Development of a Simple Clinical Score to Predict Early Neurological Improvement after Mechanical Thrombectomy: A Single-Centre Cohort Study

Background Early neurological improvement (ENI) after endovascular thrombectomy (EVT) is strongly associated with long-term functional outcome, but simple bedside tools to predict ENI are limited. We aimed to develop and internally evaluate a pragmatic clinical model and simplified risk score for ENI after EVT. Methods We conducted a single-centre retrospective cohort study including consecutive patients with acute ischemic stroke who underwent emergency mechanical thrombectomy at Shanxi Provincial People’s Hospital between January 2020 and December 2022. ENI was defined as a decrease in NIHSS ≥ 8 points or NIHSS ≤ 1 at day 7. Candidate predictors included age, sex, baseline NIHSS, diabetes, cardioembolic etiology, prior cerebrovascular disease and door-to-puncture time (DPT, including DPT > 12 h). Multivariable logistic regression was used to build a full prediction model. A simplified bedside score based on NIHSS strata, diabetes and cardioembolic etiology was derived from model coefficients. Calibration, Brier score, and decision curve analysis (DCA) were assessed, and internal validation was performed using bootstrap resampling (1,000 repetitions) to obtain optimism-corrected performance estimates. Results A total of 185 patients were included, of whom 53 (28.6%) achieved early neurological improvement (ENI). In multivariable logistic regression, baseline NIHSS was the dominant predictor of ENI, whereas the incremental effects of other candidate predictors were modest. The full model (Model 2) showed an apparent AUC of 0.706 and an optimism-corrected AUC of 0.657 after 1,000 bootstrap resamples; the Brier score was 0.181 (apparent) and 0.197 (optimism-corrected). The simplified bedside score demonstrated an apparent and optimism-corrected AUC of 0.677, while the NIHSS-only model yielded an apparent AUC of 0.673 and an optimism-corrected AUC of 0.674. Bootstrap-corrected calibration of the full model suggested some overfitting (intercept − 0.335, slope 0.591), whereas the simplified score showed acceptable calibration (intercept − 0.108, slope 0.893). Decision curve analysis indicated that the full model and simplified score provided net benefit over treat-all and treat-none across clinically relevant threshold probabilities. Conclusions A parsimonious clinical model and a simplified bedside score based on baseline NIHSS category and cardioembolic aetiology provided moderate discrimination for ENI after EVT; external validation is warranted.External validation in larger multicentre cohorts is warranted.