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

BMJ 2015; 351 doi: https://doi.org/10.1136/bmj.h5948 (Published 17 November 2015) Cite this as: BMJ 2015;351:h5948
  1. Corrie Macdonald-Wallis, research fellow12,
  2. Richard J Silverwood, lecturer in medical statistics34,
  3. Bianca L de Stavola, professor of biostatistics34,
  4. Hazel Inskip, professor of statistical epidemiology56,
  5. Cyrus Cooper, professor of rheumatology567,
  6. Keith M Godfrey, professor of epidemiology and human development56,
  7. Sarah Crozier, statistician5,
  8. Abigail Fraser, senior research fellow12,
  9. Scott M Nelson, professor of obstetrics and gynaecology8,
  10. Debbie A Lawlor, professor of epidemiology12,
  11. Kate Tilling, professor of medical statistics12
  1. 1MRC Integrative Epidemiology Unit at the University of Bristol, Bristol BS8 2BN, UK
  2. 2School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK
  3. 3Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
  4. 4Centre for Statistical Methodology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
  5. 5MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton SO16 6YD, UK
  6. 6NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton General Hospital, Southampton SO16 6YD, UK
  7. 7National Institute for Health Research Musculoskeletal Biomedical Research Unit, University of Oxford, Oxford OX3 7LE, UK
  8. 8School of Medicine, University of Glasgow, Glasgow G12 8QQ, UK
  1. Correspondence to: C Macdonald-Wallis C.Macdonald-Wallis{at}bristol.ac.uk

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.

Footnotes

  • We thank all of the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists, and nurses. We also thank the parents and children in the SWS who participated and the SWS staff who collected and processed the data.

  • Up to August 2016 the corresponding author is D Lawlor d.a.lawlor{at}bristol.ac.uk

  • Contributors: CM-W, RJS, BLDS, DAL, and KT contributed to the conception and design of the study and planned the statistical analysis. HI prepared the SWS dataset and HI and SC advised on matters relating to this cohort. CM-W completed the analyses and wrote the first draft of the paper. All authors contributed to the interpretation of findings, revising the manuscript for important intellectual content, and approved the final version to be published. All authors had full access to all of the data (including statistical reports and tables) in the study and can take responsibility for the integrity of the data and the accuracy of the data analysis. CM-W is guarantor.

  • Funding: This work was supported by the UK Wellcome Trust (grant No WT087997MA) and US National Institutes of Health (grant No R01 DK077659). CM-W and AF are funded by UK Medical Research Council (MRC) research fellowships (grant No MR/J011932/1 and 0701594, respectively). Core support for ALSPAC is provided by the UK MRC, the Wellcome Trust, and the University of Bristol. CMW, DAL, AF, and KT work in a unit that receives funds from the UK MRC (MC_UU_12013/5 and MC_UU_12013/9). DAL has a National Institute of Health Research Senior Investigator Award (NF-SI-0611-10196). Core support for SWS is provided by the UK MRC, with adjunctive support from the European Union’s Seventh Framework Programme (FP7/2007-2013), project EarlyNutrition under grant agreement n 289346. KMG and CC are supported by the National Institute for Health Research through the NIHR Southampton Biomedical Research Centre. The funders had no role in study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the article for publication.

  • Competing interest declaration: All authors have completed the Unified Competing Interest form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author). HMI received salary from UK Medical Research Council, during the conduct of the study and members of her team received grants from Danone, Nestec, and Abbott Nutrition, outside the submitted work; KMG has received funding from Nestle Nutrition Institute, Abbott Nutrition, and Nestec, outside the submitted work. KMG has a patent Phenotype prediction pending, a patent Predictive use of CpG methylation pending, and a patent Maternal Nutrition Composition pending.

  • Ethical approval: The study was approved by the ALSPAC law and ethics committee and the NHS local ethics committee.

  • Transparency declaration: The lead author (the manuscript’s guarantor) affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned have been explained.

  • Data sharing: No additional data available; collaborators can access existing data in either ALSPAC (www.bristol.ac.uk/alspac) or SWS (www.mrc.soton.ac.uk/sws) through their respective websites which provide information on how to do this.

This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/.

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