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Night Owls May Be at Greater Risk for T2D, Beyond Lifestyle
MADRID — research presented at the annual meeting of the European Association for the Study of Diabetes suggested.
In the study, night owls were almost 50% more likely to develop T2D than those who went to sleep earlier.
“The magnitude of this risk was more than I expected, [although] residual confounding may have occurred,” said Jeroen van der Velde, PhD, Leiden University Medical Center in the Netherlands, who presented the study.
“Late chronotype has previously been associated with unhealthy lifestyle and overweight or obesity and, subsequently, cardiometabolic diseases,” he said in an interview. However, although the current study found that individuals with late chronotypes did indeed have larger waists and more visceral fat, “we (and others) believe that lifestyle cannot fully explain the relation between late chronotype and metabolic disorders.”
“In addition,” he noted, “previous studies that observed that late chronotype is associated with overweight or obesity mainly focused on body mass index [BMI]. However, BMI alone does not provide accurate information regarding fat distribution in the body. People with similar BMI may have different underlying fat distribution, and this may be more relevant than BMI for metabolic risk.”
The researchers examined associations between chronotype and BMI, waist circumference, visceral fat, liver fat, and the risk for T2D in a middle-aged population from the Netherlands Epidemiology of Obesity study. Among the 5026 participants, the mean age was 56 years, 54% were women, and mean BMI was 30.
Using data from the study, the study investigators calculated the midpoint of sleep (MPS) and divided participants into three chronotypes: Early MPS < 2:30 PM (20% of participants); intermediate MPS 2:30–4:00 PM (reference category; 60% of participants); and late MPS ≥ 4:00 PM (20% of participants). BMI and waist circumference were measured in all participants, and visceral fat and liver fat were measured in 1576 participants using MRI scans and MR spectroscopy, respectively.
During a median follow-up of 6.6 years, 225 participants were diagnosed with T2D. After adjustment for age, sex, education, physical activity, smoking, alcohol intake, diet quality, sleep quality and duration, and total body fat, participants with a late chronotype had a 46% increased risk for T2D.
Further, those with a late chronotype had 0.7 higher BMI, 1.9-cm larger waist circumference, 7 cm2 more visceral fat, and 14% more liver fat.
Body Clock Out of Sync?
“Late chronotype was associated with increased ectopic body fat and with an increased risk of T2D independent of lifestyle factors and is an emerging risk factor for metabolic diseases,” the researchers concluded.
“A likely explanation is that the circadian rhythm or body clock in late chronotypes is out of sync with the work and social schedules followed by society,” Dr. van der Velde suggested. “This can lead to circadian misalignment, which we know can lead to metabolic disturbances and ultimately type 2 diabetes.”
Might trying to adjust chronotype earlier in life have an effect on risk?
“Chronotype, as measured via midpoint of sleep, does change a lot in the first 30 years or so in life,” he said. “After that it seems to stabilize. I suppose that if you adapt an intermediate or early chronotype around the age of 30 years, this will help to maintain an earlier chronotype later in life, although we cannot answer this from our study.”
Nevertheless, with respect to T2D risk, “chronotype is likely only part of the puzzle,” he noted.
“People with late chronotypes typically eat late in the evening, and this has also been associated with adverse metabolic effects. At this stage, we do not know if a person changes his/her chronotype that this will also lead to metabolic improvements. More research is needed before we can make recommendations regarding chronotype and timing of other lifestyle behaviors.”
Commenting on the study, Gianluca Iacobellis, MD, PhD, director of the University of Miami Hospital Diabetes Service, Coral Gables, Florida, said: “Interesting data. Altering the physiological circadian rhythm can affect the complex hormonal system — including cortisol, ghrelin, leptin, and serotonin — that regulates insulin sensitivity, glucose, and blood pressure control. The night owl may become more insulin resistant and therefore at higher risk of developing diabetes.”
Like Dr. van der Velde, he noted that “late sleep may be associated with night binging that can cause weight gain and ultimately obesity, further increasing the risk of diabetes.”
Dr. Iacobellis’s group recently showed that vital exhaustion, which is characterized by fatigue and loss of vigor, is associated with a higher cardiovascular risk for and markers of visceral adiposity.
“Abnormal circadian rhythms can be easily associated with vital exhaustion,” he said. Therefore, night owls with more visceral than peripheral fat accumulation might also be at higher cardiometabolic risk through that mechanism.
“However environmental factors and family history can play an important role too,” he added.
Regardless of the mechanisms involved, “preventive actions should be taken to educate teenagers and individuals at higher risk to have healthy sleep habits,” Dr. Iacobellis concluded.
No information regarding funding was provided; Dr. van der Velde and Dr. Iacobellis reported no conflicts of interest.
A version of this article first appeared on Medscape.com.
MADRID — research presented at the annual meeting of the European Association for the Study of Diabetes suggested.
In the study, night owls were almost 50% more likely to develop T2D than those who went to sleep earlier.
“The magnitude of this risk was more than I expected, [although] residual confounding may have occurred,” said Jeroen van der Velde, PhD, Leiden University Medical Center in the Netherlands, who presented the study.
“Late chronotype has previously been associated with unhealthy lifestyle and overweight or obesity and, subsequently, cardiometabolic diseases,” he said in an interview. However, although the current study found that individuals with late chronotypes did indeed have larger waists and more visceral fat, “we (and others) believe that lifestyle cannot fully explain the relation between late chronotype and metabolic disorders.”
“In addition,” he noted, “previous studies that observed that late chronotype is associated with overweight or obesity mainly focused on body mass index [BMI]. However, BMI alone does not provide accurate information regarding fat distribution in the body. People with similar BMI may have different underlying fat distribution, and this may be more relevant than BMI for metabolic risk.”
The researchers examined associations between chronotype and BMI, waist circumference, visceral fat, liver fat, and the risk for T2D in a middle-aged population from the Netherlands Epidemiology of Obesity study. Among the 5026 participants, the mean age was 56 years, 54% were women, and mean BMI was 30.
Using data from the study, the study investigators calculated the midpoint of sleep (MPS) and divided participants into three chronotypes: Early MPS < 2:30 PM (20% of participants); intermediate MPS 2:30–4:00 PM (reference category; 60% of participants); and late MPS ≥ 4:00 PM (20% of participants). BMI and waist circumference were measured in all participants, and visceral fat and liver fat were measured in 1576 participants using MRI scans and MR spectroscopy, respectively.
During a median follow-up of 6.6 years, 225 participants were diagnosed with T2D. After adjustment for age, sex, education, physical activity, smoking, alcohol intake, diet quality, sleep quality and duration, and total body fat, participants with a late chronotype had a 46% increased risk for T2D.
Further, those with a late chronotype had 0.7 higher BMI, 1.9-cm larger waist circumference, 7 cm2 more visceral fat, and 14% more liver fat.
Body Clock Out of Sync?
“Late chronotype was associated with increased ectopic body fat and with an increased risk of T2D independent of lifestyle factors and is an emerging risk factor for metabolic diseases,” the researchers concluded.
“A likely explanation is that the circadian rhythm or body clock in late chronotypes is out of sync with the work and social schedules followed by society,” Dr. van der Velde suggested. “This can lead to circadian misalignment, which we know can lead to metabolic disturbances and ultimately type 2 diabetes.”
Might trying to adjust chronotype earlier in life have an effect on risk?
“Chronotype, as measured via midpoint of sleep, does change a lot in the first 30 years or so in life,” he said. “After that it seems to stabilize. I suppose that if you adapt an intermediate or early chronotype around the age of 30 years, this will help to maintain an earlier chronotype later in life, although we cannot answer this from our study.”
Nevertheless, with respect to T2D risk, “chronotype is likely only part of the puzzle,” he noted.
“People with late chronotypes typically eat late in the evening, and this has also been associated with adverse metabolic effects. At this stage, we do not know if a person changes his/her chronotype that this will also lead to metabolic improvements. More research is needed before we can make recommendations regarding chronotype and timing of other lifestyle behaviors.”
Commenting on the study, Gianluca Iacobellis, MD, PhD, director of the University of Miami Hospital Diabetes Service, Coral Gables, Florida, said: “Interesting data. Altering the physiological circadian rhythm can affect the complex hormonal system — including cortisol, ghrelin, leptin, and serotonin — that regulates insulin sensitivity, glucose, and blood pressure control. The night owl may become more insulin resistant and therefore at higher risk of developing diabetes.”
Like Dr. van der Velde, he noted that “late sleep may be associated with night binging that can cause weight gain and ultimately obesity, further increasing the risk of diabetes.”
Dr. Iacobellis’s group recently showed that vital exhaustion, which is characterized by fatigue and loss of vigor, is associated with a higher cardiovascular risk for and markers of visceral adiposity.
“Abnormal circadian rhythms can be easily associated with vital exhaustion,” he said. Therefore, night owls with more visceral than peripheral fat accumulation might also be at higher cardiometabolic risk through that mechanism.
“However environmental factors and family history can play an important role too,” he added.
Regardless of the mechanisms involved, “preventive actions should be taken to educate teenagers and individuals at higher risk to have healthy sleep habits,” Dr. Iacobellis concluded.
No information regarding funding was provided; Dr. van der Velde and Dr. Iacobellis reported no conflicts of interest.
A version of this article first appeared on Medscape.com.
MADRID — research presented at the annual meeting of the European Association for the Study of Diabetes suggested.
In the study, night owls were almost 50% more likely to develop T2D than those who went to sleep earlier.
“The magnitude of this risk was more than I expected, [although] residual confounding may have occurred,” said Jeroen van der Velde, PhD, Leiden University Medical Center in the Netherlands, who presented the study.
“Late chronotype has previously been associated with unhealthy lifestyle and overweight or obesity and, subsequently, cardiometabolic diseases,” he said in an interview. However, although the current study found that individuals with late chronotypes did indeed have larger waists and more visceral fat, “we (and others) believe that lifestyle cannot fully explain the relation between late chronotype and metabolic disorders.”
“In addition,” he noted, “previous studies that observed that late chronotype is associated with overweight or obesity mainly focused on body mass index [BMI]. However, BMI alone does not provide accurate information regarding fat distribution in the body. People with similar BMI may have different underlying fat distribution, and this may be more relevant than BMI for metabolic risk.”
The researchers examined associations between chronotype and BMI, waist circumference, visceral fat, liver fat, and the risk for T2D in a middle-aged population from the Netherlands Epidemiology of Obesity study. Among the 5026 participants, the mean age was 56 years, 54% were women, and mean BMI was 30.
Using data from the study, the study investigators calculated the midpoint of sleep (MPS) and divided participants into three chronotypes: Early MPS < 2:30 PM (20% of participants); intermediate MPS 2:30–4:00 PM (reference category; 60% of participants); and late MPS ≥ 4:00 PM (20% of participants). BMI and waist circumference were measured in all participants, and visceral fat and liver fat were measured in 1576 participants using MRI scans and MR spectroscopy, respectively.
During a median follow-up of 6.6 years, 225 participants were diagnosed with T2D. After adjustment for age, sex, education, physical activity, smoking, alcohol intake, diet quality, sleep quality and duration, and total body fat, participants with a late chronotype had a 46% increased risk for T2D.
Further, those with a late chronotype had 0.7 higher BMI, 1.9-cm larger waist circumference, 7 cm2 more visceral fat, and 14% more liver fat.
Body Clock Out of Sync?
“Late chronotype was associated with increased ectopic body fat and with an increased risk of T2D independent of lifestyle factors and is an emerging risk factor for metabolic diseases,” the researchers concluded.
“A likely explanation is that the circadian rhythm or body clock in late chronotypes is out of sync with the work and social schedules followed by society,” Dr. van der Velde suggested. “This can lead to circadian misalignment, which we know can lead to metabolic disturbances and ultimately type 2 diabetes.”
Might trying to adjust chronotype earlier in life have an effect on risk?
“Chronotype, as measured via midpoint of sleep, does change a lot in the first 30 years or so in life,” he said. “After that it seems to stabilize. I suppose that if you adapt an intermediate or early chronotype around the age of 30 years, this will help to maintain an earlier chronotype later in life, although we cannot answer this from our study.”
Nevertheless, with respect to T2D risk, “chronotype is likely only part of the puzzle,” he noted.
“People with late chronotypes typically eat late in the evening, and this has also been associated with adverse metabolic effects. At this stage, we do not know if a person changes his/her chronotype that this will also lead to metabolic improvements. More research is needed before we can make recommendations regarding chronotype and timing of other lifestyle behaviors.”
Commenting on the study, Gianluca Iacobellis, MD, PhD, director of the University of Miami Hospital Diabetes Service, Coral Gables, Florida, said: “Interesting data. Altering the physiological circadian rhythm can affect the complex hormonal system — including cortisol, ghrelin, leptin, and serotonin — that regulates insulin sensitivity, glucose, and blood pressure control. The night owl may become more insulin resistant and therefore at higher risk of developing diabetes.”
Like Dr. van der Velde, he noted that “late sleep may be associated with night binging that can cause weight gain and ultimately obesity, further increasing the risk of diabetes.”
Dr. Iacobellis’s group recently showed that vital exhaustion, which is characterized by fatigue and loss of vigor, is associated with a higher cardiovascular risk for and markers of visceral adiposity.
“Abnormal circadian rhythms can be easily associated with vital exhaustion,” he said. Therefore, night owls with more visceral than peripheral fat accumulation might also be at higher cardiometabolic risk through that mechanism.
“However environmental factors and family history can play an important role too,” he added.
Regardless of the mechanisms involved, “preventive actions should be taken to educate teenagers and individuals at higher risk to have healthy sleep habits,” Dr. Iacobellis concluded.
No information regarding funding was provided; Dr. van der Velde and Dr. Iacobellis reported no conflicts of interest.
A version of this article first appeared on Medscape.com.
FROM EASD 2024
Cell Phone Use Linked to Higher Heart Disease Risk
“We found that a poor sleep pattern, psychological distress, and neuroticism significantly mediated the positive association between weekly mobile phone usage time and the risk for incident CVD, with a mediating proportion of 5.11%, 11.50%, and 2.25%, respectively,” said principal investigator Xianhui Qin, MD, professor of nephrology at Southern Medical University, Guangzhou, China.
Poor sleep patterns and poor mental health could disrupt circadian rhythms and endocrine and metabolic functions, as well as increase inflammation, he explained.
In addition, chronic exposure to radiofrequency electromagnetic fields (RF-EMF) emitted from cell phones could lead to oxidative stress and an inflammatory response. Combined with smoking and diabetes, this exposure “may have a synergistic effect in increasing CVD risk,” Dr. Qin suggested.
The study was published online in the Canadian Journal of Cardiology.
Risk Underestimated?
The researchers aimed to examine the association of regular cell phone use with incident CVD and explore the mediating effects of sleep and mental health using linked hospital and mortality records.
Their analysis included 444,027 participants (mean age, 56 years; 44% men) without a history of CVD from the UK Biobank. A total of 378,161 participants were regular cell phone users.
Regular cell phone use was defined as at least one call per week. Weekly use was self-reported as the average time of calls per week during the previous 3 months.
The primary outcome was incident CVD. Secondary outcomes were each component of CVD (ie, coronary heart disease, stroke, atrial fibrillation, and heart failure) and increased carotid intima media thickness (CIMT).
Compared with nonregular cell phone users, regular users were younger, had higher proportions of current smokers and urban residents, and had lower proportions of history of hypertension and diabetes. They also had higher income, Townsend deprivation index, and body mass index, and lower education levels.
During a median follow-up of 12.3 years, 56,181 participants developed incident CVD. Compared with nonregular cell phone users, regular users had a significantly higher risk for incident CVD (hazard ratio, 1.04) and increased CIMT (odds ratio, 1.11).
Among regular cell phone users, the duration of cell phone use and hands-free device/speakerphone use during calls was not significantly associated with incident CVD. Yet a significant and positive dose-response relationship was seen between weekly cell phone usage time and the risk for CVD. The positive association was stronger in current vs noncurrent smokers and people with vs without diabetes.
To different extents, sleep patterns (5.11%), psychologic distress (11.5%), and neuroticism (2.25%) mediated the relationship between weekly cell phone usage time and the risk for incident CVD.
“Our study suggests that despite the advantages of mobile phone use, we should also pay attention to the potential harm of mobile phone use to cardiovascular health,” Dr. Qin said. “Future studies to assess the risk-benefit balance will help promote mobile phone use patterns that are conducive to cardiovascular health.”
Meanwhile, he added, “We encourage measures to reduce time spent on mobile phones to promote the primary prevention of CVD. On the other hand, improving sleep and mental health status may help reduce the higher risk of CVD associated with mobile phone use.”
There are several limitations to the study in addition to its observational nature, which cannot show cause and effect. The questionnaires on cell phone use were restricted to phone calls; other use patterns of cell phones (eg, messaging, watching videos, and browsing the web) were not considered. Although the researchers adjusted for many potential confounders, unmeasured confounding bias (eg, the type of cell phone used and other sources of RF-EMF) cannot be eliminated.
Weak Link?
