Symptom subtypes of obstructive sleep apnea 10 years later: past, present, and future

阻塞性睡眠呼吸暂停 睡眠(系统调用) 医学 多导睡眠图 睡眠呼吸暂停 呼吸暂停 儿科 心理学 精神科 麻醉 计算机科学 操作系统
作者
Brendan T Keenan,Lichuan Ye,Grace W. Pien,Ulysses J. Magalang,Bryndís Benediktsdóttir,Þórarinn Gíslason,Allan I Pack
出处
期刊:Sleep [Oxford University Press]
卷期号:48 (7) 被引量:6
标识
DOI:10.1093/sleep/zsaf082
摘要

As first described in Iceland over 10 years ago and since replicated across thousands of diverse subjects from community-based and clinical cohorts throughout the world, there exist different subtypes of obstructive sleep apnea (OSA) characterized by patient-reported symptoms. Subtypes defined by excessive sleepiness, disturbed sleep, and minimal symptoms have been consistently identified across these various cohorts and are often joined by a moderately sleepy subtype. Identifying symptom subtypes using cluster analysis provided a data-driven approach to formalize the concept of symptomatic differences among patients with OSA that has been discussed for decades in prior research and has important implications for future research and clinical applications. Current evidence favors excessive sleepiness as a marker of increased cardiovascular risk related to OSA, but there remains an opportunity for more research on non-cardiovascular endpoints. The framework of symptom subtypes can inform future randomized clinical trials, which are challenging in patients with excessive sleepiness, but both feasible and clinically important in the other subtypes. Symptom heterogeneity should also be used to move beyond a one-size-fits-all approach to treatment recommendations, including consideration of whether patients with minimally symptomatic OSA require or receive any benefits from therapy. Studies to identify the underlying mechanisms of different symptom presentations, demonstrate short-term reliability, determine the minimum number of questions required for accurate identification, and implement a tool for assigning subtypes in routine clinical practice are needed to realize the full potential of symptom subtypes to inform more personalized medicine approaches.
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