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Published in: The Journal of Obstetrics and Gynecology of India 5/2023

Open Access 10-03-2022 | Short Commentary

Prediction Models for Adverse Pregnancy Outcomes in India: Methodological Considerations for an Emerging Topic

Author: Gavin Pereira

Published in: The Journal of Obstetrics and Gynecology of India | Issue 5/2023

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Abstract

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.
Literature
3.
go back to reference Malacova E, Tippaya S, Bailey HD, Chai K, Farrant BM, Gebremedhin AT, Leonard H, Marinovich ML, Nassar N, Phatak A, Raynes-Greenow C, Regan AK, Shand AW, Shepherd CCJ, Srinivasjois R, Tessema GA, Pereira G. Stillbirth risk prediction using machine learning for a large cohort of births from Western Australia, 1980–2015. Nat Sci Rep. 2020;10(1):5354. Malacova E, Tippaya S, Bailey HD, Chai K, Farrant BM, Gebremedhin AT, Leonard H, Marinovich ML, Nassar N, Phatak A, Raynes-Greenow C, Regan AK, Shand AW, Shepherd CCJ, Srinivasjois R, Tessema GA, Pereira G. Stillbirth risk prediction using machine learning for a large cohort of births from Western Australia, 1980–2015. Nat Sci Rep. 2020;10(1):5354.
4.
go back to reference Pereira G, Regan AK, Wong K, Tessema GA. Gestational age as a predictor for subsequent preterm birth in New South Wales Australia. BMC Pregnancy Childbirth. 2021;21(1):1–7.CrossRef Pereira G, Regan AK, Wong K, Tessema GA. Gestational age as a predictor for subsequent preterm birth in New South Wales Australia. BMC Pregnancy Childbirth. 2021;21(1):1–7.CrossRef
5.
go back to reference Pereira E, Tessema G, Gissler M, Regan AK, Pereira G. Re-evaluation of gestational age as a predictor for subsequent preterm birth. Plos one. 2021;16(1):e0245935.CrossRefPubMedPubMedCentral Pereira E, Tessema G, Gissler M, Regan AK, Pereira G. Re-evaluation of gestational age as a predictor for subsequent preterm birth. Plos one. 2021;16(1):e0245935.CrossRefPubMedPubMedCentral
6.
go back to reference Sexton JK, Coory M, Kumar S, Smith G, Gordon A, Chambers G, Pereira G, Raynes-Greenow C, Hilder L, Middleton P. Protocol for the development and validation of a risk prediction model for stillbirths from 35 weeks gestation in Australia. Diagn Progn Res. 2020;4(1):1–8.CrossRef Sexton JK, Coory M, Kumar S, Smith G, Gordon A, Chambers G, Pereira G, Raynes-Greenow C, Hilder L, Middleton P. Protocol for the development and validation of a risk prediction model for stillbirths from 35 weeks gestation in Australia. Diagn Progn Res. 2020;4(1):1–8.CrossRef
7.
go back to reference Malacova E, Regan A, Nassar N, Raynes-Greenow C, Leonard H, Srinivasjois R, Shand AW, Lavin T, Pereira G. Risk of stillbirth, preterm delivery, and fetal growth restriction following exposure in a previous birth: systematic review and meta-analysis. BJOG: Int J Obstet Gynaecol. 2018;125(2):183–92.CrossRef Malacova E, Regan A, Nassar N, Raynes-Greenow C, Leonard H, Srinivasjois R, Shand AW, Lavin T, Pereira G. Risk of stillbirth, preterm delivery, and fetal growth restriction following exposure in a previous birth: systematic review and meta-analysis. BJOG: Int J Obstet Gynaecol. 2018;125(2):183–92.CrossRef
Metadata
Title
Prediction Models for Adverse Pregnancy Outcomes in India: Methodological Considerations for an Emerging Topic
Author
Gavin Pereira
Publication date
10-03-2022
Publisher
Springer India
Published in
The Journal of Obstetrics and Gynecology of India / Issue 5/2023
Print ISSN: 0971-9202
Electronic ISSN: 0975-6434
DOI
https://doi.org/10.1007/s13224-021-01617-4

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