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Web-based tool for dynamic functional outcome after acute ischemic stroke and comparison with existing models

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机构: [1]Capital Med Univ, Beijing Tiantan Hosp, Tiantan Comprehens Stroke Ctr, Beijing 100050, Dongcheng Dist, Peoples R China; [2]China Natl Clin Res Ctr Neurol Dis NCRC ND, Beijing, Peoples R China; [3]Univ N Carolina, Dept Stat & Operat Res, Chapel Hill, NC USA; [4]Capital Med Univ, Beijing Tiantan Hosp, Tiantan Comprehens Stroke Ctr, 6 Tiantanxili, Beijing 100050, Dongcheng Dist, Peoples R China
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关键词: Acute ischemic stroke Prognosis Risk model

摘要:
Background: Acute ischemic stroke (AIS) is one of the leading causes of death and adult disability worldwide. In the present study, we aimed to develop a web-based risk model for predicting dynamic functional status at discharge, 3-month, 6-month, and 1-year after acute ischemic stroke (Dynamic Functional Status after Acute Ischemic Stroke, DFS-AIS). Methods: The DFS-AIS was developed based on the China National Stroke Registry (CNSR), in which eligible patients were randomly divided into derivation (60%) and validation (40%) cohorts. Good functional outcome was defined as modified Rankin Scale (mRS) score <= 2 at discharge, 3-month, 6-month, and 1-year after AIS, respectively. Independent predictors of each outcome measure were obtained using multivariable logistic regression. The area under the receiver operating characteristic curve (AUROC) and plot of observed and predicted risk were used to assess model discrimination and calibration. Results: A total of 12,026 patients were included and the median age was 67 (interquartile range: 57-75). The proportion of patients with good functional outcome at discharge, 3-month, 6-month, and 1-year after AIS was 67.9%, 66.5%, 66.9% and 66.9%, respectively. Age, gender, medical history of diabetes mellitus, stroke or transient ischemic attack, current smoking and atrial fibrillation, pre-stroke dependence, pre-stroke statins using, admission National Institutes of Health Stroke Scale score, admission blood glucose were identified as independent predictors of functional outcome at different time points after AIS. The DFS-AIS was developed from sets of predictors of mRS <= 2 at different time points following AIS. The DFS-AIS demonstrated good discrimination in the derivation and validation cohorts (AUROC range: 0.837-0.845). Plots of observed versus predicted likelihood showed excellent calibration in the derivation and validation cohorts (all r = 0.99, P < 0.001). When compared to 8 existing models, the DFS-AIS showed significantly better discrimination for good functional outcome and mortality at discharge, 3-month, 6-month, and 1-year after AIS (all P < 0.0001). Conclusion: The DFS-AIS is a valid risk model to predict functional outcome at discharge, 3-month, 6-month, and 1-year after AIS.

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出版当年[2013]版:
大类 | 3 区 医学
小类 | 3 区 临床神经病学
最新[2023]版:
大类 | 3 区 医学
小类 | 4 区 临床神经病学
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出版当年[2012]版:
Q2 CLINICAL NEUROLOGY
最新[2023]版:
Q3 CLINICAL NEUROLOGY

影响因子: 最新[2023版] 最新五年平均 出版当年[2012版] 出版当年五年平均 出版前一年[2011版] 出版后一年[2013版]

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第一作者机构: [1]Capital Med Univ, Beijing Tiantan Hosp, Tiantan Comprehens Stroke Ctr, Beijing 100050, Dongcheng Dist, Peoples R China; [2]China Natl Clin Res Ctr Neurol Dis NCRC ND, Beijing, Peoples R China;
通讯作者:
通讯机构: [1]Capital Med Univ, Beijing Tiantan Hosp, Tiantan Comprehens Stroke Ctr, Beijing 100050, Dongcheng Dist, Peoples R China; [2]China Natl Clin Res Ctr Neurol Dis NCRC ND, Beijing, Peoples R China; [4]Capital Med Univ, Beijing Tiantan Hosp, Tiantan Comprehens Stroke Ctr, 6 Tiantanxili, Beijing 100050, Dongcheng Dist, Peoples R China
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