The University of Southampton
University of Southampton Institutional Repository

Antenatal blood pressure for prediction of pre-eclampsia, preterm birth, and small for gestational age babies: developmental and validation in two general population cohorts

Antenatal blood pressure for prediction of pre-eclampsia, preterm birth, and small for gestational age babies: developmental and validation in two general population cohorts
Antenatal blood pressure for prediction of pre-eclampsia, preterm birth, and small for gestational age babies: developmental and validation in two general population cohorts
Study question
Can routine antenatal blood pressure measurements between 20 and 36 weeks’ gestation contribute to the prediction of pre-eclampsia and its associated adverse outcomes?

Methods
This study used repeated antenatal measurements of blood pressure from 12?996 women in the Avon Longitudinal Study of Parents and Children (ALSPAC) to develop prediction models and validated these in 3005 women from the Southampton Women’s Survey (SWS). A model based on maternal early pregnancy characteristics only (BMI, height, age, parity, smoking, existing and previous gestational hypertension and diabetes, and ethnicity) plus initial mean arterial pressure was compared with a model additionally including current mean arterial pressure, a model including the deviation of current mean arterial pressure from a stratified normogram, and a model including both at different gestational ages from 20-36 weeks.

Study answer and limitations
The addition of blood pressure measurements from 28 weeks onwards improved prediction models compared with use of early pregnancy risk factors alone, but they contributed little to the prediction of preterm birth or small for gestational age. Though multiple imputation of missing data was used to increase the sample size and minimise selection bias, the validation sample might have been slightly underpowered as the number of cases of pre-eclampsia was just below the recommended 100. Several risk factors were self reported, potentially introducing measurement error, but this reflects how information would be obtained in clinical practice.

What this study adds
The addition of routinely collected blood pressure measurements from 28 weeks onwards improves predictive models for pre-eclampsia based on blood pressure in early pregnancy and other characteristics, facilitating a reduction in scheduled antenatal care.

Funding, competing interests, data sharing
UK Wellcome Trust, US National Institutes of Health, and UK Medical Research Council. Other funding sources for authors are detailed in the full online paper. With the exceptions of CM-W, HMI, and KMG there were no competing interests.
0959-8138
1-11
Macdonald-Wallis, C.
5efdfe21-18c1-4355-81e3-b86d38747c21
Silverwood, R.J.
c73234a3-4416-447d-bb56-9372d65b8d22
de Stavola, B.L.
ac5a3875-c959-4f20-ac02-722c3bb61910
Inskip, H.
5fb4470a-9379-49b2-a533-9da8e61058b7
Cooper, C.
e05f5612-b493-4273-9b71-9e0ce32bdad6
Godfrey, K.M.
0931701e-fe2c-44b5-8f0d-ec5c7477a6fd
Crozier, S.
9c3595ce-45b0-44fa-8c4c-4c555e628a03
Fraser, A.
2d1912cf-9bfb-4697-b8bf-cd855ff94ceb
Nelson, S.M.
607ef4e0-e87e-451f-8cb5-1bf4acaefbf6
Lawlor, D.A.
666139b1-03b8-4d92-bee7-98b5913fcb31
Tilling, K.
b9d899ac-8cfb-4036-96f3-4bc91af4ba83
Macdonald-Wallis, C.
5efdfe21-18c1-4355-81e3-b86d38747c21
Silverwood, R.J.
c73234a3-4416-447d-bb56-9372d65b8d22
de Stavola, B.L.
ac5a3875-c959-4f20-ac02-722c3bb61910
Inskip, H.
5fb4470a-9379-49b2-a533-9da8e61058b7
Cooper, C.
e05f5612-b493-4273-9b71-9e0ce32bdad6
Godfrey, K.M.
0931701e-fe2c-44b5-8f0d-ec5c7477a6fd
Crozier, S.
9c3595ce-45b0-44fa-8c4c-4c555e628a03
Fraser, A.
2d1912cf-9bfb-4697-b8bf-cd855ff94ceb
Nelson, S.M.
607ef4e0-e87e-451f-8cb5-1bf4acaefbf6
Lawlor, D.A.
666139b1-03b8-4d92-bee7-98b5913fcb31
Tilling, K.
b9d899ac-8cfb-4036-96f3-4bc91af4ba83

