Development of risk prediction nomogram for neonatal sepsis in Group B Streptococcus-colonized mothers: A retrospective study

Background: Neonatal clinical sepsis is recognized as a significant health problem, This study sought to identify a predictive model of risk factors for clinical neonatal sepsis. Methods: From October 2018 to April 2023, a retrospective study of maternal-newborn dichotomy was conducted in a large tertiary hospital in China. Neonates were divided into patients and controls according to whether neonatal sepsis occurred. A multivariable model was used to determine risk factors and construct models. Results: A total of 339 pairs of mothers and their newborns were included in the study and divided into two groups: patients (n = 84, 24.78%) and controls (n = 255, 75.22%). Logistic regression analysis was performed to examine the relationship between various factors and outcome. The results showed that maternal age ＜26 years (odds ratio [OR] = 2.16, 95% confidence interval [CI] 1.06–4.42, p = 0.034), maternal gestational diabetes (OR 2.17, 95%CI 1.11–4.27, p = 0.024), no forceps assisted delivery (OR 0.21, 95%CI 0. 05–0.80, p = 0.023 ), no umbilical cord winding (OR 0.57, 95%CI 0.34–0.98, p = 0.041 ) and male neonatal sex (OR 1.59, 95%CI 1.00–2.62, p = 0.050 ) were identified as independent factors influencing the outcome of neonatal clinical sepsis. A main effects model was developed incorporating these five significant factors, resulting in an area under the curve (AUC) value of 0.71 (95% CI: 0.63–0.77) for predicting the occurrence of neonatal clinical sepsis. Conclusion: A main effects model incorporating the five significant factors was constructed to help healthcare professionals make informed decisions and improve clinical outcomes.