the bacteria in the gut is linked with susceptibility to long COVID-19 syndrome, according to new findings.

While links have been found between the gut’s microbiome and COVID-19, as well as other diseases, this is the first published research to show a link specifically to COVID’s long-term effects, the investigators, based at the Chinese University of Hong Kong, wrote in Gut.

Courtesy Dr. Siew Ng

“To our knowledge, this is the first study to show that altered gut microbiome composition is strongly associated with persistent symptoms in patients with COVID-19 up to 6 months after clearance of SARS-CoV-2 virus,” said Siew Ng, MBBS, PhD, associate director at the university’s Center for Gut Microbiota Research.

At three hospitals, the researchers enrolled 106 patients with COVID-19 from February to August 2020 with stool samples at admission and at 1 month and 6 months after discharge, and compared them with people who did not have COVID, recruited in 2019. The severity of COVID in the enrolled patients was mostly mild to moderate.

At 3 months, 86 of the patients with COVID had post–acute COVID-19 syndrome (PACS) – defined as at least one persistent, otherwise unexplained symptom 4 weeks after clearance of the virus. And 81 patients had PACS at 6 months, most commonly fatigue, poor memory, hair loss, anxiety, and trouble sleeping.

Using stool samples for their analysis, the researchers found that, broadly, the diversity of the types of bacteria, and the abundance of these bacteria, were significantly lower at 6 months for those with PACS, compared with those without PACS and with controls (P < .05 and P < .0001, respectively). Among those with PACS, 28 bacteria species were diminished and 14 were enriched, both at baseline and follow-up. Those patients who had COVID but not PACS showed just 25 alterations of bacteria species at the time of hospital admission, and they all normalized by 6 months.

Having respiratory symptoms at 6 months was linked with higher levels of opportunistic pathogens such as Streptococcus anginosus and S. vestibularis. Neuropsychiatric symptoms and fatigue were associated with nosocomial pathogens that are linked to opportunistic infections, such as Clostridium innocuum and Actinomyces naeslundii (P < .05).

Bacteria known for producing butyrate, a beneficial fatty acid, were significantly depleted in those patients with hair loss. And certain of these bacteria, including Bifidobacterium pseudocatenulatum and Faecalibacterium prausnitzii, had the largest inverse correlations with PACS at 6 months (P < .05), the researchers found.

“Particular gut microbial profiles may indicate heightened susceptibility,” Dr. Ng said.

Although the findings were drawn from patients with earlier strains of the COVID-19 virus, the findings still apply to new variants, including Omicron, since these pose the same problem of persistent disruption of the immune system, Dr. Ng said.

Her group is conducting trials to look at how modulating the microbiome might prevent long COVID and boost antibodies after vaccination in high-risk people, she said.

“Gut microbiota influences the health of the host,” Dr. Ng said. “It provides crucial benefits in the form of immune system development, prevention of infections, nutrient acquisition, and brain and nervous system functionality. Considering the millions of people infected during the ongoing pandemic, our findings are a strong impetus for consideration of microbiota modulation to facilitate timely recovery and reduce the burden of post–acute COVID-19 syndrome.”

Courtesy Dr. John Haran

John Haran, MD, PhD, associate professor of microbiology and physiological systems and emergency medicine at the University of Massachusetts, Worcester, said the research adds to the evidence base on the gut microbiome’s links to COVID, but there was likely be no clinical impact yet. Still, he said the findings linking specific species to specific symptoms was particularly interesting.

“Very early on during hospitalization, [the researchers] saw these differences and correlated out with people who have longer symptoms, and especially different groups of people that have longer symptoms, too,” said Dr. Haran, who has done research on the topic. “It’s very different if you have different symptoms, for example, you keep coughing for months versus you have brain fog and fatigue, or other debilitating symptoms.”

Dr. Haran noted that the findings didn’t identify bacteria types especially linked to COVID, but rather species that have already been found to be associated with a “bad” microbiome. He also pointed out that the patients enrolled in the study were not vaccinated, because vaccines weren’t available at the time. Still, further study to see whether modulation of gut bacteria can be a therapy seems worthwhile.

“Microbiome modulation is pretty safe, and that’s really the next big step that needs to be taken in this,” he said.

For now, the findings don’t give the clinician much new ammunition for treatment.

“We’re not there yet,” he added. “It’s not as if clinicians are going to tell their COVID patients: ‘Go out and buy some kale.’ ”

Eugene Chang, MD, professor of medicine at the University of Chicago, who has studied the gut microbiome and gastrointestinal disease, said it’s “too preliminary” to say whether the findings could lead to a clinical impact. The measures used merely identify the microbes present, but not what they are doing.

“These measures are unlikely to perform well enough to be useful for risk assessment or predicting clinical outcomes,” he said. “That being said, advances in technology are being made where next generations of metrics could be developed and useful as stratifiers and predictors of risk.”

Seeing shifting patterns associated with certain symptoms, he said, is “notable because it suggests that the disturbances of the gut microbiota in PACS are significant.”

But he said it’s important to know whether these changes are a cause of PACS in some way or just an effect of it.

“If causative or contributory – this has to be proven – then ‘microbiota modulation’ would make sense and could be a priority for development,” he said. “If merely an effect, these metrics and better ones to come could be useful as predictors or measures of the patient’s general state of health.”

As seen in his group’s work and other work, he said, “the gut microbiota is highly sensitive to changes in their ecosystem, which is influenced by the health state of the patient.”

Dr. Ng, Dr. Haran, and Dr. Chang reported no relevant disclosures.

This article was updated Jan. 27, 2022.

Disruption of the bacteria in the gut is linked with susceptibility to long COVID-19 syndrome, according to new findings.

While links have been found between the gut’s microbiome and COVID-19, as well as other diseases, this is the first published research to show a link specifically to COVID’s long-term effects, the investigators, based at the Chinese University of Hong Kong, wrote in Gut.

Courtesy Dr. Siew Ng

“To our knowledge, this is the first study to show that altered gut microbiome composition is strongly associated with persistent symptoms in patients with COVID-19 up to 6 months after clearance of SARS-CoV-2 virus,” said Siew Ng, MBBS, PhD, associate director at the university’s Center for Gut Microbiota Research.

At three hospitals, the researchers enrolled 106 patients with COVID-19 from February to August 2020 with stool samples at admission and at 1 month and 6 months after discharge, and compared them with people who did not have COVID, recruited in 2019. The severity of COVID in the enrolled patients was mostly mild to moderate.

At 3 months, 86 of the patients with COVID had post–acute COVID-19 syndrome (PACS) – defined as at least one persistent, otherwise unexplained symptom 4 weeks after clearance of the virus. And 81 patients had PACS at 6 months, most commonly fatigue, poor memory, hair loss, anxiety, and trouble sleeping.

Using stool samples for their analysis, the researchers found that, broadly, the diversity of the types of bacteria, and the abundance of these bacteria, were significantly lower at 6 months for those with PACS, compared with those without PACS and with controls (P < .05 and P < .0001, respectively). Among those with PACS, 28 bacteria species were diminished and 14 were enriched, both at baseline and follow-up. Those patients who had COVID but not PACS showed just 25 alterations of bacteria species at the time of hospital admission, and they all normalized by 6 months.

Having respiratory symptoms at 6 months was linked with higher levels of opportunistic pathogens such as Streptococcus anginosus and S. vestibularis. Neuropsychiatric symptoms and fatigue were associated with nosocomial pathogens that are linked to opportunistic infections, such as Clostridium innocuum and Actinomyces naeslundii (P < .05).

Bacteria known for producing butyrate, a beneficial fatty acid, were significantly depleted in those patients with hair loss. And certain of these bacteria, including Bifidobacterium pseudocatenulatum and Faecalibacterium prausnitzii, had the largest inverse correlations with PACS at 6 months (P < .05), the researchers found.

“Particular gut microbial profiles may indicate heightened susceptibility,” Dr. Ng said.

Although the findings were drawn from patients with earlier strains of the COVID-19 virus, the findings still apply to new variants, including Omicron, since these pose the same problem of persistent disruption of the immune system, Dr. Ng said.

Her group is conducting trials to look at how modulating the microbiome might prevent long COVID and boost antibodies after vaccination in high-risk people, she said.

“Gut microbiota influences the health of the host,” Dr. Ng said. “It provides crucial benefits in the form of immune system development, prevention of infections, nutrient acquisition, and brain and nervous system functionality. Considering the millions of people infected during the ongoing pandemic, our findings are a strong impetus for consideration of microbiota modulation to facilitate timely recovery and reduce the burden of post–acute COVID-19 syndrome.”

