Four-factor nomogram for early-onset sepsis in preterm neonates: Development and internal validation of a stewardship tool.

Abstract

Early-onset sepsis (EOS) remains a leading cause of mortality and neurodevelopmental injury in preterm infants, yet widely used tools (e.g., Kaiser EOS Calculator) are not designed for <35-37 weeks' gestation. To develop and internally validate a concise, clinically interpretable nomogram for EOS risk stratification in preterm neonates and to evaluate its potential for antibiotic stewardship. We performed a single-center retrospective cohort study (July 2023-June 2024) including 1,059 preterm infants admitted within 72 h of birth, randomly split 7:3 into training (n = 742) and validation (n = 317). Forty-five maternal and neonatal candidates were screened (univariable tests, LASSO), followed by multivariable logistic regression to build the final model and nomogram. Discrimination (AUC), calibration (Brier score, calibration curve, Hosmer-Lemeshow), and decision-curve analysis (DCA) were assessed; two biologically plausible interactions were prespecified. Four routinely available variables-gestational age, birth weight, umbilical cord abnormality, and mechanical ventilation within 72 h-composed the final model. In the validation cohort, AUC was 0.818 (95% CI, 0.767-0.868), Brier score 0.158, and Hosmer-Lemeshow P = 0.71; DCA showed net benefit across 5-65% risk thresholds. Using a ≥ 0.70 treatment threshold, the model identified 88% of EOS cases while recommending antibiotics for ~10% of infants. A culture-proven-only sensitivity analysis yielded comparable discrimination (AUC 0.819) with a Brier score 0.041. A four-factor nomogram using EMR-available variables accurately stratifies EOS risk in preterm infants and may support risk-based antibiotic decisions while limiting overtreatment. Prospective multicenter external validation is warranted to confirm generalizability and guide implementation.