Physiological features that cause sleep apnea also affect CPAP adherence


Sleep Disorders | Sleep Review

A study in patients with obstructive sleep apnea (OSA) and coronary artery disease (CAD) found that the physiological features that cause OSA, including a lower arousal threshold and both high and low pharyngeal muscle compensation, also affect CPAP adherence. The study results were recently published in the American Journal of Respiratory and Critical Care Medicine.

The participants in the RICCADSA study (Randomized Intervention with CPAP in CAD and OSA) included those with objective CPAP adherence (h / night) for 2 years. Using polysomnography, the researchers assessed loop gain, arousal threshold, throat collapse, and pharyngeal muscle compensation. Models were used to determine the relationship between features 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 significantly less CPAP use than those with predicted good adherence.

“In particular, we find that a lower arousal threshold (the tendency to wake up easily from a breath stimulus) is associated with a marked decrease in CPAP use over a 2-year follow-up,” the authors write. “In addition, we find that both high and low pharyngeal muscle compensation are associated with poor CPAP adherence.”

The results suggest that physiological traits might be useful in identifying a subset of patients with poor CPAP use who might benefit from early adherence.

The authors conclude: “Our results suggest that knowing a priori knowledge of an individual’s OSA pathophysiology can help identify patients at risk of poor CPAP adherence and more accurately improve OSA therapy . Understanding the physiological factors that contribute to CPAP adherence can be key to predicting CPAP usage and improving individual OSA therapy. ”

Identifying patients at risk of CPAP non-adherence is more important than ever from both clinical and reimbursement perspectives.

“As more research identifies the traits associated with poor compliance, we can better predict therapy usage,” said Subath Kamalasan, CEO of Somnoware, in a press release. “The Somnoware platform combines patient reported data and PSG data. Organizations using Somnoware, such as Kaiser Permanente, can use this data to begin identifying patients with physiological characteristics that affect CPAP adherence and delivering therapy in a more personalized manner to improve outcomes. ”

“I want to Dr. I would like to thank Zinchuk for his first hand advice and extensive clinical knowledge that has helped us incorporate these phenotyping skills, ”he said.

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