Courtesy Dr. John Haran

John Haran, MD, PhD, associate professor of microbiology and physiological systems and emergency medicine at the University of Massachusetts, Worcester, said the research adds to the evidence base on the gut microbiome’s links to COVID, but there was likely be no clinical impact yet. Still, he said the findings linking specific species to specific symptoms was particularly interesting.

“Very early on during hospitalization, [the researchers] saw these differences and correlated out with people who have longer symptoms, and especially different groups of people that have longer symptoms, too,” said Dr. Haran, who has done research on the topic. “It’s very different if you have different symptoms, for example, you keep coughing for months versus you have brain fog and fatigue, or other debilitating symptoms.”

Dr. Haran noted that the findings didn’t identify bacteria types especially linked to COVID, but rather species that have already been found to be associated with a “bad” microbiome. He also pointed out that the patients enrolled in the study were not vaccinated, because vaccines weren’t available at the time. Still, further study to see whether modulation of gut bacteria can be a therapy seems worthwhile.

“Microbiome modulation is pretty safe, and that’s really the next big step that needs to be taken in this,” he said.

For now, the findings don’t give the clinician much new ammunition for treatment.

“We’re not there yet,” he added. “It’s not as if clinicians are going to tell their COVID patients: ‘Go out and buy some kale.’ ”

Eugene Chang, MD, professor of medicine at the University of Chicago, who has studied the gut microbiome and gastrointestinal disease, said it’s “too preliminary” to say whether the findings could lead to a clinical impact. The measures used merely identify the microbes present, but not what they are doing.

“These measures are unlikely to perform well enough to be useful for risk assessment or predicting clinical outcomes,” he said. “That being said, advances in technology are being made where next generations of metrics could be developed and useful as stratifiers and predictors of risk.”

Seeing shifting patterns associated with certain symptoms, he said, is “notable because it suggests that the disturbances of the gut microbiota in PACS are significant.”

But he said it’s important to know whether these changes are a cause of PACS in some way or just an effect of it.

“If causative or contributory – this has to be proven – then ‘microbiota modulation’ would make sense and could be a priority for development,” he said. “If merely an effect, these metrics and better ones to come could be useful as predictors or measures of the patient’s general state of health.”

As seen in his group’s work and other work, he said, “the gut microbiota is highly sensitive to changes in their ecosystem, which is influenced by the health state of the patient.”

Dr. Ng, Dr. Haran, and Dr. Chang reported no relevant disclosures.

This article was updated Jan. 27, 2022.

Disruption of the bacteria in the gut is linked with susceptibility to long COVID-19 syndrome, according to new findings.

While links have been found between the gut’s microbiome and COVID-19, as well as other diseases, this is the first published research to show a link specifically to COVID’s long-term effects, the investigators, based at the Chinese University of Hong Kong, wrote in Gut.

Courtesy Dr. Siew Ng

“To our knowledge, this is the first study to show that altered gut microbiome composition is strongly associated with persistent symptoms in patients with COVID-19 up to 6 months after clearance of SARS-CoV-2 virus,” said Siew Ng, MBBS, PhD, associate director at the university’s Center for Gut Microbiota Research.

At three hospitals, the researchers enrolled 106 patients with COVID-19 from February to August 2020 with stool samples at admission and at 1 month and 6 months after discharge, and compared them with people who did not have COVID, recruited in 2019. The severity of COVID in the enrolled patients was mostly mild to moderate.

At 3 months, 86 of the patients with COVID had post–acute COVID-19 syndrome (PACS) – defined as at least one persistent, otherwise unexplained symptom 4 weeks after clearance of the virus. And 81 patients had PACS at 6 months, most commonly fatigue, poor memory, hair loss, anxiety, and trouble sleeping.

Using stool samples for their analysis, the researchers found that, broadly, the diversity of the types of bacteria, and the abundance of these bacteria, were significantly lower at 6 months for those with PACS, compared with those without PACS and with controls (P < .05 and P < .0001, respectively). Among those with PACS, 28 bacteria species were diminished and 14 were enriched, both at baseline and follow-up. Those patients who had COVID but not PACS showed just 25 alterations of bacteria species at the time of hospital admission, and they all normalized by 6 months.

Having respiratory symptoms at 6 months was linked with higher levels of opportunistic pathogens such as Streptococcus anginosus and S. vestibularis. Neuropsychiatric symptoms and fatigue were associated with nosocomial pathogens that are linked to opportunistic infections, such as Clostridium innocuum and Actinomyces naeslundii (P < .05).

Bacteria known for producing butyrate, a beneficial fatty acid, were significantly depleted in those patients with hair loss. And certain of these bacteria, including Bifidobacterium pseudocatenulatum and Faecalibacterium prausnitzii, had the largest inverse correlations with PACS at 6 months (P < .05), the researchers found.

“Particular gut microbial profiles may indicate heightened susceptibility,” Dr. Ng said.

Although the findings were drawn from patients with earlier strains of the COVID-19 virus, the findings still apply to new variants, including Omicron, since these pose the same problem of persistent disruption of the immune system, Dr. Ng said.

Her group is conducting trials to look at how modulating the microbiome might prevent long COVID and boost antibodies after vaccination in high-risk people, she said.

“Gut microbiota influences the health of the host,” Dr. Ng said. “It provides crucial benefits in the form of immune system development, prevention of infections, nutrient acquisition, and brain and nervous system functionality. Considering the millions of people infected during the ongoing pandemic, our findings are a strong impetus for consideration of microbiota modulation to facilitate timely recovery and reduce the burden of post–acute COVID-19 syndrome.”

Courtesy Dr. John Haran

John Haran, MD, PhD, associate professor of microbiology and physiological systems and emergency medicine at the University of Massachusetts, Worcester, said the research adds to the evidence base on the gut microbiome’s links to COVID, but there was likely be no clinical impact yet. Still, he said the findings linking specific species to specific symptoms was particularly interesting.

“Very early on during hospitalization, [the researchers] saw these differences and correlated out with people who have longer symptoms, and especially different groups of people that have longer symptoms, too,” said Dr. Haran, who has done research on the topic. “It’s very different if you have different symptoms, for example, you keep coughing for months versus you have brain fog and fatigue, or other debilitating symptoms.”

Dr. Haran noted that the findings didn’t identify bacteria types especially linked to COVID, but rather species that have already been found to be associated with a “bad” microbiome. He also pointed out that the patients enrolled in the study were not vaccinated, because vaccines weren’t available at the time. Still, further study to see whether modulation of gut bacteria can be a therapy seems worthwhile.

“Microbiome modulation is pretty safe, and that’s really the next big step that needs to be taken in this,” he said.

For now, the findings don’t give the clinician much new ammunition for treatment.

“We’re not there yet,” he added. “It’s not as if clinicians are going to tell their COVID patients: ‘Go out and buy some kale.’ ”

Eugene Chang, MD, professor of medicine at the University of Chicago, who has studied the gut microbiome and gastrointestinal disease, said it’s “too preliminary” to say whether the findings could lead to a clinical impact. The measures used merely identify the microbes present, but not what they are doing.

“These measures are unlikely to perform well enough to be useful for risk assessment or predicting clinical outcomes,” he said. “That being said, advances in technology are being made where next generations of metrics could be developed and useful as stratifiers and predictors of risk.”

Seeing shifting patterns associated with certain symptoms, he said, is “notable because it suggests that the disturbances of the gut microbiota in PACS are significant.”

But he said it’s important to know whether these changes are a cause of PACS in some way or just an effect of it.

“If causative or contributory – this has to be proven – then ‘microbiota modulation’ would make sense and could be a priority for development,” he said. “If merely an effect, these metrics and better ones to come could be useful as predictors or measures of the patient’s general state of health.”

As seen in his group’s work and other work, he said, “the gut microbiota is highly sensitive to changes in their ecosystem, which is influenced by the health state of the patient.”

Dr. Ng, Dr. Haran, and Dr. Chang reported no relevant disclosures.

This article was updated Jan. 27, 2022.

Can you tell which of the following statements are true and which are false?

COVID-19 is not a threat to younger people, and only those who have other medical conditions are dying from it.

The mRNA vaccines developed to prevent the coronavirus alter your genes, can make your body “magnetic,” and are killing more people than the virus itself.

President Joe Biden’s climate change plan calls for a ban on meat consumption to cut greenhouse gas emissions.

