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Residual Events during Use of CPAP: Prevalence, Predictors, and Detection Accuracy

Authors :
Robert Thomas
Joel Reiter
Pankaj Mehta
Bashar Zleik
Mihaela H. Bazalakova
Source :
Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine. 12(8)
Publication Year :
2015

Abstract

To assess the frequency, severity, and determinants of residual respiratory events during continuous positive airway therapy (CPAP) for obstructive sleep apnea (OSA) as determined by device output.Subjects were consecutive OSA patients at an American Academy of Sleep Medicine accredited multidisciplinary sleep center. Inclusion criteria included CPAP use for a minimum of 3 months, and a minimum nightly use of 4 hours. Compliance metrics and waveform data from 217 subjects were analyzed retrospectively. Events were scored manually when there was a clear reduction of amplitude (≥ 30%) or flow-limitation with 2-3 larger recovery breaths. Automatically detected versus manually scored events were subjected to statistical analyses included Bland-Altman plots, correlation coefficients, and logistic regression exploring predictors of residual events.The mean patient age was 54.7 ± 14.2 years; 63% were males. All patients had a primary diagnosis of obstructive sleep apnea, 26% defined as complex sleep apnea. Residual flow measurement based apnea-hypopnea index (AHIFLOW)5, 10, and 15/h was seen in 32.3%, 9.7%, and 1.8% vs. 60.8%, 23%, and 7.8% of subjects based on automated vs. manual scoring of waveform data. Automatically detected versus manually scored average AHIFLOW was 4.4 ± 3.8 vs. 7.3 ± 5.1 per hour. In a logistic regression analysis, the only predictors for a manual AHIFLOW5/h were the absolute central apnea index (CAI), (odds ratio [OR]: 1.5, p: 0.01, CI: 1.1-2.0), or using a CAI threshold of 5/h of sleep (OR: 5.0, p:0.001, CI: 2.2-13.8). For AHIFLOW10/h, the OR was 1.14, p: 0.03 (CI: 1.1-1.3) per every CAI unit of 1/hour.Residual respiratory events are common during CPAP treatment, may be missed by automated device detection and predicted by a high central apnea index on the baseline diagnostic study. Direct visualization of flow data is generally available and improves detection.

Details

ISSN :
15509397
Volume :
12
Issue :
8
Database :
OpenAIRE
Journal :
Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
Accession number :
edsair.doi.dedup.....4e74a770d21631a1bfe609995f8e762e