Federal Practitioner

INTRODUCTION

Excluding skin cancer, prostate cancer is the most common malignancy affecting men in the United States, accounting for ~33% of VA cancer cases. Androgen deprivation therapy (ADT) is considered standard of care in treating advanced prostate cancer. Pituitary apoplexy is a rare and morbid adverse event associated with GnRH agonist treatment. We describe a patient with advanced prostate cancer who developed pituitary apoplexy shortly after leuprolide therapy.

CASE PRESENTATION

A 70-year-old African-American male was diagnosed with a T2aN1M1 stage IVB prostate cancer, Gleason 4+5, PSA 19.5. Four hours after his first leuprolide injection, he developed vomiting, diaphoresis, myalgia, and a severe frontal headache. Brain MRI revealed a 2.4 × 1.3 × 1.3cm pituitary mass, suspicious for an adenoma with hemorrhage. Labs noted low TSH, prolactin, LH, growth hormone, ACTH, cortisol, and testosterone, consistent with pituitary apoplexy. He was treated with steroids. Three weeks later, testosterone levels remained very low. He started abiraterone and prednisone without further leuprolide.

DISCUSSION

Prostate cancer is ubiquitous among VA patients, and ADT with GnRH agonist is vital in their care. These medications stimulate the pituitary to release LH and FSH resulting in a negative feedback loop, ultimately decreasing the levels of testosterone. Common side effects of GnRH agonists include hot flashes, diaphoresis, and sexual dysfunction. We present a patient who started leuprolide for prostate cancer. Symptoms including a severe headache led to an evaluation confirming pituitary apoplexy. Literature review reveals ~ 21 cases of pituitary apoplexy associated with GnRH agonist treatment for prostate cancer, and apoplexy can occur immediately to months later Undiagnosed pituitary adenomas are common among these patients. Treatment includes pituitary surgery or conservative management. Further prostate cancer treatment needs investigation, but we propose that GnRH modifying treatment can be withheld while testosterone levels remain low.

CONCLUSIONS

Prostate cancer is extremely common in the VA population, and treatment with leuprolide is standard. Pituitary apoplexy is a rare, but devastating complication of this treatment, and providers should be aware of the symptoms in order to intervene quickly. Further testosterone lowering treatment may be withheld if testosterone levels remain low.

INTRODUCTION

Excluding skin cancer, prostate cancer is the most common malignancy affecting men in the United States, accounting for ~33% of VA cancer cases. Androgen deprivation therapy (ADT) is considered standard of care in treating advanced prostate cancer. Pituitary apoplexy is a rare and morbid adverse event associated with GnRH agonist treatment. We describe a patient with advanced prostate cancer who developed pituitary apoplexy shortly after leuprolide therapy.

CASE PRESENTATION

A 70-year-old African-American male was diagnosed with a T2aN1M1 stage IVB prostate cancer, Gleason 4+5, PSA 19.5. Four hours after his first leuprolide injection, he developed vomiting, diaphoresis, myalgia, and a severe frontal headache. Brain MRI revealed a 2.4 × 1.3 × 1.3cm pituitary mass, suspicious for an adenoma with hemorrhage. Labs noted low TSH, prolactin, LH, growth hormone, ACTH, cortisol, and testosterone, consistent with pituitary apoplexy. He was treated with steroids. Three weeks later, testosterone levels remained very low. He started abiraterone and prednisone without further leuprolide.

DISCUSSION

Prostate cancer is ubiquitous among VA patients, and ADT with GnRH agonist is vital in their care. These medications stimulate the pituitary to release LH and FSH resulting in a negative feedback loop, ultimately decreasing the levels of testosterone. Common side effects of GnRH agonists include hot flashes, diaphoresis, and sexual dysfunction. We present a patient who started leuprolide for prostate cancer. Symptoms including a severe headache led to an evaluation confirming pituitary apoplexy. Literature review reveals ~ 21 cases of pituitary apoplexy associated with GnRH agonist treatment for prostate cancer, and apoplexy can occur immediately to months later Undiagnosed pituitary adenomas are common among these patients. Treatment includes pituitary surgery or conservative management. Further prostate cancer treatment needs investigation, but we propose that GnRH modifying treatment can be withheld while testosterone levels remain low.

CONCLUSIONS

Prostate cancer is extremely common in the VA population, and treatment with leuprolide is standard. Pituitary apoplexy is a rare, but devastating complication of this treatment, and providers should be aware of the symptoms in order to intervene quickly. Further testosterone lowering treatment may be withheld if testosterone levels remain low.

INTRODUCTION

Excluding skin cancer, prostate cancer is the most common malignancy affecting men in the United States, accounting for ~33% of VA cancer cases. Androgen deprivation therapy (ADT) is considered standard of care in treating advanced prostate cancer. Pituitary apoplexy is a rare and morbid adverse event associated with GnRH agonist treatment. We describe a patient with advanced prostate cancer who developed pituitary apoplexy shortly after leuprolide therapy.

CASE PRESENTATION

A 70-year-old African-American male was diagnosed with a T2aN1M1 stage IVB prostate cancer, Gleason 4+5, PSA 19.5. Four hours after his first leuprolide injection, he developed vomiting, diaphoresis, myalgia, and a severe frontal headache. Brain MRI revealed a 2.4 × 1.3 × 1.3cm pituitary mass, suspicious for an adenoma with hemorrhage. Labs noted low TSH, prolactin, LH, growth hormone, ACTH, cortisol, and testosterone, consistent with pituitary apoplexy. He was treated with steroids. Three weeks later, testosterone levels remained very low. He started abiraterone and prednisone without further leuprolide.

DISCUSSION

Prostate cancer is ubiquitous among VA patients, and ADT with GnRH agonist is vital in their care. These medications stimulate the pituitary to release LH and FSH resulting in a negative feedback loop, ultimately decreasing the levels of testosterone. Common side effects of GnRH agonists include hot flashes, diaphoresis, and sexual dysfunction. We present a patient who started leuprolide for prostate cancer. Symptoms including a severe headache led to an evaluation confirming pituitary apoplexy. Literature review reveals ~ 21 cases of pituitary apoplexy associated with GnRH agonist treatment for prostate cancer, and apoplexy can occur immediately to months later Undiagnosed pituitary adenomas are common among these patients. Treatment includes pituitary surgery or conservative management. Further prostate cancer treatment needs investigation, but we propose that GnRH modifying treatment can be withheld while testosterone levels remain low.

CONCLUSIONS

Prostate cancer is extremely common in the VA population, and treatment with leuprolide is standard. Pituitary apoplexy is a rare, but devastating complication of this treatment, and providers should be aware of the symptoms in order to intervene quickly. Further testosterone lowering treatment may be withheld if testosterone levels remain low.

TOPLINE:

Results of a national survey show that despite a lack of data, many adults in the United States believe daily use of cannabis is safer than tobacco, a trend that’s growing over time.

METHODOLOGY:

• While aggressive campaigns have led to a dramatic reduction in the prevalence of cigarette smoking and created safer smoke-free environments, regulation governing cannabis – which is associated with some health benefits but also many negative health outcomes – has been less restrictive.
• The study included a nationally representative sample of 5,035 mostly White U.S. adults, mean age 53.4 years, who completed three online surveys between 2017 and 2021 on the safety of tobacco and cannabis.
• In all three waves of the survey, respondents were asked to rate the safety of smoking one marijuana joint a day to smoking one cigarette a day, and of secondhand smoke from marijuana to that from tobacco.
• Respondents also expressed views on the safety of secondhand smoke exposure (of both marijuana and tobacco) on specific populations, including children, pregnant women, and adults (ratings were from “completely unsafe” to “completely safe”).
• Independent variables included age, sex, race, ethnicity, education level, annual income, employment status, marital status, and state of residence.

TAKEAWAY:

• There was a significant shift over time toward an increasingly favorable perception of cannabis; more respondents reported cannabis was “somewhat safer” or “much safer” than tobacco in 2021 than 2017 (44.3% vs. 36.7%; P < .001), and more believed secondhand smoke was somewhat or much safer for cannabis vs. tobacco in 2021 than in 2017 (40.2% vs. 35.1%; P < .001).
• More people endorsed the greater safety of secondhand smoke from cannabis vs. tobacco for children and pregnant women, and these perceptions remained similar over the study period.
• Younger and unmarried individuals were significantly more likely to move toward viewing smoking cannabis as safer than cigarettes, but legality of cannabis in respondents’ state of residence was not associated with change over time, suggesting the increasing perception of cannabis safety may be a national trend rather than a trend seen only in states with legalized cannabis.

IN PRACTICE:

“Understanding changing views on tobacco and cannabis risk is important given that increases in social acceptance and decreases in risk perception may be directly associated with public health and policies,” the investigators write.

SOURCE:

The study was conducted by Julia Chambers, MD, department of medicine, University of California, San Francisco, and colleagues. It was published online in JAMA Network Open.

LIMITATIONS:

The generalizability of the study may be limited by nonresponse and loss to follow-up over time. The wording of survey questions may have introduced bias in respondents. Participants were asked about safety of smoking cannabis joints vs. tobacco cigarettes and not to compare safety of other forms of smoked and vaped cannabis, tobacco, and nicotine.

DISCLOSURES:

The study received support from the California Tobacco-Related Disease Research Program. Dr. Chambers has no relevant conflicts of interest; author Katherine J. Hoggatt, PhD, MPH, department of medicine, UCSF, reported receiving grants from the Veterans Health Administration during the conduct of the study and grants from the National Institutes of Health, Rubin Family Foundation, and Veterans Health Administration outside the submitted work.

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

TOPLINE:

Results of a national survey show that despite a lack of data, many adults in the United States believe daily use of cannabis is safer than tobacco, a trend that’s growing over time.

METHODOLOGY:

• While aggressive campaigns have led to a dramatic reduction in the prevalence of cigarette smoking and created safer smoke-free environments, regulation governing cannabis – which is associated with some health benefits but also many negative health outcomes – has been less restrictive.
• The study included a nationally representative sample of 5,035 mostly White U.S. adults, mean age 53.4 years, who completed three online surveys between 2017 and 2021 on the safety of tobacco and cannabis.
• In all three waves of the survey, respondents were asked to rate the safety of smoking one marijuana joint a day to smoking one cigarette a day, and of secondhand smoke from marijuana to that from tobacco.
• Respondents also expressed views on the safety of secondhand smoke exposure (of both marijuana and tobacco) on specific populations, including children, pregnant women, and adults (ratings were from “completely unsafe” to “completely safe”).
• Independent variables included age, sex, race, ethnicity, education level, annual income, employment status, marital status, and state of residence.

TAKEAWAY:

• There was a significant shift over time toward an increasingly favorable perception of cannabis; more respondents reported cannabis was “somewhat safer” or “much safer” than tobacco in 2021 than 2017 (44.3% vs. 36.7%; P < .001), and more believed secondhand smoke was somewhat or much safer for cannabis vs. tobacco in 2021 than in 2017 (40.2% vs. 35.1%; P < .001).
• More people endorsed the greater safety of secondhand smoke from cannabis vs. tobacco for children and pregnant women, and these perceptions remained similar over the study period.
• Younger and unmarried individuals were significantly more likely to move toward viewing smoking cannabis as safer than cigarettes, but legality of cannabis in respondents’ state of residence was not associated with change over time, suggesting the increasing perception of cannabis safety may be a national trend rather than a trend seen only in states with legalized cannabis.

IN PRACTICE:

“Understanding changing views on tobacco and cannabis risk is important given that increases in social acceptance and decreases in risk perception may be directly associated with public health and policies,” the investigators write.

SOURCE:

The study was conducted by Julia Chambers, MD, department of medicine, University of California, San Francisco, and colleagues. It was published online in JAMA Network Open.

LIMITATIONS:

The generalizability of the study may be limited by nonresponse and loss to follow-up over time. The wording of survey questions may have introduced bias in respondents. Participants were asked about safety of smoking cannabis joints vs. tobacco cigarettes and not to compare safety of other forms of smoked and vaped cannabis, tobacco, and nicotine.

DISCLOSURES:

The study received support from the California Tobacco-Related Disease Research Program. Dr. Chambers has no relevant conflicts of interest; author Katherine J. Hoggatt, PhD, MPH, department of medicine, UCSF, reported receiving grants from the Veterans Health Administration during the conduct of the study and grants from the National Institutes of Health, Rubin Family Foundation, and Veterans Health Administration outside the submitted work.

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

TOPLINE:

Results of a national survey show that despite a lack of data, many adults in the United States believe daily use of cannabis is safer than tobacco, a trend that’s growing over time.

METHODOLOGY:

• While aggressive campaigns have led to a dramatic reduction in the prevalence of cigarette smoking and created safer smoke-free environments, regulation governing cannabis – which is associated with some health benefits but also many negative health outcomes – has been less restrictive.
• The study included a nationally representative sample of 5,035 mostly White U.S. adults, mean age 53.4 years, who completed three online surveys between 2017 and 2021 on the safety of tobacco and cannabis.
• In all three waves of the survey, respondents were asked to rate the safety of smoking one marijuana joint a day to smoking one cigarette a day, and of secondhand smoke from marijuana to that from tobacco.
• Respondents also expressed views on the safety of secondhand smoke exposure (of both marijuana and tobacco) on specific populations, including children, pregnant women, and adults (ratings were from “completely unsafe” to “completely safe”).
• Independent variables included age, sex, race, ethnicity, education level, annual income, employment status, marital status, and state of residence.

