Development and Validation of a Machine Learning–Based Model for Predicting 6-Month Functional Outcomes in Patients with Intraventricular Hemorrhage Using the Brainstem Dorsal Line: A Multicenter Retrospective Cohort Study
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Objective
Intraventricular haemorrhage (IVH) carries high mortality and morbidity; accurate early prediction of 6-month functional outcome is essential for guiding treatment decisions and optimising prognosis. We developed and externally validated a prognostic model that integrates a novel neuroimaging marker, the Brainstem Dorsal Line (BSDL), with the TabICLv2 algorithm to predict 6-month functional outcomes after IVH.
Methods
In this multicentre retrospective study, patients with IVH were enrolled from nine tertiary centres in China between Dec 1, 2020, and Dec 31, 2024; seven centres constituted the derivation cohort (8:2 training–validation split), and two centres formed the external validation cohort. Feature selection followed a three-step pipeline comprising univariable testing, Spearman correlation analysis, and LASSO regression; eight machine-learning models were trained with five-fold cross-validated hyperparameter tuning. Performance was assessed by the area under the receiver operating characteristic curve (AUC), the area under the precision–recall curve (AUPRC), calibration curves, and decision curve analysis (DCA). Interpretability was evaluated using SHapley Additive exPlanations (SHAP).
Results
In total, 728 eligible patients were enrolled — 610 in the derivation cohort (unfavourable outcome, 27·9%) and 118 in the external validation cohort (26·3%). Feature selection identified nine optimal predictors, of which BSDL grade 2 ranked highest in feature importance. TabICLv2 showed the best performance in external validation (AUC 0·9014 [95% CI 0·825–0·985], AUPRC 0·8192 [0·688–0·916], F1 score 0·7742 [0·651–0·877]); calibration was excellent (Hosmer– Lemeshow test, P>0·05) and DCA showed clinical net benefit across threshold probabilities of 0·05–0·97. SHAP confirmed BSDL grade 2 as the strongest predictor of unfavourable outcome.
Conclusions
Integrating BSDL with TabICLv2 yielded a robust, interpretable prognostic model for 6-month outcomes after IVH, providing a practical tool for early risk stratification and individualised treatment planning.