The 2020 presidential election was rigged and stolen.

If you guessed that all of these claims are false, you’re right – take a bow. Not a single one of these statements has any factual support, according to scientific research, legal rulings, and legitimate government authorities.

And yet public opinion surveys show millions of Americans, and others around the world, believe some of these falsehoods are true and can’t be convinced otherwise.

Social media, politicians and partisan websites, TV programs, and commentators have widely circulated these and other unfounded claims so frequently that many people say they simply can’t tell what’s objectively true and not anymore.

So much so, the authors of a fascinating new research study have concluded we are living in a “post-truth era,” with baseless beliefs and subjective opinions given a higher priority than verifiable facts.

The new study – The Rise and Fall of Rationality in Language, published in the Proceedings of the National Academy of Sciences – found that facts have become less important in public discourse.

As a result, unsupported beliefs have taken precedent over readily identifiable truths in discussions of health, science, and politics. The upshot: “Feelings trump facts” in social media, news reports, books, and other sources of information.

And here’s the kicker: The trend did not begin with the rise of former President Donald Trump, the COVID-19 pandemic, or the advent of social media; in fact, it has been growing for much longer than you might think.

“While the current ‘post-truth era’ has taken many by surprise, the study shows that over the past 40 years, public interest has undergone an accelerating shift from the collective to the individual, and from rationality towards emotion,” concluded the researchers from Indiana University and Wageningen University & Research in the Netherlands.

“Our work suggests that the societal balance between emotion and reason has shifted back to what it used to be around 150 years ago,” says lead researcher Marten Scheffer, PhD, a professor in the department of environmental sciences at WUR. “This implies that scientists, experts, and policymakers will have to think about the best way to respond to that social change.”
 

Researchers surprised by findings

The findings are based on a very detailed analysis of language from millions of books, newspaper articles, Google searches, TV reports, social media posts, and other sources dating back to 1850.

The researchers analyzed how often the 5,000 most used words appeared over the past 170 years and found that the use of those having to do with facts and reasoning, such as “determine” and “conclusion,” has fallen dramatically since 1980. Meanwhile, the use of words related to human emotion, such as “feel” and “believe,” have skyrocketed.

Dr. Scheffer notes rapid developments in science and technology from 1850 to 1980 had profound social and economic benefits that helped boost the status of the scientific approach. That shift in public attitudes had ripple effects on culture, society, education, politics, and religion – and “the role of spiritualism dwindled” in the modern world, he says.

But since 1980, that trend has seen a major reversal, with beliefs becoming more important than facts to many people, he says. At the same time, trust in science and scientists has fallen.

Dr. Scheffer says the researchers expected to find some evidence of a swing toward more belief-based sentiments during the Trump era but were surprised to discover how strong it is and that the trend has actually been a long time coming.

“The shift in interest from rational to intuitive/emotional is pretty obvious now in the post-truth political and social media discussion,” he says. “However, our work shows that it already started in the 1980s. For me personally, that went under the radar, except perhaps for the rise of alternative (to religion) forms of spirituality.

“We were especially struck by how strong the patterns are and how universal they appear across languages, nonfiction and fiction, and even in The New York Times.”

In the political world, the implications are significant enough – impacting policies and politicians on both sides of the aisle and across the globe. Just look at the deepening political divisions during the Trump presidency.

But for health and science, the spread of misinformation and falsehoods can be matters of life or death, as we have seen in the politically charged debates over how best to combat COVID-19 and global climate change.

“Our public debate seems increasingly driven by what people want to be true rather than what is actually true. As a scientist, that worries me,” says study co-author Johan Bollen, PhD, a professor of informatics at Indiana University.

“As a society, we are now faced with major collective problems that we need to approach from a pragmatic, rational, and objective perspective to be successful,” he says. “After all, global warming doesn’t care about whether you believe in it or not … but we will all suffer as a society if we fail to take adequate measures.”

For WUR co-researcher Ingrid van de Leemput, the trend isn’t merely academic; she’s seen it play out in her personal life.

“I do speak to people that, for instance, think the vaccines are poison,” she says. “I’m also on Twitter, and there, I’m every day surprised about how easily many people form their opinions, based on feelings, on what others say, or on some unfounded source.”

Public health experts say the embrace of personal beliefs over facts is one reason only 63% of Americans have been vaccinated against COVID-19. The result: millions of preventable infections among those who downplay the risks of the virus and reject the strong scientific evidence of vaccine safety and effectiveness.

“None of this really surprises me,” Johns Hopkins University social and behavioral scientist Rupali Limaye, PhD, says of the new study findings. Dr. Limaye coauthored a paper in 2016 in JAMA Pediatrics about how to talk to parents about vaccine hesitancy and the fact that we’re living in what they called “this post-truth era.”

Dr. Limaye says the trend has made it difficult for doctors, scientists, and health authorities to make fact-based arguments for COVID-19 vaccination, mask-wearing, social distancing, and other measures to control the virus.

“It’s been really hard being a scientist to hear people say, ‘Well, that’s not true’ when we say something very basic that I think all of us can agree on – like the grass is green,” she says. “To be honest, I worry that a lot of scientists are going to quit being in science because they’re exhausted.”
 

What’s driving the trend?

So, what’s behind the embrace of “alternative facts,” as former White House counselor Kellyanne Conway put it so brazenly in 2017, in defending the White House’s false claims that Trump’s inauguration crowd was the largest ever?

Dr. Scheffer and colleagues identified a handful of things that have encouraged the embrace of falsehoods over facts in recent years.

• The Internet: Its rise in the late 1980s, and its growing role as a primary source of news and information, has allowed more belief-based misinformation to flourish and spread like wildfire.
• Social media: The new study found the use of sentiment- and intuition-related words accelerated around 2007, along with a global surge in social media that catapulted Facebook, Twitter, and others into the mainstream, replacing more traditional fact-based media (i.e., newspapers and magazines).
• The 2007 financial crisis: The downturn in the global economy meant more people were dealing with job stress, investment losses, and other problems that fed the interest in belief-based, anti-establishment social media posts.
• Conspiracy theories: Falsehoods involving hidden political agendas, shadow “elites,” and wealthy people with dark motives tend to thrive during times of crisis and societal anxiety. “Conspiracy theories originate particularly in times of uncertainty and crisis and generally depict established institutions as hiding the truth and sustaining an unfair situation,” the researchers noted. “As a result, they may find fertile grounds on social media platforms promulgating a sense of unfairness, subsequently feeding anti-system sentiments.”

Dr. Scheffer says that growing political divisions during the Trump era have widened the fact-vs.-fiction divide. The ex-president voiced many anti-science views on global climate change, for instance, and spread so many falsehoods about COVID-19 and the 2020 election that Facebook, Twitter, and YouTube suspended his accounts.

Yet Trump remains a popular figure among Republicans, with most saying in a December poll they believe his baseless claims that the 2020 election was “rigged” and “stolen,” despite all credible, easily accessible evidence that it was secure, according to a recent poll by the University of Massachusetts at Amherst.

More than 60 courts have rejected Trump’s lawsuits seeking to overturn the election results. All 50 states, the District of Columbia, and both branches of Congress have certified the election results, giving Biden the White House. Even Trump’s own Justice Department confirmed that the 2020 election was free and fair.

Nevertheless, the University of Massachusetts survey found that most Republicans believe one or more conspiracy theories floated by the former president and those pushing his “big lie” that Democrats rigged the election to elect Biden.

Ed Berliner, an Emmy Award-winning broadcast journalist and media consultant, suggests something else is driving the spread of misinformation: the pursuit of ratings by cable TV and media companies to boost ad and subscriber revenues.

As a former executive producer and syndicated cable TV show host, he says he has seen firsthand how facts are often lost in opinion-driven news programs, even on network programs claiming to offer “fair and balanced” journalism.

“Propaganda is the new currency in America, and those who do not fight back against it are doomed to be overrun by the misinformation,” says Mr. Berliner, host of The Man in the Arena and CEO of Entourage Media LLC.

“The broadcast news media has to stop this incessant ‘infotainment’ prattle, stop trying to nuzzle up to a soft side, and bear down on hard facts, exposing the lies and refusing to back down.”
 

Public health implications

Public health and media experts alike say the PNAS study findings are disheartening but underscore the need for doctors and scientists to do a better job of communicating about COVID-19 and other pressing issues.

Dr. Limaye, from Johns Hopkins, is particularly concerned about the rise in conspiracy theories that has led to COVID-19 vaccine hesitancy.

