Abstract 19050: Polysomnography and Sleep Symptom-Based Patient Profiles Associated With Atrial Fibrillation Development

Abstract

Introduction: Although sleep disorders are linked to atrial fibrillation (AF), the complex interplay remains unclear. Investigating sleep-based profiles associated with AF can deepen understanding and identify at-risk patients. Hypothesis: We hypothesized discrete phenotypes of symptoms and polysomnography (PSG)-based data differ in relation to incident AF. Methods: This retrospective cohort study of Cleveland Clinic patients (age>18) who underwent PSG 11/27/2004-12/30/2015 identified patient clusters using latent class analysis of 23 sleep-related symptoms, Epworth Sleepiness Scale (ESS) score, and 24 PSG measures of sleep disordered breathing and architecture. Cox proportional hazards models with cluster membership as the independent variable and incident AF as the dependent variable were adjusted for age, sex, race, BMI, cardiopulmonary disease and risk factors, anti-arrhythmic medication, and positive airway pressure with follow up 7.6±3.4 years. Results: Of the sample (n=43,433, age 52±15, 52% male, 74% White) 9% developed AF. Five clusters were identified: 1) Hypoxic + Sleepy (n=3,245): highest % time SaO 2 below 90%, highest ESS, 2) Apneas + Arousals (n=4,592): highest AHI, highest arousal index, 3) Short sleep + Low %REM (n=6,126): shortest sleep duration, longest REM latency, lowest %REM, 4) Hypopneas (n=2,661): most hypopneas, 5) Long sleep + High %REM (n=26,809): longest sleep duration, shortest REM latency, highest %REM (reference). Compared to reference, Hypoxic + Sleepy had 48% (HR=1.48, 95%CI=1.34-1.64), Apneas + Arousals had 22% (HR=1.22, 95%CI=1.11-1.35), and Short Sleep + Low %REM had 11% (HR=1.11, 95%CI=1.01-1.22) higher risk of AF development. Internal validation indicated reasonable predictive accuracy. Sensitivity analysis excluding split night studies confirmed the associations observed. Conclusions: Of 5 patient profiles identified, Hypoxic + Sleepy conferred the strongest AF risk. Consistent with prior evidence of hypoxia as an AF driver and cardiovascular risk of the sleepy phenotype, this constellation of symptoms and physiology illustrates risk in the clinical setting, providing potential value as a risk prediction tool. Future investigation will focus on external validation of these findings.