Sleep disorders might now be treated with AI

Artificial intelligence can improve the precision of sleep medicines, resulting in more patient-centered care and better outcomes, suggest a new study.

The position statement of the study was published in the journal - Journal of Clinical Sleep Medicine.

The position statement was developed by the AASM's Artificial Intelligence in Sleep Medicine Committee.

According to the statement, the electrophysiological data collected during polysomnography -- the most comprehensive type of sleep study -- is well-positioned for enhanced analysis through AI and machine-assisted learning.

"When we typically think of AI in sleep medicine, the obvious use case is for the scoring of sleep and associated events," said the lead researcher Dr Cathy Goldstein.

"This would streamline the processes of sleep laboratories and free up sleep technologist time for direct patient care," she added.

Because of the vast amounts of data collected by sleep centres, AI and machine learning could advance sleep care, resulting in more accurate diagnoses, prediction of disease and treatment prognosis, characterization of disease subtypes, precision in sleep scoring, and optimization and personalization of sleep treatments.

Goldstein noted that AI could be used to automate sleep scoring while identifying additional insights from sleep data.

"AI could allow us to derive more meaningful information from sleep studies, given that our current summary metrics, for example, the apnea-hypopnea index, aren't predictive of the health and quality of life outcomes that are important to patients," Dr Cathy Goldstein said.

"Additionally, AI might help us understand mechanisms underlying obstructive sleep apnea, so we can select the right treatment for the right patient at the right time, as opposed to one-size-fits-all or trial and error approaches," she added.

Important considerations for the integration of AI into the sleep medicine practice include transparency and disclosure, testing on novel data, and laboratory integration.

The statement recommends that manufacturers disclose the intended population and goal of any program used in the evaluation of patients; test programs intended for clinical use on independent data; and aid sleep centres in the evaluation of AI-based software performance.

"AI tools hold great promise for medicine in general, but there has also been a great deal of hype, exaggerated claims and misinformation," said Goldstein.

"We want to interface with industry in a way that will foster safe and efficacious use of AI software to benefit our patients. These tools can only benefit patients if used with careful oversight," Goldstein added.

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Sleep-disordered breathing linked to age acceleration

Increase in the severity of sleep-disordered breathing and sleep disruption are associated with epigenetic age acceleration, recent findings suggest.

The study shows that each standard deviation increase in the apnea-hypopnea index, a measure of sleep-disordered breathing severity, was associated with the equivalent of 215 days of biological age acceleration. Similarly, each standard deviation increase in the arousal index, a measure of sleep disruption, was associated with the equivalent of 321 days of age acceleration.

“People’s biological age might not be the same as their chronological age. Individuals, whose biological age is higher than their chronological age, exhibit age acceleration or fast ageing. In our study, we found that more severe sleep-disordered breathing is associated with epigenetic age acceleration. Our data provide biological evidence supporting adverse physiological and health effects of untreated sleep-disordered breathing,” said the lead author. 

Sleep-disordered breathing, such as obstructive sleep apnea, is characterized by abnormalities of respiration during sleep. Episodes often result in reductions in blood oxygen saturation and are usually terminated by brief arousals from sleep. Nearly 30 million adults in the US have obstructive sleep apnea. Common warning signs include snoring and excessive daytime sleepiness.

According to the authors, epigenetic age acceleration is a DNA methylation-based marker of fast biological ageing, and it is associated with modifiable lifestyle factors. Although sleep-disordered breathing is associated with multiple age-related health disorders, its relationship with epigenetic ageing has not been well studied.

Another surprising finding was that the associations were stronger in women than in men, suggesting that women may be particularly vulnerable to the adverse effects of sleep-disordered breathing.

“While women are often considered to be at lower risk for health outcomes related to sleep-disordered breathing, our findings suggest increased biological susceptibility,” said the author.  

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New study confirms link between sleep apnea and diabetes

A new study of more than 8,500 Canadian patients has demonstrated a link between obstructive sleep apnea (OSA) and the development of diabetes.

It confirms earlier evidence of such a relationship from smaller studies with shorter follow-up periods.

"Our study, with a larger sample size and a median follow-up of 67 months was able to address some of the limitations of earlier studies on the connection between OSA and diabetes," lead author Tetyana Kendzerska, said.

"We found that among patients with OSA, the initial severity of the disease predicted the subsequent risk for incident diabetes," Kendzerska said.

The study included 8,678 adults with suspected OSA without diabetes at baseline who underwent a diagnostic sleep study between 1994 and 2010 and were followed through May 2011 using provincial health administrative data to examine the occurrence of diabetes.

Sleep apnea severity was assessed with the apnea-hypopnea index (AHI), which indicates severity based on the number of apneas (complete cessation of airflow) and hypopneas (partial cessation of airflow) per hour of sleep. Patients were classified as not having OSA, or having mild, moderate or severe OSA.

During follow-up, 1,017 (11.7 percent) patients developed diabetes.

In analyses adjusting for known risk factors for diabetes, including age, sex, body mass index, neck circumference, smoking, income status and comorbidities at baseline, patients with an AHI greater than 30 had a 30 percent higher risk of developing diabetes than those with an AHI less than 5.
Patients with mild or moderate OSA had a 23 percent increased risk of developing diabetes.

Other risk factors for diabetes included AHI during rapid eye movement sleep and measures of the physiologic consequences of OSA, including oxygen desaturation, sleep deprivation and activation of the sympathetic nervous system, as indicated by a higher mean heart rate during sleep.

The findings were published online ahead of print publication in the American Thoracic Society's American Journal of Respiratory and Critical Care Medicine.

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