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通过便携式外周动脉张力测定法区分阻塞性和中枢性睡眠呼吸暂停。

Distinguish Obstructive and Central Sleep Apnea by Portable Peripheral Arterial Tonometry.

作者信息

Penzel Thomas, Glos Martin, Fietze Ingo, Herberger Sebastian, Pillar Giora

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:2780-2783. doi: 10.1109/EMBC44109.2020.9175700.

Abstract

Sleep apnea has a very high prevalence in the general population. Sleep apnea can be the cause for cardiovascular disorders. An increased risk for suffering from hypertension, stroke, and myocardial infarction had been shown in large studies, like the Sleep Heart Health Study. Sleep related breathing disorders and sleep apnea had been diagnosed in sleep laboratories with polysomnography in the past. Today in view of the high prevalence of sleep disordered breathing, home sleep apnea testing (HSAT) has become the accepted test for the diagnosis of sleep apnea, if there are no other comorbidities, and if a high pretest probability was confirmed by a sleep physician. For home sleep apnea testing, the number of sensors needed should be reduced. Some methods use indirect means to derive features to detect sleep apnea and hypopnea events. A very well developed method is peripheral arterial tonometry (PAT). This method records the pulse wave on a finger and derives sleep and sleep apnea feature. The PAT method has been tested under many conditions. As an indirect method, it was long seen as a limitation that obstructive and central sleep apnea events could not be distinguished. A new multicenter trial was set up to develop algorithms, which could distinguish central and obstructive apnea events with sufficient accuracy.

摘要

睡眠呼吸暂停在普通人群中的患病率非常高。睡眠呼吸暂停可能是心血管疾病的病因。大型研究(如睡眠心脏健康研究)表明,患高血压、中风和心肌梗死的风险增加。过去,睡眠相关呼吸障碍和睡眠呼吸暂停是在睡眠实验室通过多导睡眠图诊断的。如今,鉴于睡眠呼吸障碍的高患病率,如果没有其他合并症,且睡眠医生确认预检概率较高,家庭睡眠呼吸暂停检测(HSAT)已成为诊断睡眠呼吸暂停的公认检测方法。对于家庭睡眠呼吸暂停检测,所需传感器的数量应减少。一些方法使用间接手段来提取特征以检测睡眠呼吸暂停和呼吸不足事件。一种非常成熟的方法是外周动脉张力测定法(PAT)。该方法记录手指上的脉搏波并提取睡眠和睡眠呼吸暂停特征。PAT方法已在多种条件下进行了测试。作为一种间接方法,长期以来人们一直认为它的一个局限性是无法区分阻塞性和中枢性睡眠呼吸暂停事件。一项新的多中心试验已启动,以开发能够足够准确地区分中枢性和阻塞性呼吸暂停事件的算法。

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