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Simplifying STOP-BANG: use of a simple questionnaire to screen for OSA in an Asian population.简化 STOP-BANG:使用简单问卷筛查亚洲人群中的 OSA。
Sleep Breath. 2010 Dec;14(4):371-6. doi: 10.1007/s11325-010-0350-7. Epub 2010 Apr 26.
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A systematic review of screening questionnaires for obstructive sleep apnea.系统评价阻塞性睡眠呼吸暂停的筛查问卷
Can J Anaesth. 2010 May;57(5):423-38. doi: 10.1007/s12630-010-9280-x. Epub 2010 Feb 9.
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Simple four-variable screening tool for identification of patients with sleep-disordered breathing.用于识别睡眠呼吸障碍患者的简单四变量筛查工具。
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A meta-analysis of clinical screening tests for obstructive sleep apnea.阻塞性睡眠呼吸暂停临床筛查试验的荟萃分析。
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Validation of the Berlin questionnaire and American Society of Anesthesiologists checklist as screening tools for obstructive sleep apnea in surgical patients.验证柏林问卷和美国麻醉医师协会检查表作为外科手术患者阻塞性睡眠呼吸暂停筛查工具的有效性。
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STOP questionnaire: a tool to screen patients for obstructive sleep apnea.STOP问卷:一种用于筛查阻塞性睡眠呼吸暂停患者的工具。
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Prevalence and risk factors of obstructive sleep apnea syndrome in a population of Delhi, India.印度德里人群中阻塞性睡眠呼吸暂停综合征的患病率及危险因素
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Practice guidelines for the perioperative management of patients with obstructive sleep apnea: a report by the American Society of Anesthesiologists Task Force on Perioperative Management of patients with obstructive sleep apnea.阻塞性睡眠呼吸暂停患者围手术期管理实践指南:美国麻醉医师协会阻塞性睡眠呼吸暂停患者围手术期管理特别工作组报告
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睡眠呼吸障碍患者的识别:四变量筛查工具、STOP、STOP-Bang 和 Epworth 嗜睡量表的比较。

Identification of patients with sleep disordered breathing: comparing the four-variable screening tool, STOP, STOP-Bang, and Epworth Sleepiness Scales.

机构信息

College of Nursing & Health Innovation, Arizona State University, Phoenix, AZ 85004-0698, USA.

出版信息

J Clin Sleep Med. 2011 Oct 15;7(5):467-72. doi: 10.5664/JCSM.1308.

DOI:10.5664/JCSM.1308
PMID:22003341
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3190845/
Abstract

STUDY OBJECTIVE

The Epworth Sleepiness Scale (ESS) has been used to detect patients with potential sleep disordered breathing (SDB). Recently, a 4-Variable screening tool was proposed to identify patients with SDB, in addition to the STOP and STOP-Bang questionnaires. This study evaluated the abilities of the 4-Variable screening tool, STOP, STOP-Bang, and ESS questionnaires in identifying subjects at risk for SDB.

METHODS

A total of 4,770 participants who completed polysomnograms in the baseline evaluation of the Sleep Heart Health Study (SHHS) were included. Subjects with RDIs ≥ 15 and ≥ 30 were considered to have moderate-to-severe or severe SDB, respectively. Variables were constructed to approximate those in the questionnaires. The risk of SDB was calculated by the 4-Variable screening tool according to Takegami et al. The STOP and STOP-Bang questionnaires were evaluated including variables for snoring, tiredness/sleepiness, observed apnea, blood pressure, body mass index, age, neck circumference, and gender. Sleepiness was evaluated using the ESS questionnaire and scores were dichotomized into < 11 and ≥ 11.

RESULTS

The STOP-Bang questionnaire had higher sensitivity to predict moderate-to-severe (87.0%) and severe (70.4%) SDB, while the 4-Variable screening tool had higher specificity to predict moderate-to-severe and severe SDB (93.2% for both).

CONCLUSIONS

In community populations such as the SHHS, high specificities may be more useful in excluding low-risk patients, while avoiding false positives. However, sleep clinicians may prefer to use screening tools with high sensitivities, like the STOP-Bang, in order to avoid missing cases that may lead to adverse health consequences and increased healthcare costs.

摘要

研究目的

Epworth 嗜睡量表(ESS)已被用于检测潜在的睡眠呼吸障碍(SDB)患者。最近,提出了一种四变量筛查工具,除了 STOP 和 STOP-Bang 问卷外,还可以识别 SDB 患者。本研究评估了四变量筛查工具、STOP、STOP-Bang 和 ESS 问卷在识别 SDB 风险患者中的能力。

方法

共有 4770 名参与者在睡眠心脏健康研究(SHHS)的基线评估中完成了多导睡眠图。呼吸暂停低通气指数(RDI)≥15 和≥30 的受试者分别被认为患有中重度或重度 SDB。构建了近似于问卷中的变量。根据 Takegami 等人的方法,使用四变量筛查工具计算 SDB 的风险。评估了 STOP 和 STOP-Bang 问卷,包括打鼾、疲劳/嗜睡、观察到的呼吸暂停、血压、体重指数、年龄、颈围和性别等变量。使用 ESS 问卷评估嗜睡,得分分为<11 和≥11。

结果

STOP-Bang 问卷对预测中重度(87.0%)和重度(70.4%)SDB 的敏感性较高,而四变量筛查工具对预测中重度和重度 SDB 的特异性较高(两者均为 93.2%)。

结论

在 SHHS 等社区人群中,高特异性可能更有助于排除低风险患者,避免假阳性。然而,睡眠临床医生可能更愿意使用敏感性较高的筛查工具,如 STOP-Bang,以避免遗漏可能导致不良健康后果和增加医疗保健成本的病例。