“When we speak to individuals about getting the COVID vaccine…the types of concerns that come up now are very different than they were 8 years ago,” she says. “The comments we used to hear were much more related to vaccine safety. [People] would say, ‘I’m worried about an ingredient in the vaccine’ or ‘I’m worried that my kiddo has to get three different shots within 6 months to have a series dose completed.’”

But now, a lot of comments they receive are about government and pharma conspiracies.

What that means is doctors and scientists must do more than simply say “here are the facts” and “trust me, I’m a doctor or a scientist,” she says. And these approaches don’t only apply to public health.

“It’s funny, because when we talk to climate change scientists, as vaccine [specialists], we’ll say we can’t believe that people think COVID is a hoax,” she says. “And they’re like, ‘Hold my beer, we’ve been dealing with this for 20 years. Hello, it’s just your guys’ turn to deal with this public denial of science.’”

Dr. Limaye is also concerned about the impacts on funding for scientific research.

“There’s always been a really strong bipartisan effort with regards to funding for science, when you look at Congress and when you look at appropriations,” she says. “But what ended up happening, especially with the Trump administration, was that there was a real shift in that. We’ve never really seen that before in past generations.”

So, what’s the big take-home message?

Dr. Limaye believes doctors and public health experts must show more empathy – and not be combative or arrogant – in communicating science in one-on-one conversations. This month, she’s launching a new course for parents, school administrators, and nurses on how to do precisely that.

“It’s really all about how to have hard conversations with people who might be anti-science,” she says. “It’s being empathetic and not being dismissive. But it’s hard work, and I think a lot of people are just not cut out for it and just don’t have the time for it…You can’t just say, ‘Well, this is science, and I’m a doctor’ – that doesn’t work anymore.”

Brendan Nyhan, PhD, a Dartmouth College political scientist, echoes those sentiments in a separate paper recently published in the Proceedings of the National Academy of Sciences. In fact, he suggests that providing accurate, fact-based information to counter false claims may actually backfire and reinforce some people’s unfounded beliefs.

“One response to the prevalence of mistaken beliefs is to try to set the record straight by providing accurate information – for instance, by providing evidence of the scientific consensus on climate change,” he writes. “The failures of this approach, which is sometimes referred to as the ‘deficit model’ in science communication, are well-known.”

Dr. Nyhan argues two things make some people more prone to believe falsehoods:

What scientists call “ingrouping,” a kind of tribal mentality that makes some people choose social identity or politics over truth-seeking and demonize others who don’t agree with their views

The rise of high-profile political figures, such as Trump, who encourage their followers to indulge in their desire for “identify-affirming misinformation”

Dr. Scheffer says the most important thing for doctors, health experts, and scientists to recognize is that it’s crucial to gain the trust of someone who may believe fictions over facts to make any persuasive argument on COVID-19 or any other issue.

He also has a standard response to those who present falsehoods to him as facts that he suggests anyone can use: “That is interesting. Would you mind helping me understand how you came to that opinion?”

A version of this article first appeared on WebMD.com.

Can you tell which of the following statements are true and which are false?

COVID-19 is not a threat to younger people, and only those who have other medical conditions are dying from it.

The mRNA vaccines developed to prevent the coronavirus alter your genes, can make your body “magnetic,” and are killing more people than the virus itself.

President Joe Biden’s climate change plan calls for a ban on meat consumption to cut greenhouse gas emissions.

The 2020 presidential election was rigged and stolen.

If you guessed that all of these claims are false, you’re right – take a bow. Not a single one of these statements has any factual support, according to scientific research, legal rulings, and legitimate government authorities.

And yet public opinion surveys show millions of Americans, and others around the world, believe some of these falsehoods are true and can’t be convinced otherwise.

Social media, politicians and partisan websites, TV programs, and commentators have widely circulated these and other unfounded claims so frequently that many people say they simply can’t tell what’s objectively true and not anymore.

So much so, the authors of a fascinating new research study have concluded we are living in a “post-truth era,” with baseless beliefs and subjective opinions given a higher priority than verifiable facts.

The new study – The Rise and Fall of Rationality in Language, published in the Proceedings of the National Academy of Sciences – found that facts have become less important in public discourse.

As a result, unsupported beliefs have taken precedent over readily identifiable truths in discussions of health, science, and politics. The upshot: “Feelings trump facts” in social media, news reports, books, and other sources of information.

And here’s the kicker: The trend did not begin with the rise of former President Donald Trump, the COVID-19 pandemic, or the advent of social media; in fact, it has been growing for much longer than you might think.

“While the current ‘post-truth era’ has taken many by surprise, the study shows that over the past 40 years, public interest has undergone an accelerating shift from the collective to the individual, and from rationality towards emotion,” concluded the researchers from Indiana University and Wageningen University & Research in the Netherlands.

“Our work suggests that the societal balance between emotion and reason has shifted back to what it used to be around 150 years ago,” says lead researcher Marten Scheffer, PhD, a professor in the department of environmental sciences at WUR. “This implies that scientists, experts, and policymakers will have to think about the best way to respond to that social change.”
 

Researchers surprised by findings

The findings are based on a very detailed analysis of language from millions of books, newspaper articles, Google searches, TV reports, social media posts, and other sources dating back to 1850.

The researchers analyzed how often the 5,000 most used words appeared over the past 170 years and found that the use of those having to do with facts and reasoning, such as “determine” and “conclusion,” has fallen dramatically since 1980. Meanwhile, the use of words related to human emotion, such as “feel” and “believe,” have skyrocketed.

Dr. Scheffer notes rapid developments in science and technology from 1850 to 1980 had profound social and economic benefits that helped boost the status of the scientific approach. That shift in public attitudes had ripple effects on culture, society, education, politics, and religion – and “the role of spiritualism dwindled” in the modern world, he says.

But since 1980, that trend has seen a major reversal, with beliefs becoming more important than facts to many people, he says. At the same time, trust in science and scientists has fallen.

Dr. Scheffer says the researchers expected to find some evidence of a swing toward more belief-based sentiments during the Trump era but were surprised to discover how strong it is and that the trend has actually been a long time coming.

“The shift in interest from rational to intuitive/emotional is pretty obvious now in the post-truth political and social media discussion,” he says. “However, our work shows that it already started in the 1980s. For me personally, that went under the radar, except perhaps for the rise of alternative (to religion) forms of spirituality.

“We were especially struck by how strong the patterns are and how universal they appear across languages, nonfiction and fiction, and even in The New York Times.”

In the political world, the implications are significant enough – impacting policies and politicians on both sides of the aisle and across the globe. Just look at the deepening political divisions during the Trump presidency.

But for health and science, the spread of misinformation and falsehoods can be matters of life or death, as we have seen in the politically charged debates over how best to combat COVID-19 and global climate change.

“Our public debate seems increasingly driven by what people want to be true rather than what is actually true. As a scientist, that worries me,” says study co-author Johan Bollen, PhD, a professor of informatics at Indiana University.

“As a society, we are now faced with major collective problems that we need to approach from a pragmatic, rational, and objective perspective to be successful,” he says. “After all, global warming doesn’t care about whether you believe in it or not … but we will all suffer as a society if we fail to take adequate measures.”

For WUR co-researcher Ingrid van de Leemput, the trend isn’t merely academic; she’s seen it play out in her personal life.

“I do speak to people that, for instance, think the vaccines are poison,” she says. “I’m also on Twitter, and there, I’m every day surprised about how easily many people form their opinions, based on feelings, on what others say, or on some unfounded source.”

Public health experts say the embrace of personal beliefs over facts is one reason only 63% of Americans have been vaccinated against COVID-19. The result: millions of preventable infections among those who downplay the risks of the virus and reject the strong scientific evidence of vaccine safety and effectiveness.

“None of this really surprises me,” Johns Hopkins University social and behavioral scientist Rupali Limaye, PhD, says of the new study findings. Dr. Limaye coauthored a paper in 2016 in JAMA Pediatrics about how to talk to parents about vaccine hesitancy and the fact that we’re living in what they called “this post-truth era.”

Dr. Limaye says the trend has made it difficult for doctors, scientists, and health authorities to make fact-based arguments for COVID-19 vaccination, mask-wearing, social distancing, and other measures to control the virus.

“It’s been really hard being a scientist to hear people say, ‘Well, that’s not true’ when we say something very basic that I think all of us can agree on – like the grass is green,” she says. “To be honest, I worry that a lot of scientists are going to quit being in science because they’re exhausted.”
 

