改善需要治疗的阻塞性睡眠呼吸暂停患者的识别和分类:高风险人群的Merlin工具

A. Scott, Akke Vellinga, Miriam Geehan, Mohammad Ahmed, E. Mulloy, Gilmartin Jj
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摘要

目的和目的:一些有效的问卷被常规用于筛选特定人群的阻塞性睡眠呼吸暂停(OSA),包括STOP, STOP- bang, Berlin和Epworth嗜睡量表。这些问卷依赖于无法独立确认的主观问题。主观问题也导致高灵敏度和低特异性,因为它们通常是由OSA引起的。该研究的目的是确定可验证且可独立测量的危险因素,并增加特异性以限制多导睡眠图评估(PE)的数量并降低医疗成本。方法:回顾性收集164例PE患者的资料,包括STOP、STOP Bang、Berlin和Epworth问卷调查结果以及人口统计学和健康相关变量。OSA定义为夜间PE的AHI>=15。计算每个问卷的敏感性和特异性以及其他可独立验证的因素(IVF)的组合。设计了一份新的问卷,包括体外受精,并前瞻性地收集了接受PE的患者的数据(N=209)。结果:回顾性分析确定年龄bbbb50,男性,BMI b>0,每周饮酒b>1,领围b>6英寸(40厘米),糖尿病,使用抗抑郁药和高血压是最重要的影响因素。前瞻性数据收集和分析得出一个新的量表,根据以下公式,截断为3:OSA=(2*BMI >0)+(年龄bbb50)+(男性)+(颈部>6)+(糖尿病)+(酒精b> 21单位/周)。每100例OSA患者中,基于每种筛查工具入组PE的总人数分别为:STOP 92例入组,41例确诊,1例漏诊;STOP- bang 94例入组,42例确诊,1例漏诊;Berlin 83例入组,36例确诊,7例漏诊;Epworth 46例入组,22例确诊,20例漏诊;我们的新筛查工具65例入组,35例确诊,8例漏诊。结论:在转到PE的高危人群中,我们发现了与OSA相关的可独立验证的因素,只有2/3的患者参加了PE,我们发现了大多数OSA病例,同时保持了低漏诊病例的数量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving the identification and triage of patients with Obstructive Sleep Apnea who require treatment: The Merlin tool for high risk populations
Aims and objectives: A number of validated questionnaires are routinely used to screen specific populations for obstructive sleep apnea (OSA) including the STOP, STOP-Bang, Berlin and Epworth sleepiness scales. These questionnaires depend on subjective questions which cannot be independently confirmed. The subjective questions also result in high sensitivity and low specificity as they are generally resulting from OSA. The aim of the study was to identify verifiable and independently measurable risk factors and increase specificity to limit the number of polysomnography evaluations (PE) and lower healthcare cost. Methods: A retrospective data collection of patients (N=164) enrolled for PE was performed which included the results of STOP, STOP Bang, Berlin and Epworth questionnaires as well as demographic and health related variables. OSA was defined as an AHI>=15 obtained from an overnight PE. Sensitivity and specificity of each questionnaire as well as for combinations of other, independently verifiable factors (IVF) was calculated. A new questionnaire was devised including the IVFs and data was prospectively collected from patients undergoing PE (N=209). Results: The retrospective analysis identified age>50, male, BMI>30, alcohol consumption >21 per week, collar circumference>16 inches (40 cm), diabetes, use of antidepressants and high blood pressure as the most influential factors. Prospective data collection was performed and analysis resulted in a new scale with a cut off of 3 based on the following equation: OSA=(2*BMI>30)+(Age>50)+(Male)+(neck>16)+(diabetes)+(alcohol>21unit/week). For every 100 patients with OSA, the total number enrolled for PE based on each screening tool were respectively for STOP 92 enrolled of whom 41 were diagnosed and 1 patient missed, for STOP-Bang 94 enrolled, 42 identified and 1 missed, Berlin 83 enrolled, 36 identified and 7 missed, Epworth 46 enrolled, 22 identified and 20 missed and our new screening tool 65 enrolled, 35 identified and 8 missed. Conclusion: In a high risk population of patients referred for PE we identified independently verifiable factors associated with OSA and with only 2/3 of patients enrolled for PE, we identified most OSA cases while keeping the number of missed cases down.
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