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[post_date] => 2025-03-11 20:01:38
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The recent study, "Multinight Prevalence, Variability, and Diagnostic Misclassification of Obstructive Sleep Apnea" by Bastien Lechat and colleagues, sheds light on the limitations of single-night assessments in diagnosing obstructive sleep apnea (OSA).
OSA is a common sleep disorder in which breathing repeatedly stops and starts throughout the night. It's typically diagnosed using a sleep study that measures the apnea-hypopnea index (AHI)—the number of times per hour that a person experiences reduced or blocked airflow. Current clinical practice to diagnose OSA requires a single, overnight, in-laboratory or in-home polysomnography or polygraphy study.
The researchers looked at data from over 67,278 individuals aged 18 to 90 who had used the Withings sleep mat, a non-invasive, under-mattress sensor. In addition to the vast number of participants, the researchers were able to monitor an average of approximately 170 nights of data per participant between July 2020 and March 2021. This extensive data collection resulted in more than 11.6 million nights of sleep data–the largest standardized, objective assessment of OSA collected to date.
The study found that the global prevalence of moderate to severe OSA, defined as a nightly mean apnea-hypopnea index (AHI) of more than 15 events per hour, was 22.6% (95% confidence interval: 20.9–24.3%). Notably, the research highlighted significant night-to-night variability in OSA severity. When relying on a single night's data, the likelihood of misdiagnosis ranged from approximately 20% and up to 50% for those with mild to moderate OSA. Increasing the number of monitoring nights improved diagnostic accuracy, with misdiagnosis error rates decreasing and stabilizing after 14 nights of monitoring.
The substantial variability of OSA suggests that single-night assessments may not provide a comprehensive picture of an individual's sleep patterns, leading to possible misclassifications. However, fourteen nights of polysomnography in a sleep lab or clinic is not feasible. Tools like the Withings sleep mat offer a non-invasive, cost-effective means of multinight in-home monitoring leading to more accurate and reliable diagnosis of OSA. By offering an accessible way to capture more nights of sleep data, clinicians can reduce misdiagnosis and create a shift in how sleep disorders are screened for and tracked.
References
- Lechat, Bastien et al. “Multinight Prevalence, Variability, and Diagnostic Misclassification of Obstructive Sleep Apnea.” American journal of respiratory and critical care medicine vol. 205,5 (2022): 563-569. doi:10.1164/rccm.202107-1761OC
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[post_title] => A Single-Night Sleep Study Can Misdiagnose Sleep Apnea Up to Half the Time
[post_excerpt] => New large-scale, longitudinal studies show that monitoring sleep for at least 14 nights at home with a connected sleep tracking mat, can reduce the 30% high error rate of sleep apnea diagnosis from the usual single-night, in hospital polysomnography (PSG) technique. This technology can identify which patients most need expensive, intrusive, and difficult to access PSG. Longitudinal data also detects variability of Obstructive Sleep Apnea from night to night which is associated with hypertension
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Professor Danny Eckert of the Adelaide Sleep Institute at Flinders University didn’t set out to be one of the world’s foremost sleep experts. He started as an elite cyclist, representing Australia at the World Championships. Wanting to use his head as well as his body, he studied exercise physiology and sports science in the afternoons, trained on his mountain bike in the mornings, raced competitively, and presumably left some time for sleep. After receiving his degree, he was offered a prestigious appointment with the South Australia Sports Institute.
But on the Friday before he was due to start his internship, he was also offered a 3-year position with a respiratory and sleep unit in a hospital. When he reported for his new job at the Sports Institute on Monday, he immediately asked his new boss if he could take a walk to consider his options, came back, and left for a field he knew nothing about. “It turned out that everything I’d learned about the body being at its most vulnerable and physiologically interesting when you push it as hard as you can during exercise is also true when you are sleeping and the body is at its quietest.”
Professor Eckert was on fertile ground for his newly chosen field. Australia has long been a leader and innovator in sleep science, especially in respiratory medicine. When he started studying sleep apnea, the research centered on anatomy: the collapse of the upper airway, especially due to obesity. As such, treatments such as Continuous Positive Airway Pressure, (CPAP, invented in Australia), mouthguards, and surgery were designed to open the airway.
Professor Eckert’s groundbreaking work changed nearly everything we thought we knew about sleep apnea. Importantly, he identified three nonanatomical endotypes that can cause sleep apnea. Between them, they account for 70% of sleep apnea cases.
