Development and validation of a risk score to predict mortality in the pediatric intensive care unit using routinely collected data in Northwest Ethiopia: a retrospective study

Development and validation of a risk score to predict mortality in the pediatric intensive care unit using routinely collected data in Northwest Ethiopia: a retrospective study. Download PDF Abstract Early prediction of mortality in critically ill patients is essential for informed clinical decision-making, effective risk stratification, and optimal resource allocation. Most existing pediatric-specific mortality prediction models, however, depend on extensive laboratory testing and advanced monitoring and intervention tools, which limit their applicability in resource-limited settings.

To develop and internally validate a mortality risk score for pediatric patients admitted to the intensive care unit (ICU). A retrospective cohort study of 565 pediatric patients in northwest Ethiopia was conducted. Data were extracted from medical records using a structured data abstraction tool developed in Kobo Toolbox V2024.2.S.

Descriptive statistics, including mean, median, and standard deviation, were summarized and presented in text and tables. The least absolute shrinkage and selection operator (LASSO) was used to select variables for the multivariable logistic regression model. The reduced model’s performance was evaluated using sensitivity, specificity, Brier score, and area under the curve (AUC).

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