Outcome Prediction Models for Endovascular Treatment of Ischemic Stroke: Systematic Review and External Validation

医学 改良兰金量表 冲程(发动机) 梅德林 随机对照试验 临床试验 接收机工作特性 物理疗法 急诊医学 内科学
作者
Femke Kremers,Esmee Venema,Martijne H C Duvekot,Lonneke S. F. Yo,Reinoud P H Bokkers,Geert J. Lycklama à Nijeholt,Adriaan C.G.M. van Es,Aad van der Lugt,Charles B. L. M. Majoie,James F. Burke,Bob Roozenbeek,Hester F. Lingsma,Diederik W.J. Dippel,Clean Registry Investigators
出处
期刊:Stroke [Lippincott Williams & Wilkins]
标识
DOI:10.1161/strokeaha.120.033445
摘要

Background and Purpose: Prediction models for outcome of patients with acute ischemic stroke who will undergo endovascular treatment have been developed to improve patient management. The aim of the current study is to provide an overview of preintervention models for functional outcome after endovascular treatment and to validate these models with data from daily clinical practice. Methods: We systematically searched within Medline, Embase, Cochrane, Web of Science, to include prediction models. Models identified from the search were validated in the MR CLEAN (Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands) registry, which includes all patients treated with endovascular treatment within 6.5 hours after stroke onset in the Netherlands between March 2014 and November 2017. Predictive performance was evaluated according to discrimination (area under the curve) and calibration (slope and intercept of the calibration curve). Good functional outcome was defined as a score of 0–2 or 0–3 on the modified Rankin Scale depending on the model. Results: After screening 3468 publications, 19 models were included in this validation. Variables included in the models mainly addressed clinical and imaging characteristics at baseline. In the validation cohort of 3156 patients, discriminative performance ranged from 0.61 (SPAN-100 [Stroke Prognostication Using Age and NIH Stroke Scale]) to 0.80 (MR PREDICTS). Best-calibrated models were THRIVE (The Totaled Health Risks in Vascular Events; intercept −0.06 [95% CI, −0.14 to 0.02]; slope 0.84 [95% CI, 0.75–0.95]), THRIVE-c (intercept 0.08 [95% CI, −0.02 to 0.17]; slope 0.71 [95% CI, 0.65–0.77]), Stroke Checkerboard score (intercept −0.05 [95% CI, −0.13 to 0.03]; slope 0.97 [95% CI, 0.88–1.08]), and MR PREDICTS (intercept 0.43 [95% CI, 0.33–0.52]; slope 0.93 [95% CI, 0.85–1.01]). Conclusions: The THRIVE-c score and MR PREDICTS both showed a good combination of discrimination and calibration and were, therefore, superior in predicting functional outcome for patients with ischemic stroke after endovascular treatment within 6.5 hours. Since models used different predictors and several models had relatively good predictive performance, the decision on which model to use in practice may also depend on simplicity of the model, data availability, and the comparability of the population and setting.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
seal发布了新的文献求助20
刚刚
焦糖开水发布了新的文献求助10
刚刚
刚刚
1秒前
无尘完成签到 ,获得积分10
1秒前
Orange应助的雅采纳,获得30
1秒前
1秒前
su完成签到,获得积分10
1秒前
saner完成签到,获得积分10
1秒前
冬月初七发布了新的文献求助10
2秒前
sg发布了新的文献求助10
3秒前
康恺发布了新的文献求助10
3秒前
HelloWORLD发布了新的文献求助10
3秒前
4秒前
北音发布了新的文献求助10
4秒前
慕青应助笑点低的人采纳,获得10
4秒前
4秒前
李大晴完成签到,获得积分20
4秒前
湘寳完成签到,获得积分10
4秒前
任性鞋垫完成签到,获得积分10
4秒前
5秒前
隐形曼青应助李wf采纳,获得10
5秒前
5秒前
wuli发布了新的文献求助10
6秒前
6秒前
lalala完成签到 ,获得积分10
6秒前
7秒前
7秒前
王大玉发布了新的文献求助10
7秒前
落尘完成签到,获得积分10
7秒前
小二郎应助焦糖开水采纳,获得10
7秒前
8秒前
木棉花糖发布了新的文献求助20
8秒前
白石人家应助飘逸问梅采纳,获得10
9秒前
CipherSage应助hys采纳,获得10
9秒前
勇敢牛牛发布了新的文献求助10
9秒前
yst发布了新的文献求助10
9秒前
9秒前
陈科发布了新的文献求助10
10秒前
顺利的紫槐完成签到,获得积分10
10秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Navigating Normative Orders. Interdisciplinary Perspectives 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7763569
求助须知:如何正确求助?哪些是违规求助? 9308000
关于积分的说明 20303407
捐赠科研通 7348373
什么是DOI,文献DOI怎么找? 3314043
关于科研通互助平台的介绍 2463776
邀请新用户注册赠送积分活动 2328148