RT Journal Article
SR Electronic
T1 Pretreatment predictors of malignant evolution in patients with ischemic stroke undergoing mechanical thrombectomy
JF Journal of NeuroInterventional Surgery
JO J NeuroIntervent Surg
FD BMJ Publishing Group Ltd.
SP neurintsurg-2017-013224
DO 10.1136/neurintsurg-2017-013224
A1 Alessandro Davoli
A1 Caterina Motta
A1 Giacomo Koch
A1 Marina Diomedi
A1 Simone Napolitano
A1 Angela Giordano
A1 Marta Panella
A1 Daniele Morosetti
A1 Sebastiano Fabiano
A1 Roberto Floris
A1 Roberto Gandini
A1 Fabrizio Sallustio
YR 2017
UL http://jnis.bmj.com/content/early/2017/08/05/neurintsurg-2017-013224.abstract
AB Background 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.Methods 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.Results 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%).Conclusions 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.