Mount Sinai 'poised to shift paradigm’ on sleep testing, therapy 

NEW YORK – Mount Sinai researchers have been awarded a five-year, $4.1 million grant from the National Heart, Lung and Blood Institute at the National Institutes of Health to develop and study an artificial intelligence-powered model that predicts adverse outcomes of obstructive sleep apnea. Researchers say their model will better reflect the underlying physiology of the condition and the ways it impairs sleep, improving patient care and treatment. “Our proposal uses a state-of-the-art, artificial intelligence model that risk-profiles sleep apnea patients using data from routine sleep studies,” said principal investigator Ankit Parekh, PhD, director of the Sleep And Circadian Analysis (SCAN) Group and assistant professor of medicine (pulmonary, critical care and sleep medicine) at the Icahn School of Medicine at Mount Sinai. “Our study will assess the real-world performance of an AI approach and offer crucial evidence needed to translate metrics that go beyond the apnea-hypopnea in assessing severity of obstructive sleep apnea into clinical practice. Achieving this would leave us poised to shift the paradigm in clinical management of obstructive sleep apnea.” Researchers at Mount Sinai have developed an AI-powered approach that examines the sleep functions apnea is known to impair—breathing, oxygen levels and sleep stages—and combines these categories into a probability score that predicts the risk of short- and long-term outcomes of the disorder. They say preliminary data from three cohorts of nearly 11,000 participants suggests the machine-learning model could predict the probability of sleepiness due to apnea with an accuracy of about 87%. In contrast, the model using the existing apnea hypopnea index predicted sleepiness at about 54% precision.