TAKEAWAY:

• There was a significant shift over time toward an increasingly favorable perception of cannabis; more respondents reported cannabis was “somewhat safer” or “much safer” than tobacco in 2021 than 2017 (44.3% vs. 36.7%; P < .001), and more believed secondhand smoke was somewhat or much safer for cannabis vs. tobacco in 2021 than in 2017 (40.2% vs. 35.1%; P < .001).
• More people endorsed the greater safety of secondhand smoke from cannabis vs. tobacco for children and pregnant women, and these perceptions remained similar over the study period.
• Younger and unmarried individuals were significantly more likely to move toward viewing smoking cannabis as safer than cigarettes, but legality of cannabis in respondents’ state of residence was not associated with change over time, suggesting the increasing perception of cannabis safety may be a national trend rather than a trend seen only in states with legalized cannabis.

IN PRACTICE:

“Understanding changing views on tobacco and cannabis risk is important given that increases in social acceptance and decreases in risk perception may be directly associated with public health and policies,” the investigators write.

SOURCE:

The study was conducted by Julia Chambers, MD, department of medicine, University of California, San Francisco, and colleagues. It was published online in JAMA Network Open.

LIMITATIONS:

The generalizability of the study may be limited by nonresponse and loss to follow-up over time. The wording of survey questions may have introduced bias in respondents. Participants were asked about safety of smoking cannabis joints vs. tobacco cigarettes and not to compare safety of other forms of smoked and vaped cannabis, tobacco, and nicotine.

DISCLOSURES:

The study received support from the California Tobacco-Related Disease Research Program. Dr. Chambers has no relevant conflicts of interest; author Katherine J. Hoggatt, PhD, MPH, department of medicine, UCSF, reported receiving grants from the Veterans Health Administration during the conduct of the study and grants from the National Institutes of Health, Rubin Family Foundation, and Veterans Health Administration outside the submitted work.

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

An increase in cases of respiratory syncytial virus (RSV) in Florida and Georgia signals that RSV season has begun. 

The Centers for Disease Control and Prevention issued a national alert to health officials Sept. 5, urging them to offer new medicines that can prevent severe cases of the respiratory virus in very young children and in older people. Those two groups are at the highest risk of potentially deadly complications from RSV.

Typically, the CDC considers the start of RSV season to occur when the rate of positive tests for the virus goes above 3% for 2 consecutive weeks. In Florida, the rate has been around 5% in recent weeks, and in Georgia, there has been an increase in RSV-related hospitalizations. Most of the hospitalizations in Georgia have been among infants less than a year old.

“Historically, such regional increases have predicted the beginning of RSV season nationally, with increased RSV activity spreading north and west over the following 2-3 months,” the CDC said.

Most children have been infected with RSV by the time they are 2 years old. Historically, up to 80,000 children under 5 years old are hospitalized annually because of the virus, and between 100 and 300 die from complications each year. 

Those figures could be drastically different this year because new preventive treatments are available.

The CDC recommends that all children under 8 months old receive the newly approved monoclonal antibody treatment nirsevimab (Beyfortus). Children up to 19 months old at high risk of severe complications from RSV are also eligible for the single-dose shot. In clinical trials, the treatment was 80% effective at preventing RSV infections from becoming so severe that children had to be hospitalized. The protection lasted about 5 months.

Older people are also at a heightened risk of severe illness from RSV, and two new vaccines are available this season. The vaccines are called Arexvy and Abrysvo, and the single-dose shots are approved for people ages 60 years and older. They are more than 80% effective at making severe lower respiratory complications less likely.

Last year’s RSV season started during the summer and peaked in October and November, which was earlier than usual. There’s no indication yet of when RSV season may peak this year. Last year and throughout the pandemic, RSV held its historical pattern of starting in Florida.

A version of this article appeared on WebMD.com.

An increase in cases of respiratory syncytial virus (RSV) in Florida and Georgia signals that RSV season has begun. 

The Centers for Disease Control and Prevention issued a national alert to health officials Sept. 5, urging them to offer new medicines that can prevent severe cases of the respiratory virus in very young children and in older people. Those two groups are at the highest risk of potentially deadly complications from RSV.

Typically, the CDC considers the start of RSV season to occur when the rate of positive tests for the virus goes above 3% for 2 consecutive weeks. In Florida, the rate has been around 5% in recent weeks, and in Georgia, there has been an increase in RSV-related hospitalizations. Most of the hospitalizations in Georgia have been among infants less than a year old.

“Historically, such regional increases have predicted the beginning of RSV season nationally, with increased RSV activity spreading north and west over the following 2-3 months,” the CDC said.

Most children have been infected with RSV by the time they are 2 years old. Historically, up to 80,000 children under 5 years old are hospitalized annually because of the virus, and between 100 and 300 die from complications each year. 

Those figures could be drastically different this year because new preventive treatments are available.

The CDC recommends that all children under 8 months old receive the newly approved monoclonal antibody treatment nirsevimab (Beyfortus). Children up to 19 months old at high risk of severe complications from RSV are also eligible for the single-dose shot. In clinical trials, the treatment was 80% effective at preventing RSV infections from becoming so severe that children had to be hospitalized. The protection lasted about 5 months.

Older people are also at a heightened risk of severe illness from RSV, and two new vaccines are available this season. The vaccines are called Arexvy and Abrysvo, and the single-dose shots are approved for people ages 60 years and older. They are more than 80% effective at making severe lower respiratory complications less likely.

Last year’s RSV season started during the summer and peaked in October and November, which was earlier than usual. There’s no indication yet of when RSV season may peak this year. Last year and throughout the pandemic, RSV held its historical pattern of starting in Florida.

A version of this article appeared on WebMD.com.

An increase in cases of respiratory syncytial virus (RSV) in Florida and Georgia signals that RSV season has begun. 

The Centers for Disease Control and Prevention issued a national alert to health officials Sept. 5, urging them to offer new medicines that can prevent severe cases of the respiratory virus in very young children and in older people. Those two groups are at the highest risk of potentially deadly complications from RSV.

Typically, the CDC considers the start of RSV season to occur when the rate of positive tests for the virus goes above 3% for 2 consecutive weeks. In Florida, the rate has been around 5% in recent weeks, and in Georgia, there has been an increase in RSV-related hospitalizations. Most of the hospitalizations in Georgia have been among infants less than a year old.

“Historically, such regional increases have predicted the beginning of RSV season nationally, with increased RSV activity spreading north and west over the following 2-3 months,” the CDC said.

Most children have been infected with RSV by the time they are 2 years old. Historically, up to 80,000 children under 5 years old are hospitalized annually because of the virus, and between 100 and 300 die from complications each year. 

Those figures could be drastically different this year because new preventive treatments are available.

The CDC recommends that all children under 8 months old receive the newly approved monoclonal antibody treatment nirsevimab (Beyfortus). Children up to 19 months old at high risk of severe complications from RSV are also eligible for the single-dose shot. In clinical trials, the treatment was 80% effective at preventing RSV infections from becoming so severe that children had to be hospitalized. The protection lasted about 5 months.

Older people are also at a heightened risk of severe illness from RSV, and two new vaccines are available this season. The vaccines are called Arexvy and Abrysvo, and the single-dose shots are approved for people ages 60 years and older. They are more than 80% effective at making severe lower respiratory complications less likely.

Last year’s RSV season started during the summer and peaked in October and November, which was earlier than usual. There’s no indication yet of when RSV season may peak this year. Last year and throughout the pandemic, RSV held its historical pattern of starting in Florida.

A version of this article appeared on WebMD.com.

Moderna says its upcoming COVID-19 vaccine should work against the BA.2.86 variant that has caused worry about a possible surge in cases.

“The company said its shot generated an 8.7-fold increase in neutralizing antibodies in humans against BA.2.86, which is being tracked by the World Health Organization and the U.S. Centers for Disease Control and Prevention,” Reuters reported.

“We think this is news people will want to hear as they prepare to go out and get their fall boosters,” Jacqueline Miller, Moderna head of infectious diseases, told the news agency.

The CDC said that the BA.2.86 variant might be more likely to infect people who have already had COVID or previous vaccinations. BA.2.86 is an Omicron variant. It has undergone more mutations than XBB.1.5, which has dominated most of this year and was the intended target of the updated shots.

BA.2.86 does not have a strong presence in the United States yet. However, officials are concerned about its high number of mutations, NBC News reported.

The FDA is expected to approve the new Moderna shot by early October.

Pfizer told NBC that its updated booster also generated a strong antibody response against Omicron variants, including BA.2.86.

COVID-19 cases and hospitalizations have been increasing in the U.S. because of the rise of several variants. 

Experts told Reuters that BA.2.86 probably won’t cause a wave of severe disease and death because immunity has been built up around the world through previous infections and mass vaccinations.

A version of this article appeared on WebMD.com.

Moderna says its upcoming COVID-19 vaccine should work against the BA.2.86 variant that has caused worry about a possible surge in cases.

“The company said its shot generated an 8.7-fold increase in neutralizing antibodies in humans against BA.2.86, which is being tracked by the World Health Organization and the U.S. Centers for Disease Control and Prevention,” Reuters reported.

“We think this is news people will want to hear as they prepare to go out and get their fall boosters,” Jacqueline Miller, Moderna head of infectious diseases, told the news agency.

The CDC said that the BA.2.86 variant might be more likely to infect people who have already had COVID or previous vaccinations. BA.2.86 is an Omicron variant. It has undergone more mutations than XBB.1.5, which has dominated most of this year and was the intended target of the updated shots.

BA.2.86 does not have a strong presence in the United States yet. However, officials are concerned about its high number of mutations, NBC News reported.

The FDA is expected to approve the new Moderna shot by early October.

Pfizer told NBC that its updated booster also generated a strong antibody response against Omicron variants, including BA.2.86.

COVID-19 cases and hospitalizations have been increasing in the U.S. because of the rise of several variants. 

Experts told Reuters that BA.2.86 probably won’t cause a wave of severe disease and death because immunity has been built up around the world through previous infections and mass vaccinations.

A version of this article appeared on WebMD.com.

Moderna says its upcoming COVID-19 vaccine should work against the BA.2.86 variant that has caused worry about a possible surge in cases.

“The company said its shot generated an 8.7-fold increase in neutralizing antibodies in humans against BA.2.86, which is being tracked by the World Health Organization and the U.S. Centers for Disease Control and Prevention,” Reuters reported.

“We think this is news people will want to hear as they prepare to go out and get their fall boosters,” Jacqueline Miller, Moderna head of infectious diseases, told the news agency.

The CDC said that the BA.2.86 variant might be more likely to infect people who have already had COVID or previous vaccinations. BA.2.86 is an Omicron variant. It has undergone more mutations than XBB.1.5, which has dominated most of this year and was the intended target of the updated shots.

BA.2.86 does not have a strong presence in the United States yet. However, officials are concerned about its high number of mutations, NBC News reported.

The FDA is expected to approve the new Moderna shot by early October.

Pfizer told NBC that its updated booster also generated a strong antibody response against Omicron variants, including BA.2.86.

COVID-19 cases and hospitalizations have been increasing in the U.S. because of the rise of several variants. 

Experts told Reuters that BA.2.86 probably won’t cause a wave of severe disease and death because immunity has been built up around the world through previous infections and mass vaccinations.

A version of this article appeared on WebMD.com.

To avoid cardiovascular disease, the American Heart Association (AHA) recommends performing at least 150 minutes of moderate-intensity aerobic activity every week, 75 minutes of intense aerobic activity every week, or a combination of both, preferably spread out throughout the week. But how knowledgeable are physicians when it comes to prescribing exercise, and how should patients be assessed so that appropriate physical activity can be recommended?

In a presentation titled, “Patient Evaluation and Exercise Prescription in Primary Prevention,” Thelma Sánchez Grillo, MD, a cardiologist at the Clínica Bíblica Hospital in San José, Costa Rica, explained the benefits and risks of exercise and gave recommendations for proper patient assessment before prescribing physical activity.

“Exercise has cardioprotective, emotional, antiarrhythmic, and antithrombotic benefits, and it reduces stress,” she explained.

She also noted that the risk regarding cardiopulmonary and musculoskeletal components must be evaluated, because exercise can itself trigger coronary events, and the last thing intended when prescribing exercise is to cause complications. “We must recommend exercise progressively. We can’t suggest a high-intensity regimen to a patient if they haven’t had any preconditioning where collateral circulation could be developed and lung and cardiac capacity could be improved.”

Dr. Sánchez went on to say that, according to the AHA, patients should be classified as follows: those who exercise and those who don’t, those with a history of cardiovascular, metabolic, or renal disease, and those with symptomatic and asymptomatic diseases, in order to consider the parameters when recommending exercise.

“If the patient has symptoms and is doing light physical activity, like walking, they can keep doing this exercise and don’t need further assessments. But if they have a symptomatic disease and are not exercising, they need to be evaluated after exercise has been prescribed, and not just clinically, either. Some sort of diagnostic method should be considered. Also, for patients who are physically active and who desire to increase the intensity of their exercise, the recommendation is to perform a detailed clinical examination and, if necessary, perform additional imaging studies.”

Warning signs

• Dizziness.
• Orthopnea.
• Abnormal heart rate.
• Edema in the lower extremities.
• Chest pain, especially when occurring with exercise.
• Intermittent claudication.
• Heart murmurs.
• Dyspnea.
• Reduced output.
• Fatigue.

Calibrating exercise parameters

The parameters of frequency (number of sessions per week), intensity (perceived exertion measured by heart rate reached), time, and type (aerobic exercise vs. strength training) should be considered when forming an appropriate prescription for exercise, explained Dr. Sánchez.

“The big problem is that most physicians don’t know how to prescribe it properly. And beyond knowing how, the important thing is that, when we’re with the patient during the consultation, we ought to be doing more than just establishing a routine. We need to be motivators and we need to be identifying obstacles and the patient’s interest in exercise, because it’s clear that incorporating physical activity into our daily lives helps improve the quality and length of life,” the specialist added.

