Untreated obstructive sleep apnea (OSA) is associated with adverse outcomes in patients with coronary artery disease (CAD). Continuous positive airway pressure (CPAP) is the most common treatment, but despite interventions addressing established adherence determinants, CPAP use remains poor.
To determine whether physiological traits that cause OSA are associated with long-term CPAP adherence in patients with CAD.
Participants in the RICCADSA trial with objective CPAP adherence (hours/night) over 2 years and analyzable raw polysomnography data were included (n=249). The physiological traits -loop gain, arousal threshold (ArTH), collapsibility and muscle compensation- were measured from polysomnography. Linear mixed models assessed the relationship between the traits and adherence. We also compared actual CPAP adherence between physiology-predicted “poor” (lowest quartile of predicted adherence) and “good” (all others) adherers.
Median (IQR) CPAP use declined from 3.2 (1.0, 5.8) to 3.0 (0.0, 5.6) hours/night over 24-mo (p<0.001). In analyses adjusted for demographics, anthropometrics, OSA characteristics and clinical comorbidities, lower ArTH was associated with worse CPAP adherence (0.7 hours/SD ArTH, p=0.021). Both high and low muscle compensation were associated with lower adherence (p=0.008). Predicted "poor" adherers exhibited markedly lower CPAP use compared to "good" adherers for up to 2 years of follow-up (group differences: 2.0 to 3.2 hours/night, p<0.003 for all).
A low ArTH as well as a very low and high muscle compensation are associated with worse long-term CPAP adherence in patients with CAD and OSA. Physiological traits, alongside established determinants, may help predict and improve CPAP adherence.