Development and Validation of a Diagnostic Prediction Model for Neonatal Sepsis in a Low-Resource Setting, Ethiopia.

ABSTRACT:

Background

Neonatal sepsis remains a major cause of preventable neonatal mortality globally, yet diagnosis remains difficult in low-resource settings due to the inaccessibility and the long turnaround time of blood culture. Clinical prediction models can support the early detection and management of sepsis.

Objective

To develop and internally validate a diagnostic prediction model for the diagnosis of neonatal sepsis in a low-resource setting, Ethiopia.

Methods

An institution-based cross-sectional study was conducted from January 2022 to December 2024. We collected data through medical record review among 607 newborns with suspected sepsis. Predictors were selected using the least absolute shrinkage and selection operator (LASSO) and then subjected to multivariable lo

SUBMITTER: Teshager NW 

PROVIDER: S-EPMC12662916 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature