1,950
Views
0
CrossRef citations to date
0
Altmetric
Review Article

Estimated fetal weight standards of the INTERGROWTH-21st project for the prediction of adverse outcomes: a systematic review with meta-analysis

ORCID Icon, , , , , & show all
Article: 2230510 | Received 13 Dec 2021, Accepted 23 Jun 2023, Published online: 05 Jul 2023

References

  • McCowan LM, Figueras F, Anderson NH. Evidence-based national guidelines for the management of suspected fetal growth restriction: comparison, consensus, and controversy. Am J Obstet Gynecol. 2018;218(2S):S855–S868. DOI:10.1016/j.ajog.2017.12.004.
  • Hammami A, Zumaeta AM, Syngelaki A, et al. Ultrasonographic estimation of fetal weight: development of new model and assessment of performance of previous models. Ultrasound Obstet Gynecol. 2018;52(1):35–43. DOI:10.1002/uog.19066.
  • Hadlock FP, Harrist RB, Sharman RS, et al. Estimation of fetal weight with the use of head, body, and femur measurements-a prospective study. Am J Obstet Gynecol. 1985;151(3):333–337. DOI:10.1016/0002-9378(85)90298-4.
  • Stirnemann J, Villar J, Salomon LJ, et al. International estimated fetal weight standards of the INTERGROWTH-21st project. Ultrasound Obstet Gynecol. 2017;49(4):478–486. DOI:10.1002/uog.17347.
  • Hua X, Shen M, Reddy UM, et al. Comparison of the INTERGROWTH‐21st, national institute of child health and human development, and WHO fetal growth standards. Int J Gynaecol Obstet. 2018;143(2):156–163. DOI:10.1002/ijgo.12637.
  • Blue NR, Savabi M, Beddow ME, et al. The hadlock method is superior to newer methods for the prediction of the birth weight percentile. J Ultrasound Med. 2019;38(3):587–596. DOI:10.1002/jum.14725.
  • Nwabuobi C, Camisasca-Lopina H, Leavitt K, et al. INTERGROWTH-21st and hadlock growth standards to predict neonatal small for gestational age and short-term neonatal outcomes. Am J Obstet Gynecol. 2018;218(1):S310. DOI:10.1016/j.ajog.2017.11.044.
  • Kabiri D, Romero R, Gudicha DW, et al. Prediction of adverse perinatal outcomes by fetal biometry: a comparison of customized and population-based standards. Ultrasound Obstet Gynecol. 2020;55(2):177–188. DOI:10.1002/uog.20299.
  • Page MJ, McKenzie J, Bossuyt P, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2020;372:n71.
  • Cheikh Ismail L, Bishop DC, Pang R, et al. Gestational weight gain standards based on women enrolled in the fetal growth longitudinal study of the INTERGROWTH-21st project: a prospective longitudinal cohort study. BMJ. 2016;352:i555. DOI:10.1136/bmj.i555.
  • Papageorghiou AT, Ohuma EO, Gravett MG, et al. International standards for symphysis-fundal height based on serial measurements from the fetal growth longitudinal study of the INTERGROWTH-21st project: prospective cohort study in eight countries. BMJ. 2016;355:i5662. DOI:10.1136/bmj.i5662.
  • Papageorghiou AT, Ohuma EO, Altman DG, et al. International standards for fetal growth based on serial ultrasound measurements: the fetal growth longitudinal study of the INTERGROWTH-21st project. Lancet. 2014;384(9946):869–879. DOI:10.1016/S0140-6736(14)61490-2.
  • Villar J, Cheikh Ismail L, Victora CG, et al. International standards for newborn weight, length, and head circumference by gestational age and sex: the newborn Cross-Sectional study of the INTERGROWTH-21st project. Lancet. 2014;384(9946):857–868. DOI:10.1016/S0140-6736(14)60932-6.
  • Covidence systematic review software. Veritas Health Innovation, Melbourne, Australia. www.covidence.org
  • Fedorov S. GetData graph digitizer. 2002.
  • Cheng X, Folco EJ, Shimizu K, et al. Adiponectin induces pro-inflammatory programs in human macrophages and CD4+ T cells. J Biol Chem. 2012;287(44):36896–36904. DOI:10.1074/jbc.M112.409516.
  • Lorusso L, Kato DMP, Dalla Costa NRA, et al. Performance of local reference curve on the diagnosis of large for gestational age fetuses in diabetic pregnant women. J Matern Fetal Neonatal Med. 2022;35(10):1899–1906. DOI:10.1080/14767058.2020.1774539.
  • Moons KGM, de Groot JAH, Bouwmeester W, et al. Critical appraisal and data extraction for systematic reviews of prediction modelling studies: the CHARMS checklist. PLoS Med. 2014;11(10):e1001744. DOI:10.1371/journal.pmed.1001744.
  • Papageorghiou AT, Sarris I, Ioannou C, et al. Ultrasound methodology used to construct the fetal growth standards in the INTERGROWTH-21st project. BJOG. 2013;120:27–32. DOI:10.1111/1471-0528.12313.
  • Higgins JPT, Cochrane collaboration. Cochrane handbook for systematic reviews of interventions. 2nd ed. Hoboken (NJ): wiley-Blackwell; 2020.