The recommendations are straightforward: for individuals aged 18-64 years, 150 minutes of moderate-intensity activity per week, whether aerobic, strength training, or mixed, should be prescribed. “We need to encourage moving more and sitting less, and recommend comprehensive programs that include coordination, balance, and muscle strengthening. If a sedentary lifestyle is a risk factor, we need to encourage patients to start performing physical activity for 1-2 minutes every hour, because any exercise must be gradual and progressive to avoid complications,” she noted.
 

Evaluate, then recommend

The specialist emphasized the importance of making personalized prescriptions, exercising caution, and performing adequate assessments to know which exercise routine to recommend. “The patient should also be involved in their self-care and must have an adequate diet and hydration, and we need to remind them that they shouldn’t be exercising if they have an infection, due to the risk of myocarditis and sudden death,” she added.

Rafaelina Concepción, MD, cardiologist from the Dominican Republic and vice president of the Inter-American Society of Cardiology for Central America and the Caribbean, agreed with the importance of assessing risk and risk factors for patients who request an exercise routine. “For example, in patients with prediabetes, it has been shown that exercising can slow the progression to diabetes. The essential thing is to use stratification and know what kind of exercise to recommend, whether aerobic, strength training, or a combination of the two, to improve functional capacity without reaching the threshold heart rate while reducing the risk of other comorbidities like hypertension, obesity, and high lipids, and achieving lifestyle changes.”

Carlos Franco, MD, a cardiologist in El Salvador, emphasized that there is no such thing as zero risk when evaluating a patient. “Of course, there’s a difference between an athlete and someone who isn’t physically active, but we need to profile all patients correctly, evaluate risk factors in detail, not overlook subclinical cardiovascular disease, and check whether they need stress testing or additional imaging to assess cardiac functional capacity. Also, exercise must be prescribed gradually, and the patient’s nutritional status must be assessed.”

Dr. Franco ended by explaining that physicians must understand how to prescribe the basics of exercise and make small interventions of reasonable intensity, provide practical advice, and, to the extent possible, rely on specialists such as physiatrists, sports specialists, and physical therapists.

This article was translated from the Medscape Spanish Edition. A version of this article appeared on Medscape.com.

To avoid cardiovascular disease, the American Heart Association (AHA) recommends performing at least 150 minutes of moderate-intensity aerobic activity every week, 75 minutes of intense aerobic activity every week, or a combination of both, preferably spread out throughout the week. But how knowledgeable are physicians when it comes to prescribing exercise, and how should patients be assessed so that appropriate physical activity can be recommended?

In a presentation titled, “Patient Evaluation and Exercise Prescription in Primary Prevention,” Thelma Sánchez Grillo, MD, a cardiologist at the Clínica Bíblica Hospital in San José, Costa Rica, explained the benefits and risks of exercise and gave recommendations for proper patient assessment before prescribing physical activity.

“Exercise has cardioprotective, emotional, antiarrhythmic, and antithrombotic benefits, and it reduces stress,” she explained.

She also noted that the risk regarding cardiopulmonary and musculoskeletal components must be evaluated, because exercise can itself trigger coronary events, and the last thing intended when prescribing exercise is to cause complications. “We must recommend exercise progressively. We can’t suggest a high-intensity regimen to a patient if they haven’t had any preconditioning where collateral circulation could be developed and lung and cardiac capacity could be improved.”

Dr. Sánchez went on to say that, according to the AHA, patients should be classified as follows: those who exercise and those who don’t, those with a history of cardiovascular, metabolic, or renal disease, and those with symptomatic and asymptomatic diseases, in order to consider the parameters when recommending exercise.

“If the patient has symptoms and is doing light physical activity, like walking, they can keep doing this exercise and don’t need further assessments. But if they have a symptomatic disease and are not exercising, they need to be evaluated after exercise has been prescribed, and not just clinically, either. Some sort of diagnostic method should be considered. Also, for patients who are physically active and who desire to increase the intensity of their exercise, the recommendation is to perform a detailed clinical examination and, if necessary, perform additional imaging studies.”

Warning signs

• Dizziness.
• Orthopnea.
• Abnormal heart rate.
• Edema in the lower extremities.
• Chest pain, especially when occurring with exercise.
• Intermittent claudication.
• Heart murmurs.
• Dyspnea.
• Reduced output.
• Fatigue.

Calibrating exercise parameters

The parameters of frequency (number of sessions per week), intensity (perceived exertion measured by heart rate reached), time, and type (aerobic exercise vs. strength training) should be considered when forming an appropriate prescription for exercise, explained Dr. Sánchez.

“The big problem is that most physicians don’t know how to prescribe it properly. And beyond knowing how, the important thing is that, when we’re with the patient during the consultation, we ought to be doing more than just establishing a routine. We need to be motivators and we need to be identifying obstacles and the patient’s interest in exercise, because it’s clear that incorporating physical activity into our daily lives helps improve the quality and length of life,” the specialist added.

The recommendations are straightforward: for individuals aged 18-64 years, 150 minutes of moderate-intensity activity per week, whether aerobic, strength training, or mixed, should be prescribed. “We need to encourage moving more and sitting less, and recommend comprehensive programs that include coordination, balance, and muscle strengthening. If a sedentary lifestyle is a risk factor, we need to encourage patients to start performing physical activity for 1-2 minutes every hour, because any exercise must be gradual and progressive to avoid complications,” she noted.
 

Evaluate, then recommend

The specialist emphasized the importance of making personalized prescriptions, exercising caution, and performing adequate assessments to know which exercise routine to recommend. “The patient should also be involved in their self-care and must have an adequate diet and hydration, and we need to remind them that they shouldn’t be exercising if they have an infection, due to the risk of myocarditis and sudden death,” she added.

Rafaelina Concepción, MD, cardiologist from the Dominican Republic and vice president of the Inter-American Society of Cardiology for Central America and the Caribbean, agreed with the importance of assessing risk and risk factors for patients who request an exercise routine. “For example, in patients with prediabetes, it has been shown that exercising can slow the progression to diabetes. The essential thing is to use stratification and know what kind of exercise to recommend, whether aerobic, strength training, or a combination of the two, to improve functional capacity without reaching the threshold heart rate while reducing the risk of other comorbidities like hypertension, obesity, and high lipids, and achieving lifestyle changes.”

Carlos Franco, MD, a cardiologist in El Salvador, emphasized that there is no such thing as zero risk when evaluating a patient. “Of course, there’s a difference between an athlete and someone who isn’t physically active, but we need to profile all patients correctly, evaluate risk factors in detail, not overlook subclinical cardiovascular disease, and check whether they need stress testing or additional imaging to assess cardiac functional capacity. Also, exercise must be prescribed gradually, and the patient’s nutritional status must be assessed.”

Dr. Franco ended by explaining that physicians must understand how to prescribe the basics of exercise and make small interventions of reasonable intensity, provide practical advice, and, to the extent possible, rely on specialists such as physiatrists, sports specialists, and physical therapists.

This article was translated from the Medscape Spanish Edition. A version of this article appeared on Medscape.com.

To avoid cardiovascular disease, the American Heart Association (AHA) recommends performing at least 150 minutes of moderate-intensity aerobic activity every week, 75 minutes of intense aerobic activity every week, or a combination of both, preferably spread out throughout the week. But how knowledgeable are physicians when it comes to prescribing exercise, and how should patients be assessed so that appropriate physical activity can be recommended?

In a presentation titled, “Patient Evaluation and Exercise Prescription in Primary Prevention,” Thelma Sánchez Grillo, MD, a cardiologist at the Clínica Bíblica Hospital in San José, Costa Rica, explained the benefits and risks of exercise and gave recommendations for proper patient assessment before prescribing physical activity.

“Exercise has cardioprotective, emotional, antiarrhythmic, and antithrombotic benefits, and it reduces stress,” she explained.

She also noted that the risk regarding cardiopulmonary and musculoskeletal components must be evaluated, because exercise can itself trigger coronary events, and the last thing intended when prescribing exercise is to cause complications. “We must recommend exercise progressively. We can’t suggest a high-intensity regimen to a patient if they haven’t had any preconditioning where collateral circulation could be developed and lung and cardiac capacity could be improved.”

Dr. Sánchez went on to say that, according to the AHA, patients should be classified as follows: those who exercise and those who don’t, those with a history of cardiovascular, metabolic, or renal disease, and those with symptomatic and asymptomatic diseases, in order to consider the parameters when recommending exercise.

“If the patient has symptoms and is doing light physical activity, like walking, they can keep doing this exercise and don’t need further assessments. But if they have a symptomatic disease and are not exercising, they need to be evaluated after exercise has been prescribed, and not just clinically, either. Some sort of diagnostic method should be considered. Also, for patients who are physically active and who desire to increase the intensity of their exercise, the recommendation is to perform a detailed clinical examination and, if necessary, perform additional imaging studies.”

Warning signs

• Dizziness.
• Orthopnea.
• Abnormal heart rate.
• Edema in the lower extremities.
• Chest pain, especially when occurring with exercise.
• Intermittent claudication.
• Heart murmurs.
• Dyspnea.
• Reduced output.
• Fatigue.

Calibrating exercise parameters

The parameters of frequency (number of sessions per week), intensity (perceived exertion measured by heart rate reached), time, and type (aerobic exercise vs. strength training) should be considered when forming an appropriate prescription for exercise, explained Dr. Sánchez.

“The big problem is that most physicians don’t know how to prescribe it properly. And beyond knowing how, the important thing is that, when we’re with the patient during the consultation, we ought to be doing more than just establishing a routine. We need to be motivators and we need to be identifying obstacles and the patient’s interest in exercise, because it’s clear that incorporating physical activity into our daily lives helps improve the quality and length of life,” the specialist added.

The recommendations are straightforward: for individuals aged 18-64 years, 150 minutes of moderate-intensity activity per week, whether aerobic, strength training, or mixed, should be prescribed. “We need to encourage moving more and sitting less, and recommend comprehensive programs that include coordination, balance, and muscle strengthening. If a sedentary lifestyle is a risk factor, we need to encourage patients to start performing physical activity for 1-2 minutes every hour, because any exercise must be gradual and progressive to avoid complications,” she noted.
 

Evaluate, then recommend

The specialist emphasized the importance of making personalized prescriptions, exercising caution, and performing adequate assessments to know which exercise routine to recommend. “The patient should also be involved in their self-care and must have an adequate diet and hydration, and we need to remind them that they shouldn’t be exercising if they have an infection, due to the risk of myocarditis and sudden death,” she added.

Rafaelina Concepción, MD, cardiologist from the Dominican Republic and vice president of the Inter-American Society of Cardiology for Central America and the Caribbean, agreed with the importance of assessing risk and risk factors for patients who request an exercise routine. “For example, in patients with prediabetes, it has been shown that exercising can slow the progression to diabetes. The essential thing is to use stratification and know what kind of exercise to recommend, whether aerobic, strength training, or a combination of the two, to improve functional capacity without reaching the threshold heart rate while reducing the risk of other comorbidities like hypertension, obesity, and high lipids, and achieving lifestyle changes.”

Carlos Franco, MD, a cardiologist in El Salvador, emphasized that there is no such thing as zero risk when evaluating a patient. “Of course, there’s a difference between an athlete and someone who isn’t physically active, but we need to profile all patients correctly, evaluate risk factors in detail, not overlook subclinical cardiovascular disease, and check whether they need stress testing or additional imaging to assess cardiac functional capacity. Also, exercise must be prescribed gradually, and the patient’s nutritional status must be assessed.”

Dr. Franco ended by explaining that physicians must understand how to prescribe the basics of exercise and make small interventions of reasonable intensity, provide practical advice, and, to the extent possible, rely on specialists such as physiatrists, sports specialists, and physical therapists.

This article was translated from the Medscape Spanish Edition. A version of this article appeared on Medscape.com.

AMSTERDAM – At the Radical Health Festival Helsinki this past June, Gerhard Hindricks, MD, PhD, was challenged by a young man when he dared to look into the crystal ball. “In the middle of my presentation, a maybe 25-year-old man stood up and said, ‘Dr. Hindricks, in 10 years, we will no longer need you!’ ” Dr. Hindricks noted at the great debate event “Will Artificial Intelligence Replace Cardiologists?” held at the annual congress of the European Society of Cardiology. He subsequently had an interesting discussion with the man. In his opinion, the future role of the physician is “an unavoidable discussion for cardiovascular medicine.”

Dr. Hindricks, from the University of Leipzig (Germany), considered artificial intelligence in cardiology to be “potentially the most important topic of the congress” and suggested that “we have to be more open to introducing new technologies into our practice. I sometimes have the impression that we are neither quick nor open enough to introducing new technologies, to leaving the old and to letting the new, better technology be effective in our patients.”
 

Asset or threat?

AI is dramatically changing the field and the role of the physician – but it is not making cardiologists superfluous. In this respect, Dr. Hindricks; Folkert Asselbergs, MD, PhD, professor of cardiology at the Amsterdam Heart Center; and Harriette Van Spall, MD, associate professor of medicine at McMaster University in Hamilton, Ont., were unanimous: They agreed, although they assess the opportunities and risks posed by AI differently.

Dr. Asselbergs saw AI as less of a threat and more of an asset. In his opinion, a cardiology-specific speech model could be used to the advantage of both patient and physician. A medical chatbot could offer patients information and suggested readings, and it could create the patient’s self-reported medical history and medical summaries for laypersons.

For physicians, a medical chatbot could be beneficial in the creation of patient reports, the selection of relevant literature, the creation of automated laboratory orders, the review of clinical discharge reports, for consultations, and for processing the consultations, as well as for complying with guidelines.

