Prognosis prediction of neonatal early-onset sepsis by constructing predictors based on logistic regression model

Yi Wang; Jiahao Tian; Xiaojing Tang; Xuefeng Yang; Huiping Zhang

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Prognosis prediction of neonatal early-onset sepsis by constructing predictors based on logistic regression model

VernacularTitle:基于logistic回归模型构建预测新生儿早发败血症预后的相关模型
Author: Yi WANG ¹ ; Jiahao TIAN ; Xiaojing TANG ; Xuefeng YANG ; Huiping ZHANG
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1. 西安交通大学附属儿童医院新生儿重症医学科，西安　710003
Keywords: Logistic models; Neonatal sepsis; Prognosis
From: Journal of Chinese Physician 2022;24(3):415-419
CountryChina
Language:Chinese
Abstract: Objective:A clinical prediction model was constructed based on the related factors affecting neonatal early-onset sepsis (EOS).Methods:A retrospective study was conducted. The patients with EOS amditted to the neonatal intensive care unit of Children′s Hospital Affiliated to Xi′an Jiaotong University from April 2015 to April 2020 were enrolled. The demographic data and the clinical indicators within 8 hours after admission were collected. The death 7 days after admission was taken as the end event. The differences of various indexes between the survival group and the death group were compared. After univariate analysis of the indexes that may have an impact on the prognosis, binary logistic regression analysis was performed; The predictive model was established for the factors that may affect the prognosis; the predictive value of the relevant models was analyzed by recevier operating characteristic (ROC) curve, and the model was verified by independent clinical medical records.Results:A total of 139 children were enrolled, and 41 died within 7 days, with a fatality rate of 29.50%. Compared with the survival group, the dead group had higher white blood cells (WBC), serum procalcitonin (PCT), lactic acid (Lac), creatinine (Scr), D-dimer and Paediatric Risk of Mortality (PRISM) score {WBC(×10 9/L): 24.15[4.36, 29.36] vs 21.21[19.14, 28.36], PCT: (67.32±40.36)ng/L vs (37.76±25.11)ng/L, Lac: (8.69±6.17)mmol/L vs (2.34±1.11)mmol/L, Scr: (239.99±68.46)μmol/L vs (65.31±34.34)μmol/L, D-dimer(mg/L): 5.21[2.06, 21.49] vs 0.34[0.26, 0.45], PRISM Ⅲ: (19.52±6.25)s vs (10.63±2.05)s, all P<0.05}, and lower fibrinogen (Fib), platelet count (PLT) and hemoglobin concentration (Hb) [Fib: (1.48±1.19)g/L vs (2.44±0.83)g/L, PLT: (154±58)×10 9/L vs (189±29)×10 9/L, Hb: (169±49)g/L vs (182±52)g/L, all P<0.05]. The incidence of placental/umbilical cord lesions, amniotic fluid pollution, asphyxia, premature delivery, premature rupture of membranes, positive etiology and maternal infection in the death group were higher than those in the survival group, while the gestational age and weight were lower than those in the survival group (all P<0.05); Binary logistic regression analysis showed that Lac, PCT and premature rupture of membranes were independent risk factors for the prognosis of EOS [odds ratio ( OR) and 95% confidence interval (95% CI): Lac was 1.23(1.00-2.05), PCT was 1.05(1.03-1.85), premature rupture of membranes was 2.59(1.89-3.32), all P<0.05]; ROC curve analysis showed that the area under the curve (AUC) of the prediction model was 0.967; the predicted sensitivity was 88.70%; and the specificity was 78.20% respectively. Conclusions:PCT, Lac and premature rupture of membranes are independent risk factors affecting the prognosis of EOS. The clinical prognosis prediction model constructed by combining PLT, gestational age and weight has good prediction efficiency.