构建早产儿生后7 d内败血症风险列线图模型

Construction of nomogram model of the risk of sepsis in premature infants within 7 days after birth

目的构建预测早产儿生后7 d内发生败血症的列线图,以供指导临床识别具有败血症高危风险的早产儿。方法采用2017年1月至2020年12月产科出生并转入新生儿科住院的早产儿进行logistic回归分析找出早产儿生后7 d内败血症的独立风险因素;接着采用赤池信息量准则(AIC),即找可以最有效地解释数据且纳入的参数是最少的模型,选取变量纳入列线图模型,然后应用R软件建立预测早产儿生后7 d内发生败血症的风险系数的列线图。结果纳入2701例早产儿病例,生后7 d内共有371例发生败血症,总发病率为13.7%。Logistic回归分析显示绒毛膜羊膜炎(OR=1.468,95%CI=1.059~2.036)、羊水胎粪污染(OR=1.759,95%CI=1.118~2.768)、胎膜早破时间(OR=1.001,95%CI=1.000~1.003)、气管插管(OR=5.434,95%CI=4.126~7.157)、胎龄(OR=0.983,95%CI=0.970~0.996)、体重(OR=0.650,95%CI=0.437~0.967)是早产儿生后7 d内发生败血症的独立影响因素。根据列线图制作的AIC准则纳入模型的变量为绒毛膜羊膜炎、气管插管、胎龄和体重。列线图的AUC为0.832(95%CI=0.807~0.857)。结论以胎龄、体重、绒毛膜羊膜炎、气管插管为变量构建的列线图,其预测早产儿生后7 d内败血症的发生风险具有良好的区分度和准确度,可为早产儿生后7 d内败血症的管理提供参考依据。

Objective To construct a nomogram to predict the occurrence of sepsis in preterm infants within 7 days after birth, so as to guide the clinical identification of preterm infants who are at high risk of sepsis. Methods The logistic regression analysis of premature infants(modeling group), who were born in the obstetric department of a hospital in Guangdong Province from January 2017 to December 2020 and were transferred to the neonatology department, was performed to find out the independent risk factors of sepsis of preterm infants within 7 days after birth. The Akaike Information Criteria(AIC) and R software were used to analyze the independent risk factors of sepsis in preterm infants within 7 days. Results A total of 2 701 premature infants were collected, and 371 cases(13.7%) of sepsis occurred within 7 days after birth. Logistic regression analysis showed that chorioamnionitis(OR=1.468, 95%CI=1.059-2.036), meconium contamination of amniotic fluid(OR=1.759, 95%CI=1.118-2.768), premature rupture of membranes(OR=1.001, 95%CI=1.000-1.003), tracheal intubation(OR=5.434, 95%CI=4.126-7.157), gestational age(OR=0.983, 95%CI=0.970-0.996), and weight(OR=0.650, 95%CI=0.437-0.967) were independent risk factors for sepsis in preterm infants within 7 days after birth. The variables included in the AIC-based nomogram were chorioamnionitis, endotracheal intubation, gestational age and birth weight. The AUC of the nomogram was 0.832(95%CI=0.807-0.857). Conclusion A nomogram constructed with gestational age, birth weight, chorioamnionitis, and endotracheal intubation as variables has good discrimination and accuracy in predicting the risk of sepsis in preterm infants within 7 days after birth.