In a comment, Nicholas Grubic, MSc, a PhD student in epidemiology at the University of Toronto, Ontario, Canada, and coauthor of a related editorial, said, “I found it interesting that there was a connection observed between mobile phone use and CVD. However, it is crucial to understand that this link appeared to be much weaker compared with other well-known cardiovascular risk factors, such as smoking, diabetes, and high blood pressure. For now, mobile phone use should not be a major concern for most people.”
Nevertheless, clinicians should encourage patients to practice healthy habits around their screen time, he advised. “This could include limiting mobile phone use before bedtime and taking regular breaks to engage in activities that promote heart health, such as exercising or spending time outdoors.
“For the time being, we probably won’t see mobile phone use included in standard assessments for cardiovascular risk or as a focal point of cardiovascular health promotion initiatives,” he added. Instead, clinicians should “focus on established risk factors that have a stronger impact on patients’ cardiovascular health.”
Nieca Goldberg, MD, a clinical associate professor of medicine at NYU Grossman School of Medicine in New York City and American Heart Association volunteer expert, had a similar message. “You don’t have to go back to using a landline,” she said. “Instead, patients should be more mindful of how much phone use is taking away from their physical activity, keeping them from sleeping, and causing them stress.” Clinicians should also remember to counsel smokers on smoking cessation.
“It would be important for future studies to look at time spent on the phone and the type of activities patients are doing on their phones, such as social media, calls, texts, movies, or streaming TV shows,” she said. “It would be important to see how phone use is leading to a sedentary lifestyle” and what that means for a larger, more diverse population.
The study was supported by the National Key R&D Program, the National Natural Science Foundation of China, and the Outstanding Youth Development Scheme of Nanfang Hospital, Southern Medical University. Dr. Qin, Dr. Grubic, and Dr. Goldberg reported having no relevant financial relationships.
A version of this article first appeared on Medscape.com.
“We found that a poor sleep pattern, psychological distress, and neuroticism significantly mediated the positive association between weekly mobile phone usage time and the risk for incident CVD, with a mediating proportion of 5.11%, 11.50%, and 2.25%, respectively,” said principal investigator Xianhui Qin, MD, professor of nephrology at Southern Medical University, Guangzhou, China.
Poor sleep patterns and poor mental health could disrupt circadian rhythms and endocrine and metabolic functions, as well as increase inflammation, he explained.
In addition, chronic exposure to radiofrequency electromagnetic fields (RF-EMF) emitted from cell phones could lead to oxidative stress and an inflammatory response. Combined with smoking and diabetes, this exposure “may have a synergistic effect in increasing CVD risk,” Dr. Qin suggested.
The study was published online in the Canadian Journal of Cardiology.
Risk Underestimated?
The researchers aimed to examine the association of regular cell phone use with incident CVD and explore the mediating effects of sleep and mental health using linked hospital and mortality records.
Their analysis included 444,027 participants (mean age, 56 years; 44% men) without a history of CVD from the UK Biobank. A total of 378,161 participants were regular cell phone users.
Regular cell phone use was defined as at least one call per week. Weekly use was self-reported as the average time of calls per week during the previous 3 months.
The primary outcome was incident CVD. Secondary outcomes were each component of CVD (ie, coronary heart disease, stroke, atrial fibrillation, and heart failure) and increased carotid intima media thickness (CIMT).
Compared with nonregular cell phone users, regular users were younger, had higher proportions of current smokers and urban residents, and had lower proportions of history of hypertension and diabetes. They also had higher income, Townsend deprivation index, and body mass index, and lower education levels.
During a median follow-up of 12.3 years, 56,181 participants developed incident CVD. Compared with nonregular cell phone users, regular users had a significantly higher risk for incident CVD (hazard ratio, 1.04) and increased CIMT (odds ratio, 1.11).
Among regular cell phone users, the duration of cell phone use and hands-free device/speakerphone use during calls was not significantly associated with incident CVD. Yet a significant and positive dose-response relationship was seen between weekly cell phone usage time and the risk for CVD. The positive association was stronger in current vs noncurrent smokers and people with vs without diabetes.
To different extents, sleep patterns (5.11%), psychologic distress (11.5%), and neuroticism (2.25%) mediated the relationship between weekly cell phone usage time and the risk for incident CVD.
“Our study suggests that despite the advantages of mobile phone use, we should also pay attention to the potential harm of mobile phone use to cardiovascular health,” Dr. Qin said. “Future studies to assess the risk-benefit balance will help promote mobile phone use patterns that are conducive to cardiovascular health.”
Meanwhile, he added, “We encourage measures to reduce time spent on mobile phones to promote the primary prevention of CVD. On the other hand, improving sleep and mental health status may help reduce the higher risk of CVD associated with mobile phone use.”
There are several limitations to the study in addition to its observational nature, which cannot show cause and effect. The questionnaires on cell phone use were restricted to phone calls; other use patterns of cell phones (eg, messaging, watching videos, and browsing the web) were not considered. Although the researchers adjusted for many potential confounders, unmeasured confounding bias (eg, the type of cell phone used and other sources of RF-EMF) cannot be eliminated.
Weak Link?
In a comment, Nicholas Grubic, MSc, a PhD student in epidemiology at the University of Toronto, Ontario, Canada, and coauthor of a related editorial, said, “I found it interesting that there was a connection observed between mobile phone use and CVD. However, it is crucial to understand that this link appeared to be much weaker compared with other well-known cardiovascular risk factors, such as smoking, diabetes, and high blood pressure. For now, mobile phone use should not be a major concern for most people.”
Nevertheless, clinicians should encourage patients to practice healthy habits around their screen time, he advised. “This could include limiting mobile phone use before bedtime and taking regular breaks to engage in activities that promote heart health, such as exercising or spending time outdoors.
“For the time being, we probably won’t see mobile phone use included in standard assessments for cardiovascular risk or as a focal point of cardiovascular health promotion initiatives,” he added. Instead, clinicians should “focus on established risk factors that have a stronger impact on patients’ cardiovascular health.”
Nieca Goldberg, MD, a clinical associate professor of medicine at NYU Grossman School of Medicine in New York City and American Heart Association volunteer expert, had a similar message. “You don’t have to go back to using a landline,” she said. “Instead, patients should be more mindful of how much phone use is taking away from their physical activity, keeping them from sleeping, and causing them stress.” Clinicians should also remember to counsel smokers on smoking cessation.
“It would be important for future studies to look at time spent on the phone and the type of activities patients are doing on their phones, such as social media, calls, texts, movies, or streaming TV shows,” she said. “It would be important to see how phone use is leading to a sedentary lifestyle” and what that means for a larger, more diverse population.
The study was supported by the National Key R&D Program, the National Natural Science Foundation of China, and the Outstanding Youth Development Scheme of Nanfang Hospital, Southern Medical University. Dr. Qin, Dr. Grubic, and Dr. Goldberg reported having no relevant financial relationships.
A version of this article first appeared on Medscape.com.
“We found that a poor sleep pattern, psychological distress, and neuroticism significantly mediated the positive association between weekly mobile phone usage time and the risk for incident CVD, with a mediating proportion of 5.11%, 11.50%, and 2.25%, respectively,” said principal investigator Xianhui Qin, MD, professor of nephrology at Southern Medical University, Guangzhou, China.
Poor sleep patterns and poor mental health could disrupt circadian rhythms and endocrine and metabolic functions, as well as increase inflammation, he explained.
In addition, chronic exposure to radiofrequency electromagnetic fields (RF-EMF) emitted from cell phones could lead to oxidative stress and an inflammatory response. Combined with smoking and diabetes, this exposure “may have a synergistic effect in increasing CVD risk,” Dr. Qin suggested.
The study was published online in the Canadian Journal of Cardiology.
Risk Underestimated?
The researchers aimed to examine the association of regular cell phone use with incident CVD and explore the mediating effects of sleep and mental health using linked hospital and mortality records.
Their analysis included 444,027 participants (mean age, 56 years; 44% men) without a history of CVD from the UK Biobank. A total of 378,161 participants were regular cell phone users.
Regular cell phone use was defined as at least one call per week. Weekly use was self-reported as the average time of calls per week during the previous 3 months.
The primary outcome was incident CVD. Secondary outcomes were each component of CVD (ie, coronary heart disease, stroke, atrial fibrillation, and heart failure) and increased carotid intima media thickness (CIMT).
Compared with nonregular cell phone users, regular users were younger, had higher proportions of current smokers and urban residents, and had lower proportions of history of hypertension and diabetes. They also had higher income, Townsend deprivation index, and body mass index, and lower education levels.
During a median follow-up of 12.3 years, 56,181 participants developed incident CVD. Compared with nonregular cell phone users, regular users had a significantly higher risk for incident CVD (hazard ratio, 1.04) and increased CIMT (odds ratio, 1.11).
Among regular cell phone users, the duration of cell phone use and hands-free device/speakerphone use during calls was not significantly associated with incident CVD. Yet a significant and positive dose-response relationship was seen between weekly cell phone usage time and the risk for CVD. The positive association was stronger in current vs noncurrent smokers and people with vs without diabetes.
To different extents, sleep patterns (5.11%), psychologic distress (11.5%), and neuroticism (2.25%) mediated the relationship between weekly cell phone usage time and the risk for incident CVD.
“Our study suggests that despite the advantages of mobile phone use, we should also pay attention to the potential harm of mobile phone use to cardiovascular health,” Dr. Qin said. “Future studies to assess the risk-benefit balance will help promote mobile phone use patterns that are conducive to cardiovascular health.”
Meanwhile, he added, “We encourage measures to reduce time spent on mobile phones to promote the primary prevention of CVD. On the other hand, improving sleep and mental health status may help reduce the higher risk of CVD associated with mobile phone use.”
There are several limitations to the study in addition to its observational nature, which cannot show cause and effect. The questionnaires on cell phone use were restricted to phone calls; other use patterns of cell phones (eg, messaging, watching videos, and browsing the web) were not considered. Although the researchers adjusted for many potential confounders, unmeasured confounding bias (eg, the type of cell phone used and other sources of RF-EMF) cannot be eliminated.
Weak Link?
In a comment, Nicholas Grubic, MSc, a PhD student in epidemiology at the University of Toronto, Ontario, Canada, and coauthor of a related editorial, said, “I found it interesting that there was a connection observed between mobile phone use and CVD. However, it is crucial to understand that this link appeared to be much weaker compared with other well-known cardiovascular risk factors, such as smoking, diabetes, and high blood pressure. For now, mobile phone use should not be a major concern for most people.”
Nevertheless, clinicians should encourage patients to practice healthy habits around their screen time, he advised. “This could include limiting mobile phone use before bedtime and taking regular breaks to engage in activities that promote heart health, such as exercising or spending time outdoors.
“For the time being, we probably won’t see mobile phone use included in standard assessments for cardiovascular risk or as a focal point of cardiovascular health promotion initiatives,” he added. Instead, clinicians should “focus on established risk factors that have a stronger impact on patients’ cardiovascular health.”
Nieca Goldberg, MD, a clinical associate professor of medicine at NYU Grossman School of Medicine in New York City and American Heart Association volunteer expert, had a similar message. “You don’t have to go back to using a landline,” she said. “Instead, patients should be more mindful of how much phone use is taking away from their physical activity, keeping them from sleeping, and causing them stress.” Clinicians should also remember to counsel smokers on smoking cessation.
“It would be important for future studies to look at time spent on the phone and the type of activities patients are doing on their phones, such as social media, calls, texts, movies, or streaming TV shows,” she said. “It would be important to see how phone use is leading to a sedentary lifestyle” and what that means for a larger, more diverse population.
The study was supported by the National Key R&D Program, the National Natural Science Foundation of China, and the Outstanding Youth Development Scheme of Nanfang Hospital, Southern Medical University. Dr. Qin, Dr. Grubic, and Dr. Goldberg reported having no relevant financial relationships.
A version of this article first appeared on Medscape.com.
FROM THE CANADIAN JOURNAL OF CARDIOLOGY
Nighttime Outdoor Light Pollution Linked to Alzheimer’s Risk
a new national study suggested.
Analyses of state and county light pollution data and Medicare claims showed that areas with higher average nighttime light intensity had a greater prevalence of Alzheimer’s disease.
Among people aged 65 years or older, Alzheimer’s disease prevalence was more strongly associated with nightly light pollution exposure than with alcohol misuse, chronic kidney disease, depression, or obesity.
In those younger than 65 years, greater nighttime light intensity had a stronger association with Alzheimer’s disease prevalence than any other risk factor included in the study.
“The results are pretty striking when you do these comparisons and it’s true for people of all ages,” said Robin Voigt-Zuwala, PhD, lead author and director, Circadian Rhythm Research Laboratory, Rush University, Chicago, Illinois.
The study was published online in Frontiers of Neuroscience.
Shining a Light
Exposure to artificial outdoor light at night has been associated with adverse health effects such as sleep disruption, obesity, atherosclerosis, and cancer, but this is the first study to look specifically at Alzheimer’s disease, investigators noted.
Two recent studies reported higher risks for mild cognitive impairment among Chinese veterans and late-onset dementia among Italian residents living in areas with brighter outdoor light at night.
For this study, Dr. Voigt-Zuwala and colleagues examined the relationship between Alzheimer’s disease prevalence and average nighttime light intensity in the lower 48 states using data from Medicare Part A and B, the Centers for Disease Control and Prevention, and NASA satellite–acquired radiance data.
The data were averaged for the years 2012-2018 and states divided into five groups based on average nighttime light intensity.
The darkest states were Montana, Wyoming, South Dakota, Idaho, Maine, New Mexico, Vermont, Oregon, Utah, and Nevada. The brightest states were Indiana, Illinois, Florida, Ohio, Massachusetts, Connecticut, Maryland, Delaware, Rhode Island, and New Jersey.
Analysis of variance revealed a significant difference in Alzheimer’s disease prevalence between state groups (P < .0001). Multiple comparisons testing also showed that states with the lowest average nighttime light had significantly different Alzheimer’s disease prevalence than those with higher intensity.
The same positive relationship was observed when each year was assessed individually and at the county level, using data from 45 counties and the District of Columbia.
Strong Association
The investigators also found that state average nighttime light intensity is significantly associated with Alzheimer’s disease prevalence (P = .006). This effect was seen across all ages, sexes, and races except Asian Pacific Island, the latter possibly related to statistical power, the authors said.
When known or proposed risk factors for Alzheimer’s disease were added to the model, atrial fibrillation, diabetes, hyperlipidemia, hypertension, and stroke had a stronger association with Alzheimer’s disease than average nighttime light intensity.
Nighttime light intensity, however, was more strongly associated with Alzheimer’s disease prevalence than alcohol abuse, chronic kidney disease, depression, heart failure, and obesity.
Moreover, in people younger than 65 years, nighttime light pollution had a stronger association with Alzheimer’s disease prevalence than all other risk factors (P = .007).
The mechanism behind this increased vulnerability is unclear, but there may be an interplay between genetic susceptibility of an individual and how they respond to light, Dr. Voigt-Zuwala suggested.
“APOE4 is the genotype most highly associated with Alzheimer’s disease risk, and maybe the people who have that genotype are just more sensitive to the effects of light exposure at night, more sensitive to circadian rhythm disruption,” she said.
The authors noted that additional research is needed but suggested light pollution may also influence Alzheimer’s disease through sleep disruption, which can promote inflammation, activate microglia and astrocytes, and negatively alter the clearance of amyloid beta, and by decreasing the levels of brain-derived neurotrophic factor.
Are We Measuring the Right Light?
“It’s a good article and it’s got a good message, but I have some caveats to that,” said George C. Brainard, PhD, director, Light Research Program, Thomas Jefferson University in Philadelphia, Pennsylvania, and a pioneer in the study of how light affects biology including breast cancer in night-shift workers.
The biggest caveat, and one acknowledged by the authors, is that the study didn’t measure indoor light exposure and relied instead on satellite imaging.
“They’re very striking images, but they may not be particularly relevant. And here’s why: People don’t live outdoors all night,” Dr. Brainard said.
Instead, people spend much of their time at night indoors where they’re exposed to lighting in the home and from smartphones, laptops, and television screens.
“It doesn’t invalidate their work. It’s an important advancement, an important observation,” Dr. Brainard said. “But the important thing really is to find out what is the population exposed to that triggers this response, and it’s probably indoor lighting related to the amount and physical characteristics of indoor lighting. It doesn’t mean outdoor lighting can’t play a role. It certainly can.”
Reached for comment, Erik Musiek, MD, PhD, a professor of neurology whose lab at Washington University School of Medicine in St. Louis, Missouri, has extensively studied circadian clock disruption and Alzheimer’s disease pathology in the brain, said the study provides a 10,000-foot view of the issue.
For example, the study was not designed to detect whether people living in high light pollution areas are actually experiencing more outdoor light at night and if risk factors such as air pollution and low socioeconomic status may correlate with these areas.
“Most of what we worry about is do people have lights on in the house, do they have their TV on, their screens up to their face late at night? This can’t tell us about that,” Dr. Musiek said. “But on the other hand, this kind of light exposure is something that public policy can affect.”
