Prediction model for unfavorable treatment outcome for complicated sever acute malnutrition (SAM) in under five children admitted in hospitals at Amhara Region.

ABSTRACT:

Background

Severe acute malnutrition (SAM) affects 45 million children worldwide, with 14.89% of Ethiopian children under five suffering from it. This study validates a prediction model and develops risk scores for unfavorable treatment outcomes in SAM patients, addressing the scarcity of risk assessment tools in low-income settings and providing clinicians with a practical tool to improve decision-making.

Methods

A cohort study was conducted among 915 SAM children hospitalized with SAM hospitals in Amhara Region. Data analysis was conducted using STATA 17 and R 4.4.1. A lasso-selected multivariable model developed a nomogram for clinical utility. Model performance was assessed via AUC, calibration plot and validated with bootstrapping. Decision curve analysis evaluated the

SUBMITTER: Yeshiwas AG 

PROVIDER: S-EPMC11847673 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature