Department of Neurology, Shanghai Tenth People's Hospital, Shanghai, China.
Department of Neurology, Shanghai Tenth People's Hospital, Shanghai, China
BMJ Open. 2024 Mar 25;14(3):e076709. doi: 10.1136/bmjopen-2023-076709.
Moderate-to-severe sleep-disordered breathing (SDB) is prevalent in patients with acute ischaemic stroke (AIS) and is associated with an increased risk of unfavourable prognosis. We aimed to develop and validate a reliable scoring system for the early screening of moderate-to-severe SDB in patients with AIS, with the objective of improving the management of those patients at risk.
We developed and validated a nomogram model based on univariate and multivariate logistic analyses to identify moderate-to-severe SDB in AIS patients. Moderate-to-severe SDB was defined as an apnoea-hypopnoea index (AHI) ≥15. To evaluate the effectiveness of our nomogram, we conducted a comparison with the STOP-Bang questionnaire by analysing the area under the receiver operating characteristic curve.
Large stroke centre in northern Shanghai serving over 4000 inpatients, 100 000 outpatients and emergency visits annually.
We consecutively enrolled 116 patients with AIS from the Shanghai Tenth People's Hospital.
Five variables were independently associated with moderate-to-severe SDB in AIS patients: National Institutes of Health Stroke Scale score (OR=1.20; 95% CI 0.98 to 1.47), neck circumference (OR=1.50; 95% CI 1.16 to 1.95), presence of wake-up stroke (OR=21.91; 95% CI 3.08 to 156.05), neuron-specific enolase level (OR=1.27; 95% CI 1.05 to 1.53) and presence of brainstem infarction (OR=4.21; 95% CI 1.23 to 14.40). We developed a nomogram model comprising these five variables. The C-index was 0.872, indicated an optimal agreement between the observed and predicted SDB patients.
Our nomogram offers a practical approach for early detection of moderate-to-severe SDB in AIS patients. This tool enables individualised assessment and management, potentially leading to favourable outcomes.
中重度睡眠呼吸障碍(SDB)在急性缺血性脑卒中(AIS)患者中较为常见,且与不良预后风险增加相关。本研究旨在开发并验证一种可靠的评分系统,用于早期筛查 AIS 患者中中重度 SDB,以期改善此类高危患者的管理。
我们基于单变量和多变量逻辑分析开发并验证了一种列线图模型,以识别 AIS 患者中的中重度 SDB。中重度 SDB 定义为呼吸暂停低通气指数(AHI)≥15。为评估我们的列线图的有效性,我们通过分析受试者工作特征曲线下面积,将其与 STOP-Bang 问卷进行了比较。
上海北部一家大型卒中中心,每年服务 4000 多名住院患者、10 万名门诊患者和急诊患者。
我们连续纳入了 116 名来自上海市第十人民医院的 AIS 患者。
5 个变量与 AIS 患者中重度 SDB 独立相关:国立卫生研究院卒中量表评分(OR=1.20;95%CI 0.98 至 1.47)、颈围(OR=1.50;95%CI 1.16 至 1.95)、觉醒性卒中(OR=21.91;95%CI 3.08 至 156.05)、神经元特异性烯醇化酶水平(OR=1.27;95%CI 1.05 至 1.53)和脑干梗死(OR=4.21;95%CI 1.23 至 14.40)。我们建立了一个包含这 5 个变量的列线图模型。C 指数为 0.872,表明观察到的和预测的 SDB 患者之间有较好的一致性。
我们的列线图为 AIS 患者中重度 SDB 的早期检测提供了一种实用的方法。该工具可实现个体化评估和管理,有可能带来良好的结局。