Aykut Cilli1, Rusen Uzun, Ugur Bilge. 1. Department of Biostatistics and Medical Informatics, Akdeniz University, Antalya, Turkey. acilli@akdeniz.edu.tr
Abstract
PURPOSE: Autotitrating continuous positive airway pressure (auto-CPAP) devices not only titrate CPAP pressures but also measure residual respiratory events. The aim of the present study was to determine the accuracy of auto-CPAP-derived residual apnea-hypopnea index (AHI). METHODS: We studied 137 consecutive patients (72.3% men) with obstructive sleep apnea from January 2008 to December 2010 who underwent in-laboratory overnight polysomnography (PSG) using auto-CPAP. We excluded patients with comorbidities like congestive heart disease, chronic obstructive pulmonary disease, or hypoventilation syndromes and patients with central sleep apnea. Residual AHI obtained from the auto-CPAP device by smart card (CPAP-AHI) was compared simultaneously with AHI from an overnight PSG on auto-CPAP (PSG-AHI) using Bland-Altman analysis and Wilcoxon signed-rank test. RESULTS: The mean AHI on the diagnostic study was 45.08 ± 1.8. During the titration, auto-CPAP markedly suppressed the respiratory events (PSG-AHI, 3.40 ± 0.20). On the other hand, CPAP-AHI was 3.35 ± 0.17. Bland-Altman analysis showed good agreement between auto-CPAP-AHI and PSG-AHI (AHI mean difference of 0.05, and the limits of agreement for the AHI were from +4.9 to -4.8). Two methods have also been compared with paired samples t test and no statistically significant difference was found (p > 0.05). CONCLUSION: Auto-CPAP can identify residual respiratory events equivalent to the use of PSG in a selected population.
PURPOSE: Autotitrating continuous positive airway pressure (auto-CPAP) devices not only titrate CPAP pressures but also measure residual respiratory events. The aim of the present study was to determine the accuracy of auto-CPAP-derived residual apnea-hypopnea index (AHI). METHODS: We studied 137 consecutive patients (72.3% men) with obstructive sleep apnea from January 2008 to December 2010 who underwent in-laboratory overnight polysomnography (PSG) using auto-CPAP. We excluded patients with comorbidities like congestive heart disease, chronic obstructive pulmonary disease, or hypoventilation syndromes and patients with central sleep apnea. Residual AHI obtained from the auto-CPAP device by smart card (CPAP-AHI) was compared simultaneously with AHI from an overnight PSG on auto-CPAP (PSG-AHI) using Bland-Altman analysis and Wilcoxon signed-rank test. RESULTS: The mean AHI on the diagnostic study was 45.08 ± 1.8. During the titration, auto-CPAP markedly suppressed the respiratory events (PSG-AHI, 3.40 ± 0.20). On the other hand, CPAP-AHI was 3.35 ± 0.17. Bland-Altman analysis showed good agreement between auto-CPAP-AHI and PSG-AHI (AHI mean difference of 0.05, and the limits of agreement for the AHI were from +4.9 to -4.8). Two methods have also been compared with paired samples t test and no statistically significant difference was found (p > 0.05). CONCLUSION: Auto-CPAP can identify residual respiratory events equivalent to the use of PSG in a selected population.
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