ArticleFrontiers in neurology2026
A decision tree model for hematoma expansion prediction in women after spontaneous intracerebral hemorrhage.
Article in Frontiers in neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Women are at a higher risk of poor outcomes following spontaneous intracerebral hemorrhage (ICH) compared to men, necessitating closer clinical monitoring. Preventing hematoma expansion (HE) represents a promising therapeutic target in the management of spontaneous ICH. This study aimed to develop a clinically practical decision tree model to predict HE in women. Methods: We retrospectively reviewed women with spontaneous ICH. All patients underwent initial and follow-up non-contrast CT scans within 6 h and 72 h after symptom onset, respectively. Univariate and multivariate logistic regression analyses were used to identify independent predictors of HE. A decision tree model was developed for HE prediction. Results: A total of 417 patients were included, with 64 (15.3%) exhibiting HE on follow-up imaging. Multivariate analysis revealed that midline shift (odds ratio [OR], 1.18; 95% confidence interval [CI], 1.07-1.30; Conclusion: We developed a simple, interpretable decision tree model to predict HE in women. This tool may support clinicians in identifying high-risk patients and guiding timely interventions.
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