“It’s hard to control people’s personal habits nor should we probably, but we can control what types of bulbs you put into streetlights, how bright they are, and where you put lighting in a public place,” he added. “So I do think there’s value there.”
At least 19 states, the District of Columbia, and Puerto Rico have laws in place to reduce light pollution, with the majority doing so to promote energy conservation, public safety, aesthetic interests, or astronomical research, according to the National Conference of State Legislatures.
To respond to some of the limitations in this study, Dr. Voigt-Zuwala is writing a grant application for a new project to look at both indoor and outdoor light exposure on an individual level.
“This is what I’ve been wanting to study for a long time, and this study is just sort of the stepping stone, the proof of concept that this is something we need to be investigating,” she said.
Dr. Voigt-Zuwala reported RO1 and R24 grants from the National Institutes of Health (NIH), one coauthor reported an NIH R24 grant; another reported having no conflicts of interest. Dr. Brainard reported having no relevant conflicts of interest. Dr. Musiek reported research funding from Eisai Pharmaceuticals.
A version of this article first appeared on Medscape.com.
a new national study suggested.
Analyses of state and county light pollution data and Medicare claims showed that areas with higher average nighttime light intensity had a greater prevalence of Alzheimer’s disease.
Among people aged 65 years or older, Alzheimer’s disease prevalence was more strongly associated with nightly light pollution exposure than with alcohol misuse, chronic kidney disease, depression, or obesity.
In those younger than 65 years, greater nighttime light intensity had a stronger association with Alzheimer’s disease prevalence than any other risk factor included in the study.
“The results are pretty striking when you do these comparisons and it’s true for people of all ages,” said Robin Voigt-Zuwala, PhD, lead author and director, Circadian Rhythm Research Laboratory, Rush University, Chicago, Illinois.
The study was published online in Frontiers of Neuroscience.
Shining a Light
Exposure to artificial outdoor light at night has been associated with adverse health effects such as sleep disruption, obesity, atherosclerosis, and cancer, but this is the first study to look specifically at Alzheimer’s disease, investigators noted.
Two recent studies reported higher risks for mild cognitive impairment among Chinese veterans and late-onset dementia among Italian residents living in areas with brighter outdoor light at night.
For this study, Dr. Voigt-Zuwala and colleagues examined the relationship between Alzheimer’s disease prevalence and average nighttime light intensity in the lower 48 states using data from Medicare Part A and B, the Centers for Disease Control and Prevention, and NASA satellite–acquired radiance data.
The data were averaged for the years 2012-2018 and states divided into five groups based on average nighttime light intensity.
The darkest states were Montana, Wyoming, South Dakota, Idaho, Maine, New Mexico, Vermont, Oregon, Utah, and Nevada. The brightest states were Indiana, Illinois, Florida, Ohio, Massachusetts, Connecticut, Maryland, Delaware, Rhode Island, and New Jersey.
Analysis of variance revealed a significant difference in Alzheimer’s disease prevalence between state groups (P < .0001). Multiple comparisons testing also showed that states with the lowest average nighttime light had significantly different Alzheimer’s disease prevalence than those with higher intensity.
The same positive relationship was observed when each year was assessed individually and at the county level, using data from 45 counties and the District of Columbia.
Strong Association
The investigators also found that state average nighttime light intensity is significantly associated with Alzheimer’s disease prevalence (P = .006). This effect was seen across all ages, sexes, and races except Asian Pacific Island, the latter possibly related to statistical power, the authors said.
When known or proposed risk factors for Alzheimer’s disease were added to the model, atrial fibrillation, diabetes, hyperlipidemia, hypertension, and stroke had a stronger association with Alzheimer’s disease than average nighttime light intensity.
Nighttime light intensity, however, was more strongly associated with Alzheimer’s disease prevalence than alcohol abuse, chronic kidney disease, depression, heart failure, and obesity.
Moreover, in people younger than 65 years, nighttime light pollution had a stronger association with Alzheimer’s disease prevalence than all other risk factors (P = .007).
The mechanism behind this increased vulnerability is unclear, but there may be an interplay between genetic susceptibility of an individual and how they respond to light, Dr. Voigt-Zuwala suggested.
“APOE4 is the genotype most highly associated with Alzheimer’s disease risk, and maybe the people who have that genotype are just more sensitive to the effects of light exposure at night, more sensitive to circadian rhythm disruption,” she said.
The authors noted that additional research is needed but suggested light pollution may also influence Alzheimer’s disease through sleep disruption, which can promote inflammation, activate microglia and astrocytes, and negatively alter the clearance of amyloid beta, and by decreasing the levels of brain-derived neurotrophic factor.
Are We Measuring the Right Light?
“It’s a good article and it’s got a good message, but I have some caveats to that,” said George C. Brainard, PhD, director, Light Research Program, Thomas Jefferson University in Philadelphia, Pennsylvania, and a pioneer in the study of how light affects biology including breast cancer in night-shift workers.
The biggest caveat, and one acknowledged by the authors, is that the study didn’t measure indoor light exposure and relied instead on satellite imaging.
“They’re very striking images, but they may not be particularly relevant. And here’s why: People don’t live outdoors all night,” Dr. Brainard said.
Instead, people spend much of their time at night indoors where they’re exposed to lighting in the home and from smartphones, laptops, and television screens.
“It doesn’t invalidate their work. It’s an important advancement, an important observation,” Dr. Brainard said. “But the important thing really is to find out what is the population exposed to that triggers this response, and it’s probably indoor lighting related to the amount and physical characteristics of indoor lighting. It doesn’t mean outdoor lighting can’t play a role. It certainly can.”
Reached for comment, Erik Musiek, MD, PhD, a professor of neurology whose lab at Washington University School of Medicine in St. Louis, Missouri, has extensively studied circadian clock disruption and Alzheimer’s disease pathology in the brain, said the study provides a 10,000-foot view of the issue.
For example, the study was not designed to detect whether people living in high light pollution areas are actually experiencing more outdoor light at night and if risk factors such as air pollution and low socioeconomic status may correlate with these areas.
“Most of what we worry about is do people have lights on in the house, do they have their TV on, their screens up to their face late at night? This can’t tell us about that,” Dr. Musiek said. “But on the other hand, this kind of light exposure is something that public policy can affect.”
“It’s hard to control people’s personal habits nor should we probably, but we can control what types of bulbs you put into streetlights, how bright they are, and where you put lighting in a public place,” he added. “So I do think there’s value there.”
At least 19 states, the District of Columbia, and Puerto Rico have laws in place to reduce light pollution, with the majority doing so to promote energy conservation, public safety, aesthetic interests, or astronomical research, according to the National Conference of State Legislatures.
To respond to some of the limitations in this study, Dr. Voigt-Zuwala is writing a grant application for a new project to look at both indoor and outdoor light exposure on an individual level.
“This is what I’ve been wanting to study for a long time, and this study is just sort of the stepping stone, the proof of concept that this is something we need to be investigating,” she said.
Dr. Voigt-Zuwala reported RO1 and R24 grants from the National Institutes of Health (NIH), one coauthor reported an NIH R24 grant; another reported having no conflicts of interest. Dr. Brainard reported having no relevant conflicts of interest. Dr. Musiek reported research funding from Eisai Pharmaceuticals.
A version of this article first appeared on Medscape.com.
a new national study suggested.
Analyses of state and county light pollution data and Medicare claims showed that areas with higher average nighttime light intensity had a greater prevalence of Alzheimer’s disease.
Among people aged 65 years or older, Alzheimer’s disease prevalence was more strongly associated with nightly light pollution exposure than with alcohol misuse, chronic kidney disease, depression, or obesity.
In those younger than 65 years, greater nighttime light intensity had a stronger association with Alzheimer’s disease prevalence than any other risk factor included in the study.
“The results are pretty striking when you do these comparisons and it’s true for people of all ages,” said Robin Voigt-Zuwala, PhD, lead author and director, Circadian Rhythm Research Laboratory, Rush University, Chicago, Illinois.
The study was published online in Frontiers of Neuroscience.
Shining a Light
Exposure to artificial outdoor light at night has been associated with adverse health effects such as sleep disruption, obesity, atherosclerosis, and cancer, but this is the first study to look specifically at Alzheimer’s disease, investigators noted.
Two recent studies reported higher risks for mild cognitive impairment among Chinese veterans and late-onset dementia among Italian residents living in areas with brighter outdoor light at night.
For this study, Dr. Voigt-Zuwala and colleagues examined the relationship between Alzheimer’s disease prevalence and average nighttime light intensity in the lower 48 states using data from Medicare Part A and B, the Centers for Disease Control and Prevention, and NASA satellite–acquired radiance data.
The data were averaged for the years 2012-2018 and states divided into five groups based on average nighttime light intensity.
The darkest states were Montana, Wyoming, South Dakota, Idaho, Maine, New Mexico, Vermont, Oregon, Utah, and Nevada. The brightest states were Indiana, Illinois, Florida, Ohio, Massachusetts, Connecticut, Maryland, Delaware, Rhode Island, and New Jersey.
Analysis of variance revealed a significant difference in Alzheimer’s disease prevalence between state groups (P < .0001). Multiple comparisons testing also showed that states with the lowest average nighttime light had significantly different Alzheimer’s disease prevalence than those with higher intensity.
The same positive relationship was observed when each year was assessed individually and at the county level, using data from 45 counties and the District of Columbia.
Strong Association
The investigators also found that state average nighttime light intensity is significantly associated with Alzheimer’s disease prevalence (P = .006). This effect was seen across all ages, sexes, and races except Asian Pacific Island, the latter possibly related to statistical power, the authors said.
When known or proposed risk factors for Alzheimer’s disease were added to the model, atrial fibrillation, diabetes, hyperlipidemia, hypertension, and stroke had a stronger association with Alzheimer’s disease than average nighttime light intensity.
Nighttime light intensity, however, was more strongly associated with Alzheimer’s disease prevalence than alcohol abuse, chronic kidney disease, depression, heart failure, and obesity.
Moreover, in people younger than 65 years, nighttime light pollution had a stronger association with Alzheimer’s disease prevalence than all other risk factors (P = .007).
The mechanism behind this increased vulnerability is unclear, but there may be an interplay between genetic susceptibility of an individual and how they respond to light, Dr. Voigt-Zuwala suggested.
“APOE4 is the genotype most highly associated with Alzheimer’s disease risk, and maybe the people who have that genotype are just more sensitive to the effects of light exposure at night, more sensitive to circadian rhythm disruption,” she said.
The authors noted that additional research is needed but suggested light pollution may also influence Alzheimer’s disease through sleep disruption, which can promote inflammation, activate microglia and astrocytes, and negatively alter the clearance of amyloid beta, and by decreasing the levels of brain-derived neurotrophic factor.
Are We Measuring the Right Light?
“It’s a good article and it’s got a good message, but I have some caveats to that,” said George C. Brainard, PhD, director, Light Research Program, Thomas Jefferson University in Philadelphia, Pennsylvania, and a pioneer in the study of how light affects biology including breast cancer in night-shift workers.
The biggest caveat, and one acknowledged by the authors, is that the study didn’t measure indoor light exposure and relied instead on satellite imaging.
“They’re very striking images, but they may not be particularly relevant. And here’s why: People don’t live outdoors all night,” Dr. Brainard said.
Instead, people spend much of their time at night indoors where they’re exposed to lighting in the home and from smartphones, laptops, and television screens.
“It doesn’t invalidate their work. It’s an important advancement, an important observation,” Dr. Brainard said. “But the important thing really is to find out what is the population exposed to that triggers this response, and it’s probably indoor lighting related to the amount and physical characteristics of indoor lighting. It doesn’t mean outdoor lighting can’t play a role. It certainly can.”
Reached for comment, Erik Musiek, MD, PhD, a professor of neurology whose lab at Washington University School of Medicine in St. Louis, Missouri, has extensively studied circadian clock disruption and Alzheimer’s disease pathology in the brain, said the study provides a 10,000-foot view of the issue.
For example, the study was not designed to detect whether people living in high light pollution areas are actually experiencing more outdoor light at night and if risk factors such as air pollution and low socioeconomic status may correlate with these areas.
“Most of what we worry about is do people have lights on in the house, do they have their TV on, their screens up to their face late at night? This can’t tell us about that,” Dr. Musiek said. “But on the other hand, this kind of light exposure is something that public policy can affect.”
“It’s hard to control people’s personal habits nor should we probably, but we can control what types of bulbs you put into streetlights, how bright they are, and where you put lighting in a public place,” he added. “So I do think there’s value there.”
At least 19 states, the District of Columbia, and Puerto Rico have laws in place to reduce light pollution, with the majority doing so to promote energy conservation, public safety, aesthetic interests, or astronomical research, according to the National Conference of State Legislatures.
To respond to some of the limitations in this study, Dr. Voigt-Zuwala is writing a grant application for a new project to look at both indoor and outdoor light exposure on an individual level.
“This is what I’ve been wanting to study for a long time, and this study is just sort of the stepping stone, the proof of concept that this is something we need to be investigating,” she said.
Dr. Voigt-Zuwala reported RO1 and R24 grants from the National Institutes of Health (NIH), one coauthor reported an NIH R24 grant; another reported having no conflicts of interest. Dr. Brainard reported having no relevant conflicts of interest. Dr. Musiek reported research funding from Eisai Pharmaceuticals.
A version of this article first appeared on Medscape.com.
FROM FRONTIERS OF NEUROSCIENCE
Pulmonology Data Trends 2024
Pulmonology Data Trends 2024 is a supplement to CHEST Physician highlighting the latest breakthroughs in pulmonology research and treatments through a series of infographics.
Read more: 
Artificial Intelligence in Sleep Apnea
Ritwick Agrawal, MD, MS, FCCP
RSV Updates: Prophylaxis Approval and Hospitalization for Severe RSV
Riddhi Upadhyay, MD
Biologics in Asthma: Changing the Severe Asthma Paradigm
Shyam Subramanian, MD, FCCP
Updates in COPD Guidelines and Treatment
Dharani K. Narendra, MD, FCCP
Targeted Therapies and Surgical Resection for Lung Cancer: Evolving Treatment Options
Saadia A. Faiz, MD, FCCP
Closing the GAP in Idiopathic Pulmonary Fibrosis
Humayun Anjum, MD, FCCP
Severe Community-Acquired Pneumonia: Diagnostic Criteria, Treatment, and COVID-19
Sujith V. Cherian, MD, FCCP
Pulmonary Hypertension: Comorbidities and Novel Therapies
Mary Jo S. Farmer, MD, PhD, FCCP
The Genetic Side of Interstitial Lung Disease
Priya Balakrishnan, MD, MS, FCCP
Noninvasive Ventilation in Neuromuscular Disease
Sreelatha Naik, MD, FCCP, and Kelly Lobrutto, CRNP
Pulmonology Data Trends 2024 is a supplement to CHEST Physician highlighting the latest breakthroughs in pulmonology research and treatments through a series of infographics.
Read more:
Artificial Intelligence in Sleep Apnea
Ritwick Agrawal, MD, MS, FCCP
RSV Updates: Prophylaxis Approval and Hospitalization for Severe RSV
Riddhi Upadhyay, MD
Biologics in Asthma: Changing the Severe Asthma Paradigm
Shyam Subramanian, MD, FCCP
Updates in COPD Guidelines and Treatment
Dharani K. Narendra, MD, FCCP
Targeted Therapies and Surgical Resection for Lung Cancer: Evolving Treatment Options
Saadia A. Faiz, MD, FCCP
Closing the GAP in Idiopathic Pulmonary Fibrosis
Humayun Anjum, MD, FCCP
Severe Community-Acquired Pneumonia: Diagnostic Criteria, Treatment, and COVID-19
Sujith V. Cherian, MD, FCCP
Pulmonary Hypertension: Comorbidities and Novel Therapies
Mary Jo S. Farmer, MD, PhD, FCCP
The Genetic Side of Interstitial Lung Disease
Priya Balakrishnan, MD, MS, FCCP
Noninvasive Ventilation in Neuromuscular Disease
Sreelatha Naik, MD, FCCP, and Kelly Lobrutto, CRNP
Pulmonology Data Trends 2024 is a supplement to CHEST Physician highlighting the latest breakthroughs in pulmonology research and treatments through a series of infographics.
Read more:
Artificial Intelligence in Sleep Apnea
Ritwick Agrawal, MD, MS, FCCP
RSV Updates: Prophylaxis Approval and Hospitalization for Severe RSV
Riddhi Upadhyay, MD
Biologics in Asthma: Changing the Severe Asthma Paradigm
Shyam Subramanian, MD, FCCP
Updates in COPD Guidelines and Treatment
Dharani K. Narendra, MD, FCCP
Targeted Therapies and Surgical Resection for Lung Cancer: Evolving Treatment Options
Saadia A. Faiz, MD, FCCP
Closing the GAP in Idiopathic Pulmonary Fibrosis
Humayun Anjum, MD, FCCP
Severe Community-Acquired Pneumonia: Diagnostic Criteria, Treatment, and COVID-19
Sujith V. Cherian, MD, FCCP
Pulmonary Hypertension: Comorbidities and Novel Therapies
Mary Jo S. Farmer, MD, PhD, FCCP
The Genetic Side of Interstitial Lung Disease
Priya Balakrishnan, MD, MS, FCCP
Noninvasive Ventilation in Neuromuscular Disease
Sreelatha Naik, MD, FCCP, and Kelly Lobrutto, CRNP
SURMOUNT-OSA Results: ‘Impressive’ in Improving Sleep Apnea
This transcript has been edited for clarity.
