Department of Family Medicine, Faculty of Medicine, University of Ljubljana, 1000, Ljubljana, Slovenia.
Institute of Clinical Neurophysiology, Division of Neurology, University Medical Centre Ljubljana, 1000, Ljubljana, Slovenia.
Sleep Breath. 2024 Dec;28(6):2531-2538. doi: 10.1007/s11325-024-03142-w. Epub 2024 Sep 10.
To evaluate the effectiveness of a two-stage screening model for obstructive sleep apnea (OSA) in primary care that combines the STOP-BANG questionnaire (SBQ) with an automated home sleep apnea test (HSAT).
This cross-sectional study was conducted from August 2018 to August 2022 in four Slovenian primary care practices. It included 153 randomly selected patients aged 18 to 70 years who visited the practice for any reason. Participants completed the SBQ and underwent HSAT with type III polygraphy on the same night. The HSAT recordings were scored automatically and by an experienced, accredited somnologist.
There was a strong correlation between manual and automated HSAT scorings for the detection of OSA (Pearson's r = 0.93). Cohen's kappa was 0.80 for OSA (respiratory event index (REI) ≥ 5) and 0.77 for OSA severity categorization. The two-stage model demonstrated sensitivity of 64%, a specificity of 97.4%, a positive predictive value (PPV) of 96.0%, a negative predictive value (NPV) of 73.8% and an accuracy of 81.1% for any OSA (REI ≥ 5). For moderate to severe OSA (REI ≥ 15), the model showed 72.7% sensitivity, 96.7% specificity, 85.7% PPV, 92.8% NPV and 91.5% accuracy.
The two-stage model for OSA screening combining the SBQ and automated HSAT was shown to be effective in primary care, especially for moderate and severe OSA. This method provides a practical and efficient approach for the early detection of OSA.
评估一种两阶段筛查模型在初级保健中的有效性，该模型将 STOP-BANG 问卷（SBQ）与自动化家庭睡眠呼吸暂停测试（HSAT）相结合，用于筛查阻塞性睡眠呼吸暂停（OSA）。
本横断面研究于 2018 年 8 月至 2022 年 8 月在斯洛文尼亚的四家初级保健诊所进行，纳入了 153 名随机选择的年龄在 18 至 70 岁之间、因任何原因就诊的患者。参与者在同一晚完成 SBQ 并进行了 HSAT，采用 III 型多导睡眠图进行测试。HSAT 记录由经验丰富的认证睡眠专家进行自动和手动评分。
手动和自动 HSAT 评分在检测 OSA 方面具有很强的相关性（Pearson r=0.93）。OSA（呼吸事件指数（REI）≥5）的 Cohens kappa 值为 0.80，OSA 严重程度分类的 Cohens kappa 值为 0.77。两阶段模型对任何 OSA（REI≥5）的敏感性为 64%，特异性为 97.4%，阳性预测值（PPV）为 96.0%，阴性预测值（NPV）为 73.8%，准确性为 81.1%。对于中重度 OSA（REI≥15），该模型显示出 72.7%的敏感性、96.7%的特异性、85.7%的 PPV、92.8%的 NPV 和 91.5%的准确性。
结合 SBQ 和自动化 HSAT 的 OSA 筛查两阶段模型在初级保健中显示出有效性，尤其是对中重度 OSA。这种方法为 OSA 的早期发现提供了一种实用且高效的方法。
