Outcome prediction in patients treated with endovascular thrombectomy for acute stroke

BACKGROUND AND PURPOSE: Prognosticating patients following mechanical thrombectomy has proven challenging for clinicians within the last decade. Several scoring paradigms have subsequently been developed with the aim of aiding providers in predicting outcomes in patients status post neuro-intervention for acute ischemic stroke. The purpose of this study is to develop and validate a condensed algorithm to predict outcomes in patients 90 days post thrombectomy for acute ischemic stroke of the proximal anterior circulation.

METHODS: A retrospective chart review of 75 patients who presented to our institution with emergent large vessel occlusion of the anterior proximal circulation was performed. Five independent variables, Age, Initial NIHSS & TICI, Post-Thrombectomy NIHSS & TICI, delta NIHSS, were identified and regressed logistically upon binary outcomes defined by functional status according to the modified Rankin scale. The data was validated using JROCFIT and JLABROC4 programs for fitting receiver operating characteristic curves using the maximum likelihood fit.

RESULTS: A statistically significant relationship was identified in two of the five independent variables analyzed in the study. Post-thrombectomy NIHSS and Age were found to be the strongest independent predictors of functional status at 90 days post-neurointervention for acute ischemic stroke. The data was validated with ROC curves and area under the curve (AUC).

CONCLUSIONS: The binary logistic regression model in our study accurately predicts 90 day outcomes in patients status post mechanical thrombectomy for acute ischemic stroke. Post-thrombectomy NIHSS and age are the only mandatory covariates required to make an accurate prognosis in these patients.

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