1) Low Arousal Threshold: Light sleepers who wake up when their muscles relax.
2) Instability in Breathing Control: Sleepers who are too sensitive to minor changes in carbon dioxide. Their overactive respiratory system turns off their drive to breathe.
3) Poor Muscle Responsiveness to the Narrowing Airway
Simplified, scalable diagnostic tools and machine learning can identify the endotype(s) that causes a particular patient’s sleep apnea. Endotypes can inform targeted therapies and lead to an 80% success rate for treating sleep apnea. This individualized, precision medicine approach includes emerging pharmaco-therapies, such as drugs that can activate the muscles, or strategies, such as cognitive behavioral therapy, that can help light sleepers.
What’s next? With 70 researchers working on 40-50 studies at any one time at the Adelaide Sleep Institute, there are many exciting developments to come. One area of interest is sleep irregularity. Researchers have found varying bedtime by even 30 minutes throughout the week is associated with a 30% higher chance of hypertension; vary by 90 minutes and increase the odds by 90%, regardless of the total amount of sleep.
New technologies that allow longitudinal data are especially useful for studying sleep variability. Combining sleep data with measures like body fat, step counts, and blood pressure will allow for quicker treatment changes, better monitoring of treatment effectiveness, and reach many more people who suffer from sleep disorders.
The three pillars of health are exercise, diet, and sleep, but sleep directly affects the other two. Not getting sufficient or quality sleep makes us crave bad food and makes it hard to exercise. That’s why Dr. Eckert believes sleep is the foundation for optimal health. Through research and scientific and technological breakthroughs, Professor Eckert thinks we are at the precipice of transforming the entire sleep field. That’s a comforting thought for the billions of people around the globe desperate for a good night’s sleep.
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[post_title] => From Bicycles to Sleep Cycles: How Professor Danny Eckert’s Pursuit of Peak Performance Led to Major Advances in our Understanding of Sleep
[post_excerpt] => Professor Danny Eckert of the Adelaide Sleep Institute at Flinders University didn’t set out to be one of the world’s foremost sleep experts, but he has changed nearly everything we know about sleep apnea.
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Several new, large-scale studies1, 2, 3, 4 from the Flinders Medical Research Institute (FHMRI) in Australia found studying sleep in real-world settings over multiple nights can greatly reduce the high 30% error rate of sleep apnea diagnosis from polysomnography (PSG), the traditional, single night, in hospital gold standard technique. Using Withings Sleep Analyzer, researchers were able to easily track multiple biomarkers for participants over time revealing large variability in sleep indicators from night to night.
Withings under-the-mattress sleep trackers have enabled researchers to study large groups over time. The FHMRI studies tracked 67,278 and 12,287 participants respectively over a total of 11 million nights, a feat not feasible with traditional polysomnography.
A key finding from the study of 12,000 users is the variability in the severity of Obstructive Sleep Apnea (OSA) from night to night. The variability of OSA, independent of severity, is associated with uncontrolled hypertension which is the leading cardiovascular risk factor. Sleep Analyzer also reveals other risks associated with hypertension, such as snoring, irregular waking and sleep hours, and duration of sleep.
Using the same hardware technology as Withings Sleep Analyzer, Sleep Rx is a noninvasive, at home device that users place under their mattresses to gather biomarkers such as heart rate, respiratory rate, snoring, sleep cycles, and the Withings Sleep Index, a measure of breathing events per hour, which can aid in the diagnosis of sleep apnea. Using this simple device for at least 14 nights gives a much clearer picture of sleep quality.
The multi-night Sleep Rx data can be used to predict the right patients at the right time for in hospital PSG. Better identification of patients who most need PSG will reduce overall spending on the costly tests and ease scheduling difficulties.
Sleep Rx offers an inexpensive, easy to use method to better target high risk cardiovascular patients, reduce the high error rate of sleep apnea diagnosis, and efficiently gather longitudinal, large-scale sleep data for a variety of chronic diseases. For more information about the Withings Sleep Rx, click here.