Akshay B. Jain, MD: Welcome. I’m Dr. Akshay Jain, an endocrinologist in Vancouver, Canada, and with me is a very special guest. Today we have Dr. James Kim, a primary care physician working in Calgary, Canada. Both Dr. Kim and I were fortunate to attend the recently concluded American Diabetes Association annual conference in Orlando in June.
We thought we could share with you some of the key learnings that we found very insightful and clinically quite relevant. We were hoping to bring our own conclusion regarding what these findings were, both from a primary care perspective and an endocrinology perspective.
There were so many different studies that, frankly, it was difficult to pick them, but we handpicked a few studies we felt we could do a bit of a deeper dive on, and we’ll talk about each of these studies.
Welcome, Dr. Kim, and thanks for joining us.
James W. Kim, MBBCh, PgDip, MScCH: Thank you so much, Dr Jain. It’s a pleasure to be here.
Dr. Jain: Probably the best place to start would be with the SURMOUNT-OSA study. This was highlighted at the American Diabetes Association conference. Essentially, it looked at people who are living with obesity who also had obstructive sleep apnea.
This was a randomized controlled trial where individuals tested either got tirzepatide (trade name, Mounjaro) or placebo treatment. They looked at the change in their apnea-hypopnea index at the end of the study.
This included both people who were using CPAP machines and those who were not using CPAP machines at baseline. We do know that many individuals with sleep apnea may not use these machines.
That was a big reduction.
Dr. Kim, what’s the relevance of this study in primary care?
Dr. Kim: Oh, it’s massive. Obstructive sleep apnea is probably one of the most underdiagnosed yet huge cardiac risk factors that we tend to overlook in primary care. We sometimes say, oh, it’s just sleep apnea; what’s the big deal? We know it’s a big problem. We know that more than 50% of people with type 2 diabetes have obstructive sleep apnea, and some studies have even quoted that 90% of their population cohorts had sleep apnea. This is a big deal.
What do we know so far? We know that obstructive sleep apnea, which I’m just going to call OSA, increases the risk for hypertension, bad cholesterol, and worsening blood glucose in terms of A1c and fasting glucose, which eventually leads to myocardial infarction, arrhythmia, stroke, and eventually cardiovascular death.
We also know that people with type 2 diabetes have an increased risk for OSA. There seems to be a bidirectional relationship between diabetes and OSA. It seems like weight plays the biggest role in terms of developing OSA, and numerous studies have shown this.
Also, thankfully, some of the studies showed that weight loss improves not just OSA but also blood pressure, cholesterol, blood glucose, and insulin sensitivities. These have been fascinating. We see these patients every single day. If you think about it in your population, for 50%-90% of the patients to have OSA is a large number. If you haven’t seen a person with OSA this week, you probably missed them, very likely.
Therefore, the SURMOUNT-OSA trial was quite fascinating with, as you mentioned, 50%-60% reduction in the severity of OSA, which is very impressive. Even more impressive, I think, is that for about 50% of the patients on tirzepatide, the OSA improves so much that they may not even need to be on CPAP machines.
Those who were on CPAP may not need to be on CPAP any longer. These are huge data, especially for primary care, because as you mentioned, we see these people every single day.
Dr. Jain: Thanks for pointing that out. Clearly, it’s very clinically relevant. I think the most important takeaway for me from this study was the correlation between weight loss and AHI improvement.
Clearly, it showed that placebo had about a 6% drop in AHI, whereas there was a 60% drop in the tirzepatide group, so you can see that it’s significantly different. The placebo group did not have any significant degree of weight loss, whereas the tirzepatide group had nearly 20% weight loss. This again goes to show that there is a very close correlation between weight loss and improvement in OSA.
What’s very important to note is that we’ve seen this in the past as well. We had seen some of these data with other GLP-1 agents, but the extent of improvement that we have seen in the SURMOUNT-OSA trial is significantly more than what we’ve seen in previous studies. There is a ray of hope now where we have medical management to offer people who are living with obesity and obstructive sleep apnea.
Dr. Kim: I want to add that, from a primary care perspective, this study also showed the improvement of the sleep apnea–related symptoms as well. The biggest problem with sleep apnea — or at least what patients’ spouses complain of, is the person snoring too much; it’s a symptom.
It’s the next-day symptoms that really do disturb people, like chronic fatigue. I have numerous patients who say that, once they’ve been treated for sleep apnea, they feel like a brand-new person. They have sudden bursts of energy that they never felt before, and over 50% of these people have huge improvements in the symptoms as well.
This is a huge trial. The only thing that I wish this study included were people with mild obstructive sleep apnea who were symptomatic. I do understand that, with other studies in this population, the data have been conflicting, but it would have been really awesome if they had those patients included. However, it is still a significant study for primary care.
Dr. Jain: That’s a really good point. Fatigue improves and overall quality of life improves. That’s very important from a primary care perspective.
From an endocrinology perspective, we know that management of sleep apnea can often lead to improvement in male hypogonadism, polycystic ovary syndrome, and insulin resistance. The amount of insulin required, or the number of medications needed for managing diabetes, can improve. Hypertension can improve as well. There are multiple benefits that you can get from appropriate management of sleep apnea.
Thanks, Dr. Kim. We really appreciate your insights on SURMOUNT-OSA.
Dr. Jain is a clinical instructor, Department of Endocrinology, University of British Columbia, Vancouver. Dr. Kim is a clinical assistant professor, Department of Family Medicine, University of Calgary in Alberta. Both disclosed conflicts of interest with numerous pharmaceutical companies.
A version of this article appeared on Medscape.com.
This transcript has been edited for clarity.
Akshay B. Jain, MD: Welcome. I’m Dr. Akshay Jain, an endocrinologist in Vancouver, Canada, and with me is a very special guest. Today we have Dr. James Kim, a primary care physician working in Calgary, Canada. Both Dr. Kim and I were fortunate to attend the recently concluded American Diabetes Association annual conference in Orlando in June.
We thought we could share with you some of the key learnings that we found very insightful and clinically quite relevant. We were hoping to bring our own conclusion regarding what these findings were, both from a primary care perspective and an endocrinology perspective.
There were so many different studies that, frankly, it was difficult to pick them, but we handpicked a few studies we felt we could do a bit of a deeper dive on, and we’ll talk about each of these studies.
Welcome, Dr. Kim, and thanks for joining us.
James W. Kim, MBBCh, PgDip, MScCH: Thank you so much, Dr Jain. It’s a pleasure to be here.
Dr. Jain: Probably the best place to start would be with the SURMOUNT-OSA study. This was highlighted at the American Diabetes Association conference. Essentially, it looked at people who are living with obesity who also had obstructive sleep apnea.
This was a randomized controlled trial where individuals tested either got tirzepatide (trade name, Mounjaro) or placebo treatment. They looked at the change in their apnea-hypopnea index at the end of the study.
This included both people who were using CPAP machines and those who were not using CPAP machines at baseline. We do know that many individuals with sleep apnea may not use these machines.
That was a big reduction.
Dr. Kim, what’s the relevance of this study in primary care?
Dr. Kim: Oh, it’s massive. Obstructive sleep apnea is probably one of the most underdiagnosed yet huge cardiac risk factors that we tend to overlook in primary care. We sometimes say, oh, it’s just sleep apnea; what’s the big deal? We know it’s a big problem. We know that more than 50% of people with type 2 diabetes have obstructive sleep apnea, and some studies have even quoted that 90% of their population cohorts had sleep apnea. This is a big deal.
What do we know so far? We know that obstructive sleep apnea, which I’m just going to call OSA, increases the risk for hypertension, bad cholesterol, and worsening blood glucose in terms of A1c and fasting glucose, which eventually leads to myocardial infarction, arrhythmia, stroke, and eventually cardiovascular death.
We also know that people with type 2 diabetes have an increased risk for OSA. There seems to be a bidirectional relationship between diabetes and OSA. It seems like weight plays the biggest role in terms of developing OSA, and numerous studies have shown this.
Also, thankfully, some of the studies showed that weight loss improves not just OSA but also blood pressure, cholesterol, blood glucose, and insulin sensitivities. These have been fascinating. We see these patients every single day. If you think about it in your population, for 50%-90% of the patients to have OSA is a large number. If you haven’t seen a person with OSA this week, you probably missed them, very likely.
Therefore, the SURMOUNT-OSA trial was quite fascinating with, as you mentioned, 50%-60% reduction in the severity of OSA, which is very impressive. Even more impressive, I think, is that for about 50% of the patients on tirzepatide, the OSA improves so much that they may not even need to be on CPAP machines.
Those who were on CPAP may not need to be on CPAP any longer. These are huge data, especially for primary care, because as you mentioned, we see these people every single day.
Dr. Jain: Thanks for pointing that out. Clearly, it’s very clinically relevant. I think the most important takeaway for me from this study was the correlation between weight loss and AHI improvement.
Clearly, it showed that placebo had about a 6% drop in AHI, whereas there was a 60% drop in the tirzepatide group, so you can see that it’s significantly different. The placebo group did not have any significant degree of weight loss, whereas the tirzepatide group had nearly 20% weight loss. This again goes to show that there is a very close correlation between weight loss and improvement in OSA.
What’s very important to note is that we’ve seen this in the past as well. We had seen some of these data with other GLP-1 agents, but the extent of improvement that we have seen in the SURMOUNT-OSA trial is significantly more than what we’ve seen in previous studies. There is a ray of hope now where we have medical management to offer people who are living with obesity and obstructive sleep apnea.
Dr. Kim: I want to add that, from a primary care perspective, this study also showed the improvement of the sleep apnea–related symptoms as well. The biggest problem with sleep apnea — or at least what patients’ spouses complain of, is the person snoring too much; it’s a symptom.
It’s the next-day symptoms that really do disturb people, like chronic fatigue. I have numerous patients who say that, once they’ve been treated for sleep apnea, they feel like a brand-new person. They have sudden bursts of energy that they never felt before, and over 50% of these people have huge improvements in the symptoms as well.
This is a huge trial. The only thing that I wish this study included were people with mild obstructive sleep apnea who were symptomatic. I do understand that, with other studies in this population, the data have been conflicting, but it would have been really awesome if they had those patients included. However, it is still a significant study for primary care.
Dr. Jain: That’s a really good point. Fatigue improves and overall quality of life improves. That’s very important from a primary care perspective.
From an endocrinology perspective, we know that management of sleep apnea can often lead to improvement in male hypogonadism, polycystic ovary syndrome, and insulin resistance. The amount of insulin required, or the number of medications needed for managing diabetes, can improve. Hypertension can improve as well. There are multiple benefits that you can get from appropriate management of sleep apnea.
Thanks, Dr. Kim. We really appreciate your insights on SURMOUNT-OSA.
Dr. Jain is a clinical instructor, Department of Endocrinology, University of British Columbia, Vancouver. Dr. Kim is a clinical assistant professor, Department of Family Medicine, University of Calgary in Alberta. Both disclosed conflicts of interest with numerous pharmaceutical companies.
A version of this article appeared on Medscape.com.
This transcript has been edited for clarity.
Akshay B. Jain, MD: Welcome. I’m Dr. Akshay Jain, an endocrinologist in Vancouver, Canada, and with me is a very special guest. Today we have Dr. James Kim, a primary care physician working in Calgary, Canada. Both Dr. Kim and I were fortunate to attend the recently concluded American Diabetes Association annual conference in Orlando in June.
We thought we could share with you some of the key learnings that we found very insightful and clinically quite relevant. We were hoping to bring our own conclusion regarding what these findings were, both from a primary care perspective and an endocrinology perspective.
There were so many different studies that, frankly, it was difficult to pick them, but we handpicked a few studies we felt we could do a bit of a deeper dive on, and we’ll talk about each of these studies.
Welcome, Dr. Kim, and thanks for joining us.
James W. Kim, MBBCh, PgDip, MScCH: Thank you so much, Dr Jain. It’s a pleasure to be here.
Dr. Jain: Probably the best place to start would be with the SURMOUNT-OSA study. This was highlighted at the American Diabetes Association conference. Essentially, it looked at people who are living with obesity who also had obstructive sleep apnea.
This was a randomized controlled trial where individuals tested either got tirzepatide (trade name, Mounjaro) or placebo treatment. They looked at the change in their apnea-hypopnea index at the end of the study.
This included both people who were using CPAP machines and those who were not using CPAP machines at baseline. We do know that many individuals with sleep apnea may not use these machines.
That was a big reduction.
Dr. Kim, what’s the relevance of this study in primary care?
Dr. Kim: Oh, it’s massive. Obstructive sleep apnea is probably one of the most underdiagnosed yet huge cardiac risk factors that we tend to overlook in primary care. We sometimes say, oh, it’s just sleep apnea; what’s the big deal? We know it’s a big problem. We know that more than 50% of people with type 2 diabetes have obstructive sleep apnea, and some studies have even quoted that 90% of their population cohorts had sleep apnea. This is a big deal.
What do we know so far? We know that obstructive sleep apnea, which I’m just going to call OSA, increases the risk for hypertension, bad cholesterol, and worsening blood glucose in terms of A1c and fasting glucose, which eventually leads to myocardial infarction, arrhythmia, stroke, and eventually cardiovascular death.
We also know that people with type 2 diabetes have an increased risk for OSA. There seems to be a bidirectional relationship between diabetes and OSA. It seems like weight plays the biggest role in terms of developing OSA, and numerous studies have shown this.
Also, thankfully, some of the studies showed that weight loss improves not just OSA but also blood pressure, cholesterol, blood glucose, and insulin sensitivities. These have been fascinating. We see these patients every single day. If you think about it in your population, for 50%-90% of the patients to have OSA is a large number. If you haven’t seen a person with OSA this week, you probably missed them, very likely.
Therefore, the SURMOUNT-OSA trial was quite fascinating with, as you mentioned, 50%-60% reduction in the severity of OSA, which is very impressive. Even more impressive, I think, is that for about 50% of the patients on tirzepatide, the OSA improves so much that they may not even need to be on CPAP machines.
Those who were on CPAP may not need to be on CPAP any longer. These are huge data, especially for primary care, because as you mentioned, we see these people every single day.
Dr. Jain: Thanks for pointing that out. Clearly, it’s very clinically relevant. I think the most important takeaway for me from this study was the correlation between weight loss and AHI improvement.
Clearly, it showed that placebo had about a 6% drop in AHI, whereas there was a 60% drop in the tirzepatide group, so you can see that it’s significantly different. The placebo group did not have any significant degree of weight loss, whereas the tirzepatide group had nearly 20% weight loss. This again goes to show that there is a very close correlation between weight loss and improvement in OSA.
What’s very important to note is that we’ve seen this in the past as well. We had seen some of these data with other GLP-1 agents, but the extent of improvement that we have seen in the SURMOUNT-OSA trial is significantly more than what we’ve seen in previous studies. There is a ray of hope now where we have medical management to offer people who are living with obesity and obstructive sleep apnea.
Dr. Kim: I want to add that, from a primary care perspective, this study also showed the improvement of the sleep apnea–related symptoms as well. The biggest problem with sleep apnea — or at least what patients’ spouses complain of, is the person snoring too much; it’s a symptom.
It’s the next-day symptoms that really do disturb people, like chronic fatigue. I have numerous patients who say that, once they’ve been treated for sleep apnea, they feel like a brand-new person. They have sudden bursts of energy that they never felt before, and over 50% of these people have huge improvements in the symptoms as well.
This is a huge trial. The only thing that I wish this study included were people with mild obstructive sleep apnea who were symptomatic. I do understand that, with other studies in this population, the data have been conflicting, but it would have been really awesome if they had those patients included. However, it is still a significant study for primary care.
Dr. Jain: That’s a really good point. Fatigue improves and overall quality of life improves. That’s very important from a primary care perspective.
From an endocrinology perspective, we know that management of sleep apnea can often lead to improvement in male hypogonadism, polycystic ovary syndrome, and insulin resistance. The amount of insulin required, or the number of medications needed for managing diabetes, can improve. Hypertension can improve as well. There are multiple benefits that you can get from appropriate management of sleep apnea.
Thanks, Dr. Kim. We really appreciate your insights on SURMOUNT-OSA.
Dr. Jain is a clinical instructor, Department of Endocrinology, University of British Columbia, Vancouver. Dr. Kim is a clinical assistant professor, Department of Family Medicine, University of Calgary in Alberta. Both disclosed conflicts of interest with numerous pharmaceutical companies.
A version of this article appeared on Medscape.com.
OSA in pregnancy: Who to test, how to screen, and does treatment help?
