Achieving accurate estimates of fetal gestational age and personalised predictions of fetal growth based on data from an international prospective cohort study: a population-based machine learning study.

Journal: The Lancet. Digital health
Published Date:

Abstract

BACKGROUND: Preterm birth is a major global health challenge, the leading cause of death in children under 5 years of age, and a key measure of a population's general health and nutritional status. Current clinical methods of estimating fetal gestational age are often inaccurate. For example, between 20 and 30 weeks of gestation, the width of the 95% prediction interval around the actual gestational age is estimated to be 18-36 days, even when the best ultrasound estimates are used. The aims of this study are to improve estimates of fetal gestational age and provide personalised predictions of future growth.

Authors

  • Russell Fung
    Department of Physics, University of Wisconsin, Milwaukee, WI, USA.
  • Jose Villar
    Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK.
  • Ali Dashti
    Department of Physics, University of Wisconsin, Milwaukee, WI, USA.
  • Leila Cheikh Ismail
    Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK.
  • Eleonora Staines-Urias
    Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK.
  • Eric O Ohuma
    Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK.
  • Laurent J Salomon
    Maternité Necker-Enfants Malades, Assistance publique - Hôpitaux de Paris (AP-HP), Université Paris Descartes, Paris, France.
  • Cesar G Victora
    Programa de Pós-Graduação em Epidemiologia, Universidade Federal de Pelotas, Pelotas, Brazil.
  • Fernando C Barros
    Programa de Pós-Graduação em Epidemiologia, Universidade Federal de Pelotas, Pelotas, Brazil.
  • Ann Lambert
    Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK.
  • Maria Carvalho
    Faculty of Health Sciences, Aga Khan University, Nairobi, Kenya.
  • Yasmin A Jaffer
    Department of Family & Community Health, Ministry of Health, Muscat, Oman.
  • J Alison Noble
    Institute of Biomedical Engineering (IBME), University of Oxford, Oxford, England, UK.
  • Michael G Gravett
    Department of Obstetrics and Gynecology, University of Washington, Seattle, WA, USA.
  • Manorama Purwar
    Nagpur INTERGROWTH-21st Research Centre, Ketkar Hospital, Nagpur, India.
  • Ruyan Pang
    School of Public Health, Peking University, Beijing, China.
  • Enrico Bertino
    Dipartimento di Scienze Pediatriche e dell' Adolescenza, Struttura Complessa Direzione Universitaria Neonatologia, Università di Torino, Torino, Italy.
  • Shama Munim
    Department of Obstetrics & Gynaecology, Division of Women & Child Health, Aga Khan University, Karachi, Pakistan.
  • Aung Myat Min
    Shoklo Malaria Research Unit (SMRU), Mahidol-Oxford Tropical Medicine Research Unit (MORU), Faculty of Tropical Medicine, Mahidol University, Mae Sot, Thailand.
  • Rose McGready
    Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
  • Shane A Norris
    South African Medical Research Council Developmental Pathways for Health Research Unit, Department of Paediatrics & Child Health, University of the Witwatersrand, Johannesburg, South Africa.
  • Zulfiqar A Bhutta
    Centre for Global Child Health, Hospital for Sick Children, Toronto, ON, Canada.
  • Stephen H Kennedy
    Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK.
  • Aris T Papageorghiou
    Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, OX3 9DU, UK.
  • Abbas Ourmazd
    Department of Physics, University of Wisconsin, Milwaukee, WI, USA.