acePrediction of cardiovascular outcomes using electrocardiography from overnight polysomnography
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 to single-lead ECGs from PSG, combined with sleep stage data, to predict 10-year risk of atrial fibrillation (AF), stroke…
A neural network applied to single-lead ECGs already recorded during sleep studies, plus sleep stage data, was strongly associated with long-term risk of atrial fibrillation, stroke, heart attack, heart failure and death.
Outcomes were derived from electronic health record diagnosis codes, and the supplied text does not report effect sizes or performance metrics, so real-world clinical utility is not established here.
Evidence
- Peer-reviewedSLEEP2026-10-09
How should this claim be treated?
Truvace Impact Record TRV-2026-1591, v1: “Prediction of cardiovascular outcomes using electrocardiography from overnight polysomnography.” Truvace, 2026-10-16. /record/TRV-2026-1591 (accessed at citation time). sha256 dc96f7ce1841541c…
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