Researchers develop novel, automated measure of sleep studies to determine severity of obstructive sleep apnea

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New method can predict risks of cardiovascular disease, mortality in sleep apnea patients.

Mount Sinai researchers have developed a novel, automated measure of analyzing sleep studies to determine the severity and risk of mortality in patients with obstructive sleep apnea, a chronic sleep disorder that affects about 30 million people in the United States.

The primary diagnosis tool for obstructive sleep apnea is the Apnea-Hypopnea Index , which tells the average number of times per hour that breathing either partially or fully stops during sleep. However, this widely used standard only captures the rate of respiratory events and does not predict potential subsequent risks.

They found that the automated measure of ventilatory burden was able to effectively assess the severity of obstructive sleep apnea, remain stable from one night to another, and predict mortality associated with cardiovascular diseases in patients, making it a viable alternative to AHI.

 

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