SORA

Advancing, promoting and sharing knowledge of health through excellence in teaching, clinical practice and research into the prevention and treatment of illness

Prediction of complications in early-onset pre-eclampsia (PREP): development and external multinational validation of prognostic models.

Thangaratinam, S; Allotey, J; Marlin, N; Dodds, J; Cheong-See, F; von Dadelszen, P; Ganzevoort, W; Akkermans, J; Kerry, S; Mol, BW; et al. Thangaratinam, S; Allotey, J; Marlin, N; Dodds, J; Cheong-See, F; von Dadelszen, P; Ganzevoort, W; Akkermans, J; Kerry, S; Mol, BW; Moons, KGM; Riley, RD; Khan, KS; PREP Collaborative Network (2017) Prediction of complications in early-onset pre-eclampsia (PREP): development and external multinational validation of prognostic models. BMC Medicine, 15 (68). https://doi.org/10.1186/s12916-017-0827-3
SGUL Authors: von Dadelszen, Peter

[img]
Preview
PDF Published Version
Available under License Creative Commons Attribution.

Download (955kB) | Preview

Abstract

BACKGROUND: Unexpected clinical deterioration before 34 weeks gestation is an undesired course in early-onset pre-eclampsia. To safely prolong preterm gestation, accurate and timely prediction of complications is required. METHOD: Women with confirmed early onset pre-eclampsia were recruited from 53 maternity units in the UK to a large prospective cohort study (PREP-946) for development of prognostic models for the overall risk of experiencing a complication using logistic regression (PREP-L), and for predicting the time to adverse maternal outcome using a survival model (PREP-S). External validation of the models were carried out in a multinational cohort (PIERS-634) and another cohort from the Netherlands (PETRA-216). Main outcome measures were C-statistics to summarise discrimination of the models and calibration plots and calibration slopes. RESULTS: A total of 169 mothers (18%) in the PREP dataset had adverse outcomes by 48 hours, and 633 (67%) by discharge. The C-statistics of the models for predicting complications by 48 hours and by discharge were 0.84 (95% CI, 0.81-0.87; PREP-S) and 0.82 (0.80-0.84; PREP-L), respectively. The PREP-S model included maternal age, gestation, medical history, systolic blood pressure, deep tendon reflexes, urine protein creatinine ratio, platelets, serum alanine amino transaminase, urea, creatinine, oxygen saturation and treatment with antihypertensives or magnesium sulfate. The PREP-L model included the above except deep tendon reflexes, serum alanine amino transaminase and creatinine. On validation in the external PIERS dataset, the reduced PREP-S model showed reasonable calibration (slope 0.80) and discrimination (C-statistic 0.75) for predicting adverse outcome by 48 hours. Reduced PREP-L model showed excellent calibration (slope: 0.93 PIERS, 0.90 PETRA) and discrimination (0.81 PIERS, 0.75 PETRA) for predicting risk by discharge in the two external datasets. CONCLUSIONS: PREP models can be used to obtain predictions of adverse maternal outcome risk, including early preterm delivery, by 48 hours (PREP-S) and by discharge (PREP-L), in women with early onset pre-eclampsia in the context of current care. They have a potential role in triaging high-risk mothers who may need transfer to tertiary units for intensive maternal and neonatal care. TRIAL REGISTRATION: ISRCTN40384046 , retrospectively registered.

Item Type: Article
Additional Information: © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Keywords: Complications, Early-onset, Maternal, Pre-eclampsia, Prognostic models, Adult, Female, Gestational Age, Humans, Infant, Newborn, Logistic Models, Pre-Eclampsia, Pregnancy, Prenatal Diagnosis, Prognosis, Prospective Studies, Risk Assessment, Risk Factors, United Kingdom, Early-onset, Pre-eclampsia, Prognostic models, Maternal, Complications, General & Internal Medicine, 11 Medical And Health Sciences
SGUL Research Institute / Research Centre: Academic Structure > Molecular and Clinical Sciences Research Institute (MCS)
Journal or Publication Title: BMC Medicine
Language: eng
Dates:
DateEvent
30 March 2017Published
23 February 2017Accepted
Publisher License: Creative Commons: Attribution 4.0
Projects:
Project IDFunderFunder ID
09/22/163National Institute for Health Researchhttp://dx.doi.org/10.13039/501100000272
PubMed ID: 28356148
Web of Science ID: WOS:000397679200001
Go to PubMed abstract
URI: http://sgultest.da.ulcc.ac.uk/id/eprint/109376
Publisher's version: https://doi.org/10.1186/s12916-017-0827-3

Actions (login required)

Edit Item Edit Item