The increased prevalence in pregnancy can be explained by physiologic changes impacting the upper airway such as increases in maternal blood volume and reductions in oncotic pressure, as well as increases in circulating levels of estrogen and progesterone. OSA in pregnancy is associated with adverse perinatal outcomes such as hypertensive disorders of pregnancy, gestational diabetes, severe maternal morbidity abnormalities in fetal growth, preterm birth, and congenital abnormalities in the offspring.2,3 Despite this evidence, guidelines on the screening, diagnosis, and treatment of OSA in pregnancy have only recently been published and will be reviewed here.1
The obstetric subcommittee of the Society of Anesthesia and Sleep Medicine that produced these guidelines had expertise in obstetric anesthesiology, sleep medicine and sleep research, high-risk obstetrics, and obstetric medicine. The guideline aimed to answer 3 questions: 1) Who should be screened in pregnancy for OSA, 2) how to make a diagnosis of OSA in pregnancy and the postpartum period, and 3) what is the treatment for OSA in pregnancy and the postpartum period. Although the estimated number of annual pregnancies in the US declined between 2010 to 2019, these clinical questions remain critical considering the obesity epidemic, the ability to conceive despite advanced maternal age and chronic illnesses with the use of fertility treatments, and the crisis of severe maternal morbidity and mortality. As sleep disordered breathing (SDB) has been associated with many conditions linked to maternal mortality, better management of SDB in this population is key.
Screening for OSA in the pregnant population
The guideline does not support universal screening of all people who are pregnant, but rather suggests that people who are pregnant and at high risk for OSA, such as those with a body mass index (BMI) ≥30 kg/m2 and those with hypertensive disorders of pregnancy, or diabetes, in the index pregnancy or a prior pregnancy, be screened for OSA in the first or second trimester.1 Screening for OSA in pregnancy in limited populations is recommended due to the lower yield of universal screening and its potential burden on the health care system. Furthermore, screening for OSA in early pregnancy is suggested given the practical challenges of arranging testing, initiating, and allowing time for patients to become acclimated to therapy in later stages of pregnancy. However, even when timing of diagnosis may not allow for appropriate treatment of OSA during pregnancy, knowing a person’s OSA status before delivery is beneficial, particularly for patients at risk for Cesarean delivery who may require intubation and exposure to sedative medications, as well as those receiving epidural anesthesia, as OSA is a risk factor for respiratory depression.
Although screening was thought to be beneficial in specific populations, there is insufficient evidence to recommend any one screening tool. The guideline made recommendations against the use of the Berlin questionnaire, STOP-BANG questionnaire, Epworth Sleepiness Scale, or the ASA checklist.1 These screening tools were developed and validated in nonpregnant patient populations and their pooled sensitivity and specificity to detect OSA in pregnancy is low. Individual components of these screening tools, such as prepregnancy BMI, frequency and volume of snoring, hypertension, and neck circumference ≥16 inches have, however, been associated with OSA status.
Pregnancy-specific OSA screening tools have been proposed.4,5 The guideline suggests these pregnancy-specific tools may be considered for screening for OSA in pregnancy but still require external validation, especially in high-risk populations. The committee agreed that individuals with BMI >30kg/m2, hypertension, diabetes, and those with a history of difficult intubation or Mallampati score III or IV are considered at risk for OSA in pregnancy.
Diagnosis of OSA in the pregnant population
In the general population, in-laboratory polysomnogram (PSG) is the gold standard diagnostic test. However, for patients in whom uncomplicated OSA is suspected with a moderate to high pretest probability, unattended home sleep apnea testing (HSAT) is a reasonable initial study. On the other hand, in-lab PSG is recommended in mission-critical workers and when coexisting respiratory sleep disorders, or nonrespiratory sleep disorders, are suspected. For individuals who are pregnant and suspected of having OSA, the guideline suggests that HSAT is a reasonable diagnostic tool, as many level III devices have demonstrated good agreement between the respiratory disturbance index (RDI) and apnea-hypopnea index (AHI) measured by PSG.6 Notably, most studies have examined the performance of level III devices in late pregnancy in populations with obesity; hence, the performance of these devices in early pregnancy when risk for OSA is lower, or more subtle forms of SDB may be more common, is less clear but may be an acceptable first-line test.
The guideline did not provide recommendations for next steps following an inconclusive, technically inadequate, or negative HSAT. However, recommendations to proceed with in-lab PSG in individuals with clinical suspicion for OSA and a negative HSAT is a reasonable approach, keeping in mind the time restrictions of pregnancy. The more delayed the diagnosis, the less time there will be for initiation of and acclimation to therapy to maximize potential benefits during pregnancy. HSAT is especially practical and convenient for individuals with young families. The guideline does not recommend the use of overnight oximetry for diagnostic purposes.1
The postpartum period is usually associated with weight loss and reversal of pregnancy physiology. Generally, the decision to perform a repeat sleep study following weight loss is individualized, based on factors such as improved symptoms or sustained, significant weight loss. Though data show improvement in AHI following delivery, small studies show persistent OSA in nearly half of individuals diagnosed in pregnancy. Hence, as pregnancy increases the risk for OSA, and given that the postpartum status is not always associated with resolution of OSA, the guideline recommends considering repeat diagnostic testing in the postpartum period.1 The decision to repeat testing also depends on whether OSA or OSA symptoms predated pregnancy, on the persistence of symptoms, and the degree of weight loss with delivery and the postpartum body habitus.
Treatment of OSA in the pregnant population
The guideline recommends behavior modification in OSA similarly to individuals who are not pregnant (avoidance of sedatives, smoking, and alcohol).1 However, weight loss is not recommended in pregnancy due to the potential for harm to the fetus.
The gold standard treatment for people who are pregnant and have OSA is continuous positive airway pressure (CPAP). Treatment of OSA in pregnancy is complicated by the fact that very few women are referred to sleep practices due to time restrictions and logistical reasons, and that data demonstrating improved pregnancy outcomes with CPAP are scarce, limiting the prioritization of OSA management. However, expert consensus considers a theoretical benefit in the context of lack of current evidence of harm from treatment. Hence, at this point, the guideline recommends counseling around CPAP therapy be aimed at improvement in symptoms, AHI, and quality of life, rather than pregnancy-specific outcomes.1 This recommendation was based on observations from small case series that demonstrated improved breathing parameters during sleep and symptoms, and small randomized controlled trials (RCT), limited by short-term exposure to the intervention. However, since the publication of this guideline, a large RCT that randomized pregnant women with SDB to CPAP or usual care has demonstrated significantly lower diastolic blood pressure, an altered diastolic blood pressure trajectory, and a lower rate of preeclampsia in the group treated with CPAP compared with usual care.7
This guideline provides helpful insight on who to screen and how to manage OSA in pregnancy but additional research is needed to elucidate benefits of treatment and its effects on maternal and neonatal outcomes. Multidisciplinary collaborations between obstetric and sleep teams are necessary to ensure that screening and diagnostic strategies result in management change for improved outcomes.
References
1. Dominguez JE, Cantrell S, Habib AS, et al. Society of Anesthesia and Sleep Medicine and the Society for Obstetric Anesthesia and Perinatology Consensus Guideline on the screening, diagnosis and treatment of obstructive sleep apnea in pregnancy. Obstet Gynecol. 2023;142(2):403-423.
2. Bourjeily, G, Danilack C, Bublitz M, Muri J, Rosene-Montella K, Lipkind H. Maternal obstructive sleep apnea and neonatal birth outcomes in a population based sample. Sleep Med. 2000;66:233-240.
3. Malhamé I, Bublitz MH, Wilson D, Sanapo L, Rochin E, Bourjeily G. Sleep disordered breathing and the risk of severe maternal morbidity in women with preeclampsia: a population-based study. Pregnancy Hypertens. 2022;30:215-220.
4. Izci-Balserak B, Zhu B, Gurubhagavatula I, Keenan BT, Pien GW. A screening algorithm for obstructive sleep apnea in pregnancy. Ann Am Thorac Soc. 2019;16(10):1286-1294.
5. Louis J, Koch MA, Reddy UM, et al. Predictors of sleep-disordered breathing in pregnancy. Am J Obstet Gynecol. 2018;218(5):521.e1.e12.
6. Sharkey K, Waters K, Millman R, Moore R, Martin SM, Bourjeily. Validation of the Apnea Risk Evaluation System (ARES) device against laboratory polysomnogram in pregnant women at risk for obstructive sleep apnea syndrome. J Clin Sleep Med. 2014;10(5):497-502.
7. Tantrakul V, Ingsathit A, Liamsombut S, et al. Treatment of obstructive sleep apnea in high-risk pregnancy: a multicenter randomized controlled trial. Respir Res. 2023;24(1):171.
The increased prevalence in pregnancy can be explained by physiologic changes impacting the upper airway such as increases in maternal blood volume and reductions in oncotic pressure, as well as increases in circulating levels of estrogen and progesterone. OSA in pregnancy is associated with adverse perinatal outcomes such as hypertensive disorders of pregnancy, gestational diabetes, severe maternal morbidity abnormalities in fetal growth, preterm birth, and congenital abnormalities in the offspring.2,3 Despite this evidence, guidelines on the screening, diagnosis, and treatment of OSA in pregnancy have only recently been published and will be reviewed here.1
The obstetric subcommittee of the Society of Anesthesia and Sleep Medicine that produced these guidelines had expertise in obstetric anesthesiology, sleep medicine and sleep research, high-risk obstetrics, and obstetric medicine. The guideline aimed to answer 3 questions: 1) Who should be screened in pregnancy for OSA, 2) how to make a diagnosis of OSA in pregnancy and the postpartum period, and 3) what is the treatment for OSA in pregnancy and the postpartum period. Although the estimated number of annual pregnancies in the US declined between 2010 to 2019, these clinical questions remain critical considering the obesity epidemic, the ability to conceive despite advanced maternal age and chronic illnesses with the use of fertility treatments, and the crisis of severe maternal morbidity and mortality. As sleep disordered breathing (SDB) has been associated with many conditions linked to maternal mortality, better management of SDB in this population is key.
Screening for OSA in the pregnant population
The guideline does not support universal screening of all people who are pregnant, but rather suggests that people who are pregnant and at high risk for OSA, such as those with a body mass index (BMI) ≥30 kg/m2 and those with hypertensive disorders of pregnancy, or diabetes, in the index pregnancy or a prior pregnancy, be screened for OSA in the first or second trimester.1 Screening for OSA in pregnancy in limited populations is recommended due to the lower yield of universal screening and its potential burden on the health care system. Furthermore, screening for OSA in early pregnancy is suggested given the practical challenges of arranging testing, initiating, and allowing time for patients to become acclimated to therapy in later stages of pregnancy. However, even when timing of diagnosis may not allow for appropriate treatment of OSA during pregnancy, knowing a person’s OSA status before delivery is beneficial, particularly for patients at risk for Cesarean delivery who may require intubation and exposure to sedative medications, as well as those receiving epidural anesthesia, as OSA is a risk factor for respiratory depression.
Although screening was thought to be beneficial in specific populations, there is insufficient evidence to recommend any one screening tool. The guideline made recommendations against the use of the Berlin questionnaire, STOP-BANG questionnaire, Epworth Sleepiness Scale, or the ASA checklist.1 These screening tools were developed and validated in nonpregnant patient populations and their pooled sensitivity and specificity to detect OSA in pregnancy is low. Individual components of these screening tools, such as prepregnancy BMI, frequency and volume of snoring, hypertension, and neck circumference ≥16 inches have, however, been associated with OSA status.
Pregnancy-specific OSA screening tools have been proposed.4,5 The guideline suggests these pregnancy-specific tools may be considered for screening for OSA in pregnancy but still require external validation, especially in high-risk populations. The committee agreed that individuals with BMI >30kg/m2, hypertension, diabetes, and those with a history of difficult intubation or Mallampati score III or IV are considered at risk for OSA in pregnancy.
Diagnosis of OSA in the pregnant population
In the general population, in-laboratory polysomnogram (PSG) is the gold standard diagnostic test. However, for patients in whom uncomplicated OSA is suspected with a moderate to high pretest probability, unattended home sleep apnea testing (HSAT) is a reasonable initial study. On the other hand, in-lab PSG is recommended in mission-critical workers and when coexisting respiratory sleep disorders, or nonrespiratory sleep disorders, are suspected. For individuals who are pregnant and suspected of having OSA, the guideline suggests that HSAT is a reasonable diagnostic tool, as many level III devices have demonstrated good agreement between the respiratory disturbance index (RDI) and apnea-hypopnea index (AHI) measured by PSG.6 Notably, most studies have examined the performance of level III devices in late pregnancy in populations with obesity; hence, the performance of these devices in early pregnancy when risk for OSA is lower, or more subtle forms of SDB may be more common, is less clear but may be an acceptable first-line test.
The guideline did not provide recommendations for next steps following an inconclusive, technically inadequate, or negative HSAT. However, recommendations to proceed with in-lab PSG in individuals with clinical suspicion for OSA and a negative HSAT is a reasonable approach, keeping in mind the time restrictions of pregnancy. The more delayed the diagnosis, the less time there will be for initiation of and acclimation to therapy to maximize potential benefits during pregnancy. HSAT is especially practical and convenient for individuals with young families. The guideline does not recommend the use of overnight oximetry for diagnostic purposes.1
The postpartum period is usually associated with weight loss and reversal of pregnancy physiology. Generally, the decision to perform a repeat sleep study following weight loss is individualized, based on factors such as improved symptoms or sustained, significant weight loss. Though data show improvement in AHI following delivery, small studies show persistent OSA in nearly half of individuals diagnosed in pregnancy. Hence, as pregnancy increases the risk for OSA, and given that the postpartum status is not always associated with resolution of OSA, the guideline recommends considering repeat diagnostic testing in the postpartum period.1 The decision to repeat testing also depends on whether OSA or OSA symptoms predated pregnancy, on the persistence of symptoms, and the degree of weight loss with delivery and the postpartum body habitus.
Treatment of OSA in the pregnant population
The guideline recommends behavior modification in OSA similarly to individuals who are not pregnant (avoidance of sedatives, smoking, and alcohol).1 However, weight loss is not recommended in pregnancy due to the potential for harm to the fetus.
The gold standard treatment for people who are pregnant and have OSA is continuous positive airway pressure (CPAP). Treatment of OSA in pregnancy is complicated by the fact that very few women are referred to sleep practices due to time restrictions and logistical reasons, and that data demonstrating improved pregnancy outcomes with CPAP are scarce, limiting the prioritization of OSA management. However, expert consensus considers a theoretical benefit in the context of lack of current evidence of harm from treatment. Hence, at this point, the guideline recommends counseling around CPAP therapy be aimed at improvement in symptoms, AHI, and quality of life, rather than pregnancy-specific outcomes.1 This recommendation was based on observations from small case series that demonstrated improved breathing parameters during sleep and symptoms, and small randomized controlled trials (RCT), limited by short-term exposure to the intervention. However, since the publication of this guideline, a large RCT that randomized pregnant women with SDB to CPAP or usual care has demonstrated significantly lower diastolic blood pressure, an altered diastolic blood pressure trajectory, and a lower rate of preeclampsia in the group treated with CPAP compared with usual care.7
This guideline provides helpful insight on who to screen and how to manage OSA in pregnancy but additional research is needed to elucidate benefits of treatment and its effects on maternal and neonatal outcomes. Multidisciplinary collaborations between obstetric and sleep teams are necessary to ensure that screening and diagnostic strategies result in management change for improved outcomes.
References
1. Dominguez JE, Cantrell S, Habib AS, et al. Society of Anesthesia and Sleep Medicine and the Society for Obstetric Anesthesia and Perinatology Consensus Guideline on the screening, diagnosis and treatment of obstructive sleep apnea in pregnancy. Obstet Gynecol. 2023;142(2):403-423.
2. Bourjeily, G, Danilack C, Bublitz M, Muri J, Rosene-Montella K, Lipkind H. Maternal obstructive sleep apnea and neonatal birth outcomes in a population based sample. Sleep Med. 2000;66:233-240.
3. Malhamé I, Bublitz MH, Wilson D, Sanapo L, Rochin E, Bourjeily G. Sleep disordered breathing and the risk of severe maternal morbidity in women with preeclampsia: a population-based study. Pregnancy Hypertens. 2022;30:215-220.
4. Izci-Balserak B, Zhu B, Gurubhagavatula I, Keenan BT, Pien GW. A screening algorithm for obstructive sleep apnea in pregnancy. Ann Am Thorac Soc. 2019;16(10):1286-1294.
5. Louis J, Koch MA, Reddy UM, et al. Predictors of sleep-disordered breathing in pregnancy. Am J Obstet Gynecol. 2018;218(5):521.e1.e12.
6. Sharkey K, Waters K, Millman R, Moore R, Martin SM, Bourjeily. Validation of the Apnea Risk Evaluation System (ARES) device against laboratory polysomnogram in pregnant women at risk for obstructive sleep apnea syndrome. J Clin Sleep Med. 2014;10(5):497-502.
7. Tantrakul V, Ingsathit A, Liamsombut S, et al. Treatment of obstructive sleep apnea in high-risk pregnancy: a multicenter randomized controlled trial. Respir Res. 2023;24(1):171.
