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CC BY-NC-ND 4.0 · Indian J Radiol Imaging 2020; 30(01): 27-31
DOI: 10.4103/ijri.IJRI_383_19
Obs and Gynecology

Discordant dating of pregnancy by LMP and ultrasound and its implications in perinatal statistics

Lalit K Sharma
Raj Sonography and X-Ray Clinic, Baiju Choraha, Nayapura
,
Jyoti Bindal
Department of Woman and Child Development, Guna, Madhya Pradesh
,
Vishal A Shrivastava
Department of Woman and Child Development, Guna, Madhya Pradesh
,
Mansi Sharma
Department of Obstetrics and Gynaecology, Columbia Asia and Sahyadri Hospital, Pune, Maharashtra
,
Rijo M Choorakuttil
National Coordinator for Samrakshan IRIA, AMMA Center for Diagnosis and Preventive Medicine
,
Praveen K Nirmalan
Chief Research Mentor, AMMA Education Research Foundation, Kochi, Kerala, India
› Author Affiliations Financial support and sponsorship The NGO “Mansi Maa Beti Seva Samity” at Guna supported the purchase and distribution of medicines through the project.
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Abstract

Context: High perinatal mortality in India may be caused by inaccurate dating of pregnancy resulting from suboptimal uptake of antenatal care and ultrasound services during pregnancy. Aim: To determine the discrepancy in the last menstrual period (LMP) assigned expected date of delivery (EDD) and ultrasound assigned EDD in pregnant women in a rural district of central India. Methods: Data from an ongoing cross-sectional screening program providing fetal radiology imaging in Guna district of Madhya Pradesh from 2012–2019 was analyzed for recall of LMP and discordance between LMP and ultrasound assigned EDD. The discrepancy was present when EDD assigned by ultrasound differed by 3 or more days at gestational ages less than 8+6 weeks, 5–7 days at gestational ages 8+6 weeks till 14 weeks, and 7–10 days at gestational ages 14–20 weeks. Results: The program screened 14,701 pregnant women of which 4,683 (31.8+6%, 95% CI: 31.11, 32.61) could not recall LMP. EDD assigned by LMP and ultrasound matched in 7,035 (70.22%, 95% CI: 69.32, 71.12) of the remaining 10,018 pregnant women. EDD was overestimated by LMP for 26.06% (95% CI: 25.21, 26.93) women; these foetuses were at risk of being misclassified as a term fetus. In 2018, the project had no maternal deaths, infant mortality rate of 24.7, low birth weight rate of 9.69%, and 100% antenatal coverage. Conclusion: Accurate dating of pregnancy and systematic follow-up integrating radiology imaging and obstetrics care for appropriate risk-based management of pregnant women can significantly improve perinatal statistics of India.

Keywords

Antenatal care - dating - gestational age - pregnancy outcomes - preterm births - ultrasound


Publication History

Received: 16 September 2019

Accepted: 16 January 2020

Article published online:
19 July 2021

© 2020. Indian Radiological Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).

