@article {Heestermanse001759, author = {Tessa Heestermans and Beth Payne and Gbenga Ayodele Kayode and Mary Amoakoh-Coleman and Ewoud Schuit and Marcus J Rijken and Kerstin Klipstein-Grobusch and Kitty Bloemenkamp and Diederick E Grobbee and Joyce L Browne}, title = {Prognostic models for adverse pregnancy outcomes in low-income and middle-income countries: a systematic review}, volume = {4}, number = {5}, elocation-id = {e001759}, year = {2019}, doi = {10.1136/bmjgh-2019-001759}, publisher = {BMJ Specialist Journals}, 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 {\textquoteleft}quality of analysis{\textquoteright} 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.}, URL = {https://gh.bmj.com/content/4/5/e001759}, eprint = {https://gh.bmj.com/content/4/5/e001759.full.pdf}, journal = {BMJ Global Health} }