PDF(Pubmed)
Abstract：
To explore the influence of perinatal-related factors on meconium aspiration syndrome (MAS) in full-term neonates and construct a nomogram prediction model for risk stratification of neonatal MAS and adoption of preventive measures. A total of 424 newborns and their mothers who were regularly examined at our hospital between January 2020 and December 2023 who had meconium-contaminated amniotic fluid during delivery were retrospectively selected as participants. Neonates were divided into MAS and non-MAS groups based on whether MAS occurred within 3 days after birth. Data from the 2 groups were analyzed, and factors influencing MAS were screened using multivariate logistic regression analysis. The R3.4.3 software was used to construct a nomogram prediction model for neonatal MAS risk. Receiver operating characteristic (ROC) curve analysis and the Hosmer-Lemeshow goodness-of-fit test were used to evaluate the performance of the model, and its clinical effectiveness was evaluated using a decision curve. Among the 424 neonates with meconium-stained amniotic fluid, 51 developed MAS within 3 days of birth (12.03%). Multivariate logistic regression analysis showed that a low amniotic fluid index before delivery (OR = 2.862, P = .019), advanced gestational age (OR = 0.526, P = .034), cesarean section (OR = 2.650, P = .013), severe amniotic fluid contamination (OR = 4.199, P = .002), low umbilical cord blood pH (OR = 2.938, P = .011), and low neonatal Apgar 1-min score (OR = 3.133, P = .006) were influencing factors of MAS in full-term neonates. Based on the above indicators, a nomogram prediction model for MAS risk of full-term newborns was constructed. The area under the ROC curve of the model was 0.931. The model was also tested for goodness-of-fit deviation (χ2 = 3.465, P = .903). Decision curve analysis found that the model was clinically effective in predicting the net benefit of MAS risk in neonates with meconium-stained amniotic fluid. The construction of a column chart prediction model for neonatal MAS risk based on prenatal amniotic fluid index, gestational age, delivery method, amniotic fluid contamination level, newborn umbilical blood pH value, and Apgar 1-min score has a certain application value.
摘要：
探讨围产期相关因素对足月新生儿胎粪吸入综合征(MAS)的影响，构建新生儿MAS危险分层及预防措施的列线图预测模型。回顾性选择在2020年1月至2023年12月期间在我院接受定期检查的424名新生儿及其母亲作为参与者，这些新生儿及其母亲在分娩期间患有胎粪污染的羊水。根据出生后3天内是否发生MAS，将新生儿分为MAS组和非MAS组。对2组数据进行分析,采用多因素logistic回归分析筛选MAS影响因素。采用R3.4.3软件构建新生儿MAS风险的列线图预测模型。接收器工作特性（ROC）曲线分析和Hosmer-Lemeshow拟合优度测试用于评估模型的性能，并使用决策曲线评估其临床有效性.在424例羊水胎粪污染的新生儿中，51在出生后3天内出现MAS（12.03%）。多因素logistic回归分析显示,分娩前羊水指数较低(OR=2.862,P=0.019),胎龄提前（OR=0.526，P=0.034），剖宫产（OR=2.650，P=.013），严重羊水污染(OR=4.199,P=0.002),脐血pH值偏低(OR=2.938,P=.011),新生儿Apgar1min评分偏低(OR=3.133,P=.006)是足月新生儿MAS的影响因素。根据上述指标,构建足月新生儿MAS风险的列线图预测模型.模型ROC曲线下面积为0.931。还对模型进行了拟合优度偏差测试(χ2=3.465,P=0.903)。决策曲线分析发现，该模型在临床上可有效预测羊水粪染新生儿MAS风险的净收益。基于产前羊水指数的新生儿MAS风险柱状图预测模型的构建,胎龄,交货方式,羊水污染水平，新生儿脐血pH值,Apgar1-min评分有一定的应用价值。
