Abstract
Brainstem hemorrhage is a severe neurological condition with high mortality and poor prognosis. This study aims to develop and validate a prognostic model for brainstem hemorrhage to facilitate early prediction of patient outcomes, thereby supporting clinical decision-making. Clinical data from 140 patients with brainstem hemorrhage were collected. A prognostic model was constructed through multivariate logistic regression analysis, and a nomogram was developed for clinical use. The model's performance was evaluated using ROC curves, PR curves, and calibration curves, and was validated through cross-validation and an independent validation cohort. Additionally, decision curve analysis was conducted to assess the model's clinical benefit. The study identified hematoma expansion (adjusted OR = 12.92, 95% CI: 2.39-69.79, P = 0.003), GCS score (adjusted OR = 0.77, 95% CI: 0.63-0.93, P = 0.008), hematoma type (OR = 8.01, 95% CI: 2.02-31.78, P = 0.003), and hematoma volume (OR = 1.75, 95% CI: 1.26-2.43, P = 0.001) as independent risk factors for poor prognosis in patients with brainstem hemorrhage. The nomogram prognostic model demonstrated excellent performance in predicting clinical outcomes, with an AUC of 0.95, outperforming individual predictors (volume: 0.94, type: 0.8, GCS: 0.78, expansion: 0.59). Calibration curves showed a high degree of agreement between the model and the ideal curve. Moreover, decision curve analysis indicated that the model provided significant net clinical benefit. This nomogram can effectively provide a basis for prognostic judgment in brainstem hemorrhage, helping clinicians optimize treatment decisions and improve patient outcomes.