Relevance of Brain Regions' Eloquence Assessment in Patients With a Large Ischemic Core Treated With Mechanical Thrombectomy

逻辑回归 医学 改良兰金量表 灌注 冲程(发动机) 临床意义 内科学 缺血性中风 核医学 心脏病学 灌注扫描 缺血 机械工程 工程类
作者
Basile Kerleroux,Joseph Benzakoun,Kévin Janot,Cyril Dargazanli,Dimitri Daly Eraya,Wagih Ben Hassen,François Zhu,Benjamin Gory,Jean‐François Hak,Charline Perot,Lili Détraz,Romain Bourcier,Rouchaud Aymeric,Géraud Forestier,Gaultier Marnat,Florent Gariel,Pasquale Mordasini,Pierre Seners,Guillaume Turc,Johannes Kaesmacher
出处
期刊:Neurology [Lippincott Williams & Wilkins]
卷期号:97 (20): e1975-e1985 被引量:16
标识
DOI:10.1212/wnl.0000000000012863
摘要

Objective Individualized patient selection for mechanical thrombectomy (MT) in patients with acute ischemic stroke (AIS) and large ischemic core (LIC) at baseline is an unmet need. We tested the hypothesis that assessing the functional relevance of both infarcted and hypoperfused brain tissue would improve the selection framework of patients with LIC for MT. Methods We performed a multicenter, retrospective study of adults with LIC (ischemic core volume >70 mL on MRI diffusion-weighted imaging) with MRI perfusion treated with MT or best medical management (BMM). Primary outcome was 3-month modified Rankin Scale (mRS), favorable if 0–3. Global and regional eloquence-based core perfusion mismatch ratios were derived. The predictive accuracy for clinical outcome of eloquent regions involvement was compared in multivariable and bootstrap random forest models. Results A total of 138 patients with baseline LIC were included (MT n = 96 or BMM n = 42; mean age ± SD, 72.4 ± 14.4 years; 34.1% female; mRS 0–3: 45.1%). Mean core and critically hypoperfused volume were 100.4 mL ± 36.3 mL and 157.6 ± 56.2 mL, respectively, and did not differ between groups. Models considering the functional relevance of the infarct location showed a better accuracy for the prediction of mRS 0–3 with a c statistic of 0.76 and 0.83 for logistic regression model and bootstrap random forest testing sets, respectively. In these models, the interaction between treatment effect of MT and the mismatch was significant (p = 0.04). In comparison, in the logistic regression model disregarding functional eloquence, the c statistic was 0.67 and the interaction between MT and the mismatch was insignificant. Conclusions Considering functional eloquence of hypoperfused tissue in patients with a large infarct core at baseline allows for a more precise estimation of treatment expected benefit. Classification of Evidence This study provides Class II evidence that, in patients with AIS and LIC, considering the functional eloquence of the infarct location improves prediction of disability status at 3 months.
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