早孕期联合母体危险因素和平均动脉压预测子痫前期的效能评估

Validation of the efficacy of combining maternal risk factors and mean arterial pressure to predict preeclampsia in early pregnancy

目的:联合母体因素和平均动脉压(MAP)评估英国胎儿医学基金会(FMF)算法对子痫前期(PE)的预测效能。方法:收集2021年8月至2021年12月于北部战区总医院妇产科门诊行NT彩超(孕11~13+6周)及住院孕妇1847例的临床资料,查阅并计算NT时平均动脉压(MAP),通过FMF网站公开免费的PE风险计算器计算风险值。按妊娠结局是否患有PE分为未发病组、早发型PE组、晚发型PE组、早产型PE组、足月型PE组、全部PE组。绘制受试者工作特征曲线(ROC曲线),分别计算在固定假阳性率分别为5%、10%、15%、20%下该模型对PE及其不同亚型的灵敏度。与实际观测结果及我国《妊娠期高血压疾病诊治指南(2020)》、《ACOG指南(2018)》所建议的筛查结果进行比较,评价该模型的预测效能。结果:1847例妊娠孕妇中发生PE者112例(6.1%),其中早发型29例(1.6%),晚发型83例(4.4%),早产型PE 35例(1.9%),足月型PE 77例(4.1%)。母体因素+MAP较单一母体因素对PE的预测效果更好,ROC曲线下面积(AUC)为0.847,固定假阳性率分别为5%、10%、15%、20%下的灵敏度分别为45.50%、61.60%、70.50%、78.60%。其中对早产型PE的预测效能最佳,AUC为0.881,固定假阳性率分别为5%、10%、15%、20%下的灵敏度分别为51.40%、62.90%、74.30%、80.00%。根据我国《妊娠期高血压疾病诊治指南(2020)》、《ACOG指南(2018)》预测PE的灵敏度分别为8.04%(9/112)、56.25%(63/112)。在相同人群下,联合母体因素及MAP预测全部PE及早产型PE的灵敏度分别为77.68%(87/112)、85.71%(30/35),较各大指南对PE的预测效果明显升高。结论:联合母体因素和MAP应用FMF竞争风险模型对PE患病有较好的预测效能,且对早产型PE的预测效能最好,优于单一母体因素及各大指南。在资源欠缺的地区或医院可选择联合母体因素和MAP来预测PE。

Objective:To evaluate the efficacy of the Fetal Medicine Foundation(FMF)algorithm in predicting preeclampsia in a local population by combining maternal factors and mean arterial pressure.Methods:Baseline clinical data were collected from pregnant women who underwent NT ultrasound(11~13+6 weeks of gestation)or hospitalized in the Northern Theater General Hospital from August 2021 to the end of December 2021.Calculate mean arterial pressure(MAP)at NT,Calculate the risk value using the publicly available free preeclampsia risk calculator on the FMF website.The pregnancy outcomes were categorized according to whether or not they had preeclampsia into the no disease group,early-onset preeclampsia group,late-onset preeclampsia group,preterm-type preeclampsia group,full-term-type preeclampsia group,and all preeclampsia group.Statistical methods were used to compare the differences in baseline information between the groups.The ROC curves were plotted,and the sensitivity of the model for preeclampsia and its different subtypes was calculated at fixed false-positive rates of 5%,10%,15%,and 20%,respectively.The predictive efficacy of the model was evaluated by comparing the results with the actual observations and the screening results recommended by the《Guidelines for the Diagnosis and Treatment of Hypertensive Diseases in Pregnancy(2020)》and the《ACOG guidelines(2018)》in China.Results:A total of 1847 pregnancies were included in this study for analysis.A total of 112(6.1%)developed preeclampsia,including 29(1.6%)pregnant women with early-onset preeclampsia,83(4.4%)pregnant women with late-onset preeclampsia,35(1.9%)pregnant women with preterm-type preeclampsia,and 77(4.1%)pregnant women with full-term-type preeclampsia.Maternal factor+MAP was a better predictor of preeclampsia than single maternal factor,with an area under the ROC curve(AUC)of 0.847,and sensitivities of 45.50%,61.60%,70.50%,and 78.60%at fixed false-positive rates of 5%,10%,15%,and 20%,respectively.The best prediction of preterm preeclampsia was achieved with an AUC of 0.881,and the sensitivities were 51.40%,62.90%,74.30%,and 80.00%at a fixed false positive rate of 5%,10%,15%,and 20%,respectively.The sensitivity of predicting preeclampsia according to China's"Guidelines for the diagnosis and treatment of hypertensive disorders in pregnancy(2020)"and ACOG guidelines(2018)was 8.04%(9/112)and 56.25%(63/112),respectively.In the same population,the sensitivity of combined maternal factors and MAP in all preeclampsia and preterm preeclampsia was 77.68%(87/112)and 85.71%(30/35),respectively.Its prediction of preeclampsia was significantly higher than that of major guidelines.Conclusion:The FMF competing risk model combined with maternal factors and MAP has better predictive efficacy for the prevalence of preeclampsia in the local population,and has the best predictive efficacy for preterm preeclampsia,which is better than the single maternal factor and the major guidelines.The combination of maternal factors and MAP can be chosen to predict preeclampsia in resource-poor areas or hospitals.