What’s driving the trend?

So, what’s behind the embrace of “alternative facts,” as former White House counselor Kellyanne Conway put it so brazenly in 2017, in defending the White House’s false claims that Trump’s inauguration crowd was the largest ever?

Dr. Scheffer and colleagues identified a handful of things that have encouraged the embrace of falsehoods over facts in recent years.

• The Internet: Its rise in the late 1980s, and its growing role as a primary source of news and information, has allowed more belief-based misinformation to flourish and spread like wildfire.
• Social media: The new study found the use of sentiment- and intuition-related words accelerated around 2007, along with a global surge in social media that catapulted Facebook, Twitter, and others into the mainstream, replacing more traditional fact-based media (i.e., newspapers and magazines).
• The 2007 financial crisis: The downturn in the global economy meant more people were dealing with job stress, investment losses, and other problems that fed the interest in belief-based, anti-establishment social media posts.
• Conspiracy theories: Falsehoods involving hidden political agendas, shadow “elites,” and wealthy people with dark motives tend to thrive during times of crisis and societal anxiety. “Conspiracy theories originate particularly in times of uncertainty and crisis and generally depict established institutions as hiding the truth and sustaining an unfair situation,” the researchers noted. “As a result, they may find fertile grounds on social media platforms promulgating a sense of unfairness, subsequently feeding anti-system sentiments.”

Dr. Scheffer says that growing political divisions during the Trump era have widened the fact-vs.-fiction divide. The ex-president voiced many anti-science views on global climate change, for instance, and spread so many falsehoods about COVID-19 and the 2020 election that Facebook, Twitter, and YouTube suspended his accounts.

Yet Trump remains a popular figure among Republicans, with most saying in a December poll they believe his baseless claims that the 2020 election was “rigged” and “stolen,” despite all credible, easily accessible evidence that it was secure, according to a recent poll by the University of Massachusetts at Amherst.

More than 60 courts have rejected Trump’s lawsuits seeking to overturn the election results. All 50 states, the District of Columbia, and both branches of Congress have certified the election results, giving Biden the White House. Even Trump’s own Justice Department confirmed that the 2020 election was free and fair.

Nevertheless, the University of Massachusetts survey found that most Republicans believe one or more conspiracy theories floated by the former president and those pushing his “big lie” that Democrats rigged the election to elect Biden.

Ed Berliner, an Emmy Award-winning broadcast journalist and media consultant, suggests something else is driving the spread of misinformation: the pursuit of ratings by cable TV and media companies to boost ad and subscriber revenues.

As a former executive producer and syndicated cable TV show host, he says he has seen firsthand how facts are often lost in opinion-driven news programs, even on network programs claiming to offer “fair and balanced” journalism.

“Propaganda is the new currency in America, and those who do not fight back against it are doomed to be overrun by the misinformation,” says Mr. Berliner, host of The Man in the Arena and CEO of Entourage Media LLC.

“The broadcast news media has to stop this incessant ‘infotainment’ prattle, stop trying to nuzzle up to a soft side, and bear down on hard facts, exposing the lies and refusing to back down.”
 

Public health implications

Public health and media experts alike say the PNAS study findings are disheartening but underscore the need for doctors and scientists to do a better job of communicating about COVID-19 and other pressing issues.

Dr. Limaye, from Johns Hopkins, is particularly concerned about the rise in conspiracy theories that has led to COVID-19 vaccine hesitancy.

“When we speak to individuals about getting the COVID vaccine…the types of concerns that come up now are very different than they were 8 years ago,” she says. “The comments we used to hear were much more related to vaccine safety. [People] would say, ‘I’m worried about an ingredient in the vaccine’ or ‘I’m worried that my kiddo has to get three different shots within 6 months to have a series dose completed.’”

But now, a lot of comments they receive are about government and pharma conspiracies.

What that means is doctors and scientists must do more than simply say “here are the facts” and “trust me, I’m a doctor or a scientist,” she says. And these approaches don’t only apply to public health.

“It’s funny, because when we talk to climate change scientists, as vaccine [specialists], we’ll say we can’t believe that people think COVID is a hoax,” she says. “And they’re like, ‘Hold my beer, we’ve been dealing with this for 20 years. Hello, it’s just your guys’ turn to deal with this public denial of science.’”

Dr. Limaye is also concerned about the impacts on funding for scientific research.

“There’s always been a really strong bipartisan effort with regards to funding for science, when you look at Congress and when you look at appropriations,” she says. “But what ended up happening, especially with the Trump administration, was that there was a real shift in that. We’ve never really seen that before in past generations.”

So, what’s the big take-home message?

Dr. Limaye believes doctors and public health experts must show more empathy – and not be combative or arrogant – in communicating science in one-on-one conversations. This month, she’s launching a new course for parents, school administrators, and nurses on how to do precisely that.

“It’s really all about how to have hard conversations with people who might be anti-science,” she says. “It’s being empathetic and not being dismissive. But it’s hard work, and I think a lot of people are just not cut out for it and just don’t have the time for it…You can’t just say, ‘Well, this is science, and I’m a doctor’ – that doesn’t work anymore.”

Brendan Nyhan, PhD, a Dartmouth College political scientist, echoes those sentiments in a separate paper recently published in the Proceedings of the National Academy of Sciences. In fact, he suggests that providing accurate, fact-based information to counter false claims may actually backfire and reinforce some people’s unfounded beliefs.

“One response to the prevalence of mistaken beliefs is to try to set the record straight by providing accurate information – for instance, by providing evidence of the scientific consensus on climate change,” he writes. “The failures of this approach, which is sometimes referred to as the ‘deficit model’ in science communication, are well-known.”

Dr. Nyhan argues two things make some people more prone to believe falsehoods:

What scientists call “ingrouping,” a kind of tribal mentality that makes some people choose social identity or politics over truth-seeking and demonize others who don’t agree with their views

The rise of high-profile political figures, such as Trump, who encourage their followers to indulge in their desire for “identify-affirming misinformation”

Dr. Scheffer says the most important thing for doctors, health experts, and scientists to recognize is that it’s crucial to gain the trust of someone who may believe fictions over facts to make any persuasive argument on COVID-19 or any other issue.

He also has a standard response to those who present falsehoods to him as facts that he suggests anyone can use: “That is interesting. Would you mind helping me understand how you came to that opinion?”

A version of this article first appeared on WebMD.com.

Can you tell which of the following statements are true and which are false?

COVID-19 is not a threat to younger people, and only those who have other medical conditions are dying from it.

The mRNA vaccines developed to prevent the coronavirus alter your genes, can make your body “magnetic,” and are killing more people than the virus itself.

President Joe Biden’s climate change plan calls for a ban on meat consumption to cut greenhouse gas emissions.

The 2020 presidential election was rigged and stolen.

If you guessed that all of these claims are false, you’re right – take a bow. Not a single one of these statements has any factual support, according to scientific research, legal rulings, and legitimate government authorities.

And yet public opinion surveys show millions of Americans, and others around the world, believe some of these falsehoods are true and can’t be convinced otherwise.

Social media, politicians and partisan websites, TV programs, and commentators have widely circulated these and other unfounded claims so frequently that many people say they simply can’t tell what’s objectively true and not anymore.

So much so, the authors of a fascinating new research study have concluded we are living in a “post-truth era,” with baseless beliefs and subjective opinions given a higher priority than verifiable facts.

The new study – The Rise and Fall of Rationality in Language, published in the Proceedings of the National Academy of Sciences – found that facts have become less important in public discourse.

As a result, unsupported beliefs have taken precedent over readily identifiable truths in discussions of health, science, and politics. The upshot: “Feelings trump facts” in social media, news reports, books, and other sources of information.

And here’s the kicker: The trend did not begin with the rise of former President Donald Trump, the COVID-19 pandemic, or the advent of social media; in fact, it has been growing for much longer than you might think.

“While the current ‘post-truth era’ has taken many by surprise, the study shows that over the past 40 years, public interest has undergone an accelerating shift from the collective to the individual, and from rationality towards emotion,” concluded the researchers from Indiana University and Wageningen University & Research in the Netherlands.

“Our work suggests that the societal balance between emotion and reason has shifted back to what it used to be around 150 years ago,” says lead researcher Marten Scheffer, PhD, a professor in the department of environmental sciences at WUR. “This implies that scientists, experts, and policymakers will have to think about the best way to respond to that social change.”
 

