Abstract Background and aims Mechanical thrombectomy (MT) improves outcomes in acute ischemic stroke due to large-vessel occlusion, yet in-hospital mortality remains substantial. We aimed to develop a clinically intuitive risk score—IMPACT-EVT—to predict in-hospital mortality after MT by integrating baseline clinical severity, neuroimaging tissue vulnerability, and early procedural outcomes. Methods IMPACT-EVT was derived from published multicenter registries (MR CLEAN, HERMES) and recent thrombectomy trials. Variables with independent associations to in-hospital mortality were selected: age, baseline NIHSS, admission hyperglycemia, ASPECTS, collateral status, infarct core volume on CTP/DWI, recanalization success (mTICI ≥2b), symptomatic intracranial hemorrhage (sICH), and NIHSS at 24 hours. Infarct core volume was stratified as 30 ml, 30–70 ml, and 70 ml. Each variable was assigned points proportional to effect sizes reported in the literature. Total scores (0–18) were stratified into four risk categories: Low (0–4), Moderate (5–8), High (9–12), Very High (≥13). Results Each domain independently contributed to mortality prediction. Baseline clinical factors, particularly age ≥80 and NIHSS 20, strongly influenced risk. Neuroimaging markers, including low ASPECTS, poor collaterals, and increasing core volume, enhanced discrimination. Procedural and early post-procedure factors, especially sICH and NIHSS at 24 h, were the most potent predictors. Risk categories corresponded with reported in-hospital mortality: Low (5%), Moderate (5–15%), High (20–40%), Very High (50%). Conclusions IMPACT-EVT provides a practical, literature-based framework for early in-hospital mortality risk stratification after MT. Incorporating quantitative infarct core volume improves prognostic accuracy. External validation is required prior to clinical implementation. Conflict of interest Nothing to disclose Figure 1 - belongs to Results
Hrynykha et al. (2026) studied this question.