Researchers use grant to ID risk for cardiovascular disease in OSA patients 

NEW YORK – Mount Sinai researchers have received a $3 million grant from the National Institutes of Health to develop and study AI-powered models to identify the risk of cardiovascular disease events in patients with obstructive sleep apnea. Researchers will use machine-learning techniques on comprehensive multi-modal datasets to identify patients at enhanced risk for buildup of fats and cholesterol in the artery walls, and heightened risk for cardiovascular events such as heart attack and stroke. They said the approach will also predict the cardiovascular treatment effectiveness of CPAP therapy for patients with OSA who scored as “non-sleepy” on a standard clinical test, helping to identify patients who would benefit most from using CPAP and those who should avoid it. The foundation of this work is the team’s recently published study revealing the potential harm of CPAP therapy to non-sleepy patients with OSA and acute coronary syndrome. Those findings underscored the importance of identifying OSA patients who could benefit from CPAP and steering the team toward more personalized treatment strategies. “We are inspired by the transformative potential of machine learning techniques in health care, particularly in analyzing vast amounts of complex data to personalize treatment strategies,” said Dr. Girish Nadkarni, MPH, Irene and Dr. Arthur M. Fishberg professor of medicine, director of The Charles Bronfman Institute of Personalized Medicine, and system chief of Data-Driven and Digital Medicine at Icahn Mount Sinai. “Our study has the potential to revolutionize the management of obstructive sleep apnea by offering decision support tools that optimize treatment plans, improve patient outcomes, and reduce the burden of sleep apnea-related cardiovascular disease events on both individuals and health care systems.” The researchers will use data from two cohorts: the Multi-Ethnic Study of Atherosclerosis (MESA) cohort of more than 6,000 ethnically diverse, generally healthy non-sleepy participants, and the Sleep Apnea Cardiovascular Endpoints (SAVE) randomized clinical trial of more than 2,500 non-sleepy participants with moderate to severe obstructive sleep apnea and established cardiovascular disease. They will use these datasets to identify key variables that predict atherosclerosis progression and cardiovascular events, and to identify subgroups with differential treatment effects with CPAP for events based on demographics or risk characteristics, as well as validation of the models within the Mount Sinai Health System, using clinical data from the electronic health record.