基于Logistic回归模型的足月新生儿呼吸窘迫综合征相关因素分析

Analysis of Related Factors of Full-term Neonatal Respiratory Distress Syndrome Based on Logistic Regression Model

目的分析发生新生儿呼吸窘迫综合征(NRDS)的影响因素。方法收集2014年1月~2018年12月我院85例呼吸窘迫综合征足月新生患儿设为实验组,104例同期未被诊断为呼吸窘迫综合征足月新生儿设为对照组,比较两组性别,胎龄,出生体重,分娩方式,产妇年龄,怀孕次数,流产史和妊娠并发症等临床资料。将单因素分析有统计学差异的项目进入多因素Logistic回归,分析RDS的影响因素。结果两组性别、胎龄、分娩方式、产妇多胎、妊娠期糖尿病、胎儿宫内窘迫和新生儿窒息比较,差异有统计学意义(P<0.05)。两组新生儿体重、产妇年龄、流产史、产妇妊高症、胎膜早破、羊水过少和胎粪污染比较,差异无统计学意义(P>0.05)。Logistic回归分析显示,新生儿男性、剖宫产、多胎和妊娠期糖尿病为NRDS的危险因素。结论足月儿NRDS的危险因素为男性,剖宫产、多胎和产妇妊娠期糖尿病。早期识别NRDS相关危险因素对病情控制有积极意义。

Objective To analyze the influencing factors of neonatal respiratory distress syndrome(NRDS).Methods A total of 85 full-term newborns with respiratory distress syndrome in our hospital from January 2014 to December 2018 were collected as the experimental group,and 104 full-term newborns with respiratory distress syndrome not diagnosed in the same period were selected as the control group.Two groups of clinical data such as gender,gestational age,birth weight,mode of delivery,maternal age,number of pregnancy,miscarriage history and pregnancy complications.The items with statistical differences in univariate analysis were entered into multivariate Logistic regression to analyze the influencing factors of RDS.Results There were statistically significant differences between the two groups in gender,gestational age,delivery mode,multiple births,gestational diabetes,fetal distress and neonatal asphyxia(P<0.05).There was no significant difference between the two groups of newborn weight,maternal age,history of miscarriage,pregnancy-induced hypertension,premature rupture of membranes,oligohydramnios,and meconium contamination(P>0.05).Logistic regression analysis showed that newborn males,cesarean section,multiple births and gestational diabetes were risk factors for NRDS.Conclusion The risk factors for NRDS in term infants were male,cesarean section,multiple births and maternal gestational diabetes.Early identification of NRDS-related risk factors was of positive significance for disease control.