Dr. Asselbergs considered AI’s primary advantage to be the time that it saves, which can then be used “for complex interventions, palliative care, and acute treatment.”

The advantages of AI, he said, include the following:

• Efficiency and scale of AI in data analysis
• Automation
• AI does not get tired and is not biased
• Proactive health care provision and early intervention
• Reduction in health care costs
• Remains up to date with the latest knowledge.

He sees the following disadvantages:

• Lack of human contact, empathy, and the physician-patient relationship
• Ethical implications and challenges
• The potential for AI to make incorrect diagnoses or to be influenced by bias in the training data.

Medical supervision needed

For Dr. Van Spall, AI is primarily a tool. A generative AI could create useful materials such as images, videos, text, sound, 3D models, virtual environments, notes for clinical visits, medical summaries, and answers to clinical queries. But “the use of AI can lead to misinformation and expose the patient to risk, and there are no laws regulating liability.”

Dr. Van Spall stressed that AI could greatly increase efficiency. For example, in echocardiography, chamber volumes and function can be quantified automatically. ECGs can be interpreted automatically. “Even the workload associated with reading off of screens can be reduced, compared with unsupported reading.” However, she maintained that the use of AI requires medical supervision. “AI cannot function without cardiologists,” since it has “enormous limitations.” Dr. Van Spall does not see “any way to close the gaps that cardiologists may leave in terms of knowledge, service, and communication.”

According to the American College of Cardiology, 26% of the 32,000 cardiologists in the United States are older than 61 years. “That is a net loss of 546 cardiologists per year. We must use AI to support cardiologists, not to replace them,” said Dr. Van Spall.
 

Cardiologists becoming supervisors?

Dr. Asselbergs saw AI as a means of creating more equality. “Nearly everyone now has a smartphone. Let’s take ultrasound via AI as an example. There are rural areas that have no access to health care. If nurses or dietitians there create an ultrasound based on AI and send pictures for medical analysis, it will really help people.”

Dr. Hindricks hypothesized that machine learning and AI will make a huge difference in the field of rare diseases. Rare diseases are massively underdiagnosed simply because they are so rare and it requires a lot of experience to recognize them. “Digital elements can significantly support this,” said Dr. Hindricks.

For Dr. Van Spall, AI could make care and treatment safer. There will be more digital tools and virtual models available during training too. “I believe that the cardiologist will continue to occupy an important role, in terms of communication and processes. I do not see this role disappearing,” she said. Efficiency and precision are so important. “To make good decisions, we also want to get in touch with the person we trust.”

For Dr. Asselbergs, the role of cardiologists will change to one of a supervisor. “More joint decision-making, more discussion with our patients: I think this is the direction we’re heading in.”

This article was translated from the Medscape German Edition.

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

AMSTERDAM – At the Radical Health Festival Helsinki this past June, Gerhard Hindricks, MD, PhD, was challenged by a young man when he dared to look into the crystal ball. “In the middle of my presentation, a maybe 25-year-old man stood up and said, ‘Dr. Hindricks, in 10 years, we will no longer need you!’ ” Dr. Hindricks noted at the great debate event “Will Artificial Intelligence Replace Cardiologists?” held at the annual congress of the European Society of Cardiology. He subsequently had an interesting discussion with the man. In his opinion, the future role of the physician is “an unavoidable discussion for cardiovascular medicine.”

Dr. Hindricks, from the University of Leipzig (Germany), considered artificial intelligence in cardiology to be “potentially the most important topic of the congress” and suggested that “we have to be more open to introducing new technologies into our practice. I sometimes have the impression that we are neither quick nor open enough to introducing new technologies, to leaving the old and to letting the new, better technology be effective in our patients.”
 

Asset or threat?

AI is dramatically changing the field and the role of the physician – but it is not making cardiologists superfluous. In this respect, Dr. Hindricks; Folkert Asselbergs, MD, PhD, professor of cardiology at the Amsterdam Heart Center; and Harriette Van Spall, MD, associate professor of medicine at McMaster University in Hamilton, Ont., were unanimous: They agreed, although they assess the opportunities and risks posed by AI differently.

Dr. Asselbergs saw AI as less of a threat and more of an asset. In his opinion, a cardiology-specific speech model could be used to the advantage of both patient and physician. A medical chatbot could offer patients information and suggested readings, and it could create the patient’s self-reported medical history and medical summaries for laypersons.

For physicians, a medical chatbot could be beneficial in the creation of patient reports, the selection of relevant literature, the creation of automated laboratory orders, the review of clinical discharge reports, for consultations, and for processing the consultations, as well as for complying with guidelines.

Dr. Asselbergs considered AI’s primary advantage to be the time that it saves, which can then be used “for complex interventions, palliative care, and acute treatment.”

The advantages of AI, he said, include the following:

• Efficiency and scale of AI in data analysis
• Automation
• AI does not get tired and is not biased
• Proactive health care provision and early intervention
• Reduction in health care costs
• Remains up to date with the latest knowledge.

He sees the following disadvantages:

• Lack of human contact, empathy, and the physician-patient relationship
• Ethical implications and challenges
• The potential for AI to make incorrect diagnoses or to be influenced by bias in the training data.

Medical supervision needed

For Dr. Van Spall, AI is primarily a tool. A generative AI could create useful materials such as images, videos, text, sound, 3D models, virtual environments, notes for clinical visits, medical summaries, and answers to clinical queries. But “the use of AI can lead to misinformation and expose the patient to risk, and there are no laws regulating liability.”

Dr. Van Spall stressed that AI could greatly increase efficiency. For example, in echocardiography, chamber volumes and function can be quantified automatically. ECGs can be interpreted automatically. “Even the workload associated with reading off of screens can be reduced, compared with unsupported reading.” However, she maintained that the use of AI requires medical supervision. “AI cannot function without cardiologists,” since it has “enormous limitations.” Dr. Van Spall does not see “any way to close the gaps that cardiologists may leave in terms of knowledge, service, and communication.”

According to the American College of Cardiology, 26% of the 32,000 cardiologists in the United States are older than 61 years. “That is a net loss of 546 cardiologists per year. We must use AI to support cardiologists, not to replace them,” said Dr. Van Spall.
 

Cardiologists becoming supervisors?

Dr. Asselbergs saw AI as a means of creating more equality. “Nearly everyone now has a smartphone. Let’s take ultrasound via AI as an example. There are rural areas that have no access to health care. If nurses or dietitians there create an ultrasound based on AI and send pictures for medical analysis, it will really help people.”

Dr. Hindricks hypothesized that machine learning and AI will make a huge difference in the field of rare diseases. Rare diseases are massively underdiagnosed simply because they are so rare and it requires a lot of experience to recognize them. “Digital elements can significantly support this,” said Dr. Hindricks.

For Dr. Van Spall, AI could make care and treatment safer. There will be more digital tools and virtual models available during training too. “I believe that the cardiologist will continue to occupy an important role, in terms of communication and processes. I do not see this role disappearing,” she said. Efficiency and precision are so important. “To make good decisions, we also want to get in touch with the person we trust.”

For Dr. Asselbergs, the role of cardiologists will change to one of a supervisor. “More joint decision-making, more discussion with our patients: I think this is the direction we’re heading in.”

This article was translated from the Medscape German Edition.

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

AMSTERDAM – At the Radical Health Festival Helsinki this past June, Gerhard Hindricks, MD, PhD, was challenged by a young man when he dared to look into the crystal ball. “In the middle of my presentation, a maybe 25-year-old man stood up and said, ‘Dr. Hindricks, in 10 years, we will no longer need you!’ ” Dr. Hindricks noted at the great debate event “Will Artificial Intelligence Replace Cardiologists?” held at the annual congress of the European Society of Cardiology. He subsequently had an interesting discussion with the man. In his opinion, the future role of the physician is “an unavoidable discussion for cardiovascular medicine.”

Dr. Hindricks, from the University of Leipzig (Germany), considered artificial intelligence in cardiology to be “potentially the most important topic of the congress” and suggested that “we have to be more open to introducing new technologies into our practice. I sometimes have the impression that we are neither quick nor open enough to introducing new technologies, to leaving the old and to letting the new, better technology be effective in our patients.”
 

Asset or threat?

AI is dramatically changing the field and the role of the physician – but it is not making cardiologists superfluous. In this respect, Dr. Hindricks; Folkert Asselbergs, MD, PhD, professor of cardiology at the Amsterdam Heart Center; and Harriette Van Spall, MD, associate professor of medicine at McMaster University in Hamilton, Ont., were unanimous: They agreed, although they assess the opportunities and risks posed by AI differently.

Dr. Asselbergs saw AI as less of a threat and more of an asset. In his opinion, a cardiology-specific speech model could be used to the advantage of both patient and physician. A medical chatbot could offer patients information and suggested readings, and it could create the patient’s self-reported medical history and medical summaries for laypersons.

For physicians, a medical chatbot could be beneficial in the creation of patient reports, the selection of relevant literature, the creation of automated laboratory orders, the review of clinical discharge reports, for consultations, and for processing the consultations, as well as for complying with guidelines.

Dr. Asselbergs considered AI’s primary advantage to be the time that it saves, which can then be used “for complex interventions, palliative care, and acute treatment.”

The advantages of AI, he said, include the following:

• Efficiency and scale of AI in data analysis
• Automation
• AI does not get tired and is not biased
• Proactive health care provision and early intervention
• Reduction in health care costs
• Remains up to date with the latest knowledge.

He sees the following disadvantages:

• Lack of human contact, empathy, and the physician-patient relationship
• Ethical implications and challenges
• The potential for AI to make incorrect diagnoses or to be influenced by bias in the training data.

Medical supervision needed

For Dr. Van Spall, AI is primarily a tool. A generative AI could create useful materials such as images, videos, text, sound, 3D models, virtual environments, notes for clinical visits, medical summaries, and answers to clinical queries. But “the use of AI can lead to misinformation and expose the patient to risk, and there are no laws regulating liability.”

Dr. Van Spall stressed that AI could greatly increase efficiency. For example, in echocardiography, chamber volumes and function can be quantified automatically. ECGs can be interpreted automatically. “Even the workload associated with reading off of screens can be reduced, compared with unsupported reading.” However, she maintained that the use of AI requires medical supervision. “AI cannot function without cardiologists,” since it has “enormous limitations.” Dr. Van Spall does not see “any way to close the gaps that cardiologists may leave in terms of knowledge, service, and communication.”

According to the American College of Cardiology, 26% of the 32,000 cardiologists in the United States are older than 61 years. “That is a net loss of 546 cardiologists per year. We must use AI to support cardiologists, not to replace them,” said Dr. Van Spall.
 

Cardiologists becoming supervisors?

Dr. Asselbergs saw AI as a means of creating more equality. “Nearly everyone now has a smartphone. Let’s take ultrasound via AI as an example. There are rural areas that have no access to health care. If nurses or dietitians there create an ultrasound based on AI and send pictures for medical analysis, it will really help people.”

Dr. Hindricks hypothesized that machine learning and AI will make a huge difference in the field of rare diseases. Rare diseases are massively underdiagnosed simply because they are so rare and it requires a lot of experience to recognize them. “Digital elements can significantly support this,” said Dr. Hindricks.

For Dr. Van Spall, AI could make care and treatment safer. There will be more digital tools and virtual models available during training too. “I believe that the cardiologist will continue to occupy an important role, in terms of communication and processes. I do not see this role disappearing,” she said. Efficiency and precision are so important. “To make good decisions, we also want to get in touch with the person we trust.”

For Dr. Asselbergs, the role of cardiologists will change to one of a supervisor. “More joint decision-making, more discussion with our patients: I think this is the direction we’re heading in.”

This article was translated from the Medscape German Edition.

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

TOPLINE

Biochemical recurrence (BCR) falls short as a reliable surrogate for overall survival in localized prostate cancer trials and may not be a suitable primary endpoint.

METHODOLOGY

• In trials of localized prostate cancer, BCR remains a controversial surrogate endpoint for overall survival.
• The meta-analysis included 10,741 patients from 11 randomized clinical trials; the median follow-up was 9.2 years.
• Interventions included radiotherapy dose escalation, in which high-dose radiotherapy was compared with conventional radiotherapy (n = 3,639); short-term androgen deprivation therapy (ADT), in which radiotherapy plus short-term ADT was compared with radiotherapy alone (n = 3,930); and ADT prolongation, in which radiotherapy plus long-term ADT was compared with radiotherapy plus short-term ADT (n = 3,772).
• Prentice criteria and the two-stage meta-analytic approach were used to assess BCR as a surrogate endpoint for overall survival.
• The researchers assessed the treatment effect on BCR and on overall survival.

TAKEAWAY

• With regard to treatment effect on BCR, the three interventions significantly reduced BCR risk – dose escalation by 29%, short-term ADT by 47%, and ADT prolongation by 46%. With regard to survival, only short- and long-term ADT significantly improved overall survival, by 9% and 14%, respectively.
• At 48 months, BCR was associated with significantly increased mortality risk: 2.46-fold increased risk for dose escalation, 1.51-fold greater risk for short-term ADT, and 2.31-fold higher risk for ADT prolongation.
• However, after adjusting for BCR at 48 months, there was no significant treatment effect on overall survival (hazard ratio, 1.10; [95% confidence interval, 0.96-1.27]; HR, 0.96 [95% CI, 0.87-1.06]; HR, 1.00 [95% CI, 0.90-1.12], respectively).
• Patient-level correlation between time to BCR and overall survival was low after censoring for noncancer-related deaths. The correlation between BCR-free survival and overall survival ranged from low to moderate.

IN PRACTICE

Overall, “these results strongly suggest that BCR-based endpoints should not be the primary endpoint in randomized trials conducted for localized [prostate cancer],” the authors concluded. They added that metastasis-free survival represents a more appropriate measure.

