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Updated: Oct 11, 2025

A Neonatal Imaging Model of Gram-Negative Bacterial Sepsis
Published on: August 12, 2020
Bacteria profiles and risk factors for proven early-onset sepsis in preterm neonates
1From the Department of Laboratory Medicine, Shengjing Hospital of China Medical University, Shenyang, China.
Objectives:
To fill this gap in the literature and establish a prediction model.
Methods:
This retrospective study was conducted in a Neonatal Intensive Care Unit between April 2018 and April 2019. Sixty-five sepsis cases were clinically diagnosed with early-onset neonatal sepsis (EONS) and confirmed by bacterial culture, and 91 newborns were enrolled as control. Multivariate analysis was used to analyze the data, and the predictive efficiency of the prediction model was verified using the Hosmer-Lemeshow goodness-of-fit test and receiver operating characteristic (ROC) curve.
Results:
There were differences in multiple gestation birth, cesarean section, gestational age, birth weight, Apgar scores at 1 and 5 minutes, and laboratory parameters including white blood cells, neutrophils, lymphocytes, platelets, C-reactive protein (CRP), procalcitonin (PCT), and interleukin-6 (IL-6) between the groups. Multivariable logistic analysis showed that the Apgar score at 5 minutes and CRP, PCT, and IL-6 levels remained independent significant predictors of EONS (p=0.002, p=0.020, p=0.002, p=0.021, respectively). According to multivariate logistic regression analysis, the risk prediction model was logit p=24.280-3.270 x Apgar score at 5 minutes + 1.396 x CRP + 3.409 x PCT + 0.034 x IL-6 (Lemeshow goodness-of-fit test p=0.143). Receiver operating characteristic curve analysis indicated that the area under the curve was 0.968 (95% confidence interval: 0.936-1.000, p<0.05), and the sensitivity was 90.8% and specificity was 97.8%.
Conclusion:
The Apgar score at 5 minutes and CRP, PCT, and IL-6 levels are risk factors for EONS. The risk prediction model is highly efficient in predicting EONS among preterm infants.
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