References
1 Lechat, Bastien et al. “Multinight Prevalence, Variability, and Diagnostic Misclassification of Obstructive Sleep Apnea.” American journal of respiratory and critical care medicine vol. 205,5 (2022): 563-569. doi:10.1164/rccm.202107-1761OC
2 Lechat, Bastien et al. “High night-to-night variability in sleep apnea severity is associated with uncontrolled hypertension.” NPJ digital medicine vol. 6,1 57. 30 Mar. 2023, doi:10.1038/s41746-023-00801-2
3 Lechat, Bastien et al. “Regular snoring is associated with uncontrolled hypertension.” NPJ digital medicine vol. 7,1 38. 17 Feb. 2024, doi:10.1038/s41746-024-01026-7
4 Scott, Hannah et al. “Sleep Irregularity Is Associated With Hypertension: Findings From Over 2 Million Nights With a Large Global Population Sample.” Hypertension (Dallas, Tex. : 1979) vol. 80,5 (2023): 1117-1126. doi:10.1161/HYPERTENSIONAHA.122.20513
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[post_title] => Sleep Apnea Data from Multiple Nights is Key to Predicting Hypertension and Cardiovascular Risk
[post_excerpt] => New large-scale, longitudinal studies show that monitoring sleep for at least 14 nights at home with a connected sleep tracking mat, can reduce the 30% high error rate of sleep apnea diagnosis from the usual single-night, in hospital polysomnography (PSG) technique. This technology can identify which patients most need expensive, intrusive, and difficult to access PSG. Longitudinal data also detects variability of Obstructive Sleep Apnea from night to night which is associated with hypertension
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The recent study, "Multinight Prevalence, Variability, and Diagnostic Misclassification of Obstructive Sleep Apnea" by Bastien Lechat and colleagues, sheds light on the limitations of single-night assessments in diagnosing obstructive sleep apnea (OSA).
OSA is a common sleep disorder in which breathing repeatedly stops and starts throughout the night. It's typically diagnosed using a sleep study that measures the apnea-hypopnea index (AHI)—the number of times per hour that a person experiences reduced or blocked airflow. Current clinical practice to diagnose OSA requires a single, overnight, in-laboratory or in-home polysomnography or polygraphy study.
The researchers looked at data from over 67,278 individuals aged 18 to 90 who had used the Withings sleep mat, a non-invasive, under-mattress sensor. In addition to the vast number of participants, the researchers were able to monitor an average of approximately 170 nights of data per participant between July 2020 and March 2021. This extensive data collection resulted in more than 11.6 million nights of sleep data–the largest standardized, objective assessment of OSA collected to date.
The study found that the global prevalence of moderate to severe OSA, defined as a nightly mean apnea-hypopnea index (AHI) of more than 15 events per hour, was 22.6% (95% confidence interval: 20.9–24.3%). Notably, the research highlighted significant night-to-night variability in OSA severity. When relying on a single night's data, the likelihood of misdiagnosis ranged from approximately 20% and up to 50% for those with mild to moderate OSA. Increasing the number of monitoring nights improved diagnostic accuracy, with misdiagnosis error rates decreasing and stabilizing after 14 nights of monitoring.
The substantial variability of OSA suggests that single-night assessments may not provide a comprehensive picture of an individual's sleep patterns, leading to possible misclassifications. However, fourteen nights of polysomnography in a sleep lab or clinic is not feasible. Tools like the Withings sleep mat offer a non-invasive, cost-effective means of multinight in-home monitoring leading to more accurate and reliable diagnosis of OSA. By offering an accessible way to capture more nights of sleep data, clinicians can reduce misdiagnosis and create a shift in how sleep disorders are screened for and tracked.
References
- Lechat, Bastien et al. “Multinight Prevalence, Variability, and Diagnostic Misclassification of Obstructive Sleep Apnea.” American journal of respiratory and critical care medicine vol. 205,5 (2022): 563-569. doi:10.1164/rccm.202107-1761OC
Interested in partnering with us?
Contact Us
[post_title] => A Single-Night Sleep Study Can Misdiagnose Sleep Apnea Up to Half the Time
[post_excerpt] => New large-scale, longitudinal studies show that monitoring sleep for at least 14 nights at home with a connected sleep tracking mat, can reduce the 30% high error rate of sleep apnea diagnosis from the usual single-night, in hospital polysomnography (PSG) technique. This technology can identify which patients most need expensive, intrusive, and difficult to access PSG. Longitudinal data also detects variability of Obstructive Sleep Apnea from night to night which is associated with hypertension
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