SOURCE

The study was led by senior author Amar Kishan, MD, of the University of California, Los Angeles, and was published online in the Journal of Clinical Oncology.

LIMITATIONS

• The trials used different definitions of BCR – the older American Society of Therapeutic Radiation and Oncology definition, and the more current Phoenix criteria.
• Some trials were conducted more than 20 years ago, and a variety of factors, including patient selection, staging, diagnostic criteria, and therapeutic approaches, have evolved in that time.
• Quality of life was not captured.

DISCLOSURES

The study received support from Cancer Research UK, the UK National Health Service, the Prostate Cancer National Institutes of Health Specialized Programs of Research Excellence, the UK Department of Defense, the Prostate Cancer Foundation, and the American Society for Radiation Oncology. Authors’ relevant financial relationships are detailed in the published study.

A version of this article appeared on Medscape.com.

TOPLINE

Biochemical recurrence (BCR) falls short as a reliable surrogate for overall survival in localized prostate cancer trials and may not be a suitable primary endpoint.

METHODOLOGY

• In trials of localized prostate cancer, BCR remains a controversial surrogate endpoint for overall survival.
• The meta-analysis included 10,741 patients from 11 randomized clinical trials; the median follow-up was 9.2 years.
• Interventions included radiotherapy dose escalation, in which high-dose radiotherapy was compared with conventional radiotherapy (n = 3,639); short-term androgen deprivation therapy (ADT), in which radiotherapy plus short-term ADT was compared with radiotherapy alone (n = 3,930); and ADT prolongation, in which radiotherapy plus long-term ADT was compared with radiotherapy plus short-term ADT (n = 3,772).
• Prentice criteria and the two-stage meta-analytic approach were used to assess BCR as a surrogate endpoint for overall survival.
• The researchers assessed the treatment effect on BCR and on overall survival.

TAKEAWAY

• With regard to treatment effect on BCR, the three interventions significantly reduced BCR risk – dose escalation by 29%, short-term ADT by 47%, and ADT prolongation by 46%. With regard to survival, only short- and long-term ADT significantly improved overall survival, by 9% and 14%, respectively.
• At 48 months, BCR was associated with significantly increased mortality risk: 2.46-fold increased risk for dose escalation, 1.51-fold greater risk for short-term ADT, and 2.31-fold higher risk for ADT prolongation.
• However, after adjusting for BCR at 48 months, there was no significant treatment effect on overall survival (hazard ratio, 1.10; [95% confidence interval, 0.96-1.27]; HR, 0.96 [95% CI, 0.87-1.06]; HR, 1.00 [95% CI, 0.90-1.12], respectively).
• Patient-level correlation between time to BCR and overall survival was low after censoring for noncancer-related deaths. The correlation between BCR-free survival and overall survival ranged from low to moderate.

IN PRACTICE

Overall, “these results strongly suggest that BCR-based endpoints should not be the primary endpoint in randomized trials conducted for localized [prostate cancer],” the authors concluded. They added that metastasis-free survival represents a more appropriate measure.

SOURCE

The study was led by senior author Amar Kishan, MD, of the University of California, Los Angeles, and was published online in the Journal of Clinical Oncology.

LIMITATIONS

• The trials used different definitions of BCR – the older American Society of Therapeutic Radiation and Oncology definition, and the more current Phoenix criteria.
• Some trials were conducted more than 20 years ago, and a variety of factors, including patient selection, staging, diagnostic criteria, and therapeutic approaches, have evolved in that time.
• Quality of life was not captured.

DISCLOSURES

The study received support from Cancer Research UK, the UK National Health Service, the Prostate Cancer National Institutes of Health Specialized Programs of Research Excellence, the UK Department of Defense, the Prostate Cancer Foundation, and the American Society for Radiation Oncology. Authors’ relevant financial relationships are detailed in the published study.

A version of this article appeared on Medscape.com.

TOPLINE

Biochemical recurrence (BCR) falls short as a reliable surrogate for overall survival in localized prostate cancer trials and may not be a suitable primary endpoint.

METHODOLOGY

• In trials of localized prostate cancer, BCR remains a controversial surrogate endpoint for overall survival.
• The meta-analysis included 10,741 patients from 11 randomized clinical trials; the median follow-up was 9.2 years.
• Interventions included radiotherapy dose escalation, in which high-dose radiotherapy was compared with conventional radiotherapy (n = 3,639); short-term androgen deprivation therapy (ADT), in which radiotherapy plus short-term ADT was compared with radiotherapy alone (n = 3,930); and ADT prolongation, in which radiotherapy plus long-term ADT was compared with radiotherapy plus short-term ADT (n = 3,772).
• Prentice criteria and the two-stage meta-analytic approach were used to assess BCR as a surrogate endpoint for overall survival.
• The researchers assessed the treatment effect on BCR and on overall survival.

TAKEAWAY

• With regard to treatment effect on BCR, the three interventions significantly reduced BCR risk – dose escalation by 29%, short-term ADT by 47%, and ADT prolongation by 46%. With regard to survival, only short- and long-term ADT significantly improved overall survival, by 9% and 14%, respectively.
• At 48 months, BCR was associated with significantly increased mortality risk: 2.46-fold increased risk for dose escalation, 1.51-fold greater risk for short-term ADT, and 2.31-fold higher risk for ADT prolongation.
• However, after adjusting for BCR at 48 months, there was no significant treatment effect on overall survival (hazard ratio, 1.10; [95% confidence interval, 0.96-1.27]; HR, 0.96 [95% CI, 0.87-1.06]; HR, 1.00 [95% CI, 0.90-1.12], respectively).
• Patient-level correlation between time to BCR and overall survival was low after censoring for noncancer-related deaths. The correlation between BCR-free survival and overall survival ranged from low to moderate.

IN PRACTICE

Overall, “these results strongly suggest that BCR-based endpoints should not be the primary endpoint in randomized trials conducted for localized [prostate cancer],” the authors concluded. They added that metastasis-free survival represents a more appropriate measure.

SOURCE

The study was led by senior author Amar Kishan, MD, of the University of California, Los Angeles, and was published online in the Journal of Clinical Oncology.

LIMITATIONS

• The trials used different definitions of BCR – the older American Society of Therapeutic Radiation and Oncology definition, and the more current Phoenix criteria.
• Some trials were conducted more than 20 years ago, and a variety of factors, including patient selection, staging, diagnostic criteria, and therapeutic approaches, have evolved in that time.
• Quality of life was not captured.

DISCLOSURES

The study received support from Cancer Research UK, the UK National Health Service, the Prostate Cancer National Institutes of Health Specialized Programs of Research Excellence, the UK Department of Defense, the Prostate Cancer Foundation, and the American Society for Radiation Oncology. Authors’ relevant financial relationships are detailed in the published study.

A version of this article appeared on Medscape.com.

This transcript has been edited for clarity.

Every branch of science has its constants. Physics has the speed of light, the gravitational constant, the Planck constant. Chemistry gives us Avogadro’s number, Faraday’s constant, the charge of an electron. Medicine isn’t quite as reliable as physics when it comes to these things, but insofar as there are any constants in medicine, might I suggest normal body temperature: 37° Celsius, 98.6° Fahrenheit.

Sure, serum sodium may be less variable and lactate concentration more clinically relevant, but even my 7-year-old knows that normal body temperature is 98.6°.

Except, as it turns out, 98.6° isn’t normal at all.

How did we arrive at 37.0° C for normal body temperature? We got it from this guy – German physician Carl Reinhold August Wunderlich, who, in addition to looking eerily like Luciano Pavarotti, was the first to realize that fever was not itself a disease but a symptom of one.

In 1851, Dr. Wunderlich released his measurements of more than 1 million body temperatures taken from 25,000 Germans – a painstaking process at the time, which employed a foot-long thermometer and took 20 minutes to obtain a measurement.

The average temperature measured, of course, was 37° C.

We’re more than 150 years post-Wunderlich right now, and the average person in the United States might be quite a bit different from the average German in 1850. Moreover, we can do a lot better than just measuring a ton of people and taking the average, because we have statistics. The problem with measuring a bunch of people and taking the average temperature as normal is that you can’t be sure that the people you are measuring are normal. There are obvious causes of elevated temperature that you could exclude. Let’s not take people with a respiratory infection or who are taking Tylenol, for example. But as highlighted in this paper in JAMA Internal Medicine, we can do a lot better than that.

The study leverages the fact that body temperature is typically measured during all medical office visits and recorded in the ever-present electronic medical record.

Researchers from Stanford identified 724,199 patient encounters with outpatient temperature data. They excluded extreme temperatures – less than 34° C or greater than 40° C – excluded patients under 20 or above 80 years, and excluded those with extremes of height, weight, or body mass index.

You end up with a distribution like this. Note that the peak is clearly lower than 37° C.

JAMA Internal Medicine

JAMA Internal Medicine

Dr. Wilson

JAMA Internal Medicine

JAMA Internal Medicine

JAMA Internal Medicine

Dr. Wilson is associate professor of medicine and public health at Yale University, New Haven, Conn., and director of Yale’s Clinical and Translational Research Accelerator. He has no disclosures.

A version of this article appeared on Medscape.com.

This transcript has been edited for clarity.

Every branch of science has its constants. Physics has the speed of light, the gravitational constant, the Planck constant. Chemistry gives us Avogadro’s number, Faraday’s constant, the charge of an electron. Medicine isn’t quite as reliable as physics when it comes to these things, but insofar as there are any constants in medicine, might I suggest normal body temperature: 37° Celsius, 98.6° Fahrenheit.

Sure, serum sodium may be less variable and lactate concentration more clinically relevant, but even my 7-year-old knows that normal body temperature is 98.6°.

Except, as it turns out, 98.6° isn’t normal at all.

How did we arrive at 37.0° C for normal body temperature? We got it from this guy – German physician Carl Reinhold August Wunderlich, who, in addition to looking eerily like Luciano Pavarotti, was the first to realize that fever was not itself a disease but a symptom of one.

In 1851, Dr. Wunderlich released his measurements of more than 1 million body temperatures taken from 25,000 Germans – a painstaking process at the time, which employed a foot-long thermometer and took 20 minutes to obtain a measurement.

The average temperature measured, of course, was 37° C.

We’re more than 150 years post-Wunderlich right now, and the average person in the United States might be quite a bit different from the average German in 1850. Moreover, we can do a lot better than just measuring a ton of people and taking the average, because we have statistics. The problem with measuring a bunch of people and taking the average temperature as normal is that you can’t be sure that the people you are measuring are normal. There are obvious causes of elevated temperature that you could exclude. Let’s not take people with a respiratory infection or who are taking Tylenol, for example. But as highlighted in this paper in JAMA Internal Medicine, we can do a lot better than that.

The study leverages the fact that body temperature is typically measured during all medical office visits and recorded in the ever-present electronic medical record.

Researchers from Stanford identified 724,199 patient encounters with outpatient temperature data. They excluded extreme temperatures – less than 34° C or greater than 40° C – excluded patients under 20 or above 80 years, and excluded those with extremes of height, weight, or body mass index.

You end up with a distribution like this. Note that the peak is clearly lower than 37° C.

JAMA Internal Medicine

JAMA Internal Medicine

Dr. Wilson

JAMA Internal Medicine

JAMA Internal Medicine

JAMA Internal Medicine

Dr. Wilson is associate professor of medicine and public health at Yale University, New Haven, Conn., and director of Yale’s Clinical and Translational Research Accelerator. He has no disclosures.

A version of this article appeared on Medscape.com.

This transcript has been edited for clarity.

Every branch of science has its constants. Physics has the speed of light, the gravitational constant, the Planck constant. Chemistry gives us Avogadro’s number, Faraday’s constant, the charge of an electron. Medicine isn’t quite as reliable as physics when it comes to these things, but insofar as there are any constants in medicine, might I suggest normal body temperature: 37° Celsius, 98.6° Fahrenheit.

Sure, serum sodium may be less variable and lactate concentration more clinically relevant, but even my 7-year-old knows that normal body temperature is 98.6°.

Except, as it turns out, 98.6° isn’t normal at all.

How did we arrive at 37.0° C for normal body temperature? We got it from this guy – German physician Carl Reinhold August Wunderlich, who, in addition to looking eerily like Luciano Pavarotti, was the first to realize that fever was not itself a disease but a symptom of one.

In 1851, Dr. Wunderlich released his measurements of more than 1 million body temperatures taken from 25,000 Germans – a painstaking process at the time, which employed a foot-long thermometer and took 20 minutes to obtain a measurement.

The average temperature measured, of course, was 37° C.

We’re more than 150 years post-Wunderlich right now, and the average person in the United States might be quite a bit different from the average German in 1850. Moreover, we can do a lot better than just measuring a ton of people and taking the average, because we have statistics. The problem with measuring a bunch of people and taking the average temperature as normal is that you can’t be sure that the people you are measuring are normal. There are obvious causes of elevated temperature that you could exclude. Let’s not take people with a respiratory infection or who are taking Tylenol, for example. But as highlighted in this paper in JAMA Internal Medicine, we can do a lot better than that.

The study leverages the fact that body temperature is typically measured during all medical office visits and recorded in the ever-present electronic medical record.

Researchers from Stanford identified 724,199 patient encounters with outpatient temperature data. They excluded extreme temperatures – less than 34° C or greater than 40° C – excluded patients under 20 or above 80 years, and excluded those with extremes of height, weight, or body mass index.

You end up with a distribution like this. Note that the peak is clearly lower than 37° C.