Researchers surprised by findings

The findings are based on a very detailed analysis of language from millions of books, newspaper articles, Google searches, TV reports, social media posts, and other sources dating back to 1850.

The researchers analyzed how often the 5,000 most used words appeared over the past 170 years and found that the use of those having to do with facts and reasoning, such as “determine” and “conclusion,” has fallen dramatically since 1980. Meanwhile, the use of words related to human emotion, such as “feel” and “believe,” have skyrocketed.

Dr. Scheffer notes rapid developments in science and technology from 1850 to 1980 had profound social and economic benefits that helped boost the status of the scientific approach. That shift in public attitudes had ripple effects on culture, society, education, politics, and religion – and “the role of spiritualism dwindled” in the modern world, he says.

But since 1980, that trend has seen a major reversal, with beliefs becoming more important than facts to many people, he says. At the same time, trust in science and scientists has fallen.

Dr. Scheffer says the researchers expected to find some evidence of a swing toward more belief-based sentiments during the Trump era but were surprised to discover how strong it is and that the trend has actually been a long time coming.

“The shift in interest from rational to intuitive/emotional is pretty obvious now in the post-truth political and social media discussion,” he says. “However, our work shows that it already started in the 1980s. For me personally, that went under the radar, except perhaps for the rise of alternative (to religion) forms of spirituality.

“We were especially struck by how strong the patterns are and how universal they appear across languages, nonfiction and fiction, and even in The New York Times.”

In the political world, the implications are significant enough – impacting policies and politicians on both sides of the aisle and across the globe. Just look at the deepening political divisions during the Trump presidency.

But for health and science, the spread of misinformation and falsehoods can be matters of life or death, as we have seen in the politically charged debates over how best to combat COVID-19 and global climate change.

“Our public debate seems increasingly driven by what people want to be true rather than what is actually true. As a scientist, that worries me,” says study co-author Johan Bollen, PhD, a professor of informatics at Indiana University.

“As a society, we are now faced with major collective problems that we need to approach from a pragmatic, rational, and objective perspective to be successful,” he says. “After all, global warming doesn’t care about whether you believe in it or not … but we will all suffer as a society if we fail to take adequate measures.”

For WUR co-researcher Ingrid van de Leemput, the trend isn’t merely academic; she’s seen it play out in her personal life.

“I do speak to people that, for instance, think the vaccines are poison,” she says. “I’m also on Twitter, and there, I’m every day surprised about how easily many people form their opinions, based on feelings, on what others say, or on some unfounded source.”

Public health experts say the embrace of personal beliefs over facts is one reason only 63% of Americans have been vaccinated against COVID-19. The result: millions of preventable infections among those who downplay the risks of the virus and reject the strong scientific evidence of vaccine safety and effectiveness.

“None of this really surprises me,” Johns Hopkins University social and behavioral scientist Rupali Limaye, PhD, says of the new study findings. Dr. Limaye coauthored a paper in 2016 in JAMA Pediatrics about how to talk to parents about vaccine hesitancy and the fact that we’re living in what they called “this post-truth era.”

Dr. Limaye says the trend has made it difficult for doctors, scientists, and health authorities to make fact-based arguments for COVID-19 vaccination, mask-wearing, social distancing, and other measures to control the virus.

“It’s been really hard being a scientist to hear people say, ‘Well, that’s not true’ when we say something very basic that I think all of us can agree on – like the grass is green,” she says. “To be honest, I worry that a lot of scientists are going to quit being in science because they’re exhausted.”
 

What’s driving the trend?

So, what’s behind the embrace of “alternative facts,” as former White House counselor Kellyanne Conway put it so brazenly in 2017, in defending the White House’s false claims that Trump’s inauguration crowd was the largest ever?

Dr. Scheffer and colleagues identified a handful of things that have encouraged the embrace of falsehoods over facts in recent years.

• The Internet: Its rise in the late 1980s, and its growing role as a primary source of news and information, has allowed more belief-based misinformation to flourish and spread like wildfire.
• Social media: The new study found the use of sentiment- and intuition-related words accelerated around 2007, along with a global surge in social media that catapulted Facebook, Twitter, and others into the mainstream, replacing more traditional fact-based media (i.e., newspapers and magazines).
• The 2007 financial crisis: The downturn in the global economy meant more people were dealing with job stress, investment losses, and other problems that fed the interest in belief-based, anti-establishment social media posts.
• Conspiracy theories: Falsehoods involving hidden political agendas, shadow “elites,” and wealthy people with dark motives tend to thrive during times of crisis and societal anxiety. “Conspiracy theories originate particularly in times of uncertainty and crisis and generally depict established institutions as hiding the truth and sustaining an unfair situation,” the researchers noted. “As a result, they may find fertile grounds on social media platforms promulgating a sense of unfairness, subsequently feeding anti-system sentiments.”

Dr. Scheffer says that growing political divisions during the Trump era have widened the fact-vs.-fiction divide. The ex-president voiced many anti-science views on global climate change, for instance, and spread so many falsehoods about COVID-19 and the 2020 election that Facebook, Twitter, and YouTube suspended his accounts.

Yet Trump remains a popular figure among Republicans, with most saying in a December poll they believe his baseless claims that the 2020 election was “rigged” and “stolen,” despite all credible, easily accessible evidence that it was secure, according to a recent poll by the University of Massachusetts at Amherst.

More than 60 courts have rejected Trump’s lawsuits seeking to overturn the election results. All 50 states, the District of Columbia, and both branches of Congress have certified the election results, giving Biden the White House. Even Trump’s own Justice Department confirmed that the 2020 election was free and fair.

Nevertheless, the University of Massachusetts survey found that most Republicans believe one or more conspiracy theories floated by the former president and those pushing his “big lie” that Democrats rigged the election to elect Biden.

Ed Berliner, an Emmy Award-winning broadcast journalist and media consultant, suggests something else is driving the spread of misinformation: the pursuit of ratings by cable TV and media companies to boost ad and subscriber revenues.

As a former executive producer and syndicated cable TV show host, he says he has seen firsthand how facts are often lost in opinion-driven news programs, even on network programs claiming to offer “fair and balanced” journalism.

“Propaganda is the new currency in America, and those who do not fight back against it are doomed to be overrun by the misinformation,” says Mr. Berliner, host of The Man in the Arena and CEO of Entourage Media LLC.

“The broadcast news media has to stop this incessant ‘infotainment’ prattle, stop trying to nuzzle up to a soft side, and bear down on hard facts, exposing the lies and refusing to back down.”
 

Public health implications

Public health and media experts alike say the PNAS study findings are disheartening but underscore the need for doctors and scientists to do a better job of communicating about COVID-19 and other pressing issues.

Dr. Limaye, from Johns Hopkins, is particularly concerned about the rise in conspiracy theories that has led to COVID-19 vaccine hesitancy.

“When we speak to individuals about getting the COVID vaccine…the types of concerns that come up now are very different than they were 8 years ago,” she says. “The comments we used to hear were much more related to vaccine safety. [People] would say, ‘I’m worried about an ingredient in the vaccine’ or ‘I’m worried that my kiddo has to get three different shots within 6 months to have a series dose completed.’”

But now, a lot of comments they receive are about government and pharma conspiracies.

What that means is doctors and scientists must do more than simply say “here are the facts” and “trust me, I’m a doctor or a scientist,” she says. And these approaches don’t only apply to public health.

“It’s funny, because when we talk to climate change scientists, as vaccine [specialists], we’ll say we can’t believe that people think COVID is a hoax,” she says. “And they’re like, ‘Hold my beer, we’ve been dealing with this for 20 years. Hello, it’s just your guys’ turn to deal with this public denial of science.’”

Dr. Limaye is also concerned about the impacts on funding for scientific research.

“There’s always been a really strong bipartisan effort with regards to funding for science, when you look at Congress and when you look at appropriations,” she says. “But what ended up happening, especially with the Trump administration, was that there was a real shift in that. We’ve never really seen that before in past generations.”

So, what’s the big take-home message?

Dr. Limaye believes doctors and public health experts must show more empathy – and not be combative or arrogant – in communicating science in one-on-one conversations. This month, she’s launching a new course for parents, school administrators, and nurses on how to do precisely that.

“It’s really all about how to have hard conversations with people who might be anti-science,” she says. “It’s being empathetic and not being dismissive. But it’s hard work, and I think a lot of people are just not cut out for it and just don’t have the time for it…You can’t just say, ‘Well, this is science, and I’m a doctor’ – that doesn’t work anymore.”

