Health AI Central
Peer-Reviewed Publication
Sleep2026October 9, 2026Journal Article

Prediction of cardiovascular outcomes using electrocardiography from overnight polysomnography.

Zuzana Koscova1, Samaneh Nasiri1, Matthew A Reyna1, Neal K Bhatia2, Ali Bahrami Rad1, Reza Sameni1,3, Haoqi Sun4, Niels Turley4, Umakanth Katwa5, Dennis Hwang6, Katie L Stone7, Lynn M Trotti8, Robert J Thomas9, Emmanuel Mignot10, Brandon M Westover4, Gari D Clifford1,3
1Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA, United States.
2Division of Cardiovascular Medicine, School of Medicine, Emory University, Atlanta, GA, United States.
3Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, United States.
4Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, United States.
5Boston Children's Hospital, Department of Internal Medicine, Boston, MA, United States.
6Kaiser Permanente San Bernardino County, Sleep Disorders Center, San Bernardino, CA, United States.
7Sutter Health/California Pacific Medical Center, Center for Aging Science, San Francisco, CA, United States.
8Department of Neurology and Emory Sleep Center, School of Medicine, Emory University, Atlanta, GA, United States.
9Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States.
10Howard Hughes Medical Institute, Stanford University, Palo Alto, CA, United States.
PubMed DOI

Abstract

STUDY OBJECTIVES: Polysomnography (PSG) is the gold standard for diagnosing sleep disorders, which are recognized as cardiovascular risk factors. Single-lead electrocardiograms (ECGs) are recorded during PSG but rarely analyzed, presenting an opportunity to leverage overnight ECGs for cardiovascular risk prediction. MATERIALS AND METHODS: We applied a deep residual neural network with attention t…

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