Excessive Daytime Sleepiness Independently Predicts Increased Cardiovascular Risk After Myocardial Infarction

Background-Excessive daytime sleepiness (EDS), a common symptom among patients with sleep-disordered breathing, is closely associated with the development of cardiovascular diseases, but its long-term prognostic value is not completely understood. The aim of this study was to investigate whether EDS would be an independent prognostic factor after myocardial infarction. Methods and Results-We prospectively recruited 112 post-myocardial infarction patients. The Epworth Sleepiness Scale was completed before polysomnography, and EDS was defined as a score >= 11. After exclusion of 8 patients who accepted treatment with continuous positive airway pressure, 104 patients were followed up for 48 months. The primary composite end point was major adverse cardiac events. Patients with EDS had higher rates of major adverse cardiac events (48.4% versus 27.4%, chi(2) =5.27, P=0.022) and reinfarction (29.0% versus 5.5%, chi(2)=13.51, P=0.0002) compared with those without EDS. In the Cox proportional hazards model, patients with EDS had 2.15 times (95% confidence interval, 1.08-4.18; P=0.030) higher crude risk of major adverse cardiac events, with prognostic significance persisting after adjusting for age, diabetes mellitus, depression, left ventricular ejection fraction, apnea-hypopnea index, and nocturnal nadir oxygen saturation (hazard ratio: 2.13, 95% confidence interval, 1.04-4.26, P=0.039). Furthermore, among participants with moderate to severe sleep-disordered breathing, the presence of EDS was associated with higher risk of major adverse cardiac events than those without EDS, after adjusting for age and nadir oxygen saturation (hazard ratio: 3.17, 95% confidence interval, 1.22-7.76, P=0.019). Conclusions-EDS may be an independent prognostic factor of adverse outcome in post-myocardial infarction patients with moderate to severe sleep-disordered breathing. Evaluation of EDS may shed new light on risk stratification and identify treatment responders for this patient population.