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岛叶梗塞>25%是大脑中动脉近端梗塞大不匹配损失的最强预测因子。

Admission insular infarction >25% is the strongest predictor of large mismatch loss in proximal middle cerebral artery stroke.

机构信息

From the Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA.

出版信息

Stroke. 2013 Nov;44(11):3084-9. doi: 10.1161/STROKEAHA.113.002260. Epub 2013 Aug 29.

DOI:10.1161/STROKEAHA.113.002260
PMID:23988643
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3894265/
Abstract

BACKGROUND AND PURPOSE

Previous univariate analyses have suggested that proximal middle cerebral artery infarcts with insular involvement have greater severity and are more likely to progress into surrounding penumbral tissue at risk. We hypothesized that a practical, simple scoring method to assess percent insular ribbon infarction (PIRI score) would improve prediction of penumbral loss over other common imaging biomarkers.

METHODS

Of consecutive acute stroke patients from 2003 to 2008, 45 with proximal middle cerebral artery-only occlusion met inclusion criteria, including available penumbral imaging. Infarct (diffusion-weighted imaging), tissue at risk (magnetic resonance mean transit time), and final infarct volume (magnetic resonance/computed tomography) were manually segmented. Diffusion-weighted imaging images were rated according to the 5-point PIRI score (0, normal; 1, <25%; 2, 25%-49%; 3, 50%-74%; 4, ≥75% insula involvement). Percent mismatch loss was calculated as an outcome measure of infarct progression. Receiver operating characteristic curve and multivariate analyses were performed.

RESULTS

Mean admission diffusion-weighted imaging infarct volume was 30.9 (±38.8) mL and median (interquartile range) PIRI score was 3 (0.75-4). PIRI score was significantly correlated with percent mismatch loss (P<0.0001). When percent mismatch loss was dichotomized based on its median value (30.0%), receiver operating characteristic curve area under curve was 0.89 (P=0.0001) with a 25% insula infarction optimal threshold. After adjusting for time to imaging and treatment, binary logistic regression, including dichotomized PIRI (25% threshold), age, National Institutes of Health Stroke Scale score, diffusion-weighted imaging infarct volume, and computed tomography angiography collateral score as covariates, revealed that only dichotomized insula score (P=0.03) and age (P=0.02) were independent predictors of large (68.2%) versus small (8.1%) mismatch loss. There was excellent interobserver agreement for dichotomized PIRI scoring (κ=0.91).

CONCLUSIONS

Admission insular infarction >25% is the strongest predictor of large mismatch loss in this cohort of proximal middle cerebral artery occlusive stroke. This outcome marker may help to identify treatment-eligible patients who are in greatest need of rapid reperfusion therapy.

摘要

背景与目的

既往的单变量分析表明,伴有岛叶受累的近端大脑中动脉梗死患者的病情更严重,更有可能进展为周围有风险的半暗带组织。我们假设一种实用、简单的评估岛叶带梗死百分比的评分方法(PIRI 评分),可以提高对缺血半暗带丢失的预测能力,优于其他常见的影像学生物标志物。

方法

2003 年至 2008 年间,连续入组的急性脑卒中患者中有 45 例符合近端大脑中动脉闭塞且有可用的缺血半暗带影像学检查,纳入本研究。采用手动分割方法对梗死(弥散加权成像)、组织缺血(磁共振平均通过时间)和最终梗死体积(磁共振/计算机断层扫描)进行分割。根据 5 分 PIRI 评分(0 分,正常;1 分,<25%;2 分,25%-49%;3 分,50%-74%;4 分,≥75%岛叶受累)对弥散加权成像图像进行评分。计算梗死进展的失配百分比损失作为结局指标。进行受试者工作特征曲线和多变量分析。

结果

平均入院时弥散加权成像梗死体积为 30.9(±38.8)mL,中位数(四分位间距)PIRI 评分为 3(0.75-4)。PIRI 评分与失配百分比损失显著相关(P<0.0001)。当根据其中位数(30.0%)将失配百分比损失分为两组时,受试者工作特征曲线下面积为 0.89(P=0.0001),岛叶梗死 25%的阈值为最佳截断值。调整成像和治疗时间后,将二元逻辑回归纳入作为协变量的二分类 PIRI(25%阈值)、年龄、国立卫生研究院卒中量表评分、弥散加权成像梗死体积和计算机断层血管造影侧支评分,发现只有二分类岛叶评分(P=0.03)和年龄(P=0.02)是大(68.2%)与小(8.1%)失配损失的独立预测因素。二分类 PIRI 评分的观察者间一致性极好(κ=0.91)。

结论

入院时岛叶梗死>25%是本队列近端大脑中动脉闭塞性卒中大失配损失的最强预测因子。这种结局标志物可能有助于识别最需要快速再灌注治疗的治疗合格患者。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e265/3894265/2b8ef45696bf/nihms518821f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e265/3894265/6a832b32ecd1/nihms518821f1a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e265/3894265/624b31a4957d/nihms518821f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e265/3894265/2b8ef45696bf/nihms518821f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e265/3894265/6a832b32ecd1/nihms518821f1a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e265/3894265/624b31a4957d/nihms518821f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e265/3894265/2b8ef45696bf/nihms518821f3.jpg

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