Machine Learning Prediction of 6-Month Functional Outcomes in IVH Using the Brainstem Dorsal Line: A Multicenter Study
Journal:
medRxiv
Published Date:
Jul 30, 2026
Abstract
[Abstract] 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.
