A study involving patients with obstructive sleep apnea (OSA) and coronary artery disease (CAD) found that the physiological traits that cause OSA, including lower arousal threshold and both high and low pharyngeal muscle compensation, also influence CPAP adherence. Study results were recently published in the American Journal of Respiratory and Critical Care Medicine.
Participants in the RICCADSA (Randomized Intervention with CPAP in CAD and OSA) trial included those with objective CPAP adherence (h/night) over 2 years. Using polysomnography, researchers evaluated loop gain, arousal threshold, pharyngeal collapsibility, and pharyngeal muscle compensation. Models were used to determine the relationship between the traits and adherence. The researchers also compared CPAP adherence between those with physiologically predicted “poor” adherence and those with physiologically predicted “good” adherence.
The researchers found that those with predicted poor adherence showed considerably lower CPAP use than those with predicted good adherence.
“Specifically, we find that a lower arousal threshold (propensity to easily awaken from a respiratory stimulus) is associated with a marked reduction in CPAP use over a 2-year follow-up,” the authors wrote. “Moreover, we find that both high and low pharyngeal muscle compensation are linked to poor CPAP adherence.”
The findings suggest that physiological traits might be useful for spotting a subgroup of patients with poor CPAP use who may benefit from an early adherence intervention.
The authors conclude, “Our findings suggest that a priori knowledge of an individual’s OSA pathophysiology may aid with the identification of patients who are at risk of poor CPAP adherence and may improve OSA therapy in a more precise way. Understanding the physiological contributors to CPAP adherence may be a key to predicting CPAP use and improving OSA therapy in a personalized way.”
Identifying patients who are at risk of CPAP nonadherence is more important than ever both from a clinical and reimbursement perspective.
“As more research identifies the traits associated with poor adherence, we can better predict therapy usage,” says Subath Kamalasan, CEO of Somnoware, in a press release. “The Somnoware platform unifies patient-reported data and PSG data. Organizations that use Somnoware such as Kaiser Permanente can use this data to begin to identify patients with physiological traits that influence CPAP adherence and deliver therapy in a more individualized way to help improve outcomes.”
“I’d like to extend my appreciation to Dr. Zinchuk for his firsthand guidance and vast clinical knowledge in helping us incorporate these phenotyping capabilities,” he said.
