Reena Mehra, MD: Exploring Endophenotypes for Predicting Clinical Sleep Outcomes
“How can we use these data to harness the power it has to do a better job of predicting clinical outcomes and looking at treatment responsiveness?” Dr. Reena Mehra asks.
Endophenotypes derived from sleep studies hold immense potential for predicting clinical outcomes, including conditions like atrial fibrillation, Reena Mehra, MD, MS, director, professor of medicine, at the Sleep Disorders Center, Cleveland Clinic, explained in an interview at SLEEP 2023.
“In sleep studies, we collect a wealth of information on physiology and we use a very cursory amount of that information clinically,” she said.
Among the studies presented by investigators from the Cleveland Clinic, data from a review of 170,000 sleep studies from the institution’s registries were featured at the conference. The study assessed the relationship between sleep apnea and atrial fibrillation (AF) and identified the significant role of hypoxia.
“The idea is that the sleep studies house a wealth of data and information in terms of physiologic signals from the brain, the heart, the lungs, the breathing, and even muscle,” Mehra said. “How can we use these data to harness the power it has to do a better job of predicting clinical outcomes and looking at treatment responsiveness?”
The Cleveland Clinic received a Discovery Accelerator Award and is currently working with IBM to further examine how different facets of sleep apnea pathophysiology contribute to AF and other clinical outcomes.
“(The award) will allow us to collaborate with them and do some signal processing analyses, apply machine learning algorithms in a more refined way, to really get at the degree of hypoxia, heart rate arousal response, other EEG arousals and fragmentation of sleep, and potentially-associated sympathetic activation,” Mehra said.
