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Comparison of first trimester dating methods for gestational age estimation and their implication on preterm birth classification in a North Indian cohort

Authors
  • Vijayram, Ramya1, 2
  • Damaraju, Nikhita1, 2
  • Xavier, Ashley1, 2
  • Desiraju, Bapu Koundinya3, 3
  • Thiruvengadam, Ramachandran3, 3
  • Misra, Sumit3, 3
  • Chopra, Shilpa3, 3
  • Khurana, Ashok4
  • Wadhwa, Nitya3, 3
  • Bal, Vineeta3
  • Bhatnagar, Shinjini
  • Das, Bhabatosh
  • Dash, Mahadev
  • Desiraju, Bapu Koundinya
  • Kshetrapal, Pallavi
  • Misra, Sumit
  • Natchu, Uma Chandra Mouli
  • Rath, Satyajit
  • Sachdeva, Kanika
  • Sharma, Dharmendra
  • And 29 more
  • 1 Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, India , Chennai (India)
  • 2 Centre for Integrative Biology and Systems Medicine, Indian Institute of Technology Madras, Chennai, India , Chennai (India)
  • 3 Translational Health Science and Technology Institute, Faridabad, India , Faridabad (India)
  • 4 The Ultrasound Lab, Defence Colony, New Delhi, India , New Delhi (India)
Type
Published Article
Journal
BMC Pregnancy and Childbirth
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Apr 30, 2021
Volume
21
Issue
1
Identifiers
DOI: 10.1186/s12884-021-03807-4
Source
Springer Nature
Keywords
License
Green

Abstract

BackgroundDifferent formulae have been developed globally to estimate gestational age (GA) by ultrasonography in the first trimester of pregnancy. In this study, we develop an Indian population-specific dating formula and compare its performance with published formulae. Finally, we evaluate the implications of the choice of dating method on preterm birth (PTB) rate. This study’s data was from GARBH-Ini, an ongoing pregnancy cohort of North Indian women to study PTB.MethodsComparisons between ultrasonography-Hadlock and last menstrual period (LMP) based dating methods were made by studying the distribution of their differences by Bland-Altman analysis. Using data-driven approaches, we removed data outliers more efficiently than by applying clinical parameters. We applied advanced machine learning algorithms to identify relevant features for GA estimation and developed an Indian population-specific formula (Garbhini-GA1) for the first trimester. PTB rates of Garbhini-GA1 and other formulae were compared by estimating sensitivity and accuracy.ResultsPerformance of Garbhini-GA1 formula, a non-linear function of crown-rump length (CRL), was equivalent to published formulae for estimation of first trimester GA (LoA, − 0.46,0.96 weeks). We found that CRL was the most crucial parameter in estimating GA and no other clinical or socioeconomic covariates contributed to GA estimation. The estimated PTB rate across all the formulae including LMP ranged 11.27–16.50% with Garbhini-GA1 estimating the least rate with highest sensitivity and accuracy. While the LMP-based method overestimated GA by 3 days compared to USG-Hadlock formula; at an individual level, these methods had less than 50% agreement in the classification of PTB.ConclusionsAn accurate estimation of GA is crucial for the management of PTB. Garbhini-GA1, the first such formula developed in an Indian setting, estimates PTB rates with higher accuracy, especially when compared to commonly used Hadlock formula. Our results reinforce the need to develop population-specific gestational age formulae.

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