A nomogram predictive model for factors influencing prognosis of acute ischemic stroke patients after intravenous thrombolysis.

Abstract

Aims: This study aimed to develop and validate a nomogram for the early prediction of prognosis in patients with acute ischemic stroke (AIS) following intravenous thrombolysis (IVT), to facilitate clinical decision-making.

Methods: This retrospective study included 393 consecutive AIS patients who underwent IVT between January 2021 to December 2023. Patients were classified into either a good or a poor prognosis group. Logistic regression analysis was performed to identify prognostic factors associated with clinical outcome, including medical records, laboratory findings, and independent risk factors. The independent factors were then used to construct a prognostic nomogram.

Results: Among the 393 AIS patients treated with IVT, 142 had a poor prognosis. Six independent predictors were identified: baseline National Institutes of Health Stroke Scale (NIHSS) score (95% CI: 1.133-1.229, P<0.001), B-type natriuretic peptide (95% CI: 1.044-1.532, P=0.036), age group (Group 1: 95% CI: 0.004-0.086, P<0.001; Group 2: 95% CI: 0.034-0.063, P=0.004), time from onset to thrombolysis (95% CI: 1.004-1.067, P=0.014), diabetes (95% CI: 0.315-0.887, P=0.016), and pre-thrombolysis prothrombin time (PT) (95% CI: 1.050-1.553, P=0.015). These factors were incorporated into a nomogram, which achieved an under the receiver operating characteristic curve (AUC-ROC) of 0.8075882, 95% CI (0.664-0.962).

Conclusion: We identified six independent prognostic factors for AIS patients after IVT, including NIHSS score, B-type natriuretic peptide, pre-thrombolysis PT, age, diabetes, and time from onset to thrombolysis. The developed nomogram demonstrated strong predictive performance and may aid clinicians in prognosis assessment for AIS patients receiving IVT.