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缺血性脑卒中血管内治疗后预测预后的术后模型的开发与验证

Development and Validation of a Postprocedural Model to Predict Outcome After Endovascular Treatment for Ischemic Stroke.

作者信息

Chalos Vicky, Venema Esmee, Mulder Maxim J H L, Roozenbeek Bob, Steyerberg Ewout W, Wermer Marieke J H, Lycklama À Nijeholt Geert J, van der Worp H Bart, Goyal Mayank, Campbell Bruce C V, Muir Keith W, Guillemin Francis, Bracard Serge, White Philip, Dávalos Antoni, Jovin Tudor G, Hill Michael D, Mitchell Peter J, Demchuk Andrew M, Saver Jeffrey L, van der Lugt Aad, Brown Scott, Dippel Diederik W J, Lingsma Hester F

机构信息

Department of Neurology, Erasmus MC University Medical Center, Rotterdam, the Netherlands.

Department of Public Health, Erasmus MC University Medical Center, Rotterdam, the Netherlands.

出版信息

JAMA Neurol. 2023 Jul 31;80(9):940-8. doi: 10.1001/jamaneurol.2023.2392.

Abstract

IMPORTANCE

Outcome prediction after endovascular treatment (EVT) for ischemic stroke is important to patients, family members, and physicians.

OBJECTIVE

To develop and validate a model based on preprocedural and postprocedural characteristics to predict functional outcome for individual patients after EVT.

DESIGN, SETTING, AND PARTICIPANTS: A prediction model was developed using individual patient data from 7 randomized clinical trials, performed between December 2010 and December 2014. The model was developed within the Highly Effective Reperfusion Evaluated in Multiple Endovascular Stroke Trials (HERMES) collaboration and external validation in data from the Dutch Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands (MR CLEAN) Registry of patients treated in clinical practice between March 2014 and November 2017. Participants included patients from multiple centers throughout different countries in Europe, North America, East Asia, and Oceania (derivation cohort), and multiple centers in the Netherlands (validation cohort). Included were adult patients with a history of ischemic stroke from an intracranial large vessel occlusion in the anterior circulation who underwent EVT within 12 hours of symptom onset or last seen well. Data were last analyzed in July 2022.

MAIN OUTCOME(S) AND MEASURE(S): A total of 19 variables were assessed by multivariable ordinal regression to predict functional outcome (modified Rankin Scale [mRS] score) 90 days after EVT. Variables were routinely available 1 day after EVT. Akaike information criterion (AIC) was used to optimize model fit vs model complexity. Probabilities for functional independence (mRS 0-2) and survival (mRS 0-5) were derived from the ordinal model. Model performance was expressed with discrimination (C statistic) and calibration.

RESULTS

A total of 781 patients (median [IQR] age, 67 [57-76] years; 414 men [53%]) constituted the derivation cohort, and 3260 patients (median [IQR] age, 72 [61-80] years; 1684 men [52%]) composed the validation cohort. Nine variables were included in the model: age, baseline National Institutes of Health Stroke Scale (NIHSS) score, prestroke mRS score, history of diabetes, occlusion location, collateral score, reperfusion grade, NIHSS score at 24 hours, and symptomatic intracranial hemorrhage 24 hours after EVT. External validation in the MR CLEAN Registry showed excellent discriminative ability for functional independence (C statistic, 0.91; 95% CI, 0.90-0.92) and survival (0.89; 95% CI, 0.88-0.90). The proportion of functional independence in the MR CLEAN Registry was systematically higher than predicted by the model (41% vs 34%), whereas observed and predicted survival were similar (72% vs 75%). The model was updated and implemented for clinical use.

CONCLUSION AND RELEVANCE

The prognostic tool MR PREDICTS@24H can be applied 1 day after EVT to accurately predict functional outcome for individual patients at 90 days and to provide reliable outcome expectations and personalize follow-up and rehabilitation plans. It will need further validation and updating for contemporary patients.

摘要

重要性

缺血性卒中血管内治疗(EVT)后的预后预测对患者、家属和医生都很重要。

目的

开发并验证一种基于术前和术后特征的模型,以预测EVT后个体患者的功能结局。

设计、设置和参与者:使用2010年12月至2014年12月期间进行的7项随机临床试验的个体患者数据开发了一种预测模型。该模型是在多中心血管内卒中试验高效再灌注评估(HERMES)协作组中开发的,并在荷兰急性缺血性卒中血管内治疗多中心随机临床试验(MR CLEAN)的数据中进行了外部验证,这些数据来自2014年3月至2017年11月在临床实践中接受治疗的患者登记册。参与者包括来自欧洲、北美、东亚和大洋洲不同国家的多个中心的患者(推导队列),以及荷兰的多个中心的患者(验证队列)。纳入的患者为有颅内前循环大血管闭塞性缺血性卒中病史的成年人,他们在症状发作或最后一次看起来正常的12小时内接受了EVT。数据最后一次分析于2022年7月进行。

主要结局和测量指标

通过多变量有序回归评估总共19个变量,以预测EVT后90天的功能结局(改良Rankin量表[mRS]评分)。这些变量在EVT后1天即可常规获取。使用赤池信息准则(AIC)来优化模型拟合与模型复杂性之间的平衡。功能独立(mRS 0 - 2)和生存(mRS 0 - 5)的概率来自有序模型。模型性能用辨别力(C统计量)和校准来表示。

结果

总共781例患者(年龄中位数[四分位间距],67[57 - 76]岁;414例男性[53%])构成推导队列,3260例患者(年龄中位数[四分位间距],72[61 - 80]岁;1684例男性[52%])构成验证队列。模型纳入了9个变量:年龄、基线美国国立卫生研究院卒中量表(NIHSS)评分、卒中前mRS评分、糖尿病史、闭塞部位、侧支循环评分、再灌注分级、24小时时的NIHSS评分以及EVT后24小时的症状性颅内出血。在MR CLEAN登记册中的外部验证显示,该模型对功能独立具有出色的辨别能力(C统计量,0.91;95%置信区间,0.90 - 0.92)和生存辨别能力(0.89;95%置信区间,0.88 - 0.90)。MR CLEAN登记册中功能独立的比例系统性地高于模型预测值(41%对34%),而观察到的和预测的生存率相似(72%对75%)。该模型已更新并用于临床。

结论及相关性

预后工具MR PREDICTS@24H可在EVT后1天应用,以准确预测个体患者90天时的功能结局,并提供可靠的结局预期,以及个性化的随访和康复计划。对于当代患者,它还需要进一步验证和更新。

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