JAMA Internal Medicine

JAMA Internal Medicine

Dr. Wilson

JAMA Internal Medicine

JAMA Internal Medicine

JAMA Internal Medicine

Dr. Wilson is associate professor of medicine and public health at Yale University, New Haven, Conn., and director of Yale’s Clinical and Translational Research Accelerator. He has no disclosures.

A version of this article appeared on Medscape.com.

Suicide is not a trivial matter – it upends families, robs partners of a loved one, prevents children from having a parent, and can destroy a parent’s most cherished being. It is not surprising that societies have repeatedly made it a goal to study and reduce suicide within their populations.

The suicide rate in the United States is trending upward, from about 10 per 100,000 in 2000 to about 15 per 100,000 in more recent reports. The increasing suicide rates have been accompanied by increasing distress among many strata of society. From a public health level, analysts are not just witnessing increasing suicide rates, but a shocking rise in all “deaths of despair,”¹ among which suicide can be considered the ultimate example.

On an individual level, many know someone who has died of suicide or suffered from a serious suicide attempt. From the public health level to the individual level, advocacy has called for various interventions in the field of psychiatry to remedy this tragic problem.

Psychiatrists have been firsthand witnesses to this increasing demand for suicide interventions. When in residency, the norm was to perform a suicide risk assessment at the time of admission to the hospital and again at the time of discharge. As the years passed, the new normal within psychiatric hospitals has shifted to asking about suicidality on a daily basis.

In what seems to us like an escalating arms race, the emerging standard of care at many facilities is now not only for daily suicide risk assessments by each psychiatrist, but also to require nurses to ask about suicidality during every 8-hour shift – in addition to documented inquiries about suicidality by other allied staff on the psychiatric unit. As a result, it is not uncommon for a patient hospitalized at an academic center to receive more than half a dozen suicide risk assessments in a day (first by the medical student, at least once – often more than once – by the resident, again by the attending psychiatrist, then the social worker and three nurses in 24 hours).

One of the concerns about such an approach is the lack of logic inherent to many risk assessment tools and symptom scales. Many of us are familiar with the Patient Health Questionnaire (PHQ-9) to assess depression.² The PHQ-9 asks to consider “over the last 2 weeks, how often have you ...” in relation to nine symptoms associated with depression. It has always defied reason to perform a PHQ-9 every day and expect the answers to change from “nearly every day” to “not at all,” considering only 1 day has passed since the last time the patient has answered the questions. Yet daily, or near daily, PHQ-9 scores are a frequently used tool of tracking symptom improvement in response to treatments, such as electroconvulsive therapy, performed multiple times a week.

One can argue that the patient’s perspective on how symptomatic he or she has been over the past 2 weeks may change rapidly with alleviation of a depressed mood. However, the PHQ-9 is both reported to be, and often regarded as, an objective score. If one wishes to utilize it as such, the defense of its use should not be that it is a subjective report with just as much utility as “Rate your depression on a scale of 0-27.”

Similarly, many suicide scales were intended to assess thoughts of suicide in the past month³ or have been re-tooled to address this particular concern by asking “since the last contact.”⁴ It is baffling to see a chart with many dozens of suicide risk assessments with at times widely differing answers, yet all measuring thoughts of suicide in the past month. Is one to expect the answer to “How many times have you had these thoughts [of suicide ideation]? (1) Less than once a week (2) Once a week ...” to change between 8 a.m. and noon? Furthermore, for the purpose of assessing acute risk of suicidality in the immediate future, to only consider symptoms since the last contact – or past 2 weeks, past month, etc. – is of unclear significance.
 

Provider liability

Another concern is the liability placed on providers. A common problem encountered in the inpatient setting is insurance companies refusing to reimburse a hospital stay for depressed patients denying suicidality.

Any provider in the position of caring for such a patient must ask: What is the likelihood of someone providing a false negative – a false denial of suicidality? Is the likelihood of a suicidal person denying suicidality different if asked 5 or 10 or more times in a day? There are innumerable instances where a patient at a very high risk of self-harm has denied suicidality, been discharged from the hospital, and suffered terrible consequences. Ethically, the psychiatrist aware of this risk is no more at ease discharging these patients, whether it is one suicide risk scale or a dozen that suggests a patient is at low risk.

Alternatively, it may feel untenable from a medicolegal perspective for a psychiatrist to discharge a patient denying suicidality when the chart includes over a dozen previously documented elevated suicide risk assessments in the past 72 hours. By placing the job of suicide risk assessment in the hands of providers of varying levels of training and responsibility, a situation is created in which the seasoned psychiatrist who would otherwise be comfortable discharging a patient feels unable to do so because every other note-writer in the record – from the triage nurse to the medical assistant to the sitter in the emergency department – has recorded the patient as high risk for suicide. When put in such a position, the thought often occurs that systems of care, rather than individual providers, are protected most by ever escalating requirements for suicide risk documentation. To make a clinical decision contrary to the body of suicide risk documentation puts the provider at risk of being scapegoated by the system of care, which can point to its illogical and ineffective, though profusely documented, suicide prevention protocols.
 

Limitations of risk assessments

Considering the ongoing rise in the use of suicide risk assessments, one would expect that the evidence for their efficacy was robust and well established. Yet a thorough review of suicide risk assessments funded by the MacArthur Foundation, which examined decades of research, came to disheartening conclusions: “predictive ability has not improved over the past 50 years”; “no risk factor category or subcategory is substantially stronger than any other”; and “predicting solely according to base rates may be comparable to prediction with current risk factors.”⁵

Those findings were consistent with the conclusions of many other studies, which have summarized the utility of suicide risk assessments as follows: “occurrence of suicide is too low to identify those individuals who are likely to die by suicide”;⁶ “suicide prediction models produce accurate overall classification models, but their accuracy of predicting a future event is near zero”;⁷ “risk stratification is too inaccurate to be clinically useful and might even be harmful”;⁸ “suicide risk prediction [lacks] any items or information that to a useful degree permit the identification of persons who will complete suicide”;⁹ “existing suicide prediction tools have little current clinical value”;¹⁰ “our current preoccupation with risk assessment has ... created a mythology with no evidence to support it.”¹¹ And that’s to cite just a few.

Sadly, we have known about the limitations of suicide risk assessments for many decades. In 1983 a large VA prospective study, which aimed to identify veterans who will die by suicide, examined 4,800 patients with a wide range of instruments and measures.¹² This study concluded that “discriminant analysis was clearly inadequate in correctly classifying the subjects. For an event as rare as suicide, our predictive tools and guides are simply not equal to the task.” The authors described the feelings of many in stating “courts and public opinion expect physicians to be able to pick out the particular persons who will later commit suicide. Although we may reconstruct causal chains and motives, we do not possess the tools to predict suicides.”

Yet, even several decades prior, in 1954, Dr. Albert Rosen performed an elegant statistical analysis and predicted that, considering the low base rate of suicide, suicide risk assessments are “of no practical value, for it would be impossible to treat the prodigious number of false positives.”¹³ It seems that we continue to be unable to accept Dr. Rosen’s premonition despite decades of confirmatory evidence.
 

“Quantity over quality”

Regardless of those sobering reports, the field of psychiatry is seemingly doubling down on efforts to predict and prevent suicide deaths, and the way it is doing so has very questionable validity.

One can reasonably argue that the periodic performance of a suicide risk assessment may have clinical utility in reminding us of modifiable risk factors such as intoxication, social isolation, and access to lethal means. One can also reasonably argue that these risk assessments may provide useful education to patients and their families on epidemiological risk factors such as gender, age, and marital status. But our pursuit of serial suicide risk assessments throughout the day is encouraging providers to focus on a particular risk factor that changes from moment to moment and has particularly low validity, that being self-reported suicidality.

Reported suicidality is one of the few risk factors that can change from shift to shift. But 80% of people who die by suicide had not previously expressed suicidality, and 98.3% of people who have endorsed suicidality do not die by suicide.¹⁴ While the former statistic may improve with increased assessment, the later will likely worsen.

Suicide is not a trivial matter. We admire those that study it and advocate for better interventions. We have compassion for those who have suffered the loss of a loved one to suicide. Our patients have died as a result of the human limitations surrounding suicide prevention. Recognizing the weight of suicide and making an effort to avoid minimizing its immense consequences drive our desire to be honest with ourselves, our patients and their families, and society. That includes the unfortunate truth regarding the current state of the evidence and our ability to enact change.

It is our concern that the rising fascination with repeated suicide risk assessment is misguided in its current form and serves the purpose of appeasing administrators more than reflecting a scientific understanding of the literature. More sadly, we are concerned that this “quantity-over-quality” approach is yet another barrier to practicing what may be one of the few interventions with any hope of meaningfully impacting a patient’s risk of suicide in the clinical setting – spending time connecting with our patients.

Dr. Badre is a clinical and forensic psychiatrist in San Diego. He holds teaching positions at the University of California, San Diego, and the University of San Diego. He teaches medical education, psychopharmacology, ethics in psychiatry, and correctional care. Dr. Badre can be reached at his website, BadreMD.com. Dr. Compton is a member of the psychiatry faculty at University of California, San Diego. His background includes medical education, mental health advocacy, work with underserved populations, and brain cancer research. Dr. Badre and Dr. Compton have no conflicts of interest.

References

1. Joint Economic Committee. (2019). Long Term Trends in Deaths of Despair. SCP Report 4-19.

2. Kroenke K and Spitzer RL. The PHQ-9: A new depression diagnostic and severity measure. Psychiatr Ann. 2013;32(9):509-15. doi: 10.3928/0048-5713-20020901-06.

3. Columbia-Suicide Severity Rating Scale (C-SSRS) Full Lifetime/Recent.

4. Columbia-Suicide Severity Rating Scale (C-SSRS) Full Since Last Contact.

5. Franklin JC et al. Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research. Psychol Bull. 2017 Feb;143(2):187-232. doi: 10.1037/bul0000084.

6. Beautrais AL. Further suicidal behavior among medically serious suicide attempters. Suicide Life Threat Behav. 2004 Spring;34(1):1-11. doi: 10.1521/suli.34.1.1.27772.

7. Belsher BE. Prediction models for suicide attempts and deaths: A systematic review and simulation. JAMA Psychiatry. 2019 Jun 1;76(6):642-651. doi: 10.1001/jamapsychiatry.2019.0174.

8. Carter G et al. Royal Australian and New Zealand College of Psychiatrists clinical practice guideline for the management of deliberate self-harm. Aust N Z J Psychiatry. 2016 Oct;50(10):939-1000. doi: 10.1177/0004867416661039.

9. Fosse R et al. Predictors of suicide in the patient population admitted to a locked-door psychiatric acute ward. PLoS One. 2017 Mar 16;12(3):e0173958. doi: 10.1371/journal.pone.0173958.

10. Kessler RC et al. Suicide prediction models: A critical review of recent research with recommendations for the way forward. Mol Psychiatry. 2020 Jan;25(1):168-79. doi: 10.1038/s41380-019-0531-0.

11. Mulder R. Problems with suicide risk assessment. Aust N Z J Psychiatry. 2011 Aug;45(8):605-7. doi: 10.3109/00048674.2011.594786.

12. Pokorny AD. Prediction of suicide in psychiatric patients: Report of a prospective study. Arch Gen Psychiatry. 1983 Mar;40(3):249-57. doi: 10.1001/archpsyc.1983.01790030019002.

13. Rosen A. Detection of suicidal patients: An example of some limitations in the prediction of infrequent events. J Consult Psychol. 1954 Dec;18(6):397-403. doi: 10.1037/h0058579.

14. McHugh CM et al. (2019). Association between suicidal ideation and suicide: Meta-analyses of odds ratios, sensitivity, specificity and positive predictive value. BJPsych Open. 2019 Mar;5(2):e18. doi: 10.1192/bjo.2018.88.

Suicide is not a trivial matter – it upends families, robs partners of a loved one, prevents children from having a parent, and can destroy a parent’s most cherished being. It is not surprising that societies have repeatedly made it a goal to study and reduce suicide within their populations.

The suicide rate in the United States is trending upward, from about 10 per 100,000 in 2000 to about 15 per 100,000 in more recent reports. The increasing suicide rates have been accompanied by increasing distress among many strata of society. From a public health level, analysts are not just witnessing increasing suicide rates, but a shocking rise in all “deaths of despair,”¹ among which suicide can be considered the ultimate example.

On an individual level, many know someone who has died of suicide or suffered from a serious suicide attempt. From the public health level to the individual level, advocacy has called for various interventions in the field of psychiatry to remedy this tragic problem.

Psychiatrists have been firsthand witnesses to this increasing demand for suicide interventions. When in residency, the norm was to perform a suicide risk assessment at the time of admission to the hospital and again at the time of discharge. As the years passed, the new normal within psychiatric hospitals has shifted to asking about suicidality on a daily basis.

In what seems to us like an escalating arms race, the emerging standard of care at many facilities is now not only for daily suicide risk assessments by each psychiatrist, but also to require nurses to ask about suicidality during every 8-hour shift – in addition to documented inquiries about suicidality by other allied staff on the psychiatric unit. As a result, it is not uncommon for a patient hospitalized at an academic center to receive more than half a dozen suicide risk assessments in a day (first by the medical student, at least once – often more than once – by the resident, again by the attending psychiatrist, then the social worker and three nurses in 24 hours).

One of the concerns about such an approach is the lack of logic inherent to many risk assessment tools and symptom scales. Many of us are familiar with the Patient Health Questionnaire (PHQ-9) to assess depression.² The PHQ-9 asks to consider “over the last 2 weeks, how often have you ...” in relation to nine symptoms associated with depression. It has always defied reason to perform a PHQ-9 every day and expect the answers to change from “nearly every day” to “not at all,” considering only 1 day has passed since the last time the patient has answered the questions. Yet daily, or near daily, PHQ-9 scores are a frequently used tool of tracking symptom improvement in response to treatments, such as electroconvulsive therapy, performed multiple times a week.

