Abstract

BackgroundSleep-disordered breathing (SDB) is common among pulmonary arterial hypertension (PAH) patients and has been associated with unfavorable outcomes. This study aims to cluster overnight cardiorespiratory signals to investigate PAH phenotypes and examining their prognostic implications. MethodsIn this retrospective cohort study, we recruited consecutive PAH patients who underwent right heart catheterization and nocturnal cardiorespiratory polygraphy to evaluate SDB. Cluster analysis was employed to classify patients based on their SDB patterns. Cox regression analysis and Kaplan-Meier curves were utilized to assess the association between cluster membership and clinical outcomes. Logistic regression was used to identify risk factors associated with the cluster at higher risk of adverse outcomes. ResultsThe study comprised 386 PAH patients, with a mean age of 44.7 ± 17.0 years, of which 46.6 % were male. Three distinct clusters of PAH patients were identified: Cluster 1 (N = 182) presented with minimal SDB, Cluster 2 (N = 125) displayed obstructive sleep apnea (OSA) without significant hypoxemia, and Cluster 3 (N = 79) exhibited predominantly severe hypoxemic burden along with comorbid OSA. Notably, patients in Cluster 3 had an independent association with an increased risk of clinical worsening (hazard ratio 1.96, 95 % confidence interval [CI] 1.08–3.56, P = 0.027) compared to those in Clusters 1, even after adjusting for common confounders. The rate of clinical worsening for PAH-related events and mortality was higher in Cluster 3 than in Clusters 1 and 2 (26.6 % vs. 12.6 % and 19.2 %, respectively, log-rank P = 0.024). Moreover, the left ventricular mass index was identified as an independent risk factor for Cluster 3 (odds ratios 1.01, 95 % CI 1.00–1.02, P = 0.004). ConclusionsPatients with PAH who have nocturnal hypoxemia and OSA had worse clinical outcomes compared to those with only minimal SDB. Tailored management strategies that address both PAH and nocturnal hypoxemia may be effective in improving clinical outcomes.

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