Prognostic yield of imaging before and after recanalization treatments in ischemic stroke.

Objectives: The scores to predict outcome in ischemic stroke were validated prior to the approval of modern revascularization treatments. We evaluated the accuracy of pre and post-treatment models in a recent recanalization therapy cohort and whether radiological and ultrasound findings could improve their accuracy.

Material & Methods: We included 375 anterior circulation ischemic stroke patients treated with intravenous thrombolysis or thrombectomy during 2017 and 2018. We collected demographic, clinical, and imaging data. We built pre and post-treatment logistic regression models to predict independence (modified Rankin Scale 0-2) at 3 months. The models included the Alberta Stroke Program Early CT Score (ASPECTS), infarct volume (ABC/2 method), and the Thrombolysis in Brain Ischemia (TIBI) ultrasonographic grade of recanalization. We compared areas under the receiver operating characteristic curve (AUC).

Results: Our preintervention model, combining neurological deficit severity, age, and admission glycemia, was not improved by the inclusion of ASPECTS (AUC 0.80 vs 0.79, P = .28). Early neurological recovery at 24-hour significantly increased prognostic performance (AUC = 0.85, P < .01), which did not change by adding final infarct volume or the persistence of arterial occlusion of the affected territory (AUC = 0.86 and 0.85, P > .05).

Conclusions: Models that combine simple variables such as neurological deficit severity, age, and admission glycemia were the most useful for predicting functional outcome in ischemic stroke patients submitted to revascularization treatments. Pre and post-treatment imaging findings did not enhance prognostic accuracy when compared to the patient's clinical improvement.