• Jingwen Hu and Xiaosong Qin.
• From the Department of Laboratory Medicine, Shengjing Hospital of China Medical University, Shenyang, China.
• Saudi Med J. 2021 Dec 1; 42 (12): 1281-1288.

ObjectivesTo fill this gap in the literature and establish a prediction model.MethodsThis 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.ResultsThere 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%.ConclusionThe 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.Copyright: © Saudi Medical Journal.

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