脑白质病变严重程度与缺血性脑血管病介入治疗预后不良有关

张芾.脑白质病变严重程度与缺血性脑血管病介入治疗预后不良有关[J].内科急危重症杂志,2024,30(6):536-541

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DOI：10.11768/nkjwzzzz.20240611

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作者	单位	E-mail
张芾	如皋市人民医院	13601495108@163.com

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中文摘要:

摘要目的：探讨脑白质病变（WMLs）严重程度与缺血性脑血管病患者介入治疗预后不良的关系。方法：选取收治的102例缺血性脑血管病患者为研究对象，收集一般资料和临床指标，并根据介入治疗的预后情况分为预后不良组（43例）和预后良好组（59例）。通过单因素和多因素分析影响患者预后的独立危险因素，并通过拟合曲线及相关性分析探究WMLs与患者预后的关系。依据影响因素构建列线图预测模型，并对模型进行验证。结果：与预后良好组比较，预后不良组年龄更大，糖尿病及高血脂的患者比例更多，体重指数（BMI）、治疗前美国国立卫生研究院卒中量表（NIHSS）、治疗后即刻NIHSS、术后24h MAP、WMLs评分、超敏C反应蛋白（hs-CRP）、白介素（IL）-1、IL-6、IL-8、尿酸（UA）、肌肝（Scr）及糖化血红蛋白（HbAc1）更高（P均＜0.05）。多因素Cox回归分析显示，治疗后即刻NIHSS评分、WMLs评分、hs-CRP及IL-6为患者介入治疗预后不良的独立危险因素（P均＜0.05）。曲线拟合发现，随着WMLs评分的升高，患者介入治疗后预后不良的概率呈上升趋势。Pearson相关性分析显示，WMLs评分与治疗后即刻NIHSS评分、hs-CRP及IL-6呈显著正相关（P均＜0.05）。用以上因素构建列线图预测模型，其一致性指数（C-index）为0.815（95%CI: 0.794~0.826），受试者工作特征曲线（ROC）曲线下面积（AUC）为0.832（95%CI: 0.814~0.843），具有较好的区分度。结论：WMLs严重程度为缺血性脑血管病患者介入治疗预后不良的独立危险因素。

英文摘要:

Abstract Objective: To explore the relationship between the severity of white matter lesions (WMLs) and poor prognosis of interventional treatment in patients with ischemic cerebrovascular disease. Methods: A total of 102 patients with ischemic cerebrovascular disease were selected as the research objects. The general data and clinical indicators of the patients were collected, and the patients were divided into poor prognosis group (n =43) and good prognosis group (n= 59) according to the prognosis of patients after interventional therapy. The independent risk factors influencing the prognosis of patients were analyzed by univariate and multivariate analysis, and the relationship between WMLs and prognosis was explored by fitting curve and correlation analysis. The nomograph prediction model was constructed according to the influencing factors, and the model was verified. Results: The poor prognosis group had a higher mean age, a larger proportion of patients with diabetes and hyperlipidemia, and higher values of body mass index (BMI), National Institute of Health Stroke Scale(NIHSS) before treatment, NIHSS immediately after treatment, mean arterial pressure (MAP) 24 h postoperatively, WMLs score, high-sensitivity C-reactive protein (hs-CRP), interleukin (IL)-1, IL-6, IL-8, uric acid (UA), serum creatinine (Scr), and glycosylated hemoglobin (HbA1c) than the good prognosis group (all P<0.05). Multivariate Cox regression analysis revealed that NIHSS immediately after treatment, WMLs score, hs-CRP, and IL-6 were independent risk factors for poor prognosis in patients undergoing interventional therapy (all P<0.05). Curve fitting showed that the probability of poor prognosis after interventional therapy increased with higher WMLs scores. Pearson correlation analysis indicated a significantly positive correlation between WMLs score and NIHSS immediately after treatment, hs-CRP, and IL-6 (all P<0.05). A nomogram prediction model was constructed using these independent influencing factors, with a concordance index (C-index) of 0.815 (95%CI: 0.794-0.826) and an area under the receiver operating characteristic (ROC) curve (AUC) of 0.832 (95%CI: 0.814-0.843), demonstrating good discrimination. Conclusion: The severity of WMLs may be an independent risk factor of poor prognosis following interventional treatment in patients with ischemic cerebrovascular disease.