The increased prevalence in pregnancy can be explained by physiologic changes impacting the upper airway such as increases in maternal blood volume and reductions in oncotic pressure, as well as increases in circulating levels of estrogen and progesterone. OSA in pregnancy is associated with adverse perinatal outcomes such as hypertensive disorders of pregnancy, gestational diabetes, severe maternal morbidity abnormalities in fetal growth, preterm birth, and congenital abnormalities in the offspring.2,3 Despite this evidence, guidelines on the screening, diagnosis, and treatment of OSA in pregnancy have only recently been published and will be reviewed here.1
The obstetric subcommittee of the Society of Anesthesia and Sleep Medicine that produced these guidelines had expertise in obstetric anesthesiology, sleep medicine and sleep research, high-risk obstetrics, and obstetric medicine. The guideline aimed to answer 3 questions: 1) Who should be screened in pregnancy for OSA, 2) how to make a diagnosis of OSA in pregnancy and the postpartum period, and 3) what is the treatment for OSA in pregnancy and the postpartum period. Although the estimated number of annual pregnancies in the US declined between 2010 to 2019, these clinical questions remain critical considering the obesity epidemic, the ability to conceive despite advanced maternal age and chronic illnesses with the use of fertility treatments, and the crisis of severe maternal morbidity and mortality. As sleep disordered breathing (SDB) has been associated with many conditions linked to maternal mortality, better management of SDB in this population is key.
Screening for OSA in the pregnant population
The guideline does not support universal screening of all people who are pregnant, but rather suggests that people who are pregnant and at high risk for OSA, such as those with a body mass index (BMI) ≥30 kg/m2 and those with hypertensive disorders of pregnancy, or diabetes, in the index pregnancy or a prior pregnancy, be screened for OSA in the first or second trimester.1 Screening for OSA in pregnancy in limited populations is recommended due to the lower yield of universal screening and its potential burden on the health care system. Furthermore, screening for OSA in early pregnancy is suggested given the practical challenges of arranging testing, initiating, and allowing time for patients to become acclimated to therapy in later stages of pregnancy. However, even when timing of diagnosis may not allow for appropriate treatment of OSA during pregnancy, knowing a person’s OSA status before delivery is beneficial, particularly for patients at risk for Cesarean delivery who may require intubation and exposure to sedative medications, as well as those receiving epidural anesthesia, as OSA is a risk factor for respiratory depression.
Although screening was thought to be beneficial in specific populations, there is insufficient evidence to recommend any one screening tool. The guideline made recommendations against the use of the Berlin questionnaire, STOP-BANG questionnaire, Epworth Sleepiness Scale, or the ASA checklist.1 These screening tools were developed and validated in nonpregnant patient populations and their pooled sensitivity and specificity to detect OSA in pregnancy is low. Individual components of these screening tools, such as prepregnancy BMI, frequency and volume of snoring, hypertension, and neck circumference ≥16 inches have, however, been associated with OSA status.
Pregnancy-specific OSA screening tools have been proposed.4,5 The guideline suggests these pregnancy-specific tools may be considered for screening for OSA in pregnancy but still require external validation, especially in high-risk populations. The committee agreed that individuals with BMI >30kg/m2, hypertension, diabetes, and those with a history of difficult intubation or Mallampati score III or IV are considered at risk for OSA in pregnancy.
Diagnosis of OSA in the pregnant population
In the general population, in-laboratory polysomnogram (PSG) is the gold standard diagnostic test. However, for patients in whom uncomplicated OSA is suspected with a moderate to high pretest probability, unattended home sleep apnea testing (HSAT) is a reasonable initial study. On the other hand, in-lab PSG is recommended in mission-critical workers and when coexisting respiratory sleep disorders, or nonrespiratory sleep disorders, are suspected. For individuals who are pregnant and suspected of having OSA, the guideline suggests that HSAT is a reasonable diagnostic tool, as many level III devices have demonstrated good agreement between the respiratory disturbance index (RDI) and apnea-hypopnea index (AHI) measured by PSG.6 Notably, most studies have examined the performance of level III devices in late pregnancy in populations with obesity; hence, the performance of these devices in early pregnancy when risk for OSA is lower, or more subtle forms of SDB may be more common, is less clear but may be an acceptable first-line test.
The guideline did not provide recommendations for next steps following an inconclusive, technically inadequate, or negative HSAT. However, recommendations to proceed with in-lab PSG in individuals with clinical suspicion for OSA and a negative HSAT is a reasonable approach, keeping in mind the time restrictions of pregnancy. The more delayed the diagnosis, the less time there will be for initiation of and acclimation to therapy to maximize potential benefits during pregnancy. HSAT is especially practical and convenient for individuals with young families. The guideline does not recommend the use of overnight oximetry for diagnostic purposes.1
The postpartum period is usually associated with weight loss and reversal of pregnancy physiology. Generally, the decision to perform a repeat sleep study following weight loss is individualized, based on factors such as improved symptoms or sustained, significant weight loss. Though data show improvement in AHI following delivery, small studies show persistent OSA in nearly half of individuals diagnosed in pregnancy. Hence, as pregnancy increases the risk for OSA, and given that the postpartum status is not always associated with resolution of OSA, the guideline recommends considering repeat diagnostic testing in the postpartum period.1 The decision to repeat testing also depends on whether OSA or OSA symptoms predated pregnancy, on the persistence of symptoms, and the degree of weight loss with delivery and the postpartum body habitus.
Treatment of OSA in the pregnant population
The guideline recommends behavior modification in OSA similarly to individuals who are not pregnant (avoidance of sedatives, smoking, and alcohol).1 However, weight loss is not recommended in pregnancy due to the potential for harm to the fetus.
The gold standard treatment for people who are pregnant and have OSA is continuous positive airway pressure (CPAP). Treatment of OSA in pregnancy is complicated by the fact that very few women are referred to sleep practices due to time restrictions and logistical reasons, and that data demonstrating improved pregnancy outcomes with CPAP are scarce, limiting the prioritization of OSA management. However, expert consensus considers a theoretical benefit in the context of lack of current evidence of harm from treatment. Hence, at this point, the guideline recommends counseling around CPAP therapy be aimed at improvement in symptoms, AHI, and quality of life, rather than pregnancy-specific outcomes.1 This recommendation was based on observations from small case series that demonstrated improved breathing parameters during sleep and symptoms, and small randomized controlled trials (RCT), limited by short-term exposure to the intervention. However, since the publication of this guideline, a large RCT that randomized pregnant women with SDB to CPAP or usual care has demonstrated significantly lower diastolic blood pressure, an altered diastolic blood pressure trajectory, and a lower rate of preeclampsia in the group treated with CPAP compared with usual care.7
This guideline provides helpful insight on who to screen and how to manage OSA in pregnancy but additional research is needed to elucidate benefits of treatment and its effects on maternal and neonatal outcomes. Multidisciplinary collaborations between obstetric and sleep teams are necessary to ensure that screening and diagnostic strategies result in management change for improved outcomes.
References
1. Dominguez JE, Cantrell S, Habib AS, et al. Society of Anesthesia and Sleep Medicine and the Society for Obstetric Anesthesia and Perinatology Consensus Guideline on the screening, diagnosis and treatment of obstructive sleep apnea in pregnancy. Obstet Gynecol. 2023;142(2):403-423.
2. Bourjeily, G, Danilack C, Bublitz M, Muri J, Rosene-Montella K, Lipkind H. Maternal obstructive sleep apnea and neonatal birth outcomes in a population based sample. Sleep Med. 2000;66:233-240.
3. Malhamé I, Bublitz MH, Wilson D, Sanapo L, Rochin E, Bourjeily G. Sleep disordered breathing and the risk of severe maternal morbidity in women with preeclampsia: a population-based study. Pregnancy Hypertens. 2022;30:215-220.
4. Izci-Balserak B, Zhu B, Gurubhagavatula I, Keenan BT, Pien GW. A screening algorithm for obstructive sleep apnea in pregnancy. Ann Am Thorac Soc. 2019;16(10):1286-1294.
5. Louis J, Koch MA, Reddy UM, et al. Predictors of sleep-disordered breathing in pregnancy. Am J Obstet Gynecol. 2018;218(5):521.e1.e12.
6. Sharkey K, Waters K, Millman R, Moore R, Martin SM, Bourjeily. Validation of the Apnea Risk Evaluation System (ARES) device against laboratory polysomnogram in pregnant women at risk for obstructive sleep apnea syndrome. J Clin Sleep Med. 2014;10(5):497-502.
7. Tantrakul V, Ingsathit A, Liamsombut S, et al. Treatment of obstructive sleep apnea in high-risk pregnancy: a multicenter randomized controlled trial. Respir Res. 2023;24(1):171.
Artificial Intelligence in Sleep Apnea
Benjafield AV, Ayas NT, Eastwood PR, et al. Estimation of the global prevalence and burden of obstructive sleep apnoea: a literature-based analysis. Lancet Respir Med. 2019;7(8):687-698. doi:10.1016/S2213-2600(19)30198-5
Peppard PE, Young T, Barnet JH, Palta M, Hagen EW, Hia KM. Increased prevalence of sleep-disordered breathing in adults. Am J Epidemiol. 2013;177(9):1006-1014. doi:10.1093/aje/kws342
Nag DS, Swain A, Sahu S, Chatterjee A, Swain BP. Relevance of sleep for wellness: new trends in using artificial intelligence and machine learning. World J Clin Cases. 2024;12(7):1196-1199. doi:10.12998/wjcc.v12.i7.1196
Duarte M, Pereira-Rodrigues P, Ferreira-Santos D. The role of novel digital clinical tools in the screening or diagnosis of obstructive sleep apnea: systematic review. J Med Internet Res. 2023;25:e47735. doi:10.2196/47735
Bandyopadhyay A, Goldstein C. Clinical applications of artificial intelligence in sleep medicine: a sleep clinician's perspective. Sleep Breath. 2023;27(1):39-55. doi:10.1007/s11325-022-02592-4
Verma RK, Dhillon G, Grewal H, et al. Artificial intelligence in sleep medicine: present and future. World J Clin Cases. 2023;11(34):8106-8110. doi:10.12998/wjcc.v11.i34.8106
Brennan HL, Kirby SD. The role of artificial intelligence in the treatment of obstructive sleep apnea. J Otolaryngol Head Neck Surg. 2023;52(1):7. doi:10.1186/s40463-023-00621-0
Chung TT, Lee MT, Ku MC, Yang KC, Wei CY. Efficacy of a smart antisnore pillow in patients with obstructive sleep apnea syndrome. Behav Neurol. 2021;2021:8824011. doi:10.1155/2021/8824011
Rusk S, Nygate YN, Fernandez C, et al. 0463 Deep learning classification of future PAP adherence based on CMS and other adherence criteria. Sleep. 2023;46(suppl 1):A206. doi:10.1093/sleep/zsad077.0463
Benjafield AV, Ayas NT, Eastwood PR, et al. Estimation of the global prevalence and burden of obstructive sleep apnoea: a literature-based analysis. Lancet Respir Med. 2019;7(8):687-698. doi:10.1016/S2213-2600(19)30198-5
Peppard PE, Young T, Barnet JH, Palta M, Hagen EW, Hia KM. Increased prevalence of sleep-disordered breathing in adults. Am J Epidemiol. 2013;177(9):1006-1014. doi:10.1093/aje/kws342
Nag DS, Swain A, Sahu S, Chatterjee A, Swain BP. Relevance of sleep for wellness: new trends in using artificial intelligence and machine learning. World J Clin Cases. 2024;12(7):1196-1199. doi:10.12998/wjcc.v12.i7.1196
Duarte M, Pereira-Rodrigues P, Ferreira-Santos D. The role of novel digital clinical tools in the screening or diagnosis of obstructive sleep apnea: systematic review. J Med Internet Res. 2023;25:e47735. doi:10.2196/47735
Bandyopadhyay A, Goldstein C. Clinical applications of artificial intelligence in sleep medicine: a sleep clinician's perspective. Sleep Breath. 2023;27(1):39-55. doi:10.1007/s11325-022-02592-4
Verma RK, Dhillon G, Grewal H, et al. Artificial intelligence in sleep medicine: present and future. World J Clin Cases. 2023;11(34):8106-8110. doi:10.12998/wjcc.v11.i34.8106
Brennan HL, Kirby SD. The role of artificial intelligence in the treatment of obstructive sleep apnea. J Otolaryngol Head Neck Surg. 2023;52(1):7. doi:10.1186/s40463-023-00621-0
Chung TT, Lee MT, Ku MC, Yang KC, Wei CY. Efficacy of a smart antisnore pillow in patients with obstructive sleep apnea syndrome. Behav Neurol. 2021;2021:8824011. doi:10.1155/2021/8824011
Rusk S, Nygate YN, Fernandez C, et al. 0463 Deep learning classification of future PAP adherence based on CMS and other adherence criteria. Sleep. 2023;46(suppl 1):A206. doi:10.1093/sleep/zsad077.0463
Benjafield AV, Ayas NT, Eastwood PR, et al. Estimation of the global prevalence and burden of obstructive sleep apnoea: a literature-based analysis. Lancet Respir Med. 2019;7(8):687-698. doi:10.1016/S2213-2600(19)30198-5
Peppard PE, Young T, Barnet JH, Palta M, Hagen EW, Hia KM. Increased prevalence of sleep-disordered breathing in adults. Am J Epidemiol. 2013;177(9):1006-1014. doi:10.1093/aje/kws342
Nag DS, Swain A, Sahu S, Chatterjee A, Swain BP. Relevance of sleep for wellness: new trends in using artificial intelligence and machine learning. World J Clin Cases. 2024;12(7):1196-1199. doi:10.12998/wjcc.v12.i7.1196
Duarte M, Pereira-Rodrigues P, Ferreira-Santos D. The role of novel digital clinical tools in the screening or diagnosis of obstructive sleep apnea: systematic review. J Med Internet Res. 2023;25:e47735. doi:10.2196/47735
Bandyopadhyay A, Goldstein C. Clinical applications of artificial intelligence in sleep medicine: a sleep clinician's perspective. Sleep Breath. 2023;27(1):39-55. doi:10.1007/s11325-022-02592-4
Verma RK, Dhillon G, Grewal H, et al. Artificial intelligence in sleep medicine: present and future. World J Clin Cases. 2023;11(34):8106-8110. doi:10.12998/wjcc.v11.i34.8106
Brennan HL, Kirby SD. The role of artificial intelligence in the treatment of obstructive sleep apnea. J Otolaryngol Head Neck Surg. 2023;52(1):7. doi:10.1186/s40463-023-00621-0
Chung TT, Lee MT, Ku MC, Yang KC, Wei CY. Efficacy of a smart antisnore pillow in patients with obstructive sleep apnea syndrome. Behav Neurol. 2021;2021:8824011. doi:10.1155/2021/8824011
Rusk S, Nygate YN, Fernandez C, et al. 0463 Deep learning classification of future PAP adherence based on CMS and other adherence criteria. Sleep. 2023;46(suppl 1):A206. doi:10.1093/sleep/zsad077.0463
New AFib Guidelines Address Underlying Illness, Comorbidities
LONDON — Updated guidelines for the management of atrial fibrillation released by the European Society of Cardiology are revamping the approach to care for this complex, multifactorial disease.
, Isabelle Van Gelder, MD, PhD, professor of cardiology at the University Medical Center in Groningen, the Netherlands, explained at the European Society of Cardiology (ESC) Congress.
It is not just appropriate to place the same emphasis on the control of comorbidities as on the rhythm disturbance, it is critical, said Dr. Van Gelder, who served as chair of the ESC-AF guidelines task force.
Comorbidities are the drivers of both the onset and recurrence of atrial fibrillation, and a dynamic approach to comorbidities is “central for the success of AF management.”
Class I Recommendation
In fact, on the basis of overwhelming evidence, a class I recommendation has been issued for a large number of goals in the comorbidity and risk factor management step of atrial fibrillation management, including those for hypertension, components of heart failure, obesity, diabetes, alcohol consumption, and exercise.
Sodium-glucose cotransporter-2 (SGLT2) inhibitors “should be offered to all patients with AF,” according to Dr. Van Gelder, who identified this as a new class I recommendation.
Patients who are not managed aggressively for the listed comorbidities ultimately face “treatment failure, poor patient outcomes, and a waste of healthcare resources,” she said.
Control of sleep apnea is also noted as a key target, although Van Gelder acknowledged that the supporting evidence only allows for a class IIb recommendation.
Control of comorbidities is not a new idea. In the 2023 joint guideline, led by a consortium of professional groups, including the American Heart Association (AHA) and the American College of Cardiology (ACC), the control of comorbidities, including most of those identified in the new ESC guidelines, was second in a list of 10 key take-home messages.
However, the new ESC guidelines have prioritized comorbidity management by listing it first in each of the specific patient-care pathways developed to define optimized care.
These pathways, defined in algorithms for newly diagnosed AF, paroxysmal AF, and persistent AF, always start with the assessment of comorbidities, followed by step A — avoiding stroke — largely with anticoagulation.
