Accuracy of residual respiratory event detection by CPAPs: a meta-analysis

Most continuous positive airway pressure (CPAP) machines have built-in manufacturer-specific proprietary algorithms for automatic respiratory event detection (AED) based on very specific respiratory events scoring criteria. With regards to the accuracy of these data from CPAP machines, evidence from the literature seems conflicting, which formed the basis for this meta-analysis.

A meta-analysis was performed on studies that reported Bland-Altman analysis data on agreement (mean bias and limits of agreement [LoA]) of CPAP-determined apnea-hypopnea index (AHI) at therapeutic pressures (AHI_FLOW) with that determined from simultaneously conducted polysomnograms (AHI_PSG).

In six studies, ResMed CPAPs were used, and in another six studies, Respironics CPAPs were used, while only one study used Fisher & Paykel (F&P) CPAPs. The pooled mean AHI bias from ResMed CPAP studies was − 1.01 with pooled LoAs from − 3.55 to 1.54 (I² = 17.5%), and from Respironics CPAP studies, pooled mean AHI bias was − 0.59 with pooled LoAs from − 3.22 to 2.05 (I² = 0%). Pooled percentage errors (corresponding to LoAs) from four ResMed CPAP studies, four Respironics CPAP studies, and the F&P CPAP study were 73%, 59%, and 112%, respectively. A review of the literature for this meta-analysis also revealed lack of uniformity not only in the CPAP manufacturers’ respiratory events scoring criteria but also in that used for PSGs across the studies analyzed.

Even though the pooled results of mean AHI bias suggest good clinical agreement between AHI_PSG and AHI_FLOW, percentage errors calculated in this meta-analysis indicate the possibility of a significant degree of imprecision in the estimation of AHI_FLOW by CPAP machines.