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  • References

  • 1 Committee on Obstetric Practice. The American Institute of Ultrasound in Medicine, and The Society for Maternal-Fetal Medicine. Committee Opinion No 700: Methods for estimating the due date. Obstet Gynecol 2017; 129: e150-4
    CrossrefPubMedGoogle Scholar
  • 2 Petersson K, Lindkvist M, Persson M, Conner P, Ahman A, Mogren I. Prenatal diagnosis in Sweden 2011 to 2013 – A register-based study. BMC Pregnancy Childbirth 2016; 16: 365
    CrossrefPubMedGoogle Scholar
  • 3 Loughna P, Chitty L, Evans T, Chudleigh T. Fetal size and dating: Charts recommended for clinical obstetric practice. Ultrasound 2009; 17: 161-7
    CrossrefGoogle Scholar
  • 4 Tan MY, Syngelaki A, Poon LC, Rolnik DL, O’Gorman N, Delgado JL. et al. Screening for pre-eclampsia by maternal factors and biomarkers at 11-13 weeks’ gestation. Ultrasound Obstet Gynecol 2018; 52: 186-95
    CrossrefPubMedGoogle Scholar
  • 5 Rolnik DL, Wright D, Poon LC, O’Gorman N, Syngelaki A, de Paco Matallana C. et al. Aspirin versus placebo in pregnancies at high risk for preterm preeclampsia. N Engl J Med 2017; 377: 613-22
    CrossrefPubMedGoogle Scholar
  • 6 Litwinska M, Syngelaki A, Wright A, Wright D, Nicolaides KH. Management of pregnancies after combined screening for pre-eclampsia at 19-24 weeks’ gestation. Ultrasound Obstet Gynecol 2018; 52: 365-72
    CrossrefPubMedGoogle Scholar
  • 7 Panaitescu A, Ciobanu A, Syngelaki A, Wright A, Wright D, Nicolaides KH. Screening for preeclampsia at 35–37 weeks’ gestation. Ultrasound Obstet Gynecol 2018; 52: 501-6
    CrossrefPubMedGoogle Scholar
  • 8 Figueras F, Gratacós E. Update on the diagnosis and classification of fetal growth restriction and proposal of a stage-based management protocol. Fetal Diagn Ther 2014; 36: 86-98
    CrossrefPubMedGoogle Scholar
  • 9 Committee on Obstetric Practice. Committee opinion no. 688: Management of suboptimally dated pregnancies. Obstet Gynecol 2017; 129: e29-32
    CrossrefPubMedGoogle Scholar
  • 10 International Institute for Population Sciences (IIPS) and ICF. 2017. National Family Health Survey (NFHS-4) 2015-16. India. Mumbai: IIPS;
    Google Scholar
  • 11 Million Death Study Collaborators. Bassani DG, Kumar R, Awasthi S, Morris SK, Paul VK. et al. Causes of neonatal and child mortality in India: A nationally representative mortality survey. Lancet 2010; 376: 1853-60
    CrossrefPubMedGoogle Scholar
  • 12 Niti Ayog, India. [Internet] Maternal Mortality Ratio (per 100,000 live births). Available from: https://www.niti.gov.in/content/maternal-mortality-ratio-mmr-100000-live-births. [Last cited on 2019 Sep 02]
  • 13 National Health Portal, Government of India. [Internet]. Available from: https://www.nhp.gov.in/disease/gynaecology-and-obstetrics/preeclampsia. [Last cited on 2019 Sep 10]
  • 14 Robinson HP, Fleming JE. A critical evaluation of sonar crown rump length measurements. Br J Obstet Gynaecol 1975; 82: 702-10
    CrossrefPubMedGoogle Scholar
  • 15 MacGregor SN, Tamura RK, Sabbagha RE, Minogue JP, Gibson ME, Hoffman DI. Underestimation of gestational age by conventional crown-rump length dating curves. Obstet Gynecol 1987; 70: 344-8
    PubMedGoogle Scholar
  • 16 Blondel B, Morin I, Platt RW, Kramer MS, Usher R, Breart G. Algorithms for combining menstrual and ultrasound estimates of gestational age: Consequences for rates of preterm and post-term birth. BJOG 2002; 109: 718-20
    CrossrefPubMedGoogle Scholar
  • 17 De Jong CL, Francis A, Van Geijn HP, Gardosi J. Customized fetal weight limits for antenatal detection of fetal growth restriction. Ultrasound Obstet Gynecol 2000; 15: 36-40
    CrossrefPubMedGoogle Scholar
  • 18 Ioannou C, Talbot K, Ohuma E, Sarris I, Villar J, Conde-Agudelo A. et al. Systematic review of methodology used in ultrasound studies aimed at creating charts of fetal size. BJOG 2012; 119: 1425-39
    CrossrefPubMedGoogle Scholar
  • 19 Axell R, Lynch C, Chudleigh T, Bradshaw L, Mangat J, White P. et al. Clinical implications of machine-probe combinations on obstetric ultrasound measurements used in pregnancy dating. Ultrasound Obstet Gynecol 2012; 40: 194-9
    CrossrefPubMedGoogle Scholar
  • 20 Kramer MS, McLean FH, Boyd ME, Usher RH. The validity of gestational age estimation by menstrual dating in term, preterm, and post-term gestations. JAMA 1988; 260: 3306-8
    CrossrefPubMedGoogle Scholar
  • 21 Moore WM, Ward BS, Jones VP, Bamford FN. Sex difference in fetal head growth. Br J Obstet Gynaecol 1988; 95: 238-42
    CrossrefPubMedGoogle Scholar
  • 22 Smith GC, Smith MF, McNay MB, Fleming JE. First-trimester growth and the risk of low birth weight. N Engl J Med 1998; 339: 1817-22
    CrossrefPubMedGoogle Scholar
  • 23 Kallen K. Mid-trimester ultrasound prediction of gestational age: Advantages and systematic errors. Ultrasound Obstet Gynecol 2002; 20: 558-63
    CrossrefPubMedGoogle Scholar
  • 24 Kallen B, Finnstrom O, Nygren KG, Olausson PO. Maternal and fetal factors which affect fetometry: Use of in vitro fertilization and birth register data. Eur J Obstet Gynecol Reprod Biol 2013; 170: 372-6
    CrossrefPubMedGoogle Scholar
  • 25 Bak GS, Sperling L, Kallen K, Salvesen KA. Prospective population-based cohort study of maternal obesity as a source of error in gestational age estimation at 11–14 weeks. Acta Obstet Gynecol Scand 2016; 95: 1281-7
    CrossrefPubMedGoogle Scholar
  • 26 Kallen K. Increased risk of perinatal/neonatal death in infants who were smaller than expected at ultrasound fetometry in early pregnancy. Ultrasound Obstet Gynecol 2004; 24: 30-4
    CrossrefPubMedGoogle Scholar
  • 27 Thorsell M, Kaijser M, Almstrom H, Andolf E. Expected day of delivery from ultrasound dating versus last menstrual period–obstetric outcome when dates mismatch. BJOG 2008; 115: 585-9
    CrossrefPubMedGoogle Scholar
  • 28 Henriksen TB, Wilcox AJ, Hedegaard M, Secher NJ. Bias in studies of preterm and post-term delivery due to ultrasound assessment of gestational age. Epidemiology 1995; 6: 533-7
    CrossrefPubMedGoogle Scholar
  • 29 Harland KK, Saftlas AF, Wallis AB, Yankowitz J, Triche EW, Zimmerman MB. Correction of systematic bias in ultrasound dating in studies of small-for-gestational-age birth: An example from the Iowa health in pregnancy study. Am J Epidemiol 2012; 176: 443-55
    CrossrefPubMedGoogle Scholar
  • 30 Morken NH, Klungsoyr K, Skjaerven R. Perinatal mortality by gestational week and size at birth in singleton pregnancies at and beyond term: A nationwide population-based cohort study. BMC Pregnancy Childbirth 2014; 14: 172
    CrossrefPubMedGoogle Scholar
  • 31 Morken NH, Skjaerven R, Richards JL, Kramer MR, Cnattingius S, Johansson S. et al. PREBIC Epidemiology Working Group. Adverse infant outcomes associated with discordant gestational age estimates. Paediatr Perinat Epidemiol 2016; 30: 541-9
    CrossrefPubMedGoogle Scholar