Construction and validation of a nomogram model to predict symptomatic intracranial hemorrhage after intravenous thrombolysis in elderly population with severe white matter lesions

IF 0.2 4区 医学 Q4 CLINICAL NEUROLOGY Neurology Asia Pub Date : 2023-12-01 DOI:10.54029/2023icn
Qiurui Nie, Yu Shen, Zhisheng Deng, Wenwen Xiang, Shenjian Chen, Guangmin Li
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Abstract

Background and Objective: Elderly people are at high prevalence of atherosclerotic cerebral infarction. Cerebral white matter lesions (WMLs) increase the risk of bleeding after intravenous thrombolysis (IVT) although they may also require the IVT. The aim of this study is to develop a clinical nomogram model for post-IVT symptomatic intracranial hemorrhage (sICH), with the aim to prevent sICH in elderly patients with severe WMLs when IVT is being considered. Methods: This is a large single-center retrospective analysis study of elderly patients with severe WMLs receiving IVT from January 2018 to December 2022. Univariate and multi-factor logistic regression analysis were used to construct nomogram model, and a series of validations were performed on the model. Results: More than 2,000 patients with IVT were screened for inclusion in this study after cranial magnetic resonance imaging evaluation. Out of these, 163 elderly patients had cerebral WMLs, and 25 had sICH. In univariate analysis, history of hypertension (p=0.037), hyperlipidemia (p<0.001), NIHSS score before IVT (p<0.001), low-density lipoprotein levels (p=0.016), cholesterol levels (p=0.020), platelet count (p=0.006), systolic blood pressure (p<0.001), diastolic blood pressure (p<0.001) were significantly associated with sICH. In a multifactorial analysis, the NIHSS score before IVT (OR 42.056 CI 7.308-242.012, p<0.001), and diastolic blood pressure (OR 1.050 CI 1.002-1.100, p=0.040) were found to be significantly associated with sICH after IVT. The four most significant risk factors from logistic regression are subsequently fitted to create a predictive model. The accuracy was verified using calibration curves, decision curves, and clinical impact curves, and the model was considered to have strong stability. Conclusions: The NHISS score before IVT and diastolic blood pressure are independent risk factors for sICH after IVT in elderly patients with severe WMLs. The models are highly accurate and can be applied clinically to provide a reliable predictive basis for IVT in elderly patients with severe WMLs.
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构建并验证预测严重白质病变老年人静脉溶栓后无症状颅内出血的提名图模型
背景和目的:老年人是动脉粥样硬化性脑梗塞的高发人群。脑白质病变(WMLs)会增加静脉溶栓(IVT)后出血的风险,尽管它们也可能需要进行 IVT。本研究的目的是建立静脉溶栓后无症状性颅内出血(sICH)的临床提名图模型,以预防患有严重脑白质病变的老年患者在考虑静脉溶栓时发生 sICH。方法:这是一项大型单中心回顾性分析研究,研究对象为2018年1月至2022年12月期间接受IVT治疗的重度WMLs老年患者。采用单变量和多因素逻辑回归分析构建提名图模型,并对模型进行一系列验证。结果:经过头颅磁共振成像评估,2000 多名 IVT 患者被筛选纳入本研究。其中,163 名老年患者患有脑WML,25 名患有sICH。在单变量分析中,高血压病史(p=0.037)、高脂血症(p<0.001)、IVT 前的 NIHSS 评分(p<0.001)、低密度脂蛋白水平(p=0.016)、胆固醇水平(p=0.020)、血小板计数(p=0.006)、收缩压(p<0.001)、舒张压(p<0.001)与 sICH 显著相关。在多因素分析中,IVT 前的 NIHSS 评分(OR 42.056 CI 7.308-242.012,p<0.001)和舒张压(OR 1.050 CI 1.002-1.100,p=0.040)与 IVT 后的 sICH 显著相关。随后对逻辑回归中四个最重要的风险因素进行拟合,建立了一个预测模型。利用校准曲线、决策曲线和临床影响曲线验证了模型的准确性,并认为该模型具有很强的稳定性。结论:IVT 前的 NHISS 评分和舒张压是老年重度 WML 患者 IVT 后发生 sICH 的独立危险因素。模型的准确性很高,可应用于临床,为重度 WMLs 老年患者的 IVT 提供可靠的预测依据。
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来源期刊
Neurology Asia
Neurology Asia CLINICAL NEUROLOGY-
CiteScore
0.30
自引率
0.00%
发文量
76
审稿时长
>0 weeks
期刊介绍: Neurology Asia (ISSN 1823-6138), previously known as Neurological Journal of South East Asia (ISSN 1394-780X), is the official journal of the ASEAN Neurological Association (ASNA), Asian & Oceanian Association of Neurology (AOAN), and the Asian & Oceanian Child Neurology Association. The primary purpose is to publish the results of study and research in neurology, with emphasis to neurological diseases occurring primarily in Asia, aspects of the diseases peculiar to Asia, and practices of neurology in Asia (Asian neurology).
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