Direct oral anticoagulants should be used, “except in those with a mechanical valve or mitral stenosis,” Dr. Van Gelder said. This includes, essentially, all patients with a CHA2DS2-VASc score of 2 or greater, and it should be “considered” in those with a score of 1.
The ESC framework has been identified with the acronym AF-CARE, in which the C stands for comorbidities.
In the A step of the framework, identifying and treating all modifiable bleeding risk factors in AF patients is a class I recommendation. On the basis of a class III recommendation, she cautioned against withholding anticoagulants because of CHA2DS2-VASc risk factors alone. Rather, Dr. Van Gelder called the decision to administer or withhold anticoagulation — like all decisions — one that should be individualized in consultation with the patient.
For reducing AF symptoms and rhythm control, the specific pathways diverge for newly diagnosed AF, paroxysmal AF, and persistent AF. Like all of the guidelines, the specific options for symptom management and AF ablation are color coded, with green signifying level 1 evidence.
The evaluation and dynamic reassessment step refers to the need to periodically assess patients for new modifiable risk factors related to comorbidities, risk for stroke, risk for bleeding, and risk for AF.
The management of risk factors for AF has long been emphasized in guidelines, but a previous focus on AF with attention to comorbidities has been replaced by a focus on comorbidities with an expectation of more durable AF control. The success of this pivot is based on multidisciplinary care, chosen in collaboration with the patient, to reduce or eliminate the triggers of AF and the risks of its complications.
Pathways Are Appropriate for All Patients
A very important recommendation — and this is new — is “to treat all our patients with atrial fibrillation, whether they are young or old, men or women, Black or White, or at high or low risk, according to our patient-centered integrated AF-CARE approach,” Dr. Van Gelder said.
The changes reflect a shared appreciation for the tight relation between the control of comorbidities and the control of AF, according to José A. Joglar, MD, professor of cardiac electrophysiologic research at the University of Texas Southwestern Medical Center in Dallas. Dr. Joglar was chair of the writing committee for the joint 2023 AF guidelines released by the AHA, ACC, the American College of Clinical Pharmacy, and the Heart Rhythm Society.
“It is increasingly clear that AF in many cases is the consequence of underlying risk factors and comorbidities, which cannot be separated from AF alone,” Dr. Joglar explained in an interview.
This was placed first “to emphasize the importance of viewing AFib as a complex disease that requires a holistic, multidisciplinary approach to care, as opposed to being viewed just as a rhythm abnormality,” he said.
A version of this article first appeared on Medscape.com.
LONDON — Updated guidelines for the management of atrial fibrillation released by the European Society of Cardiology are revamping the approach to care for this complex, multifactorial disease.
, Isabelle Van Gelder, MD, PhD, professor of cardiology at the University Medical Center in Groningen, the Netherlands, explained at the European Society of Cardiology (ESC) Congress.
It is not just appropriate to place the same emphasis on the control of comorbidities as on the rhythm disturbance, it is critical, said Dr. Van Gelder, who served as chair of the ESC-AF guidelines task force.
Comorbidities are the drivers of both the onset and recurrence of atrial fibrillation, and a dynamic approach to comorbidities is “central for the success of AF management.”
Class I Recommendation
In fact, on the basis of overwhelming evidence, a class I recommendation has been issued for a large number of goals in the comorbidity and risk factor management step of atrial fibrillation management, including those for hypertension, components of heart failure, obesity, diabetes, alcohol consumption, and exercise.
Sodium-glucose cotransporter-2 (SGLT2) inhibitors “should be offered to all patients with AF,” according to Dr. Van Gelder, who identified this as a new class I recommendation.
Patients who are not managed aggressively for the listed comorbidities ultimately face “treatment failure, poor patient outcomes, and a waste of healthcare resources,” she said.
Control of sleep apnea is also noted as a key target, although Van Gelder acknowledged that the supporting evidence only allows for a class IIb recommendation.
Control of comorbidities is not a new idea. In the 2023 joint guideline, led by a consortium of professional groups, including the American Heart Association (AHA) and the American College of Cardiology (ACC), the control of comorbidities, including most of those identified in the new ESC guidelines, was second in a list of 10 key take-home messages.
However, the new ESC guidelines have prioritized comorbidity management by listing it first in each of the specific patient-care pathways developed to define optimized care.
These pathways, defined in algorithms for newly diagnosed AF, paroxysmal AF, and persistent AF, always start with the assessment of comorbidities, followed by step A — avoiding stroke — largely with anticoagulation.
Direct oral anticoagulants should be used, “except in those with a mechanical valve or mitral stenosis,” Dr. Van Gelder said. This includes, essentially, all patients with a CHA2DS2-VASc score of 2 or greater, and it should be “considered” in those with a score of 1.
The ESC framework has been identified with the acronym AF-CARE, in which the C stands for comorbidities.
In the A step of the framework, identifying and treating all modifiable bleeding risk factors in AF patients is a class I recommendation. On the basis of a class III recommendation, she cautioned against withholding anticoagulants because of CHA2DS2-VASc risk factors alone. Rather, Dr. Van Gelder called the decision to administer or withhold anticoagulation — like all decisions — one that should be individualized in consultation with the patient.
For reducing AF symptoms and rhythm control, the specific pathways diverge for newly diagnosed AF, paroxysmal AF, and persistent AF. Like all of the guidelines, the specific options for symptom management and AF ablation are color coded, with green signifying level 1 evidence.
The evaluation and dynamic reassessment step refers to the need to periodically assess patients for new modifiable risk factors related to comorbidities, risk for stroke, risk for bleeding, and risk for AF.
The management of risk factors for AF has long been emphasized in guidelines, but a previous focus on AF with attention to comorbidities has been replaced by a focus on comorbidities with an expectation of more durable AF control. The success of this pivot is based on multidisciplinary care, chosen in collaboration with the patient, to reduce or eliminate the triggers of AF and the risks of its complications.
Pathways Are Appropriate for All Patients
A very important recommendation — and this is new — is “to treat all our patients with atrial fibrillation, whether they are young or old, men or women, Black or White, or at high or low risk, according to our patient-centered integrated AF-CARE approach,” Dr. Van Gelder said.
The changes reflect a shared appreciation for the tight relation between the control of comorbidities and the control of AF, according to José A. Joglar, MD, professor of cardiac electrophysiologic research at the University of Texas Southwestern Medical Center in Dallas. Dr. Joglar was chair of the writing committee for the joint 2023 AF guidelines released by the AHA, ACC, the American College of Clinical Pharmacy, and the Heart Rhythm Society.
“It is increasingly clear that AF in many cases is the consequence of underlying risk factors and comorbidities, which cannot be separated from AF alone,” Dr. Joglar explained in an interview.
This was placed first “to emphasize the importance of viewing AFib as a complex disease that requires a holistic, multidisciplinary approach to care, as opposed to being viewed just as a rhythm abnormality,” he said.
A version of this article first appeared on Medscape.com.
LONDON — Updated guidelines for the management of atrial fibrillation released by the European Society of Cardiology are revamping the approach to care for this complex, multifactorial disease.
, Isabelle Van Gelder, MD, PhD, professor of cardiology at the University Medical Center in Groningen, the Netherlands, explained at the European Society of Cardiology (ESC) Congress.
It is not just appropriate to place the same emphasis on the control of comorbidities as on the rhythm disturbance, it is critical, said Dr. Van Gelder, who served as chair of the ESC-AF guidelines task force.
Comorbidities are the drivers of both the onset and recurrence of atrial fibrillation, and a dynamic approach to comorbidities is “central for the success of AF management.”
Class I Recommendation
In fact, on the basis of overwhelming evidence, a class I recommendation has been issued for a large number of goals in the comorbidity and risk factor management step of atrial fibrillation management, including those for hypertension, components of heart failure, obesity, diabetes, alcohol consumption, and exercise.
Sodium-glucose cotransporter-2 (SGLT2) inhibitors “should be offered to all patients with AF,” according to Dr. Van Gelder, who identified this as a new class I recommendation.
Patients who are not managed aggressively for the listed comorbidities ultimately face “treatment failure, poor patient outcomes, and a waste of healthcare resources,” she said.
Control of sleep apnea is also noted as a key target, although Van Gelder acknowledged that the supporting evidence only allows for a class IIb recommendation.
Control of comorbidities is not a new idea. In the 2023 joint guideline, led by a consortium of professional groups, including the American Heart Association (AHA) and the American College of Cardiology (ACC), the control of comorbidities, including most of those identified in the new ESC guidelines, was second in a list of 10 key take-home messages.
However, the new ESC guidelines have prioritized comorbidity management by listing it first in each of the specific patient-care pathways developed to define optimized care.
These pathways, defined in algorithms for newly diagnosed AF, paroxysmal AF, and persistent AF, always start with the assessment of comorbidities, followed by step A — avoiding stroke — largely with anticoagulation.
Direct oral anticoagulants should be used, “except in those with a mechanical valve or mitral stenosis,” Dr. Van Gelder said. This includes, essentially, all patients with a CHA2DS2-VASc score of 2 or greater, and it should be “considered” in those with a score of 1.
The ESC framework has been identified with the acronym AF-CARE, in which the C stands for comorbidities.
In the A step of the framework, identifying and treating all modifiable bleeding risk factors in AF patients is a class I recommendation. On the basis of a class III recommendation, she cautioned against withholding anticoagulants because of CHA2DS2-VASc risk factors alone. Rather, Dr. Van Gelder called the decision to administer or withhold anticoagulation — like all decisions — one that should be individualized in consultation with the patient.
For reducing AF symptoms and rhythm control, the specific pathways diverge for newly diagnosed AF, paroxysmal AF, and persistent AF. Like all of the guidelines, the specific options for symptom management and AF ablation are color coded, with green signifying level 1 evidence.
The evaluation and dynamic reassessment step refers to the need to periodically assess patients for new modifiable risk factors related to comorbidities, risk for stroke, risk for bleeding, and risk for AF.
The management of risk factors for AF has long been emphasized in guidelines, but a previous focus on AF with attention to comorbidities has been replaced by a focus on comorbidities with an expectation of more durable AF control. The success of this pivot is based on multidisciplinary care, chosen in collaboration with the patient, to reduce or eliminate the triggers of AF and the risks of its complications.
Pathways Are Appropriate for All Patients
A very important recommendation — and this is new — is “to treat all our patients with atrial fibrillation, whether they are young or old, men or women, Black or White, or at high or low risk, according to our patient-centered integrated AF-CARE approach,” Dr. Van Gelder said.
The changes reflect a shared appreciation for the tight relation between the control of comorbidities and the control of AF, according to José A. Joglar, MD, professor of cardiac electrophysiologic research at the University of Texas Southwestern Medical Center in Dallas. Dr. Joglar was chair of the writing committee for the joint 2023 AF guidelines released by the AHA, ACC, the American College of Clinical Pharmacy, and the Heart Rhythm Society.
“It is increasingly clear that AF in many cases is the consequence of underlying risk factors and comorbidities, which cannot be separated from AF alone,” Dr. Joglar explained in an interview.
This was placed first “to emphasize the importance of viewing AFib as a complex disease that requires a holistic, multidisciplinary approach to care, as opposed to being viewed just as a rhythm abnormality,” he said.
A version of this article first appeared on Medscape.com.
FROM ESC 2024
Just A Single Night of Poor Sleep May Change Serum Proteins
wrote Alvhild Alette Bjørkum, MD, of Western Norway University of Applied Sciences, Bergen, and colleagues.
In a pilot study published in Sleep Advances, the researchers recruited eight healthy adult women aged 22-57 years with no history of neurologic or psychiatric problems to participate in a study of the effect of compromised sleep on protein profiles, with implications for effects on cells, tissues, and organ systems. Each of the participants served as their own controls, and blood samples were taken after 6 hours of sleep at night, and again after 6 hours of sleep deprivation the following night.
The researchers identified analyzed 494 proteins using mass spectrometry. Of these, 66 were differentially expressed after 6 hours of sleep deprivation. The top enriched biologic processes of these significantly changed proteins were protein activation cascade, platelet degranulation, blood coagulation, and hemostasis.
Further analysis using gene ontology showed changes in response to sleep deprivation in biologic process, molecular function, and immune system process categories, including specific associations related to wound healing, cholesterol transport, high-density lipoprotein particle receptor binding, and granulocyte chemotaxis.
The findings were limited by several factors including the small sample size, inclusion only of adult females, and the use of data from only 1 night of sleep deprivation, the researchers noted. However, the results support previous studies showing a negative impact of sleep deprivation on biologic functions, they said.
“Our study was able to reveal another set of human serum proteins that were altered by sleep deprivation and could connect similar biological processes to sleep deprivation that have been identified before with slightly different methods,” the researchers concluded. The study findings add to the knowledge base for the protein profiling of sleep deprivation, which may inform the development of tools to manage lack of sleep and mistimed sleep, particularly in shift workers.
Too Soon for Clinical Implications
“The adverse impact of poor sleep across many organ systems is gaining recognition, but the mechanisms underlying sleep-related pathology are not well understood,” Evan L. Brittain, MD, of Vanderbilt University, Nashville, Tennessee, said in an interview. “Studies like this begin to shed light on the mechanisms by which poor or reduced sleep affects specific bodily functions,” added Dr. Brittain, who was not involved in the study.
“The effects of other acute physiologic stressor such as exercise on the circulating proteome are well described. In that regard, it is not surprising that a brief episode of sleep deprivation would lead to detectable changes in the circulation,” Dr. Brittain said.
However, the specific changes reported in this study are difficult to interpret because of methodological and analytical concerns, particularly the small sample size, lack of an external validation cohort, and absence of appropriate statistical adjustments in the results, Dr. Brittain noted. These limitations prevent consideration of clinical implications without further study.
The study received no outside funding. Neither the researchers nor Dr. Brittain disclosed any conflicts of interest.
A version of this article first appeared on Medscape.com.
wrote Alvhild Alette Bjørkum, MD, of Western Norway University of Applied Sciences, Bergen, and colleagues.
In a pilot study published in Sleep Advances, the researchers recruited eight healthy adult women aged 22-57 years with no history of neurologic or psychiatric problems to participate in a study of the effect of compromised sleep on protein profiles, with implications for effects on cells, tissues, and organ systems. Each of the participants served as their own controls, and blood samples were taken after 6 hours of sleep at night, and again after 6 hours of sleep deprivation the following night.
The researchers identified analyzed 494 proteins using mass spectrometry. Of these, 66 were differentially expressed after 6 hours of sleep deprivation. The top enriched biologic processes of these significantly changed proteins were protein activation cascade, platelet degranulation, blood coagulation, and hemostasis.
Further analysis using gene ontology showed changes in response to sleep deprivation in biologic process, molecular function, and immune system process categories, including specific associations related to wound healing, cholesterol transport, high-density lipoprotein particle receptor binding, and granulocyte chemotaxis.
The findings were limited by several factors including the small sample size, inclusion only of adult females, and the use of data from only 1 night of sleep deprivation, the researchers noted. However, the results support previous studies showing a negative impact of sleep deprivation on biologic functions, they said.
“Our study was able to reveal another set of human serum proteins that were altered by sleep deprivation and could connect similar biological processes to sleep deprivation that have been identified before with slightly different methods,” the researchers concluded. The study findings add to the knowledge base for the protein profiling of sleep deprivation, which may inform the development of tools to manage lack of sleep and mistimed sleep, particularly in shift workers.
Too Soon for Clinical Implications
“The adverse impact of poor sleep across many organ systems is gaining recognition, but the mechanisms underlying sleep-related pathology are not well understood,” Evan L. Brittain, MD, of Vanderbilt University, Nashville, Tennessee, said in an interview. “Studies like this begin to shed light on the mechanisms by which poor or reduced sleep affects specific bodily functions,” added Dr. Brittain, who was not involved in the study.
“The effects of other acute physiologic stressor such as exercise on the circulating proteome are well described. In that regard, it is not surprising that a brief episode of sleep deprivation would lead to detectable changes in the circulation,” Dr. Brittain said.
However, the specific changes reported in this study are difficult to interpret because of methodological and analytical concerns, particularly the small sample size, lack of an external validation cohort, and absence of appropriate statistical adjustments in the results, Dr. Brittain noted. These limitations prevent consideration of clinical implications without further study.
The study received no outside funding. Neither the researchers nor Dr. Brittain disclosed any conflicts of interest.
A version of this article first appeared on Medscape.com.
wrote Alvhild Alette Bjørkum, MD, of Western Norway University of Applied Sciences, Bergen, and colleagues.
In a pilot study published in Sleep Advances, the researchers recruited eight healthy adult women aged 22-57 years with no history of neurologic or psychiatric problems to participate in a study of the effect of compromised sleep on protein profiles, with implications for effects on cells, tissues, and organ systems. Each of the participants served as their own controls, and blood samples were taken after 6 hours of sleep at night, and again after 6 hours of sleep deprivation the following night.
The researchers identified analyzed 494 proteins using mass spectrometry. Of these, 66 were differentially expressed after 6 hours of sleep deprivation. The top enriched biologic processes of these significantly changed proteins were protein activation cascade, platelet degranulation, blood coagulation, and hemostasis.
