Department of Obstetrics and Gynaecology, School of Clinical Medicine, University of KwaZulu-Natal, 719 Umbilo Road, Congella, 4013, South Africa.
Centre for the AIDS Programme of Research in South Africa, 719 Umbilo Road, Congella, 4013, South Africa.
BMC Pregnancy Childbirth. 2021 Jul 7;21(1):493. doi: 10.1186/s12884-021-03980-6.
A reliable expected date of delivery (EDD) is important for pregnant women in planning for a safe delivery and critical for management of obstetric emergencies. We compared the accuracy of LMP recall, an early ultrasound (EUS) and a Smartphone App in predicting the EDD in South African pregnant women. We further evaluated the rates of preterm and post-term births based on using the different measures.
This is a retrospective sub-study of pregnant women enrolled in a randomized controlled trial between October 2017-December 2019. EDD and gestational age (GA) at delivery were calculated from EUS, LMP and Smartphone App. Data were analysed using SPSS version 25. A Bland-Altman plot was constructed to determine the limits of agreement between LMP and EUS.
Three hundred twenty-five pregnant women who delivered at term (≥ 37 weeks by EUS) and without pregnancy complications were included in this analysis. Women had an EUS at a mean GA of 16 weeks and 3 days). The mean difference between LMP dating and EUS is 0.8 days with the limits of agreement 31.4-30.3 days (Concordance Correlation Co-efficient 0.835; 95%CI 0.802, 0.867). The mean(SD) of the marginal time distribution of the two methods differ significantly (p = 0.00187). EDDs were < 14 days of the actual date of delivery (ADD) for 287 (88.3%;95%CI 84.4-91.4), 279 (85.9%;95%CI 81.6-89.2) and 215 (66.2%;95%CI 60.9-71.1) women for EUS, Smartphone App and LMP respectively but overall agreement between EUS and LMP was only 46.5% using a five category scale for EDD-ADD with a kappa of .22. EUS 14-24 weeks and EUS < 14 weeks predicted EDDs < 14 days of ADD in 88.1% and 79.3% of women respectively. The proportion of births classified as preterm (< 37 weeks) was 9.9% (95%CI 7.1-13.6) by LMP and 0.3% (95%CI 0.1-1.7) by Smartphone App. The proportion of post-term (> 42 weeks gestation) births was 11.4% (95%CI 8.4-15.3), 1.9% (95%CI 0.9-3.9) and 3.4% (95%CI 1.9-5.9) by LMP, EUS and Smartphone respectively.
EUS and Smartphone App were the most accurate to estimate the EDD in pregnant women. LMP-based dating resulted in misclassification of a significantly greater number of preterm and post-term deliveries compared to EUS and the Smartphone App.
对于孕妇来说,可靠的预计分娩日期(EDD)对于安全分娩计划和产科急症管理至关重要。我们比较了 LMP 回忆、早期超声(EUS)和智能手机应用程序在预测南非孕妇 EDD 方面的准确性。我们进一步评估了基于不同测量值的早产和过期分娩的发生率。
这是 2017 年 10 月至 2019 年 12 月期间入组的一项随机对照试验的回顾性亚研究。EUS、LMP 和智能手机应用程序用于计算 EDD 和分娩时的孕龄(GA)。使用 SPSS 版本 25 进行数据分析。构建 Bland-Altman 图以确定 LMP 和 EUS 之间的协议限。
本分析纳入了 325 名足月(EUS 为≥37 周)且无妊娠并发症的孕妇。孕妇在 EUS 检查时的平均 GA 为 16 周 3 天。LMP 与 EUS 的平均差异为 0.8 天,协议限为 31.4-30.3 天(一致性相关系数 0.835;95%CI 0.802,0.867)。两种方法的边缘时间分布均值(SD)差异有统计学意义(p=0.00187)。EDD 比实际分娩日期(ADD)早 14 天的有 287 例(88.3%;95%CI 84.4-91.4)、279 例(85.9%;95%CI 81.6-89.2)和 215 例(66.2%;95%CI 60.9-71.1)女性分别为 EUS、智能手机应用程序和 LMP,但 EUS 和 LMP 之间的总体一致性仅为 46.5%,使用 EDD-ADD 的五分类量表,kappa 值为 0.22。EUS 14-24 周和 EUS<14 周预测 EDD 早于 ADD 的比例分别为 88.1%和 79.3%的女性。LMP 预测的早产(<37 周)比例为 9.9%(95%CI 7.1-13.6),智能手机应用程序为 0.3%(95%CI 0.1-1.7)。LMP、EUS 和智能手机预测的过期(>42 周妊娠)分娩比例分别为 11.4%(95%CI 8.4-15.3)、1.9%(95%CI 0.9-3.9)和 3.4%(95%CI 1.9-5.9)。
EUS 和智能手机应用程序是估计孕妇 EDD 最准确的方法。与 EUS 和智能手机应用程序相比,基于 LMP 的妊娠时间估计导致明显更多的早产和过期分娩的分类错误。