BACKGROUND: The applicability of the current models for predicting functional outcome after thrombectomy in strokes with large vessel occlusion (LVO) is affected by a moderate predictive performance.
AIMS: We aimed to develop and validate a nomogram with pre- and post-treatment factors for prediction of the probability of unfavorable outcome in patients with anterior and posterior LVO who received bridging therapy or direct thrombectomy <6 h of stroke onset.
METHODS: We conducted a cohort study on patients data collected prospectively in the Italian Endovascular Registry (IER). Unfavorable outcome was defined as three-month modified Rankin Scale (mRS) score 3-6. Six predictors, including NIH Stroke Scale (NIHSS) score, age, pre-stroke mRS score, bridging therapy or direct thrombectomy, grade of recanalization according to the thrombolysis in cerebral ischemia (TICI) grading system, and onset-to-end procedure time were identified a priori by three stroke experts. To generate the IER-START, the pre-established predictors were entered into a logistic regression model. The discriminative performance of the model was assessed by using the area under the receiver operating characteristic curve (AUC-ROC).
RESULTS: A total of 1802 patients with complete data for generating the IER-START was randomly dichotomized into training ( n = 1219) and test ( n = 583) sets. The AUC-ROC of IER-START was 0.838 (95% confidence interval [CI]): 0.816-0.869) in the training set, and 0.820 (95% CI: 0.786-0.854) in the test set.
CONCLUSIONS: The IER-START nomogram is the first prognostic model developed and validated in the largest population of stroke patients currently candidates to thrombectomy which reliably calculates the probability of three-month unfavorable outcome.