High burden of moderate-to-severe obstructive sleep apnea: comparative accuracy of screening tools against polysomnography

Asmaa Ali , Liang Wu , Seham Ezzat Fathy Elfeky , Mohammad H. Alhassoon , Dhuha S. Aldrees , Eman M. Moazen , Abdulaziz Alghulayqah , Mai M. Saleh
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Abstract

Background and objectives

Timely diagnosis of obstructive sleep apnea (OSA) is essential, but polysomnography (PSG) is resource intensive. Simple screening tools may aid triage, yet their comparative accuracy in high-risk populations remains unclear. This study aimed to assess OSA burden and evaluate the diagnostic performance of three tools (STOP-BANG, Epworth Sleepiness Scale (ESS), and NoSAS) against PSG, along with a Combined Screening Model (CSM) integrating these tools.

Methods

In this cross-sectional study, 140 patients referred for overnight PSG were screened using STOP-BANG, ESS, and NoSAS. Sensitivity, specificity, predictive values, and area under the receiver operating characteristic curve (AUC) were calculated using an apnea–hypopnea index (AHI) ≥5 events/h and oxygen desaturation index (ODI) ≥5 events/h as diagnostic thresholds. A CSM was developed to assess the combined predictive value.

Results

OSA was confirmed in 91% of patients, with 74% having moderate-to-severe disease. NoSAS had the highest AUC (0.70), followed by STOP-BANG (0.67), CSM (0.65), and ESS (0.61), with no significant differences. CSM showed the greatest sensitivity (71%), while NoSAS had the highest specificity (64%).

Conclusion

OSA was highly prevalent and often severe in this referral population. NoSAS performed slightly better individually, and combined models showed potential for supporting early triage. However, PSG remains essential for definitive diagnosis and management.
中度至重度阻塞性睡眠呼吸暂停的高负担:多导睡眠图筛选工具的相对准确性
背景和客观诊断阻塞性睡眠呼吸暂停(OSA)是必要的,但多导睡眠图(PSG)是资源密集的。简单的筛查工具可能有助于分诊,但它们在高危人群中的相对准确性尚不清楚。本研究旨在评估OSA负担,并评估三种工具(STOP-BANG, Epworth嗜睡量表(ESS)和NoSAS)对PSG的诊断性能,以及整合这些工具的联合筛选模型(CSM)。方法在这项横断面研究中,使用STOP-BANG、ESS和NoSAS对140例接受过夜PSG的患者进行筛选。以呼吸暂停低通气指数(AHI)≥5个事件/小时和氧去饱和指数(ODI)≥5个事件/小时作为诊断阈值,计算敏感性、特异性、预测值和受试者工作特征曲线下面积(AUC)。开发了CSM来评估联合预测值。结果91%的患者确诊为sosa,其中74%为中重度疾病。NoSAS的AUC最高(0.70),其次是STOP-BANG(0.67)、CSM(0.65)和ESS(0.61),差异无统计学意义。CSM的敏感性最高(71%),NoSAS的特异性最高(64%)。结论osa在该转诊人群中发病率高,且病情严重。NoSAS单独表现稍好,联合模型显示支持早期分诊的潜力。然而,PSG对于明确诊断和治疗仍然至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Sleep epidemiology
Sleep epidemiology Dentistry, Oral Surgery and Medicine, Clinical Neurology, Pulmonary and Respiratory Medicine
CiteScore
1.80
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