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Prognostic models for adverse pregnancy outcomes in low-income and middle-income countries: a systematic review
  1. Tessa Heestermans1,
  2. Beth Payne1,2,
  3. Gbenga Ayodele Kayode1,3,
  4. Mary Amoakoh-Coleman1,4,
  5. Ewoud Schuit5,
  6. Marcus J Rijken1,6,
  7. Kerstin Klipstein-Grobusch1,7,
  8. Kitty Bloemenkamp6,
  9. Diederick E Grobbee1,
  10. Joyce L Browne1
  1. 1Julius Global Health, Julius Center for Health Sciences and Primary Care, Universitair Medisch Centrum Utrecht, Utrecht University, Utrecht, The Netherlands
  2. 2Women's Health Research Institute, School of Population and Public Health, The University of British Columbia, Vancouver, British Columbia, Canada
  3. 3International Research Centre of Excellence, Institute of Human Virology, Abuja, Nigeria
  4. 4Noguchi Memorial Research Institute for Medical Research, University of Ghana, Legon, Ghana
  5. 5Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
  6. 6Division of Woman and Baby, Universitair Medisch Centrum Utrecht, Utrecht University, Utrecht, The Netherlands
  7. 7Division of Epidemiology & Biostatistics, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg-Braamfontein, South Africa
  1. Correspondence to Tessa Heestermans; tessaheestermans{at}gmail.com

Abstract

Introduction Ninety-nine per cent of all maternal and neonatal deaths occur in low-income and middle-income countries (LMIC). Prognostic models can provide standardised risk assessment to guide clinical management and can be vital to reduce and prevent maternal and perinatal mortality and morbidity. This review provides a comprehensive summary of prognostic models for adverse maternal and perinatal outcomes developed and/or validated in LMIC.

Methods A systematic search in four databases (PubMed/Medline, EMBASE, Global Health Library and The Cochrane Library) was conducted from inception (1970) up to 2 May 2018. Risk of bias was assessed with the PROBAST tool and narratively summarised.

Results 1741 articles were screened and 21 prognostic models identified. Seventeen models focused on maternal outcomes and four on perinatal outcomes, of which hypertensive disorders of pregnancy (n=9) and perinatal death including stillbirth (n=4) was most reported. Only one model was externally validated. Thirty different predictors were used to develop the models. Risk of bias varied across studies, with the item ‘quality of analysis’ performing the least.

Conclusion Prognostic models can be easy to use, informative and low cost with great potential to improve maternal and neonatal health in LMIC settings. However, the number of prognostic models developed or validated in LMIC settings is low and mirrors the 10/90 gap in which only 10% of resources are dedicated to 90% of the global disease burden. External validation of existing models developed in both LMIC and high-income countries instead of developing new models should be encouraged.

PROSPERO registration number CRD42017058044.

  • obstetrics
  • systematic review
  • maternal health

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/bmjgh-2019-001759

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    Footnotes

    • Handling editor Sanni Yaya

    • Contributors TH and JLB: conceptualised the study and created the first version of the review protocol. GAK, MA-C, ES, BP, MR, KK-G, KB and DG critically reviewed the review protocol and approved it. TH, JB, GAK and MA-C screened eligible articles. TH extracted the data, supported by JB, ES and BP. TH drafted the first version of the manuscript, supported by JLB and BP. All authors contributed to data interpretation and critically assessed it. All authors gave approval for the final version to be published and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or the integrity of any part of the work are appropriately investigated and resolved.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Competing interests None declared.

    • Patient consent for publication Not required.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data availability statement Data are available on reasonable request. All data relevant to the study are included in the article or uploaded as supplementary information.