One can argue that the patient’s perspective on how symptomatic he or she has been over the past 2 weeks may change rapidly with alleviation of a depressed mood. However, the PHQ-9 is both reported to be, and often regarded as, an objective score. If one wishes to utilize it as such, the defense of its use should not be that it is a subjective report with just as much utility as “Rate your depression on a scale of 0-27.”

Similarly, many suicide scales were intended to assess thoughts of suicide in the past month³ or have been re-tooled to address this particular concern by asking “since the last contact.”⁴ It is baffling to see a chart with many dozens of suicide risk assessments with at times widely differing answers, yet all measuring thoughts of suicide in the past month. Is one to expect the answer to “How many times have you had these thoughts [of suicide ideation]? (1) Less than once a week (2) Once a week ...” to change between 8 a.m. and noon? Furthermore, for the purpose of assessing acute risk of suicidality in the immediate future, to only consider symptoms since the last contact – or past 2 weeks, past month, etc. – is of unclear significance.
 

Provider liability

Another concern is the liability placed on providers. A common problem encountered in the inpatient setting is insurance companies refusing to reimburse a hospital stay for depressed patients denying suicidality.

Any provider in the position of caring for such a patient must ask: What is the likelihood of someone providing a false negative – a false denial of suicidality? Is the likelihood of a suicidal person denying suicidality different if asked 5 or 10 or more times in a day? There are innumerable instances where a patient at a very high risk of self-harm has denied suicidality, been discharged from the hospital, and suffered terrible consequences. Ethically, the psychiatrist aware of this risk is no more at ease discharging these patients, whether it is one suicide risk scale or a dozen that suggests a patient is at low risk.

Alternatively, it may feel untenable from a medicolegal perspective for a psychiatrist to discharge a patient denying suicidality when the chart includes over a dozen previously documented elevated suicide risk assessments in the past 72 hours. By placing the job of suicide risk assessment in the hands of providers of varying levels of training and responsibility, a situation is created in which the seasoned psychiatrist who would otherwise be comfortable discharging a patient feels unable to do so because every other note-writer in the record – from the triage nurse to the medical assistant to the sitter in the emergency department – has recorded the patient as high risk for suicide. When put in such a position, the thought often occurs that systems of care, rather than individual providers, are protected most by ever escalating requirements for suicide risk documentation. To make a clinical decision contrary to the body of suicide risk documentation puts the provider at risk of being scapegoated by the system of care, which can point to its illogical and ineffective, though profusely documented, suicide prevention protocols.
 

Limitations of risk assessments

Considering the ongoing rise in the use of suicide risk assessments, one would expect that the evidence for their efficacy was robust and well established. Yet a thorough review of suicide risk assessments funded by the MacArthur Foundation, which examined decades of research, came to disheartening conclusions: “predictive ability has not improved over the past 50 years”; “no risk factor category or subcategory is substantially stronger than any other”; and “predicting solely according to base rates may be comparable to prediction with current risk factors.”⁵

Those findings were consistent with the conclusions of many other studies, which have summarized the utility of suicide risk assessments as follows: “occurrence of suicide is too low to identify those individuals who are likely to die by suicide”;⁶ “suicide prediction models produce accurate overall classification models, but their accuracy of predicting a future event is near zero”;⁷ “risk stratification is too inaccurate to be clinically useful and might even be harmful”;⁸ “suicide risk prediction [lacks] any items or information that to a useful degree permit the identification of persons who will complete suicide”;⁹ “existing suicide prediction tools have little current clinical value”;¹⁰ “our current preoccupation with risk assessment has ... created a mythology with no evidence to support it.”¹¹ And that’s to cite just a few.

Sadly, we have known about the limitations of suicide risk assessments for many decades. In 1983 a large VA prospective study, which aimed to identify veterans who will die by suicide, examined 4,800 patients with a wide range of instruments and measures.¹² This study concluded that “discriminant analysis was clearly inadequate in correctly classifying the subjects. For an event as rare as suicide, our predictive tools and guides are simply not equal to the task.” The authors described the feelings of many in stating “courts and public opinion expect physicians to be able to pick out the particular persons who will later commit suicide. Although we may reconstruct causal chains and motives, we do not possess the tools to predict suicides.”

Yet, even several decades prior, in 1954, Dr. Albert Rosen performed an elegant statistical analysis and predicted that, considering the low base rate of suicide, suicide risk assessments are “of no practical value, for it would be impossible to treat the prodigious number of false positives.”¹³ It seems that we continue to be unable to accept Dr. Rosen’s premonition despite decades of confirmatory evidence.
 

“Quantity over quality”

Regardless of those sobering reports, the field of psychiatry is seemingly doubling down on efforts to predict and prevent suicide deaths, and the way it is doing so has very questionable validity.

One can reasonably argue that the periodic performance of a suicide risk assessment may have clinical utility in reminding us of modifiable risk factors such as intoxication, social isolation, and access to lethal means. One can also reasonably argue that these risk assessments may provide useful education to patients and their families on epidemiological risk factors such as gender, age, and marital status. But our pursuit of serial suicide risk assessments throughout the day is encouraging providers to focus on a particular risk factor that changes from moment to moment and has particularly low validity, that being self-reported suicidality.

Reported suicidality is one of the few risk factors that can change from shift to shift. But 80% of people who die by suicide had not previously expressed suicidality, and 98.3% of people who have endorsed suicidality do not die by suicide.¹⁴ While the former statistic may improve with increased assessment, the later will likely worsen.

Suicide is not a trivial matter. We admire those that study it and advocate for better interventions. We have compassion for those who have suffered the loss of a loved one to suicide. Our patients have died as a result of the human limitations surrounding suicide prevention. Recognizing the weight of suicide and making an effort to avoid minimizing its immense consequences drive our desire to be honest with ourselves, our patients and their families, and society. That includes the unfortunate truth regarding the current state of the evidence and our ability to enact change.

It is our concern that the rising fascination with repeated suicide risk assessment is misguided in its current form and serves the purpose of appeasing administrators more than reflecting a scientific understanding of the literature. More sadly, we are concerned that this “quantity-over-quality” approach is yet another barrier to practicing what may be one of the few interventions with any hope of meaningfully impacting a patient’s risk of suicide in the clinical setting – spending time connecting with our patients.

Dr. Badre is a clinical and forensic psychiatrist in San Diego. He holds teaching positions at the University of California, San Diego, and the University of San Diego. He teaches medical education, psychopharmacology, ethics in psychiatry, and correctional care. Dr. Badre can be reached at his website, BadreMD.com. Dr. Compton is a member of the psychiatry faculty at University of California, San Diego. His background includes medical education, mental health advocacy, work with underserved populations, and brain cancer research. Dr. Badre and Dr. Compton have no conflicts of interest.

References

1. Joint Economic Committee. (2019). Long Term Trends in Deaths of Despair. SCP Report 4-19.

2. Kroenke K and Spitzer RL. The PHQ-9: A new depression diagnostic and severity measure. Psychiatr Ann. 2013;32(9):509-15. doi: 10.3928/0048-5713-20020901-06.

3. Columbia-Suicide Severity Rating Scale (C-SSRS) Full Lifetime/Recent.

4. Columbia-Suicide Severity Rating Scale (C-SSRS) Full Since Last Contact.

5. Franklin JC et al. Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research. Psychol Bull. 2017 Feb;143(2):187-232. doi: 10.1037/bul0000084.

6. Beautrais AL. Further suicidal behavior among medically serious suicide attempters. Suicide Life Threat Behav. 2004 Spring;34(1):1-11. doi: 10.1521/suli.34.1.1.27772.

7. Belsher BE. Prediction models for suicide attempts and deaths: A systematic review and simulation. JAMA Psychiatry. 2019 Jun 1;76(6):642-651. doi: 10.1001/jamapsychiatry.2019.0174.

8. Carter G et al. Royal Australian and New Zealand College of Psychiatrists clinical practice guideline for the management of deliberate self-harm. Aust N Z J Psychiatry. 2016 Oct;50(10):939-1000. doi: 10.1177/0004867416661039.

9. Fosse R et al. Predictors of suicide in the patient population admitted to a locked-door psychiatric acute ward. PLoS One. 2017 Mar 16;12(3):e0173958. doi: 10.1371/journal.pone.0173958.

10. Kessler RC et al. Suicide prediction models: A critical review of recent research with recommendations for the way forward. Mol Psychiatry. 2020 Jan;25(1):168-79. doi: 10.1038/s41380-019-0531-0.

11. Mulder R. Problems with suicide risk assessment. Aust N Z J Psychiatry. 2011 Aug;45(8):605-7. doi: 10.3109/00048674.2011.594786.

12. Pokorny AD. Prediction of suicide in psychiatric patients: Report of a prospective study. Arch Gen Psychiatry. 1983 Mar;40(3):249-57. doi: 10.1001/archpsyc.1983.01790030019002.

13. Rosen A. Detection of suicidal patients: An example of some limitations in the prediction of infrequent events. J Consult Psychol. 1954 Dec;18(6):397-403. doi: 10.1037/h0058579.

14. McHugh CM et al. (2019). Association between suicidal ideation and suicide: Meta-analyses of odds ratios, sensitivity, specificity and positive predictive value. BJPsych Open. 2019 Mar;5(2):e18. doi: 10.1192/bjo.2018.88.

Suicide is not a trivial matter – it upends families, robs partners of a loved one, prevents children from having a parent, and can destroy a parent’s most cherished being. It is not surprising that societies have repeatedly made it a goal to study and reduce suicide within their populations.

The suicide rate in the United States is trending upward, from about 10 per 100,000 in 2000 to about 15 per 100,000 in more recent reports. The increasing suicide rates have been accompanied by increasing distress among many strata of society. From a public health level, analysts are not just witnessing increasing suicide rates, but a shocking rise in all “deaths of despair,”¹ among which suicide can be considered the ultimate example.

On an individual level, many know someone who has died of suicide or suffered from a serious suicide attempt. From the public health level to the individual level, advocacy has called for various interventions in the field of psychiatry to remedy this tragic problem.

Psychiatrists have been firsthand witnesses to this increasing demand for suicide interventions. When in residency, the norm was to perform a suicide risk assessment at the time of admission to the hospital and again at the time of discharge. As the years passed, the new normal within psychiatric hospitals has shifted to asking about suicidality on a daily basis.

In what seems to us like an escalating arms race, the emerging standard of care at many facilities is now not only for daily suicide risk assessments by each psychiatrist, but also to require nurses to ask about suicidality during every 8-hour shift – in addition to documented inquiries about suicidality by other allied staff on the psychiatric unit. As a result, it is not uncommon for a patient hospitalized at an academic center to receive more than half a dozen suicide risk assessments in a day (first by the medical student, at least once – often more than once – by the resident, again by the attending psychiatrist, then the social worker and three nurses in 24 hours).

One of the concerns about such an approach is the lack of logic inherent to many risk assessment tools and symptom scales. Many of us are familiar with the Patient Health Questionnaire (PHQ-9) to assess depression.² The PHQ-9 asks to consider “over the last 2 weeks, how often have you ...” in relation to nine symptoms associated with depression. It has always defied reason to perform a PHQ-9 every day and expect the answers to change from “nearly every day” to “not at all,” considering only 1 day has passed since the last time the patient has answered the questions. Yet daily, or near daily, PHQ-9 scores are a frequently used tool of tracking symptom improvement in response to treatments, such as electroconvulsive therapy, performed multiple times a week.

One can argue that the patient’s perspective on how symptomatic he or she has been over the past 2 weeks may change rapidly with alleviation of a depressed mood. However, the PHQ-9 is both reported to be, and often regarded as, an objective score. If one wishes to utilize it as such, the defense of its use should not be that it is a subjective report with just as much utility as “Rate your depression on a scale of 0-27.”

Similarly, many suicide scales were intended to assess thoughts of suicide in the past month³ or have been re-tooled to address this particular concern by asking “since the last contact.”⁴ It is baffling to see a chart with many dozens of suicide risk assessments with at times widely differing answers, yet all measuring thoughts of suicide in the past month. Is one to expect the answer to “How many times have you had these thoughts [of suicide ideation]? (1) Less than once a week (2) Once a week ...” to change between 8 a.m. and noon? Furthermore, for the purpose of assessing acute risk of suicidality in the immediate future, to only consider symptoms since the last contact – or past 2 weeks, past month, etc. – is of unclear significance.
 

Provider liability

Another concern is the liability placed on providers. A common problem encountered in the inpatient setting is insurance companies refusing to reimburse a hospital stay for depressed patients denying suicidality.

Any provider in the position of caring for such a patient must ask: What is the likelihood of someone providing a false negative – a false denial of suicidality? Is the likelihood of a suicidal person denying suicidality different if asked 5 or 10 or more times in a day? There are innumerable instances where a patient at a very high risk of self-harm has denied suicidality, been discharged from the hospital, and suffered terrible consequences. Ethically, the psychiatrist aware of this risk is no more at ease discharging these patients, whether it is one suicide risk scale or a dozen that suggests a patient is at low risk.

Alternatively, it may feel untenable from a medicolegal perspective for a psychiatrist to discharge a patient denying suicidality when the chart includes over a dozen previously documented elevated suicide risk assessments in the past 72 hours. By placing the job of suicide risk assessment in the hands of providers of varying levels of training and responsibility, a situation is created in which the seasoned psychiatrist who would otherwise be comfortable discharging a patient feels unable to do so because every other note-writer in the record – from the triage nurse to the medical assistant to the sitter in the emergency department – has recorded the patient as high risk for suicide. When put in such a position, the thought often occurs that systems of care, rather than individual providers, are protected most by ever escalating requirements for suicide risk documentation. To make a clinical decision contrary to the body of suicide risk documentation puts the provider at risk of being scapegoated by the system of care, which can point to its illogical and ineffective, though profusely documented, suicide prevention protocols.
 

