Department of Neuroscience, Comprehensive Stroke Center, University of Tor Vergata, Rome, Italy.
Santa Lucia Foundation, Rome, Italy.
J Neurointerv Surg. 2018 Apr;10(4):340-344. doi: 10.1136/neurintsurg-2017-013224. Epub 2017 Aug 10.
Few data exist on malignant middle cerebral artery infarction (MMI) among patients with acute ischemic stroke (AIS) after endovascular treatment (ET). Numerous predictors of MMI evolution have been proposed, but a comprehensive research of patients undergoing ET has never been performed. Our purpose was to find a practical model to determine robust predictors of MMI in patients undergoing ET.
Patients from a prospective single-center database with AIS secondary to large intracranial vessel occlusion of the anterior circulation, treated with ET, were retrospectively analyzed. We investigated demographic, clinical, and radiological data. Multivariate regression analysis was used to identify clinical and imaging predictors of MMI.
98 patients were included in the analysis, 35 of whom developed MMI (35.7%). No differences in the rate of successful reperfusion and time from stroke onset to reperfusion were found between the MMI and non-MMI groups. The following parameters were identified as independent predictors of MMI: systolic blood pressure (SBP) on admission (p=0.008), blood glucose (BG) on admission (p=0.024), and the CTangiography (CTA) Alberta Stroke Program Early CT Score (ASPECTS) (p=0.001). A scoreof ≤5 in CTA ASPECTS was the best cut-off to predict MMI evolution (sensitivity 46%; specificity 97%; positive predictive value 78%; negative predictive value 65%).
in our study a clinical and radiological features-based model was strongly predictive of MMI evolution in AIS. High SBP and BG on admission and, especially, a CTA ASPECTS ≤5 may help to make decisions quickly, regardless of time to treatment and successful reperfusion.
在接受血管内治疗(ET)的急性缺血性卒中(AIS)患者中,恶性大脑中动脉梗死(MMI)的数据很少。已经提出了许多 MMI 演变的预测因素,但从未对接受 ET 的患者进行过全面研究。我们的目的是找到一种实用的模型,以确定接受 ET 的患者发生 MMI 的可靠预测因素。
回顾性分析了来自前瞻性单中心数据库的 AIS 患者,这些患者由于前循环大颅内血管闭塞而继发于 AIS,接受了 ET 治疗。我们调查了人口统计学、临床和影像学数据。采用多变量回归分析来确定 MMI 的临床和影像学预测因素。
98 例患者纳入分析,其中 35 例发生 MMI(35.7%)。MMI 组和非 MMI 组之间成功再灌注率和从卒中发病到再灌注的时间没有差异。以下参数被确定为 MMI 的独立预测因素:入院时的收缩压(SBP)(p=0.008)、入院时的血糖(BG)(p=0.024)和 CT 血管造影(CTA)Alberta 卒中计划早期 CT 评分(ASPECTS)(p=0.001)。CTA ASPECTS 评分≤5 是预测 MMI 演变的最佳截断值(敏感性 46%;特异性 97%;阳性预测值 78%;阴性预测值 65%)。
在我们的研究中,基于临床和影像学特征的模型强烈预测了 AIS 中 MMI 的演变。入院时的 SBP 和 BG 较高,尤其是 CTA ASPECTS≤5,可能有助于快速做出决策,而与治疗时间和再灌注成功无关。