Brendan Nyhan, PhD, a Dartmouth College political scientist, echoes those sentiments in a separate paper recently published in the Proceedings of the National Academy of Sciences. In fact, he suggests that providing accurate, fact-based information to counter false claims may actually backfire and reinforce some people’s unfounded beliefs.

“One response to the prevalence of mistaken beliefs is to try to set the record straight by providing accurate information – for instance, by providing evidence of the scientific consensus on climate change,” he writes. “The failures of this approach, which is sometimes referred to as the ‘deficit model’ in science communication, are well-known.”

Dr. Nyhan argues two things make some people more prone to believe falsehoods:

What scientists call “ingrouping,” a kind of tribal mentality that makes some people choose social identity or politics over truth-seeking and demonize others who don’t agree with their views

The rise of high-profile political figures, such as Trump, who encourage their followers to indulge in their desire for “identify-affirming misinformation”

Dr. Scheffer says the most important thing for doctors, health experts, and scientists to recognize is that it’s crucial to gain the trust of someone who may believe fictions over facts to make any persuasive argument on COVID-19 or any other issue.

He also has a standard response to those who present falsehoods to him as facts that he suggests anyone can use: “That is interesting. Would you mind helping me understand how you came to that opinion?”

A version of this article first appeared on WebMD.com.

In another salvo in the heated debate over treatment for kids who believe they’re transgender, a study published in PLoS One suggests that transgender adults who received hormone therapy as teenagers are mentally healthier in a pair of ways than those who didn’t.

The study, which only looks at transgender adults, doesn’t confirm that hormone therapy in childhood is a beneficial treatment. Still, “we found that for all age groups, access to [adolescent] gender-affirming hormone initiation was associated with lower odds of past-year suicidal ideation and past-month severe psychological distress measured in adulthood,” said lead author Jack Turban, MD, chief fellow in child and adolescent psychiatry at Stanford (Calif.) University, in an interview. “We also found better mental-health outcomes for those who started gender-affirming hormones as adolescents when compared to those who didn’t start them until they were adults.”

The use of hormone treatment and puberty blockers by transgender teens is extremely controversial. Critics say the treatments are harmful and unnecessary, and Republican politicians are trying to ban their use in some states. Last spring, Arkansas became the first state to ban the treatments. The law is on hold amid a legal challenge.

The researchers launched the study to gain more insight into the impact of hormone therapy on children. “There have been several longitudinal studies showing that mental health improves following gender-affirming medical care for transgender youth, but there has been less research looking at the relationship between when these medications are started and adult mental health outcomes,” Dr. Turban said. “This is the first study to look at various ages of initiation of gender-affirming hormones and compare outcomes between those who started gender-affirming hormones during adolescence and those who did not start them until adulthood.”

For the new study, the authors analyzed the findings of the 2015 U.S. Transgender Survey of 27,715 adults and focused on 21,598 who said they’d wanted hormone therapy (40% aged 18-24, 83% White, 35% transgender male, 41% transgender female, with the rest using other terms such as “queer” or “nonbinary” to describe themselves).

Of these subjects, 41.0% never received hormone therapy, 0.6% underwent therapy in early adolescence, 1.7% received it in late adolescence, and 56.8% got it as adults.

The researchers made various adjustments for confounders – age, partnership status, employment status, K-12 harassment, and experience of gender identity conversion efforts. Those who received hormone therapy had lower odds of past-year suicidal ideation vs. those who didn’t: adjusted odds ratio, 0.4; 95% confidence interval, 0.2-0.6; P < .0001 for therapy that occurred from age 14 to 15, aOR, 0.5; 95% CI, 0.4-0.7; P < .0001, for therapy that occurred from age 16 to 17, and aOR, 0.8; 95% CI, 0.7-0.8; P < .0001 for therapy that occurred in adulthood.

However, there was no statistically significant link between hormone therapy and past-year suicidal ideation with a plan or past-year suicide attempt.

The study also found lower rates of past-month severe psychological distress: aOR. 0.3; 95% CI, 0.2-0.4; P < .0001 for therapy from age 14 to 15, aOR, 0.3; 95% CI, 0.3-0.4; P < .0001 for therapy from age 16 to 17, and aOR, 0.6 (95% CI, 0.5-0.6; P < .0001) for therapy in adulthood.

There was no statistically significant link between hormone therapy and past-month binge drinking or lifetime illicit drug use.

“The findings indicate that clinicians caring for adolescents need to be properly trained in gender-affirming medical care, including hormone therapy, in order to help promote good mental health outcomes for transgender people. Comprehensive training in gender-affirming care is currently not part of standard medical education curricula,” said study coauthor Alex Keuroghlian, MD, MPH, director of the National LGBTQIA+ Health Education Center at the Fenway Institute and associate professor of psychiatry at Harvard Medical School, Boston, in an interview.

The study has limitations. The survey population doesn’t include anyone who committed suicide, nor does it include people who had gender dysphoria as children but didn’t go on to identify as transgender as adults. It is also retrospective. “There is a general consensus that, given the data we have so far, it would be unethical to conduct a randomized controlled trial in this space,” said study lead author Dr. Turban.

Several critics of hormone therapy in teens support a psychotherapy-based approach to gender dysphoria that considers whether other factors are at play than transgender orientation. They’ve united to attack research based on the 2015 transgender survey. In a 2021 report in Archives of Sexual Behavior, they called it “a highly skewed sample” and objected to “a conflation of ethical nonaffirmative psychotherapy with conversion therapy.”

In an interview, one of the critics – developmental psychologist and retired University of Sydney professor Dianna Kenny, PhD – said the new study’s “serious problem of recall bias” about hormone therapy in the survey is “insurmountable.” The survey, she said, also fails to explore why participants who wanted hormone therapy didn’t get it.

Dr. Kenny, who believes all hormone therapy in teens with gender dysphoria outside of clinical trials is inappropriate, also pointed out that hormone therapy has many side effects. She added that young people with gender dysphoria often “realize through a process of cognitive and psychosocial maturation that they were not ‘genuinely’ trans but suffering from other conditions that needed treatment – e.g., internalized homophobia, trauma, including sexual abuse, attention-deficit/hyperactivity disorder, autism spectrum disorder, etc.”

No specific funding is reported, although two of the authors report receiving various grants, fellowship and research funding. Dr. Turban discloses textbook royalties from Springer Nature and expert witness payments from the ACLU. Dr. Keuroghlian discloses textbook royalties from McGraw Hill. Dr. Kenny reports no disclosures.

In another salvo in the heated debate over treatment for kids who believe they’re transgender, a study published in PLoS One suggests that transgender adults who received hormone therapy as teenagers are mentally healthier in a pair of ways than those who didn’t.

The study, which only looks at transgender adults, doesn’t confirm that hormone therapy in childhood is a beneficial treatment. Still, “we found that for all age groups, access to [adolescent] gender-affirming hormone initiation was associated with lower odds of past-year suicidal ideation and past-month severe psychological distress measured in adulthood,” said lead author Jack Turban, MD, chief fellow in child and adolescent psychiatry at Stanford (Calif.) University, in an interview. “We also found better mental-health outcomes for those who started gender-affirming hormones as adolescents when compared to those who didn’t start them until they were adults.”

The use of hormone treatment and puberty blockers by transgender teens is extremely controversial. Critics say the treatments are harmful and unnecessary, and Republican politicians are trying to ban their use in some states. Last spring, Arkansas became the first state to ban the treatments. The law is on hold amid a legal challenge.

The researchers launched the study to gain more insight into the impact of hormone therapy on children. “There have been several longitudinal studies showing that mental health improves following gender-affirming medical care for transgender youth, but there has been less research looking at the relationship between when these medications are started and adult mental health outcomes,” Dr. Turban said. “This is the first study to look at various ages of initiation of gender-affirming hormones and compare outcomes between those who started gender-affirming hormones during adolescence and those who did not start them until adulthood.”

For the new study, the authors analyzed the findings of the 2015 U.S. Transgender Survey of 27,715 adults and focused on 21,598 who said they’d wanted hormone therapy (40% aged 18-24, 83% White, 35% transgender male, 41% transgender female, with the rest using other terms such as “queer” or “nonbinary” to describe themselves).

Of these subjects, 41.0% never received hormone therapy, 0.6% underwent therapy in early adolescence, 1.7% received it in late adolescence, and 56.8% got it as adults.

