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Prediction Models for Adverse Pregnancy Outcomes in India: Methodological Considerations for an Emerging Topic
Stillbirth is over-represented in lower and lower-middle-income countries and understandably this has motivated greater research investment in the development of prediction models. Prediction is particularly challenging for pregnancy outcomes because only part of the population is represented in obs...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer India
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10615984/ https://www.ncbi.nlm.nih.gov/pubmed/37916050 http://dx.doi.org/10.1007/s13224-021-01617-4 |
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author | Pereira, Gavin |
author_facet | Pereira, Gavin |
author_sort | Pereira, Gavin |
collection | PubMed |
description | Stillbirth is over-represented in lower and lower-middle-income countries and understandably this has motivated greater research investment in the development of prediction models. Prediction is particularly challenging for pregnancy outcomes because only part of the population is represented in observational research. Notably, unrecognised pregnancies and miscarriages are typically excluded from the development of prediction models and the consequences of such selection are not well understood. Other methodological challenges in developing stillbirth prediction models are within the control of the researcher. Identifying whether the intended model is for aetiological explanation versus prediction, attainment of a sufficiently large representative sample, and internal and external validation are among such methodological considerations. These considerations are discussed in relation to a recently published study on prediction of stillbirth after 28 weeks of pregnancy for women with hypertensive disorders of pregnancy in India. The predictive ability of this model amounts to the flip of a coin. Future screening based on such a model may be expensive, increase psychological distress among patients and introduce additional iatrogenic perinatal morbidities from over-treatment. Future research should address the methodological considerations described in this article. |
format | Online Article Text |
id | pubmed-10615984 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer India |
record_format | MEDLINE/PubMed |
spelling | pubmed-106159842023-11-01 Prediction Models for Adverse Pregnancy Outcomes in India: Methodological Considerations for an Emerging Topic Pereira, Gavin J Obstet Gynaecol India Short Commentary Stillbirth is over-represented in lower and lower-middle-income countries and understandably this has motivated greater research investment in the development of prediction models. Prediction is particularly challenging for pregnancy outcomes because only part of the population is represented in observational research. Notably, unrecognised pregnancies and miscarriages are typically excluded from the development of prediction models and the consequences of such selection are not well understood. Other methodological challenges in developing stillbirth prediction models are within the control of the researcher. Identifying whether the intended model is for aetiological explanation versus prediction, attainment of a sufficiently large representative sample, and internal and external validation are among such methodological considerations. These considerations are discussed in relation to a recently published study on prediction of stillbirth after 28 weeks of pregnancy for women with hypertensive disorders of pregnancy in India. The predictive ability of this model amounts to the flip of a coin. Future screening based on such a model may be expensive, increase psychological distress among patients and introduce additional iatrogenic perinatal morbidities from over-treatment. Future research should address the methodological considerations described in this article. Springer India 2022-03-10 2023-10 /pmc/articles/PMC10615984/ /pubmed/37916050 http://dx.doi.org/10.1007/s13224-021-01617-4 Text en © Crown 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Short Commentary Pereira, Gavin Prediction Models for Adverse Pregnancy Outcomes in India: Methodological Considerations for an Emerging Topic |
title | Prediction Models for Adverse Pregnancy Outcomes in India: Methodological Considerations for an Emerging Topic |
title_full | Prediction Models for Adverse Pregnancy Outcomes in India: Methodological Considerations for an Emerging Topic |
title_fullStr | Prediction Models for Adverse Pregnancy Outcomes in India: Methodological Considerations for an Emerging Topic |
title_full_unstemmed | Prediction Models for Adverse Pregnancy Outcomes in India: Methodological Considerations for an Emerging Topic |
title_short | Prediction Models for Adverse Pregnancy Outcomes in India: Methodological Considerations for an Emerging Topic |
title_sort | prediction models for adverse pregnancy outcomes in india: methodological considerations for an emerging topic |
topic | Short Commentary |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10615984/ https://www.ncbi.nlm.nih.gov/pubmed/37916050 http://dx.doi.org/10.1007/s13224-021-01617-4 |
work_keys_str_mv | AT pereiragavin predictionmodelsforadversepregnancyoutcomesinindiamethodologicalconsiderationsforanemergingtopic |