Abstract
AIMS: To develop and validate a user-friendly scale for predicting acute-phase adverse outcomes in acute ischemic stroke (AIS), thereby optimizing clinical management. METHODS: This retrospective study enrolled AIS patients within 72 h of onset (excluding thrombectomy), stratified according to thrombolysis status to develop treatment-specific prognostic models. The prognostic scale of AIS acute stage based on treatment stratification (PAIST) was developed using clinical variables, with discharge mRS as the primary endpoint, followed by external validation. RESULTS: A total of 1971 AIS patients (437 thrombolyzed) were included. Both thrombolysis-specific and non-thrombolysis-specific models incorporated core predictors (baseline NIHSS, deep vein thrombosis, neuron specific enolase, neutrophil percentage) but differed in cut-off values and weightings. Additionally, the non-thrombolysis-specific model integrated three extra variables: age, fasting blood glucose, and serum potassium. External validation demonstrated PAIST outperformed the benchmark model (AUCs: thrombolysis group 0.759 vs. 0.698; non-thrombolysis group 0.850 vs. 0.801; all p ≤ 0.05). PAIST-based risk stratification effectively identified high-risk patients, with poor prognosis rates of 76.92% (thrombolysis group) and 61.11% (non-thrombolysis group). CONCLUSION: The PAIST scale is an effective and practical tool for acute-phase prognostic risk stratification in AIS. Its treatment-stratified design enables accurate risk assessment, thereby supporting individualized clinical decision-making.