McLaren Declan M, Evans Jonathan, Baylan Satu, Harvey Monika, Montgomery Megan C, Gardani Maria
School of Psychology & Neuroscience, University of Glasgow, Glasgow, UK.
School of Health & Wellbeing, University of Glasgow, Glasgow, UK.
BMJ Neurol Open. 2024 Oct 31;6(2):e000768. doi: 10.1136/bmjno-2024-000768. eCollection 2024.
Insomnia is common after stroke and is associated with poorer recovery and greater risk of subsequent strokes. Yet, no insomnia measures have been validated in English-speaking individuals affected by stroke.
This prospective diagnostic validation study investigated the discriminatory validity and optimal diagnostic cut-off of the Sleep Condition Indicator when screening for Diagnostic and Statistical Manual of Mental Disorders-fifth edition (DSM-5) insomnia disorder post-stroke.
A convenience sample of 180 (60.0% women, mean age=49.61 ± 12.41 years) community-based, adult (≥18 years) self-reported stroke survivors completed an online questionnaire. Diagnosis of DSM-5 insomnia disorder was based on analysis of a detailed sleep history questionnaire. Statistical analyses explored discriminant validity, convergent validity, relationships with demographic and mood variables, and internal consistency. Receiver operating characteristic curves were plotted to assess diagnostic accuracy.
Data from the sleep history questionnaire suggested that 75 participants (41.67%) met criteria for DSM-5 insomnia disorder, 33 (18.33%) exhibited symptoms of insomnia but did not meet diagnostic criteria, and 72 (40.0%) had no insomnia symptoms at the time of assessment. The Sleep Condition Indicator (SCI) demonstrated 'excellent' diagnostic accuracy in the detection of insomnia post-stroke, with an area under the curve of 0.86 (95% CI (0.81, 0.91)). The optimal cut-off was determined as being ≤13, yielding a sensitivity of 88.0% and a specificity of 71.43%.
The findings of this study demonstrate the SCI to be a valid and reliable method with which to diagnose DSM-5 insomnia disorder and symptoms post-stroke. However, a lower threshold than is used in the general population may be necessary after stroke.
失眠在中风后很常见，且与恢复较差以及后续中风风险增加有关。然而，尚未有失眠测量方法在受中风影响的英语使用者中得到验证。
这项前瞻性诊断验证研究调查了睡眠状况指标在筛查中风后《精神疾病诊断与统计手册》第五版（DSM-5）失眠症时的区分效度和最佳诊断临界值。
一个由180名（60.0%为女性，平均年龄 = 49.61 ± 12.41岁）基于社区的成年（≥18岁）自我报告中风幸存者组成的便利样本完成了一份在线问卷。DSM-5失眠症的诊断基于对一份详细睡眠史问卷的分析。统计分析探讨了区分效度、聚合效度、与人口统计学和情绪变量的关系以及内部一致性。绘制受试者工作特征曲线以评估诊断准确性。
睡眠史问卷数据表明，75名参与者（41.67%）符合DSM-5失眠症标准，33名（18.33%）表现出失眠症状但未达到诊断标准，72名（40.0%）在评估时没有失眠症状。睡眠状况指标（SCI）在检测中风后失眠方面显示出“极佳”的诊断准确性，曲线下面积为0.86（95%置信区间（0.81, 0.91））。最佳临界值确定为≤13，灵敏度为88.0%，特异度为71.43%。
本研究结果表明，SCI是诊断中风后DSM-5失眠症和症状的有效且可靠的方法。然而，中风后可能需要比一般人群更低的阈值。