Limitations of risk assessments

Considering the ongoing rise in the use of suicide risk assessments, one would expect that the evidence for their efficacy was robust and well established. Yet a thorough review of suicide risk assessments funded by the MacArthur Foundation, which examined decades of research, came to disheartening conclusions: “predictive ability has not improved over the past 50 years”; “no risk factor category or subcategory is substantially stronger than any other”; and “predicting solely according to base rates may be comparable to prediction with current risk factors.”⁵

Those findings were consistent with the conclusions of many other studies, which have summarized the utility of suicide risk assessments as follows: “occurrence of suicide is too low to identify those individuals who are likely to die by suicide”;⁶ “suicide prediction models produce accurate overall classification models, but their accuracy of predicting a future event is near zero”;⁷ “risk stratification is too inaccurate to be clinically useful and might even be harmful”;⁸ “suicide risk prediction [lacks] any items or information that to a useful degree permit the identification of persons who will complete suicide”;⁹ “existing suicide prediction tools have little current clinical value”;¹⁰ “our current preoccupation with risk assessment has ... created a mythology with no evidence to support it.”¹¹ And that’s to cite just a few.

Sadly, we have known about the limitations of suicide risk assessments for many decades. In 1983 a large VA prospective study, which aimed to identify veterans who will die by suicide, examined 4,800 patients with a wide range of instruments and measures.¹² This study concluded that “discriminant analysis was clearly inadequate in correctly classifying the subjects. For an event as rare as suicide, our predictive tools and guides are simply not equal to the task.” The authors described the feelings of many in stating “courts and public opinion expect physicians to be able to pick out the particular persons who will later commit suicide. Although we may reconstruct causal chains and motives, we do not possess the tools to predict suicides.”

Yet, even several decades prior, in 1954, Dr. Albert Rosen performed an elegant statistical analysis and predicted that, considering the low base rate of suicide, suicide risk assessments are “of no practical value, for it would be impossible to treat the prodigious number of false positives.”¹³ It seems that we continue to be unable to accept Dr. Rosen’s premonition despite decades of confirmatory evidence.
 

“Quantity over quality”

Regardless of those sobering reports, the field of psychiatry is seemingly doubling down on efforts to predict and prevent suicide deaths, and the way it is doing so has very questionable validity.

One can reasonably argue that the periodic performance of a suicide risk assessment may have clinical utility in reminding us of modifiable risk factors such as intoxication, social isolation, and access to lethal means. One can also reasonably argue that these risk assessments may provide useful education to patients and their families on epidemiological risk factors such as gender, age, and marital status. But our pursuit of serial suicide risk assessments throughout the day is encouraging providers to focus on a particular risk factor that changes from moment to moment and has particularly low validity, that being self-reported suicidality.

Reported suicidality is one of the few risk factors that can change from shift to shift. But 80% of people who die by suicide had not previously expressed suicidality, and 98.3% of people who have endorsed suicidality do not die by suicide.¹⁴ While the former statistic may improve with increased assessment, the later will likely worsen.

Suicide is not a trivial matter. We admire those that study it and advocate for better interventions. We have compassion for those who have suffered the loss of a loved one to suicide. Our patients have died as a result of the human limitations surrounding suicide prevention. Recognizing the weight of suicide and making an effort to avoid minimizing its immense consequences drive our desire to be honest with ourselves, our patients and their families, and society. That includes the unfortunate truth regarding the current state of the evidence and our ability to enact change.

It is our concern that the rising fascination with repeated suicide risk assessment is misguided in its current form and serves the purpose of appeasing administrators more than reflecting a scientific understanding of the literature. More sadly, we are concerned that this “quantity-over-quality” approach is yet another barrier to practicing what may be one of the few interventions with any hope of meaningfully impacting a patient’s risk of suicide in the clinical setting – spending time connecting with our patients.

Dr. Badre is a clinical and forensic psychiatrist in San Diego. He holds teaching positions at the University of California, San Diego, and the University of San Diego. He teaches medical education, psychopharmacology, ethics in psychiatry, and correctional care. Dr. Badre can be reached at his website, BadreMD.com. Dr. Compton is a member of the psychiatry faculty at University of California, San Diego. His background includes medical education, mental health advocacy, work with underserved populations, and brain cancer research. Dr. Badre and Dr. Compton have no conflicts of interest.

References

1. Joint Economic Committee. (2019). Long Term Trends in Deaths of Despair. SCP Report 4-19.

2. Kroenke K and Spitzer RL. The PHQ-9: A new depression diagnostic and severity measure. Psychiatr Ann. 2013;32(9):509-15. doi: 10.3928/0048-5713-20020901-06.

3. Columbia-Suicide Severity Rating Scale (C-SSRS) Full Lifetime/Recent.

4. Columbia-Suicide Severity Rating Scale (C-SSRS) Full Since Last Contact.

5. Franklin JC et al. Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research. Psychol Bull. 2017 Feb;143(2):187-232. doi: 10.1037/bul0000084.

6. Beautrais AL. Further suicidal behavior among medically serious suicide attempters. Suicide Life Threat Behav. 2004 Spring;34(1):1-11. doi: 10.1521/suli.34.1.1.27772.

7. Belsher BE. Prediction models for suicide attempts and deaths: A systematic review and simulation. JAMA Psychiatry. 2019 Jun 1;76(6):642-651. doi: 10.1001/jamapsychiatry.2019.0174.

8. Carter G et al. Royal Australian and New Zealand College of Psychiatrists clinical practice guideline for the management of deliberate self-harm. Aust N Z J Psychiatry. 2016 Oct;50(10):939-1000. doi: 10.1177/0004867416661039.

9. Fosse R et al. Predictors of suicide in the patient population admitted to a locked-door psychiatric acute ward. PLoS One. 2017 Mar 16;12(3):e0173958. doi: 10.1371/journal.pone.0173958.

10. Kessler RC et al. Suicide prediction models: A critical review of recent research with recommendations for the way forward. Mol Psychiatry. 2020 Jan;25(1):168-79. doi: 10.1038/s41380-019-0531-0.

11. Mulder R. Problems with suicide risk assessment. Aust N Z J Psychiatry. 2011 Aug;45(8):605-7. doi: 10.3109/00048674.2011.594786.

12. Pokorny AD. Prediction of suicide in psychiatric patients: Report of a prospective study. Arch Gen Psychiatry. 1983 Mar;40(3):249-57. doi: 10.1001/archpsyc.1983.01790030019002.

13. Rosen A. Detection of suicidal patients: An example of some limitations in the prediction of infrequent events. J Consult Psychol. 1954 Dec;18(6):397-403. doi: 10.1037/h0058579.

14. McHugh CM et al. (2019). Association between suicidal ideation and suicide: Meta-analyses of odds ratios, sensitivity, specificity and positive predictive value. BJPsych Open. 2019 Mar;5(2):e18. doi: 10.1192/bjo.2018.88.

You cut yourself. You put on a bandage. In a week or so, your wound heals.

Most people take this routine for granted. But for the more than 8.2 million Americans who have chronic wounds, it’s not so simple.

Traumatic injuries, post-surgical complications, advanced age, and chronic illnesses like diabetes and vascular disease can all disrupt the delicate healing process, leading to wounds that last months or years. 

Left untreated, about 30% led to amputation. And recent studies show the risk of dying from a chronic wound complication within 5 years rivals that of most cancers.

Yet until recently, medical technology had not kept up with what experts say is a snowballing threat to public health.

“Wound care – even with all of the billions of products that are sold – still exists on kind of a medieval level,” said Geoffrey Gurtner, MD, chair of the department of surgery and professor of biomedical engineering at the University of Arizona College of Medicine. “We’re still putting on poultices and salves ... and when it comes to diagnosing infection, it’s really an art. I think we can do better.” 
 

Old-school bandage meets AI

Dr. Gurtner is among dozens of clinicians and researchers reimagining the humble bandage, combining cutting-edge materials science with artificial intelligence and patient data to develop “smart bandages” that do far more than shield a wound.

Someday soon, these paper-thin bandages embedded with miniaturized electronics could monitor the healing process in real time, alerting the patient – or a doctor – when things go wrong. With the press of a smartphone button, that bandage could deliver medicine to fight an infection or an electrical pulse to stimulate healing.

Some “closed-loop” designs need no prompting, instead monitoring the wound and automatically giving it what it needs.

Others in development could halt a battlefield wound from hemorrhaging or kick-start healing in a blast wound, preventing longer-term disability. 

The same technologies could – if the price is right – speed up healing and reduce scarring in minor cuts and scrapes, too, said Dr. Gurtner. 

And unlike many cutting-edge medical innovations, these next-generation bandages could be made relatively cheaply and benefit some of the most vulnerable populations, including older adults, people with low incomes, and those in developing countries.

They could also save the health care system money, as the U.S. spends more than $28 billion annually treating chronic wounds.

“This is a condition that many patients find shameful and embarrassing, so there hasn’t been a lot of advocacy,” said Dr. Gurtner, outgoing board president of the Wound Healing Society. “It’s a relatively ignored problem afflicting an underserved population that has a huge cost. It’s a perfect storm.”
 

How wounds heal, or don’t

Wound healing is one of the most complex processes of the human body.

First platelets rush to the injury, prompting blood to clot. Then immune cells emit compounds called inflammatory cytokines, helping to fight off pathogens and keep infection at bay. Other compounds, including nitric oxide, spark the growth of new blood vessels and collagen to rebuild skin and connective tissue. As inflammation slows and stops, the flesh continues to reform.

But some conditions can stall the process, often in the inflammatory stage. 

In people with diabetes, high glucose levels and poor circulation tend to sabotage the process. And people with nerve damage from spinal cord injuries, diabetes, or other ailments may not be able to feel it when a wound is getting worse or reinjured.

“We end up with patients going months with open wounds that are festering and infected,” said Roslyn Rivkah Isseroff, MD, professor of dermatology at the University of California Davis and head of the VA Northern California Health Care System’s wound healing clinic. “The patients are upset with the smell. These open ulcers put the patient at risk for systemic infection, like sepsis.” It can impact mental health, draining the patient’s ability to care for their wound.

“We see them once a week and send them home and say change your dressing every day, and they say, ‘I can barely move. I can’t do this,’ ” said Dr. Isseroff.

Checking for infection means removing bandages and culturing the wound. That can be painful, and results take time. 

A lot can happen to a wound in a week.

“Sometimes, they come back and it’s a disaster, and they have to be admitted to the ER or even get an amputation,” Dr. Gurtner said. 

People who are housing insecure or lack access to health care are even more vulnerable to complications. 

“If you had the ability to say ‘there is something bad happening,’ you could do a lot to prevent this cascade and downward spiral.” 
 

Bandages 2.0

In 2019, the Defense Advanced Research Projects Agency, the research arm of the Department of Defense, launched the Bioelectronics for Tissue Regeneration program to encourage scientists to develop a “closed-loop” bandage capable of both monitoring and hastening healing.

Tens of millions in funding has kick-started a flood of innovation since.

“It’s kind of a race to the finish,” said Marco Rolandi, PhD, associate professor of electrical and computer engineering at the University of California Santa Cruz and the principal investigator for a team including engineers, medical doctors, and computer scientists from UC Santa Cruz, UC Davis, and Tufts. “I’ve been amazed and impressed at all the work coming out.”

His team’s goal is to cut healing time in half by using (a) real-time monitoring of how a wound is healing – using indicators like temperature, pH level, oxygen, moisture, glucose, electrical activity, and certain proteins, and (b) appropriate stimulation.

“Every wound is different, so there is no one solution,” said Dr. Isseroff, the team’s clinical lead. “The idea is that it will be able to sense different parameters unique to the wound, use AI to figure out what stage it is in, and provide the right stimulus to kick it out of that stalled stage.”

The team has developed a proof-of-concept prototype: a bandage embedded with a tiny camera that takes pictures and transmits them to a computer algorithm to assess the wound’s progress. Miniaturized battery-powered actuators, or motors, automatically deliver medication.

Phase I trials in rodents went well, Dr. Rolandi said. The team is now testing the bandage on pigs.

Across the globe, other promising developments are underway.

In a scientific paper published in May, researchers at the University of Glasgow described a new “low-cost, environmentally friendly” bandage embedded with light-emitting diodes that use ultraviolet light to kill bacteria – no antibiotics needed. The fabric is stitched with a slim, flexible coil that powers the lights without a battery using wireless power transfer. In lab studies, it eradicated gram-negative bacteria (some of the nastiest bugs) in 6 hours.

Also in May, in the journal Bioactive Materials, a Penn State team detailed a bandage with medicine-injecting microneedles that can halt bleeding immediately after injury. In lab and animal tests, it reduced clotting time from 11.5 minutes to 1.3 minutes and bleeding by 90%.

“With hemorrhaging injuries, it is often the loss of blood – not the injury itself – that causes death,” said study author Amir Sheikhi, PhD, assistant professor of chemical and biomedical engineering at Penn State. “Those 10 minutes could be the difference between life and death.” 

Another smart bandage, developed at Northwestern University, Chicago, harmlessly dissolves – electrodes and all – into the body after it is no longer needed, eliminating what can be a painful removal.

Guillermo Ameer, DSc, a study author reporting on the technology in Science Advances, hopes it could be made cheaply and used in developing countries.

“We’d like to create something that you could use in your home, even in a very remote village,” said Dr. Ameer, professor of biomedical engineering at Northwestern.