  • StataCorp. Stata Statistical Software: release 12. 2011;
  • The Cochrane Collaboration. Review Manager (RevMan). 2020;
  • Finneran MM, Ware CA, Russo J, et al. Use of birth weight- vs. ultrasound-derived fetal weight classification methods: implications for detection of abnormal umbilical artery doppler. J Perinat Med. 2020;48(6):615–624. DOI:10.1515/jpm-2020-0068.
  • Nahirney M, Chaput K, Metcalfe A. Assessing the role of maternal race on the prediction of NICU admission by three growth charts: a cross-sectional study. J Matern-Fetal Neonatal Med. 2021;34(8):1233–1240. DOI:10.1080/14767058.2019.1631791.
  • Morales-Roselló J, Cañada Martínez AJ, Scarinci E, et al. Comparison of cerebroplacental ratio, intergrowth-21st standards, customized growth, and local population references for the prediction of fetal compromise: which is the best approach? Fetal Diagn Ther. 2019;46(5):341–352. DOI:10.1159/000497142.
  • Saviron-Cornudella R, Mariano Esteban L, Lerma D, et al. Comparison of fetal weight distribution improved by paternal height by spanish standard versus intergrowth 21st standard. J Perinat Med. 2018;46(7):750–759. DOI:10.1515/jpm-2016-0298.
  • Savirón-Cornudella R, Esteban LM, Aznar-Gimeno R, et al. Prediction of large for gestational age by ultrasound at 35 weeks and impact of Ultrasound-Delivery interval: comparison of 6 standards. Fetal Diagn Ther. 2021;48(1):15–23. DOI:10.1159/000510020.
  • Hiersch L, Lipworth H, Kingdom J, et al. Identification of the optimal growth chart and threshold for the prediction of antepartum stillbirth. Arch Gynecol Obstet. 2021;303(2):381–390. DOI:10.1007/s00404-020-05747-4.
  • Melamed N, Hiersch L, Aviram A, et al. Diagnostic accuracy of fetal growth charts for placenta-related fetal growth restriction. Placenta. 2021;105:70–77. DOI:10.1016/j.placenta.2021.01.022.
  • Kato DMP, Lorusso L, Bruns RF, et al. Performance of a local reference curve for predicting small for gestational age fetuses in pregnant women with HIV/AIDS. J Clin Ultrasound. 2021;49(4):322–327. DOI:10.1002/jcu.22961.
  • Zhu C, Ren Y-Y, Wu J-N, et al. A comparison of prediction of adverse perinatal outcomes between hadlock and INTERGROWTH-21st standards at the third trimester. Biomed Res Int. 2019;2019:7698038. DOI:10.1155/2019/7698038.
  • Vikraman S, Elayedatt R. Prospective comparative evaluation of performance of fetal growth charts in the diagnosis of suboptimal fetal growth during third trimester ultrasound. J Fetal Med. 2020;07(02):103–110. DOI:10.1007/s40556-020-00244-9.
  • Choi SKY, Gordon A, Hilder L, et al. Performance of six birthweight and estimated fetal weight standards for predicting adverse perinatal outcomes: a 10-year nationwide population-based study. Ultrasound Obstet Gynecol. 2021;58(2):264–277. DOI:10.1002/uog.22151.
  • Sovio U, Smith GCS. Comparison of estimated fetal weight percentiles near term for predicting extremes of birthweight percentile. Am J Obstet Gynecol. 2021;224(3):292.e1–292.e19. e1-292.e19. DOI:10.1016/j.ajog.2020.08.054.
  • Savirón-Cornudella R, Esteban LM, Tajada-Duaso M, et al. Detection of adverse perinatal outcomes at term delivery using ultrasound estimated percentile weight at 35 weeks of gestation: comparison of five fetal growth standards. Fetal Diagn Ther. 2020;47(2):104–114. DOI:10.1159/000500453.
  • Callec R, Lamy C, Perdriolle‐Galet E, et al. Impact on obstetric outcome of third-trimester screening for small-for-gestational-age fetuses. Ultrasound Obstet Gynecol. 2015;46(2):216–220. DOI:10.1002/uog.14755.
  • Habibzadeh F, Habibzadeh P, Yadollahie M. On determining the most appropriate test cut-off value: the case of tests with continuous results. Biochem Med. 2016;26(3):297–307. DOI:10.11613/BM.2016.034.
  • Ranganathan P, Aggarwal R. Common pitfalls in statistical analysis: understanding the properties of diagnostic tests – part 1. Perspect Clin Res. 2018;9(1):40–43. DOI:10.4103/picr.PICR_170_17.
  • Whiting P, Rutjes AWS, Reitsma B, et al. Sources of variation and bias in studies of diagnostic accuracy. Ann Intern Med. 2004;140(3):189–202. DOI:10.7326/0003-4819-140-3-200402030-00010.
  • Steyerberg EW, Vickers AJ, Cook NR, et al. Assessing the performance of prediction models: a framework for some traditional and novel measures. Epidemiology. 2010;21(1):128–138. DOI:10.1097/EDE.0b013e3181c30fb2.
  • Royston P, Altman DG, Sauerbrei W. Dichotomizing continuous predictors in multiple regression: a bad idea. Stat Med. 2006;25(1):127–141. DOI:10.1002/sim.2331.