The researchers made various adjustments for confounders – age, partnership status, employment status, K-12 harassment, and experience of gender identity conversion efforts. Those who received hormone therapy had lower odds of past-year suicidal ideation vs. those who didn’t: adjusted odds ratio, 0.4; 95% confidence interval, 0.2-0.6; P < .0001 for therapy that occurred from age 14 to 15, aOR, 0.5; 95% CI, 0.4-0.7; P < .0001, for therapy that occurred from age 16 to 17, and aOR, 0.8; 95% CI, 0.7-0.8; P < .0001 for therapy that occurred in adulthood.

However, there was no statistically significant link between hormone therapy and past-year suicidal ideation with a plan or past-year suicide attempt.

The study also found lower rates of past-month severe psychological distress: aOR. 0.3; 95% CI, 0.2-0.4; P < .0001 for therapy from age 14 to 15, aOR, 0.3; 95% CI, 0.3-0.4; P < .0001 for therapy from age 16 to 17, and aOR, 0.6 (95% CI, 0.5-0.6; P < .0001) for therapy in adulthood.

There was no statistically significant link between hormone therapy and past-month binge drinking or lifetime illicit drug use.

“The findings indicate that clinicians caring for adolescents need to be properly trained in gender-affirming medical care, including hormone therapy, in order to help promote good mental health outcomes for transgender people. Comprehensive training in gender-affirming care is currently not part of standard medical education curricula,” said study coauthor Alex Keuroghlian, MD, MPH, director of the National LGBTQIA+ Health Education Center at the Fenway Institute and associate professor of psychiatry at Harvard Medical School, Boston, in an interview.

The study has limitations. The survey population doesn’t include anyone who committed suicide, nor does it include people who had gender dysphoria as children but didn’t go on to identify as transgender as adults. It is also retrospective. “There is a general consensus that, given the data we have so far, it would be unethical to conduct a randomized controlled trial in this space,” said study lead author Dr. Turban.

Several critics of hormone therapy in teens support a psychotherapy-based approach to gender dysphoria that considers whether other factors are at play than transgender orientation. They’ve united to attack research based on the 2015 transgender survey. In a 2021 report in Archives of Sexual Behavior, they called it “a highly skewed sample” and objected to “a conflation of ethical nonaffirmative psychotherapy with conversion therapy.”

In an interview, one of the critics – developmental psychologist and retired University of Sydney professor Dianna Kenny, PhD – said the new study’s “serious problem of recall bias” about hormone therapy in the survey is “insurmountable.” The survey, she said, also fails to explore why participants who wanted hormone therapy didn’t get it.

Dr. Kenny, who believes all hormone therapy in teens with gender dysphoria outside of clinical trials is inappropriate, also pointed out that hormone therapy has many side effects. She added that young people with gender dysphoria often “realize through a process of cognitive and psychosocial maturation that they were not ‘genuinely’ trans but suffering from other conditions that needed treatment – e.g., internalized homophobia, trauma, including sexual abuse, attention-deficit/hyperactivity disorder, autism spectrum disorder, etc.”

No specific funding is reported, although two of the authors report receiving various grants, fellowship and research funding. Dr. Turban discloses textbook royalties from Springer Nature and expert witness payments from the ACLU. Dr. Keuroghlian discloses textbook royalties from McGraw Hill. Dr. Kenny reports no disclosures.

In another salvo in the heated debate over treatment for kids who believe they’re transgender, a study published in PLoS One suggests that transgender adults who received hormone therapy as teenagers are mentally healthier in a pair of ways than those who didn’t.

The study, which only looks at transgender adults, doesn’t confirm that hormone therapy in childhood is a beneficial treatment. Still, “we found that for all age groups, access to [adolescent] gender-affirming hormone initiation was associated with lower odds of past-year suicidal ideation and past-month severe psychological distress measured in adulthood,” said lead author Jack Turban, MD, chief fellow in child and adolescent psychiatry at Stanford (Calif.) University, in an interview. “We also found better mental-health outcomes for those who started gender-affirming hormones as adolescents when compared to those who didn’t start them until they were adults.”

The use of hormone treatment and puberty blockers by transgender teens is extremely controversial. Critics say the treatments are harmful and unnecessary, and Republican politicians are trying to ban their use in some states. Last spring, Arkansas became the first state to ban the treatments. The law is on hold amid a legal challenge.

The researchers launched the study to gain more insight into the impact of hormone therapy on children. “There have been several longitudinal studies showing that mental health improves following gender-affirming medical care for transgender youth, but there has been less research looking at the relationship between when these medications are started and adult mental health outcomes,” Dr. Turban said. “This is the first study to look at various ages of initiation of gender-affirming hormones and compare outcomes between those who started gender-affirming hormones during adolescence and those who did not start them until adulthood.”

For the new study, the authors analyzed the findings of the 2015 U.S. Transgender Survey of 27,715 adults and focused on 21,598 who said they’d wanted hormone therapy (40% aged 18-24, 83% White, 35% transgender male, 41% transgender female, with the rest using other terms such as “queer” or “nonbinary” to describe themselves).

Of these subjects, 41.0% never received hormone therapy, 0.6% underwent therapy in early adolescence, 1.7% received it in late adolescence, and 56.8% got it as adults.

The researchers made various adjustments for confounders – age, partnership status, employment status, K-12 harassment, and experience of gender identity conversion efforts. Those who received hormone therapy had lower odds of past-year suicidal ideation vs. those who didn’t: adjusted odds ratio, 0.4; 95% confidence interval, 0.2-0.6; P < .0001 for therapy that occurred from age 14 to 15, aOR, 0.5; 95% CI, 0.4-0.7; P < .0001, for therapy that occurred from age 16 to 17, and aOR, 0.8; 95% CI, 0.7-0.8; P < .0001 for therapy that occurred in adulthood.

However, there was no statistically significant link between hormone therapy and past-year suicidal ideation with a plan or past-year suicide attempt.

The study also found lower rates of past-month severe psychological distress: aOR. 0.3; 95% CI, 0.2-0.4; P < .0001 for therapy from age 14 to 15, aOR, 0.3; 95% CI, 0.3-0.4; P < .0001 for therapy from age 16 to 17, and aOR, 0.6 (95% CI, 0.5-0.6; P < .0001) for therapy in adulthood.

There was no statistically significant link between hormone therapy and past-month binge drinking or lifetime illicit drug use.

“The findings indicate that clinicians caring for adolescents need to be properly trained in gender-affirming medical care, including hormone therapy, in order to help promote good mental health outcomes for transgender people. Comprehensive training in gender-affirming care is currently not part of standard medical education curricula,” said study coauthor Alex Keuroghlian, MD, MPH, director of the National LGBTQIA+ Health Education Center at the Fenway Institute and associate professor of psychiatry at Harvard Medical School, Boston, in an interview.

The study has limitations. The survey population doesn’t include anyone who committed suicide, nor does it include people who had gender dysphoria as children but didn’t go on to identify as transgender as adults. It is also retrospective. “There is a general consensus that, given the data we have so far, it would be unethical to conduct a randomized controlled trial in this space,” said study lead author Dr. Turban.

Several critics of hormone therapy in teens support a psychotherapy-based approach to gender dysphoria that considers whether other factors are at play than transgender orientation. They’ve united to attack research based on the 2015 transgender survey. In a 2021 report in Archives of Sexual Behavior, they called it “a highly skewed sample” and objected to “a conflation of ethical nonaffirmative psychotherapy with conversion therapy.”

In an interview, one of the critics – developmental psychologist and retired University of Sydney professor Dianna Kenny, PhD – said the new study’s “serious problem of recall bias” about hormone therapy in the survey is “insurmountable.” The survey, she said, also fails to explore why participants who wanted hormone therapy didn’t get it.

Dr. Kenny, who believes all hormone therapy in teens with gender dysphoria outside of clinical trials is inappropriate, also pointed out that hormone therapy has many side effects. She added that young people with gender dysphoria often “realize through a process of cognitive and psychosocial maturation that they were not ‘genuinely’ trans but suffering from other conditions that needed treatment – e.g., internalized homophobia, trauma, including sexual abuse, attention-deficit/hyperactivity disorder, autism spectrum disorder, etc.”

No specific funding is reported, although two of the authors report receiving various grants, fellowship and research funding. Dr. Turban discloses textbook royalties from Springer Nature and expert witness payments from the ACLU. Dr. Keuroghlian discloses textbook royalties from McGraw Hill. Dr. Kenny reports no disclosures.