胎儿生长受限发生因素分析及其列线图预测模型的建立

Analysis of factors of fetal growth restriction and establishment of nomogram prediction model

目的 分析胎儿生长受限发生因素并以此建立列线图预测模型。方法 选择2018年1月至2021年12月在深圳市南山区妇幼保健院产检并分娩的3469例单胎孕妇资料进行回顾性分析。采用回归性分析法收集可能引起胎儿生长受限发生的因素,根据是否胎儿生长受限将研究对象分为2组,比较2组孕妇相关资料及胎儿相关资料,并以LASSO回归筛选变量后行多因素Logistic回归筛选出独立性影响因素,根据Logistic回归结果构建列线图模型。结果 本研究纳入的3469例研究对象中有183例(5.28%)被确诊为胎儿生长受限。经LASSO回归筛选变量后行多因素Logistic回归分析结果显示:孕妇年龄、不良孕产史、妊娠高血压疾病、吸烟史、叶酸补充情况、脐带异常、羊水过少、自身免疫性疾病、胎儿窘迫为胎儿生长受限的独立性影响因素(P<0.05)。以R软件构建列线图模型,经ROC分析及Bootstrap法对列线图进行内部验证,以原始数据重复抽样1000次,结果显示:列线图模型具有较高的准确性与区分度。结论 胎儿生长受限的发生主要受孕妇年龄、不良孕产史、妊娠高血压疾病等因素的影响,本研究建立的列线图模型对胎儿生长受限预测具有较高的准确性与区分度。

Objective To analyze the risk factors of fetal growth restriction and to establish a nomogram prediction model. Methods The data of 3469 singleton pregnant women who underwent obstetric examination and delivered in Shenzhen Nanshan Maternity & Child Healthcare Hospital from January 2018 to December 2021 were selected for retrospective analysis.The factors that may cause fetal growth restriction were collected by regression analysis, and the subjects were divided into 2 groups according to whether fetal growth restriction occurred. The data of pregnant women and fetuses of the two groups were compared, and the variables were screened by LASSO regression, and then multivariate Logistic regression was performed to screen out independent influencing factors, and a nomogram model was constructed according to the results of Logistic regression. Results Of the 3469 subjects included in this study, 183(5.28%) were diagnosed with fetal growth restriction. The results of multivariate Logistic regression analysis showed that: Maternal age, adverse pregnancy history, pregnancy-induced hypertension, smoking history, folic acid supplementation, abnormal umbilical cord, oligohydramnios, autoimmune disease, and fetal distress were independent influencing factors of fetal growth restriction(P<0.05). The nomogram model was constructed with R software, and the nomogram was internally verified by ROC analysis and Bootstrap method. The original data was repeatedly sampled 1000 times. The results showed that the nomogram model has high accuracy and accuracy. Conclusion The occurrence of fetal growth restriction is mainly affected by factors such as maternal age, adverse pregnancy history, pregnancy-induced hypertension and other factors. The nomogram model established in this study has high accuracy and discrimination for the prediction of fetal growth restriction.