Šiarnik Pavel, Jurík Matúš, Klobučníková Katarína, Kollár Branislav, Pirošová Margita, Malík Miroslav, Turčáni Peter, Sýkora Marek
1(st) Department of Neurology, Faculty of Medicine, Comenius University, Bratislava, Slovakia.
Department of Internal Medicine, Faculty of Medicine, Comenius University, Bratislava, Slovakia.
Sleep Med. 2021 Jan;77:23-28. doi: 10.1016/j.sleep.2020.11.022. Epub 2020 Nov 25.
Despite its high prevalence and negative impact, sleep-disordered breathing (SDB) remain commonly underdiagnosed and undertreated in stroke subjects. Multiple stroke comorbidities and risk factors, including obesity, hypertension, diabetes mellitus, ischemic heart disease, atrial fibrillation, and heart failure (H.F.) have been associated with SDB. This study aimed to examine associations of clinical and demographic characteristics with moderate-to-severe SDB (msSDB) in stroke patients and to develop a predictive score.
Consecutive patients with ischemic stroke were enrolled in an open, prospective study. SDB was assessed using standard polysomnography. Clinical and demographic characteristics, as well as findings from echocardiography, entered the analysis. Multivariate logistic regression models were used to examine the associations with msSDB. Based on the results, an original score to predict msSDB was proposed and tested.
120 patients with acute ischemic stroke (mean age: 64.0 ± 12.2 years, median NIHSS: 4) were included. Body-mass index (BMI), wake-up stroke onset (WUS), and diastolic dysfunction were independently associated with msSDB. A score allocating 1 point for BMI≥25 kg/m and <30 kg/m, 2 points for BMI≥30 kg/m, 1 point for WUS and 1 point for diastolic dysfunction resulted in an area under the curve of 0.81 (95% CI 0.71-0.90, p<0.001), sensitivity 82.9%, specificity 71.9% to identify stroke patients with msSDB.
BMI, WUS, and diastolic dysfunction were associated with msSDB. A simple score might help to identify acute stroke patients with msSDB, who are usual candidates for positive airway pressure therapy.
尽管睡眠呼吸障碍(SDB)患病率高且有负面影响,但在中风患者中仍普遍存在诊断不足和治疗不足的情况。多种中风合并症和危险因素,包括肥胖、高血压、糖尿病、缺血性心脏病、心房颤动和心力衰竭(H.F.)都与SDB有关。本研究旨在探讨中风患者的临床和人口统计学特征与中重度SDB(msSDB)之间的关联,并制定一个预测评分。
连续纳入缺血性中风患者进行一项开放性前瞻性研究。使用标准多导睡眠图评估SDB。分析纳入临床和人口统计学特征以及超声心动图检查结果。采用多变量逻辑回归模型研究与msSDB的关联。基于研究结果,提出并测试了一个预测msSDB的原始评分。
纳入120例急性缺血性中风患者(平均年龄:64.0±12.2岁,美国国立卫生研究院卒中量表[NIHSS]中位数:4)。体重指数(BMI)、醒来时中风发作(WUS)和舒张功能障碍与msSDB独立相关。对于BMI≥25kg/m且<30kg/m得1分,BMI≥30kg/m得2分,WUS得1分,舒张功能障碍得1分,所得曲线下面积为0.81(95%CI 0.71-0.90,p<0.001),识别中风合并msSDB患者的灵敏度为82.9%,特异度为71.9%。
BMI、WUS和舒张功能障碍与msSDB有关。一个简单的评分可能有助于识别中风合并msSDB的急性患者,这些患者通常是气道正压通气治疗的候选对象。