Implantable cardioverter-defibrillator–computed respiratory disturbance index accurately identifies severe sleep apnea: The DASAP-HF study

Background Sleep apnea (SA) is a relevant issue in the management of patients with heart failure for risk stratification and for implementing treatment strategies. Objective The purpose of this study was to evaluate in patients with implantable cardioverter-defibrillators (ICDs) the performance of the respiratory disturbance index (RDI) computed by the ApneaScan algorithm (Boston Scientific Inc., Natick, MA) as a discriminator of severe SA. Methods ICD-indicated patients with left ventricular ejection fraction ≤35% were enrolled. One month after implantation, patients underwent a polysomnographic study. We evaluated the accuracy of the RDI for the prediction of severe SA (apnea-hypopnea index [AHI] ≥30 episodes/h) and the agreement between RDI and AHI during the sleep study night. Results Two hundred sixty-five patients were enrolled to obtain the required sample of 173 patients with AHI and RDI data for analysis. The mean AHI was 21 ± 15 episodes/h and severe SA was diagnosed in 38 patients (22%), while the mean RDI was 33 ± 13 episodes/h. On the basis of the receiver operating characteristic curve analysis of RDI values, the area under the curve was 0.77 (95% confidence interval [CI] 0.70–0.83; P < .001). At an RDI value of 31 episodes/h, severe SA was detected with 87% (95% CI 72%–96%) sensitivity and 56% (95% CI 48%–66%) specificity. RDI closely correlated with AHI recorded during the same night (r = 0.74; 95% CI 0.57–0.84; P < .001), and the Bland-Altman agreement analysis revealed a bias of 11 episodes/h, with limits of agreement being −10 to 32 episodes/h. Conclusion The RDI accurately identified severe SA and demonstrated good agreement with AHI. Therefore, it may serve as an efficient tool for screening patients at risk of SA