Dekkers Martijn Petrus Josephus, Horvath Christian Michael, Woerz Vanessa S, Bernasconi Corrado, Duss Simone B, Schmidt Markus H, Manconi Mauro, Brill Anne-Kathrin, Bassetti Claudio L A
Department of Neurology, Bern University Hospital (Inselspital) and University Bern, Bern, Switzerland.
Department of Pulmonary Medicine, Allergology and Clinical Immunology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
J Sleep Res. 2025 Aug;34(4):e14416. doi: 10.1111/jsr.14416. Epub 2024 Nov 26.
Sleep-disordered breathing is common in stroke and may negatively affect its outcome. Screening for sleep-disordered breathing in this setting is of interest but poorly studied. We aimed to evaluate the performance of eight obstructive sleep apnea screening questionnaires to predict sleep-disordered breathing in acute stroke or transient ischaemic attack patients, and to assess the impact of stroke/transient ischaemic attack-specific factors on sleep-disordered breathing prediction. We analysed acute stroke/transient ischaemic attack patients (N = 195) from a prospective cohort ("Sleep Deficiency and Stroke Outcome study"). Assessments included anthropometrics, stroke-specific parameters, sleep history, an in-hospital respiratory polygraphy within the first week after stroke, and obstructive sleep apnea screening questionnaires (Berlin Questionnaire, Epworth Sleepiness Scale, STOP-BANG, NoSAS, Sleep Apnea Clinical Score, No-Apnea, Sleep Obstructive apnea score optimized for Stroke, SLEEP-IN). In a binary classification task for respiratory event index ≥ 15 per hr, we evaluated the performance of the above-mentioned questionnaires. We used logistic regression to identify predictors for sleep-disordered breathing in this cohort. The areas under the curve for respiratory event index ≥ 15 per hr were: Berlin Questionnaire 0.60; STOP-BANG 0.72; NoSAS 0.69; No-Apnea 0.69; Sleep Apnea Clinical Score 0.75; Epworth Sleepiness Scale 0.50; Sleep Obstructive apnea score optimized for Stroke 0.58; and SLEEP-IN 0.67. The No-Apnea had the lowest false omission rate (0.13), a sensitivity of 0.97 and a specificity of 0.12. In multiple logistic regression analysis (respiratory event index ≥ 15 per hr), age, neck circumference, National Institutes of Health Stroke Scale at admission, prior stroke, cardioembolic stroke aetiology and observed apneas were associated with sleep-disordered breathing. The logistic regression model performed similar (area under the curve 0.80) to Sleep Apnea Clinical Score (p = 0.402) and STOP-BANG (p = 0.127), but outperformed the other questionnaires. Neither existing questionnaires nor our statistical model are sufficient to accurately diagnose sleep-disordered breathing after stroke, thus requiring sleep study evaluation. The No-Apnea questionnaire may help to identify patients amenable to sleep testing.
睡眠呼吸障碍在中风患者中很常见，可能会对其预后产生负面影响。在这种情况下筛查睡眠呼吸障碍很有意义，但相关研究较少。我们旨在评估8种阻塞性睡眠呼吸暂停筛查问卷在预测急性中风或短暂性脑缺血发作患者睡眠呼吸障碍方面的性能，并评估中风/短暂性脑缺血发作特异性因素对睡眠呼吸障碍预测的影响。我们分析了来自前瞻性队列（“睡眠不足与中风结局研究”）的急性中风/短暂性脑缺血发作患者（N = 195）。评估内容包括人体测量学、中风特异性参数、睡眠史、中风后第一周内的院内呼吸多导睡眠图，以及阻塞性睡眠呼吸暂停筛查问卷（柏林问卷、爱泼华嗜睡量表、STOP-BANG、NoSAS、睡眠呼吸暂停临床评分、No-Apnea、针对中风优化的睡眠阻塞性呼吸暂停评分、SLEEP-IN）。在呼吸事件指数≥每小时15次的二元分类任务中，我们评估了上述问卷的性能。我们使用逻辑回归来确定该队列中睡眠呼吸障碍的预测因素。呼吸事件指数≥每小时15次的曲线下面积分别为：柏林问卷0.60；STOP-BANG 0.72；NoSAS 0.69；No-Apnea 0.69；睡眠呼吸暂停临床评分0.75；爱泼华嗜睡量表0.50；针对中风优化的睡眠阻塞性呼吸暂停评分0.58；以及SLEEP-IN 0.67。No-Apnea的漏诊率最低（0.13），敏感性为0.97，特异性为0.12。在多因素逻辑回归分析（呼吸事件指数≥每小时15次）中，年龄、颈围、入院时的美国国立卫生研究院卒中量表评分、既往中风史、心源性栓塞性中风病因和观察到的呼吸暂停与睡眠呼吸障碍相关。逻辑回归模型的表现与睡眠呼吸暂停临床评分（p = 0.402）和STOP-BANG（p = 0.127）相似（曲线下面积0.80），但优于其他问卷。现有的问卷和我们的统计模型都不足以准确诊断中风后的睡眠呼吸障碍，因此需要进行睡眠研究评估。No-Apnea问卷可能有助于识别适合进行睡眠测试的患者。
