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

Abstract

Study objectives: 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.

Methods: 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.

Results: 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 AHIFLOW > 5/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 AHIFLOW > 10/h, the OR was 1.14, p: 0.03 (CI: 1.1-1.3) per every CAI unit of 1/hour.

Conclusions: 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.

Keywords: auto-CPAP; residual apnea; sleep.

Figure 1. Snapshot from the EncoreAnywhere database, generated from high resolution flow (“waveform”) data.

Each horizontal line is 6 minutes long. The red line is the pressure output, with a treatment auto-CPAP range set at 10–15 cm H₂O in this 46-year-old male, without heart failure, but severe periodic breathing and obstructions on the baseline assessment. Increasing or narrowing the pressure range of the auto-CPAP had minimal effect on the residual device-detected respiratory event indices. Highlighted in green is machine detected periodic breathing; green bars represent machine-detected obstructive apneas, yellow bars designate “vibratory snoring.” Note large numbers of missed overt severe hypopneas/apneas (arrows) and periodic breathing with relatively short (approximately 20 seconds) cycle length.

Figure 2. Snapshot from the EncoreAnywhere database, generated from high-resolution flow (“waveform”) data.

Same patient as in Figure 1, a period of stable breathing, showing the contrast and relative ease of visual recognition of stable breathing periods (with flow limitation in this instance) and periods with respiratory events. VS is machine estimated vibratory snoring.