Antonio D'Onofrio1, Maria Teresa La Rovere2, Michele Emdin3, Alessandro Capucci4, Gianfranco Sinagra5, Valter Bianchi1, Ennio C L Pisanò6, Paolo Pieragnoli7, Maurizio Tespili8, Mario Luzi4, Antonello Talarico9, Massimo Zecchin5, Antonio Rapacciuolo10, Marcello Piacenti11, Ciro Indolfi12, Miguel Angel Arias13, Igor Diemberger14, Catia Checchinato15, Giuseppe Boriani16, Luigi Padeletti17. 1. Ospedale Monaldi, Naples, Italy. 2. Fondazione 'Salvatore Maugeri', IRCCS, Istituto Scientifico di Montescano, Montescano (PV), Italy. 3. Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy; Fondazione Toscana Gabriele Monasterio, Pisa, Italy. 4. Università Politecnica delle Marche, Ancona, Italy. 5. University of Trieste, Trieste, Italy. 6. Vito Fazzi Hospital, Lecce, Italy. 7. University of Florence, Florence, Italy. 8. "Bolognini" Hospital, Seriate (BG), Italy. 9. Ospedale SS. Annunziata, Cosenza, Italy. 10. Federico II University, Naples, Italy. 11. Fondazione Toscana Gabriele Monasterio, Pisa, Italy. 12. "Magna Graecia" University, Catanzaro, Italy. 13. Hospital Virgen de la Salud, Toledo, Spain. 14. University of Bologna, Policlinico S.Orsola-Malpighi, Bologna, Italy. 15. Ospedale Santa Croce, Moncalieri (TO), Italy. 16. University of Modena and Reggio Emilia, Modena, Italy. 17. IRCCS MultiMedica, Sesto San Giovanni, Milan, Italy. Electronic address: lpadeletti@interfree.it.
Abstract
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.
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.