Development and Validation of a Nomogram for Predicting Multiple Organ Dysfunction Syndrome in Low Birth Weight Infants with Early- Onset Sepsis

Background: Early-onset neonatal sepsis is one of the most common causes of multiple organ dysfunction syndrome (MODS) in newborns. The incidence of neonatal MODS is 14.6%, and the mortality rate reaches 75.4%. Low-birth-weight infants with early-onset sepsis face an even higher risk of death when complicated by MODS. Therefore, developing a predictive model to assess the likelihood of MODS in low-birth-weight infants with early-onset sepsis (EOS) has become a key focus in clinical research. Methods : Three hundred and seventy low-birth-weight infants diagnosed with EOS from January 2019 to January 2024 were involved in this study. The clinical features and pregnancy details of newborns in the MODS group and the non-MODS group were compared. Univariable and multivariable analyses were established sequentially to identify independent risk factors. Nomogram was developed using multivariable binary logistic regression analysis. the validity of the model is evaluated through discrimination and calibration performance. The model was internally validated using bootstrapping technique. Results: A total of 370 newborns were included in the analysis. Of the 370 newborns, 74 (20%) were in the MODS group. The study identified that gestational hypothyroidism ( OR = 4.009, P = 0.048, 95% CI : 0.010 – 15.910), glycemic lability ( OR = 7.707, P < 0.001, 95% CI : 3.019 –19.671), high‑sensitivity troponin T (hs‑TnT) ( OR = 1.014, P < 0.001, 95% CI : 1.009 – 1.019), blood lactic acid (Lac) ( OR = 1.375, P < 0.001, 95% CI : 1.196 – 1.581), and platelet count (PLT) <100×10^9/L ( OR = 3.263, P = 0.005, 95% CI : 1.416–7.517) were independent risk factors for MODS in low-birth-weight infants with EOS. The model had discriminatory power of 93.7% (95% CI : 0.903–0.971). The model retained excellent discrimination under internal. The sensitivity, specificity, and positive predictive value, negative predictive value of the model was 86.5%, 91.2%, 71.1%, and 96.4%, respectively. Conclusion: This study developed a risk scoring model using the gestational hypothyroidism, glycemic lability, hsTnT, Lac, and PLT<100×10ˆ9/L to predict MODS in low-birth-weight infants with EOS, presenting a sufficient predictive value and calibration.