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

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. A retrospective study was conducted from 1 October 2018 to 31 March 2023 in a large tertiary hospital in China. Neonates were divided...

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Bibliographic Details
Published in:Scientific reports 2024-03, Vol.14 (1), p.5629-5629, Article 5629
Main Authors: Wu, Mengqi, Deng, Yanbing, Wang, Xinye, He, Baomei, Wei, Fangqiang, Zhang, Ying
Format: Article
Language:English
Subjects:
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Adult
Diabetes mellitus
Female
Group B Streptococcus
Humanities and Social Sciences
Humans
Infant, Newborn
Intrapartum antibiotic prophylaxis (IAP)
Male
multidisciplinary
Neonatal infection
Neonatal Sepsis - diagnosis
Neonatal Sepsis - epidemiology
Neonates
Nomogram prediction model
Nomograms
Patients
Prediction models
Regression analysis
Retrospective Studies
Risk Factors
Science
Science (multidisciplinary)
Sepsis
Sepsis - diagnosis
Sepsis - epidemiology
Sepsis - etiology
Streptococcus
Streptococcus infections
Umbilical cord
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Summary: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. A retrospective study was conducted from 1 October 2018 to 31 March 2023 in a large tertiary hospital in China. Neonates were divided into patients and controls based on the occurrence of neonatal sepsis. A multivariable model was used to determine risk factors and construct models.The utilization and assessment of model presentation were conducted using Norman charts and web calculators, with a focus on model differentiation, calibration, and clinical applicability (DCA). Furthermore, the hospital’s data from 1 April 2023 to 1 January 2024 was utilized for internal validation. In the modelling dataset, 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 
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-55783-2