Validation of a risk-prediction model for pediatric post-discharge mortality after hospital admission for infection in Rwanda: A prospective cohort study.

ABSTRACT: Mortality following hospital discharge remains a significant threat to child health, particularly in resource-limited settings. The Smart Discharges risk-prediction models use simple clinical, socio-behavioral, and point-of-care lab test variables to successfully predict children at the highest risk of death after hospital admission for infection to guide a risk-based approach to post-discharge care. In Rwanda, we externally validated five models derived from the prior Smart Discharges Uganda studies in a new cohort of children ages 0 days to 60 months admitted for suspected sepsis at two hospitals. We evaluated model performance using metrics including area under the receiver operating characteristic curve (AUROC), Brier score, and test characteristics (e.g., sensitivity, specificity). Pe

SUBMITTER: Hooft A 

PROVIDER: S-EPMC12212559 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature