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September 10, 2025npj Digital MedicineOpen Access

Machine learning based CAGIB score predicts in-hospital mortality of cirrhotic patients with acute gastrointestinal bleeding

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Prospective study validates CAGIB score predicting in-hospital mortality in cirrhotic patients with AGIB, indicating effective risk stratification.

CAGIB score effectively predicts in-hospital mortality, with the LS-SVMR model achieving an AUC of 0.986.
In-hospital mortality rates among risk groups were 0.38% for low, 2.22% for moderate, and 64.37% for high risk.
This international multi-center study involved 2467 cirrhotic patients with AGIB to validate the CAGIB score.
The LS-SVMR model demonstrates strong predictive performance, supporting its potential clinical application.

Bai et al. (2025) studied this question.

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Prospective study validates CAGIB score predicting in-hospital mortality in cirrhotic patients with AGIB, indicating effective risk stratification.