Prognostic models for adverse pregnancy outcomes in low-income and middle-income countries: a systematic review
IntroductionNinety-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....
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMJ Publishing Group
2019-09-01
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| Series: | BMJ Global Health |
| Online Access: | https://gh.bmj.com/content/4/5/e001759.full |
| _version_ | 1818611078855131136 |
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| author | Kerstin Klipstein-Grobusch Kitty Bloemenkamp Joyce L Browne Marcus J Rijken Mary Amoakoh-Coleman Tessa Heestermans Beth Payne Gbenga Ayodele Kayode Ewoud Schuit |
| author_facet | Kerstin Klipstein-Grobusch Kitty Bloemenkamp Joyce L Browne Marcus J Rijken Mary Amoakoh-Coleman Tessa Heestermans Beth Payne Gbenga Ayodele Kayode Ewoud Schuit |
| author_sort | Kerstin Klipstein-Grobusch |
| collection | DOAJ |
| description | IntroductionNinety-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.MethodsA 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.Results1741 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.ConclusionPrognostic 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 numberCRD42017058044. |
| first_indexed | 2024-12-16T15:24:37Z |
| format | Article |
| id | doaj.art-9d92e1b3833d4ef4a2114b7f3ba534f1 |
| institution | Directory Open Access Journal |
| issn | 2059-7908 |
| language | English |
| last_indexed | 2024-12-16T15:24:37Z |
| publishDate | 2019-09-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Global Health |
| spelling | doaj.art-9d92e1b3833d4ef4a2114b7f3ba534f12022-12-21T22:26:33ZengBMJ Publishing GroupBMJ Global Health2059-79082019-09-014510.1136/bmjgh-2019-001759Prognostic models for adverse pregnancy outcomes in low-income and middle-income countries: a systematic reviewKerstin Klipstein-Grobusch0Kitty Bloemenkamp1Joyce L Browne2Marcus J Rijken3Mary Amoakoh-Coleman4Tessa Heestermans5Beth Payne6Gbenga Ayodele Kayode7Ewoud Schuit8Julius Global Health, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, NetherlandsDivision of Woman and Baby, Universitair Medisch Centrum Utrecht, Utrecht University, Utrecht, The NetherlandsJulius Global Health, Julius Center for Health Sciences and Primary Care, Universitair Medisch Centrum Utrecht, Utrecht University, Utrecht, The NetherlandsJulius Global Health, Julius Center for Health Sciences and Primary Care, Universitair Medisch Centrum Utrecht, Utrecht University, Utrecht, The NetherlandsJulius Global Health, Julius Center for Health Sciences and Primary Care, Universitair Medisch Centrum Utrecht, Utrecht University, Utrecht, The NetherlandsJulius Global Health, Julius Center for Health Sciences and Primary Care, Universitair Medisch Centrum Utrecht, Utrecht University, Utrecht, The NetherlandsJulius Global Health, Julius Center for Health Sciences and Primary Care, Universitair Medisch Centrum Utrecht, Utrecht University, Utrecht, The NetherlandsJulius Global Health, Julius Center for Health Sciences and Primary Care, Universitair Medisch Centrum Utrecht, Utrecht University, Utrecht, The NetherlandsJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The NetherlandsIntroductionNinety-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.MethodsA 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.Results1741 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.ConclusionPrognostic 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 numberCRD42017058044.https://gh.bmj.com/content/4/5/e001759.full |
| spellingShingle | Kerstin Klipstein-Grobusch Kitty Bloemenkamp Joyce L Browne Marcus J Rijken Mary Amoakoh-Coleman Tessa Heestermans Beth Payne Gbenga Ayodele Kayode Ewoud Schuit Prognostic models for adverse pregnancy outcomes in low-income and middle-income countries: a systematic review BMJ Global Health |
| title | Prognostic models for adverse pregnancy outcomes in low-income and middle-income countries: a systematic review |
| title_full | Prognostic models for adverse pregnancy outcomes in low-income and middle-income countries: a systematic review |
| title_fullStr | Prognostic models for adverse pregnancy outcomes in low-income and middle-income countries: a systematic review |
| title_full_unstemmed | Prognostic models for adverse pregnancy outcomes in low-income and middle-income countries: a systematic review |
| title_short | Prognostic models for adverse pregnancy outcomes in low-income and middle-income countries: a systematic review |
| title_sort | prognostic models for adverse pregnancy outcomes in low income and middle income countries a systematic review |
| url | https://gh.bmj.com/content/4/5/e001759.full |
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