Physiological Traits and Adherence to Sleep Apnea Therapy in Individuals with Coronary Artery Disease
Year: 2021
Type: article
Abstract: Rationale 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. Objectives To determine whether physiological traits that cause OSA are associated with long-term CPAP adherence in patients with CAD. Methods Participants in the RICCADSA (Randomized Intervention with CPAP in CAD and OSA) trial with objective CPAP adherence (h/night) over 2 years and analyzable raw polysomnography data were included (N = 249). The physiological traits—loop gain, arousal threshold (ArTH), pharyngeal collapsibility (Vpassive), and pharyngeal muscle compensation (Vcomp)—were measured by using polysomnography. Linear mixed models were used to assess the relationship between the traits and adherence. We also compared actual CPAP adherence between those with physiologically predicted “poor” adherence (lowest quartile of predicted adherence) and those with physiologically predicted “good” adherence (all others). Measurements and Main Results The median (interquartile range) CPAP use declined from 3.2 (1.0–5.8) h/night to 3.0 (0.0–5.6) h/night over 24 months (P < 0.001). In analyses adjusted for demographics, anthropometrics, OSA characteristics, and clinical comorbidities, a lower ArTH was associated with worse CPAP adherence (0.7 h/SD of the ArTH; P = 0.021). Both high and low Vcomp were associated with lower adherence (P = 0.008). Those with predicted poor adherence exhibited markedly lower CPAP use than those with predicted good adherence for up to 2 years of follow-up (group differences of 2.0–3.2 h/night; P < 0.003 for all). Conclusions A low ArTH, as well as a very low and high Vcomp, 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. Clinical trial registered with www.clinicaltrials.gov (NCT 00519597).
Authors: Andrey V. Zinchuk, Jen-hwa Chu, Jiasheng Liang, Yeliz Celik, Sara Op de Beeck, Nancy S. Redeker, Andrew Wellman, H. Klar Yaggi, Yüksel Peker, Scott A. Sands
Institutions: Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi, University of Antwerp, Antwerp University Hospital, Yale University, Brigham and Women's Hospital, Harvard University, VA Connecticut Healthcare System, Koç University, University of Pittsburgh, Lund University, University of Gothenburg
Language: English
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
Open Access status: green
Awards: G1472918012, A Novel Pharmacological Therapy for Obstructive Sleep Apnea, Mentoring in Sleep Research and Sleep Interventions in Heart Disease, and Stroke, Mechanisms of sleep and sleep apnea, Determination of the site of pharyngeal collapse in Obstructive Sleep Apnea patients from snoring sounds, Predicting response to non-PAP therapies in OSA using PSG-derived endotypes, Novel physiologiC prEdictors of Positive Airway Pressure effectiveness: NICE-PAP study., Yale Clinical and Translational Science Award
OpenAlex ID: W3175756369