Macdonald-Wallis, C., Silverwood, R.J., de Stavola, B.L., Inskip, H., Cooper, C., Godfrey, K.M., Crozier, S., Fraser, A., Nelson, S.M., Lawlor, D.A. and Tilling, K. (2015) Antenatal blood pressure for prediction of pre-eclampsia, preterm birth, and small for gestational age babies: developmental and validation in two general population cohorts. British Medical Journal, 351 (h5948), 1-11. (doi:10.1136/bmj.h5948). (PMID:26578347)

Record type: Article

Abstract

Study question
Can routine antenatal blood pressure measurements between 20 and 36 weeks’ gestation contribute to the prediction of pre-eclampsia and its associated adverse outcomes?

Methods
This study used repeated antenatal measurements of blood pressure from 12?996 women in the Avon Longitudinal Study of Parents and Children (ALSPAC) to develop prediction models and validated these in 3005 women from the Southampton Women’s Survey (SWS). A model based on maternal early pregnancy characteristics only (BMI, height, age, parity, smoking, existing and previous gestational hypertension and diabetes, and ethnicity) plus initial mean arterial pressure was compared with a model additionally including current mean arterial pressure, a model including the deviation of current mean arterial pressure from a stratified normogram, and a model including both at different gestational ages from 20-36 weeks.

Study answer and limitations
The addition of blood pressure measurements from 28 weeks onwards improved prediction models compared with use of early pregnancy risk factors alone, but they contributed little to the prediction of preterm birth or small for gestational age. Though multiple imputation of missing data was used to increase the sample size and minimise selection bias, the validation sample might have been slightly underpowered as the number of cases of pre-eclampsia was just below the recommended 100. Several risk factors were self reported, potentially introducing measurement error, but this reflects how information would be obtained in clinical practice.

What this study adds
The addition of routinely collected blood pressure measurements from 28 weeks onwards improves predictive models for pre-eclampsia based on blood pressure in early pregnancy and other characteristics, facilitating a reduction in scheduled antenatal care.

Funding, competing interests, data sharing
UK Wellcome Trust, US National Institutes of Health, and UK Medical Research Council. Other funding sources for authors are detailed in the full online paper. With the exceptions of CM-W, HMI, and KMG there were no competing interests.

Text
Antenatal_BP_prediction_BMJ_pico 071020.docx - Accepted Manuscript
Download (38kB)
Text
bmj.h5948.full.pdf - Version of Record
Available under License Creative Commons Attribution.
Download (526kB)
Text
Supplemental Material 280715 BMJ McDonald-Wallis.docx - Other
Download (5MB)

More information

Published date: 17 November 2015
Organisations: Faculty of Medicine

Identifiers

Local EPrints ID: 384734
URI: http://eprints.soton.ac.uk/id/eprint/384734
ISSN: 0959-8138
PURE UUID: 90b2b2f2-da47-4ae4-9782-2a5745c7c45f
ORCID for H. Inskip: ORCID iD orcid.org/0000-0001-8897-1749
ORCID for C. Cooper: ORCID iD orcid.org/0000-0003-3510-0709
ORCID for K.M. Godfrey: ORCID iD orcid.org/0000-0002-4643-0618
ORCID for S. Crozier: ORCID iD orcid.org/0000-0002-9524-1127

Catalogue record

Date deposited: 14 Dec 2015 15:25
Last modified: 18 Mar 2024 02:53

Export record

Altmetrics

Contributors

Author: C. Macdonald-Wallis
Author: R.J. Silverwood
Author: B.L. de Stavola
Author: H. Inskip ORCID iD
Author: C. Cooper ORCID iD
Author: K.M. Godfrey ORCID iD
Author: S. Crozier ORCID iD
Author: A. Fraser
Author: S.M. Nelson
Author: D.A. Lawlor
Author: K. Tilling

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×