1. Reliability of last menstrual period recall, an early ultrasound and a Smartphone App in predicting date of delivery and classification of preterm and post-term births.
- Author
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Majola L, Budhram S, Govender V, Naidoo M, Godlwana Z, Lombard C, and Moodley D
- Subjects
- Adult, Delivery, Obstetric statistics & numerical data, Female, Humans, Infant, Newborn, Menstruation psychology, Mental Recall, Predictive Value of Tests, Pregnancy, Pregnancy, Prolonged diagnosis, Premature Birth diagnosis, Reproducibility of Results, Retrospective Studies, Smartphone, Time Factors, Ultrasonography, Prenatal methods, Mobile Applications, Pregnancy, Prolonged classification, Premature Birth classification, Statistics as Topic methods, Ultrasonography, Prenatal statistics & numerical data
- Abstract
Background: 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., Methods: 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., Results: 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., Conclusions: 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.
- Published
- 2021
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