失眠症
医学
睡眠呼吸暂停
睡眠(系统调用)
呼吸暂停
多导睡眠图
认知
慢性失眠
失眠的认知行为疗法
认知行为疗法
阻塞性睡眠呼吸暂停
精神科
睡眠障碍
临床心理学
内科学
操作系统
计算机科学
作者
E Brooker,Shane A. Landry,Pedro R. Genta,Gabriel T. Abdelmessih,Bradley A. Edwards,Sean P. A. Drummond
摘要
Cognitive behavioral therapy for insomnia (CBT-I) improves obstructive sleep apnea (OSA) severity in comorbid insomnia and sleep apnea (COMISA), though the mechanisms underlying this change are unstudied. CBT-I, which promotes sleep continuity and reduces hyperarousal, may improve OSA by raising the respiratory arousal threshold. We aimed to investigate the effect of CBT-I on OSA severity and its impact on the arousal threshold and other endotype traits. In this single-arm trial, 25 patients with COMISA (13F:12M, Mage=53.7, SDage=8.7 years) completed a seven-week individual CBT-I program. Patients met diagnostic criteria for insomnia and demonstrated an apnea-hypopnea index (AHI) ≥ 10 events/h (MAHI=35.2, SDAHI=16.4 events/h). Overnight polysomnography before and after CBT-I measured OSA severity, sleep architecture, and the four OSA endotypes (i.e., collapsibility, muscle compensation, loop gain, arousal threshold). There was a 7.7±10.2 event/h reduction in the AHI from baseline to post treatment (p=.001), however, no change in any of the OSA endotype traits studied (all p>.05). Secondary analyses showed a relationship whereby increases in N3 sleep were associated with decreases in AHI (r2=.19, p=.03). Significant improvements were also found in insomnia severity and sleep diary-based sleep efficiency, sleep onset latency, and wake after sleep onset at post-treatment (all p<.001). CBT-I is beneficial in improving insomnia symptoms and we provide further support CBT-I improves OSA severity. Despite no change in the OSA endotype traits, the improvement in the AHI may be associated with increased amounts N3 sleep. These results underscore the importance of managing insomnia in COMISA. Registry: Australian and New Zealand Clinical Trial Registry; Identifier: ACTRN12622000226707.
科研通智能强力驱动
Strongly Powered by AbleSci AI