Further analysis using gene ontology showed changes in response to sleep deprivation in biologic process, molecular function, and immune system process categories, including specific associations related to wound healing, cholesterol transport, high-density lipoprotein particle receptor binding, and granulocyte chemotaxis.
The findings were limited by several factors including the small sample size, inclusion only of adult females, and the use of data from only 1 night of sleep deprivation, the researchers noted. However, the results support previous studies showing a negative impact of sleep deprivation on biologic functions, they said.
“Our study was able to reveal another set of human serum proteins that were altered by sleep deprivation and could connect similar biological processes to sleep deprivation that have been identified before with slightly different methods,” the researchers concluded. The study findings add to the knowledge base for the protein profiling of sleep deprivation, which may inform the development of tools to manage lack of sleep and mistimed sleep, particularly in shift workers.
Too Soon for Clinical Implications
“The adverse impact of poor sleep across many organ systems is gaining recognition, but the mechanisms underlying sleep-related pathology are not well understood,” Evan L. Brittain, MD, of Vanderbilt University, Nashville, Tennessee, said in an interview. “Studies like this begin to shed light on the mechanisms by which poor or reduced sleep affects specific bodily functions,” added Dr. Brittain, who was not involved in the study.
“The effects of other acute physiologic stressor such as exercise on the circulating proteome are well described. In that regard, it is not surprising that a brief episode of sleep deprivation would lead to detectable changes in the circulation,” Dr. Brittain said.
However, the specific changes reported in this study are difficult to interpret because of methodological and analytical concerns, particularly the small sample size, lack of an external validation cohort, and absence of appropriate statistical adjustments in the results, Dr. Brittain noted. These limitations prevent consideration of clinical implications without further study.
The study received no outside funding. Neither the researchers nor Dr. Brittain disclosed any conflicts of interest.
A version of this article first appeared on Medscape.com.
FROM SLEEP ADVANCES
Signal of Suicide Ideation With GLP-1 RA Semaglutide, but Experts Urge Caution
A new analysis has detected a signal of suicidal ideation associated with the glucagon-like peptide 1 receptor agonist (GLP-1 RA) semaglutide, especially among individuals concurrently using antidepressants or benzodiazepines.
However, the investigators and outside experts urge caution in drawing any firm conclusions based on the study’s observations.
,” study investigator Georgios Schoretsanitis, MD, PhD, Department of Psychiatry, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, New York, told this news organization.
Nonetheless, “physicians prescribing semaglutide should inform their patients about the medications’ risks and assess the psychiatric history and evaluate the mental state of patients before starting treatment with semaglutide,” Dr. Schoretsanitis said.
“For patients with history of mental disorders or suicidal ideation/behaviors/attempts, physicians should be cautious and regularly monitor their mental state while taking semaglutide. If needed, the treating physician should involve different specialists, including a psychiatrist and/or clinical psychologists,” he added.
The study was published online on August 20 in JAMA Network Open.
Emerging Concerns
GLP-1 RAs are increasingly prescribed not only for type 2 diabetes but also for weight loss. However, concerns have emerged about a potential association with suicidality, which has prompted a closer look by regulators in the United States and Europe.
Dr. Schoretsanitis and colleagues evaluated potential signals of suicidality related to semaglutide and liraglutide using data from global World Health Organization database of suspected adverse drug reactions (ADRs).
They conducted sensitivity analyses including patients with co-reported use of antidepressants and benzodiazepines and using dapagliflozin, metformin, and orlistat as comparators.
Between November 2000 and August 2023, there were 107 cases of suicidal and/or self-injurious ADRs reported with semaglutide (median age, 48 years; 55% women) and 162 reported with liraglutide (median age 47 years; 61% women).
The researchers noted that a “significant disproportionality” signal emerged for semaglutide-associated suicidal ideation (reporting odds ratio [ROR], 1.45), when compared with comparator drugs.
This signal remained significant in sensitivity analyses that included patients on concurrent antidepressants (ROR, 4.45) and benzodiazepines (ROR, 4.07), “suggesting that people with anxiety and depressive disorders may be at higher probability of reporting suicidal ideation when medicated with semaglutide,” the authors wrote.
No significant disproportionality signal was detected for liraglutide regarding suicidal ideation (ROR, 1.04).
However, the authors noted that pooled data from previous phase 2 and 3 trials on liraglutide vs placebo for weight management identified a potential risk for suicidal ideation, with nine of 3384 participants in the liraglutide group vs two of 1941 in the placebo group reporting suicidal ideation or behavior during the trial (0.27% vs 0.10%).
More Research Needed
GLP-1 RAs “should be used cautiously until further data are available on this topic,” Dr. Schoretsanitis said.
“Further real-world studies should investigate the risk of suicidal ideation or behavior in people treated with these drugs in every-day clinical practice. We categorically discourage off-label use of GLP1-RA and without any medical supervision,” he added.
The coauthors of an invited commentary published with the study note that between 2020 and 2023, GLP-1 RA use rose 594% in younger people, particularly in women.
This “timely and well-conducted study” by Dr. Schoretsanitis and colleagues adds “an important piece to the very relevant safety issue” related to GLP-1 RAs, wrote Francesco Salvo, MD, PhD, with Université de Bordeaux, and Jean-Luc Faillie, MD, PhD, with Université de Montpellier, both in France.
Pending further studies, the position of the US Food and Drug Administration (FDA) recommending caution “continues to be reasonable. Whatever the cause, depression or suicidality are rare but extremely severe events and need to be prevented and managed as much as possible.
“Waiting for more precise data, GPL-1 receptor agonists, and appetite suppressants in general, should be prescribed with great caution in patients with a history of depression or suicidal attempts, while in patients with new onset of depression without other apparent precipitants, immediate discontinuation of GLP-1 receptor agonists should be considered,” wrote Dr. Salvo and Dr. Faillie.
Outside experts also weighed in on the study in a statement from the UK nonprofit Science Media Centre.
The paper presents, “at best, weak evidence of an association between semaglutide and suicidality,” Ian Douglas, PhD, professor of pharmacoepidemiology, London School of Hygiene & Tropical Medicine, United Kingdom, said in the statement. “Signal detection studies in pharmacovigilance databases are good for generating hypotheses but are not suitable for assessing whether there is a causal association between a drug and an outcome.”
Stephen Evans, MSc, emeritus professor of pharmacoepidemiology, London School of Hygiene & Tropical Medicine, cautioned that the study has “major limitations.”
“This paper is based just on spontaneous reports which are sent to regulatory authorities in the country of the person reporting a suspected adverse reaction. These are sent by health professionals and patients to authorities, but are very subject to bias, including effects of media reporting. The evidence is extremely weak for a genuine effect in this instance,” Mr. Evans said.
The study had no specific funding. Dr. Schoretsanitis reported receiving personal fees from HLS, Dexcel, Saladax, and Thermo Fisher outside the submitted work. Dr. Salvo and Dr. Faillie have no conflicts of interest. Dr. Douglas has received research grants from GSK and AstraZeneca. Mr. Evans has no conflicts of interest.
A version of this article appeared on Medscape.com.
A new analysis has detected a signal of suicidal ideation associated with the glucagon-like peptide 1 receptor agonist (GLP-1 RA) semaglutide, especially among individuals concurrently using antidepressants or benzodiazepines.
However, the investigators and outside experts urge caution in drawing any firm conclusions based on the study’s observations.
,” study investigator Georgios Schoretsanitis, MD, PhD, Department of Psychiatry, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, New York, told this news organization.
Nonetheless, “physicians prescribing semaglutide should inform their patients about the medications’ risks and assess the psychiatric history and evaluate the mental state of patients before starting treatment with semaglutide,” Dr. Schoretsanitis said.
“For patients with history of mental disorders or suicidal ideation/behaviors/attempts, physicians should be cautious and regularly monitor their mental state while taking semaglutide. If needed, the treating physician should involve different specialists, including a psychiatrist and/or clinical psychologists,” he added.
The study was published online on August 20 in JAMA Network Open.
Emerging Concerns
GLP-1 RAs are increasingly prescribed not only for type 2 diabetes but also for weight loss. However, concerns have emerged about a potential association with suicidality, which has prompted a closer look by regulators in the United States and Europe.
Dr. Schoretsanitis and colleagues evaluated potential signals of suicidality related to semaglutide and liraglutide using data from global World Health Organization database of suspected adverse drug reactions (ADRs).
They conducted sensitivity analyses including patients with co-reported use of antidepressants and benzodiazepines and using dapagliflozin, metformin, and orlistat as comparators.
Between November 2000 and August 2023, there were 107 cases of suicidal and/or self-injurious ADRs reported with semaglutide (median age, 48 years; 55% women) and 162 reported with liraglutide (median age 47 years; 61% women).
The researchers noted that a “significant disproportionality” signal emerged for semaglutide-associated suicidal ideation (reporting odds ratio [ROR], 1.45), when compared with comparator drugs.
This signal remained significant in sensitivity analyses that included patients on concurrent antidepressants (ROR, 4.45) and benzodiazepines (ROR, 4.07), “suggesting that people with anxiety and depressive disorders may be at higher probability of reporting suicidal ideation when medicated with semaglutide,” the authors wrote.
No significant disproportionality signal was detected for liraglutide regarding suicidal ideation (ROR, 1.04).
However, the authors noted that pooled data from previous phase 2 and 3 trials on liraglutide vs placebo for weight management identified a potential risk for suicidal ideation, with nine of 3384 participants in the liraglutide group vs two of 1941 in the placebo group reporting suicidal ideation or behavior during the trial (0.27% vs 0.10%).
More Research Needed
GLP-1 RAs “should be used cautiously until further data are available on this topic,” Dr. Schoretsanitis said.
“Further real-world studies should investigate the risk of suicidal ideation or behavior in people treated with these drugs in every-day clinical practice. We categorically discourage off-label use of GLP1-RA and without any medical supervision,” he added.
The coauthors of an invited commentary published with the study note that between 2020 and 2023, GLP-1 RA use rose 594% in younger people, particularly in women.
This “timely and well-conducted study” by Dr. Schoretsanitis and colleagues adds “an important piece to the very relevant safety issue” related to GLP-1 RAs, wrote Francesco Salvo, MD, PhD, with Université de Bordeaux, and Jean-Luc Faillie, MD, PhD, with Université de Montpellier, both in France.
Pending further studies, the position of the US Food and Drug Administration (FDA) recommending caution “continues to be reasonable. Whatever the cause, depression or suicidality are rare but extremely severe events and need to be prevented and managed as much as possible.
“Waiting for more precise data, GPL-1 receptor agonists, and appetite suppressants in general, should be prescribed with great caution in patients with a history of depression or suicidal attempts, while in patients with new onset of depression without other apparent precipitants, immediate discontinuation of GLP-1 receptor agonists should be considered,” wrote Dr. Salvo and Dr. Faillie.
Outside experts also weighed in on the study in a statement from the UK nonprofit Science Media Centre.
The paper presents, “at best, weak evidence of an association between semaglutide and suicidality,” Ian Douglas, PhD, professor of pharmacoepidemiology, London School of Hygiene & Tropical Medicine, United Kingdom, said in the statement. “Signal detection studies in pharmacovigilance databases are good for generating hypotheses but are not suitable for assessing whether there is a causal association between a drug and an outcome.”
Stephen Evans, MSc, emeritus professor of pharmacoepidemiology, London School of Hygiene & Tropical Medicine, cautioned that the study has “major limitations.”
“This paper is based just on spontaneous reports which are sent to regulatory authorities in the country of the person reporting a suspected adverse reaction. These are sent by health professionals and patients to authorities, but are very subject to bias, including effects of media reporting. The evidence is extremely weak for a genuine effect in this instance,” Mr. Evans said.
The study had no specific funding. Dr. Schoretsanitis reported receiving personal fees from HLS, Dexcel, Saladax, and Thermo Fisher outside the submitted work. Dr. Salvo and Dr. Faillie have no conflicts of interest. Dr. Douglas has received research grants from GSK and AstraZeneca. Mr. Evans has no conflicts of interest.
A version of this article appeared on Medscape.com.
A new analysis has detected a signal of suicidal ideation associated with the glucagon-like peptide 1 receptor agonist (GLP-1 RA) semaglutide, especially among individuals concurrently using antidepressants or benzodiazepines.
However, the investigators and outside experts urge caution in drawing any firm conclusions based on the study’s observations.
,” study investigator Georgios Schoretsanitis, MD, PhD, Department of Psychiatry, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, New York, told this news organization.
Nonetheless, “physicians prescribing semaglutide should inform their patients about the medications’ risks and assess the psychiatric history and evaluate the mental state of patients before starting treatment with semaglutide,” Dr. Schoretsanitis said.
“For patients with history of mental disorders or suicidal ideation/behaviors/attempts, physicians should be cautious and regularly monitor their mental state while taking semaglutide. If needed, the treating physician should involve different specialists, including a psychiatrist and/or clinical psychologists,” he added.
The study was published online on August 20 in JAMA Network Open.
Emerging Concerns
GLP-1 RAs are increasingly prescribed not only for type 2 diabetes but also for weight loss. However, concerns have emerged about a potential association with suicidality, which has prompted a closer look by regulators in the United States and Europe.
Dr. Schoretsanitis and colleagues evaluated potential signals of suicidality related to semaglutide and liraglutide using data from global World Health Organization database of suspected adverse drug reactions (ADRs).
They conducted sensitivity analyses including patients with co-reported use of antidepressants and benzodiazepines and using dapagliflozin, metformin, and orlistat as comparators.
Between November 2000 and August 2023, there were 107 cases of suicidal and/or self-injurious ADRs reported with semaglutide (median age, 48 years; 55% women) and 162 reported with liraglutide (median age 47 years; 61% women).
The researchers noted that a “significant disproportionality” signal emerged for semaglutide-associated suicidal ideation (reporting odds ratio [ROR], 1.45), when compared with comparator drugs.
This signal remained significant in sensitivity analyses that included patients on concurrent antidepressants (ROR, 4.45) and benzodiazepines (ROR, 4.07), “suggesting that people with anxiety and depressive disorders may be at higher probability of reporting suicidal ideation when medicated with semaglutide,” the authors wrote.
No significant disproportionality signal was detected for liraglutide regarding suicidal ideation (ROR, 1.04).
However, the authors noted that pooled data from previous phase 2 and 3 trials on liraglutide vs placebo for weight management identified a potential risk for suicidal ideation, with nine of 3384 participants in the liraglutide group vs two of 1941 in the placebo group reporting suicidal ideation or behavior during the trial (0.27% vs 0.10%).
More Research Needed
GLP-1 RAs “should be used cautiously until further data are available on this topic,” Dr. Schoretsanitis said.
“Further real-world studies should investigate the risk of suicidal ideation or behavior in people treated with these drugs in every-day clinical practice. We categorically discourage off-label use of GLP1-RA and without any medical supervision,” he added.
The coauthors of an invited commentary published with the study note that between 2020 and 2023, GLP-1 RA use rose 594% in younger people, particularly in women.
This “timely and well-conducted study” by Dr. Schoretsanitis and colleagues adds “an important piece to the very relevant safety issue” related to GLP-1 RAs, wrote Francesco Salvo, MD, PhD, with Université de Bordeaux, and Jean-Luc Faillie, MD, PhD, with Université de Montpellier, both in France.
Pending further studies, the position of the US Food and Drug Administration (FDA) recommending caution “continues to be reasonable. Whatever the cause, depression or suicidality are rare but extremely severe events and need to be prevented and managed as much as possible.
“Waiting for more precise data, GPL-1 receptor agonists, and appetite suppressants in general, should be prescribed with great caution in patients with a history of depression or suicidal attempts, while in patients with new onset of depression without other apparent precipitants, immediate discontinuation of GLP-1 receptor agonists should be considered,” wrote Dr. Salvo and Dr. Faillie.
Outside experts also weighed in on the study in a statement from the UK nonprofit Science Media Centre.
The paper presents, “at best, weak evidence of an association between semaglutide and suicidality,” Ian Douglas, PhD, professor of pharmacoepidemiology, London School of Hygiene & Tropical Medicine, United Kingdom, said in the statement. “Signal detection studies in pharmacovigilance databases are good for generating hypotheses but are not suitable for assessing whether there is a causal association between a drug and an outcome.”
Stephen Evans, MSc, emeritus professor of pharmacoepidemiology, London School of Hygiene & Tropical Medicine, cautioned that the study has “major limitations.”
“This paper is based just on spontaneous reports which are sent to regulatory authorities in the country of the person reporting a suspected adverse reaction. These are sent by health professionals and patients to authorities, but are very subject to bias, including effects of media reporting. The evidence is extremely weak for a genuine effect in this instance,” Mr. Evans said.
The study had no specific funding. Dr. Schoretsanitis reported receiving personal fees from HLS, Dexcel, Saladax, and Thermo Fisher outside the submitted work. Dr. Salvo and Dr. Faillie have no conflicts of interest. Dr. Douglas has received research grants from GSK and AstraZeneca. Mr. Evans has no conflicts of interest.
A version of this article appeared on Medscape.com.