High Risk Characteristics for Recurrent Cardiovascular Events among Patients with Obstructive Sleep Apnoea in the SAVE Study

Abstract

Background: Obstructive sleep apnoea (OSA) is a common comorbidity in patients with cardiovascular (CV) disease. We aimed to identify specific OSA clinical phenotypes relating to risks of serious CV events and response to continuous positive airway pressure (CPAP) treatment. Methods: Post-hoc analyses of the Sleep Apnea Cardiovascular Endpoints (SAVE) study in participants with moderate-to-severe OSA and coronary artery disease (CAD) and/or cerebrovascular disease (CeVD) randomised to CPAP plus usual care or usual care alone. Latent class analysis (LCA) was used to identify OSA clinical phenotypes among 2649 (out of 2687 total) patients with complete data on 19 patient-centered variables, supported by Bayesian information criteria and clinical interpretability. Cox regression models were used to evaluate risks of composite cardiac and stroke outcome events in phenotype groups. Preferential response to CPAP treatment was evaluated using interaction terms as well as the Chi-square test. Findings: LCA identified four OSA clinical phenotypes: CAD alone and with diabetes mellitus (CAD+DM), and CeVD alone and with DM (CeVD+DM), in 39%, 15%, 37% and 9% of participants, respectively. The rates of composite CV events were the highest in CAD+DM phenotype (HR 2.08, 95% CI 1.57–2.76) and for stroke were highest in CeVD+DM phenotype (HR 6.84, 95% CI 3.77–12.42). Adherence to CPAP treatment (nil or <4 h vs ≥4 h in the first two years of the study) was shown to influence the risk of composite CV outcome in the phenotypes (P-interaction = 0.04); CPAP adherent patients of the CeVD+DM phenotype had the lowest risk of CV outcome (P = 0.02). Interpretation: High risk clinical phenotypes were identified in relation to CV events and response to CPAP treatment, which may allow improved targeting of therapies in OSA patients. Funding: The National Health and Medical Research Council (NHMRC) of Australia, Fisher & Paykel Healthcare, and ResMed. Keywords: Obstructive sleep apnoea, Phenotype, Cardiovascular disease, Stroke, Latent class analysis