Evidence map›Paper›PMID 28356148›Full record

ArticleBMC medicine2017

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

Shakila Thangaratinam, John Allotey, Nadine Marlin, Julie Dodds, Fiona Cheong-See, Peter von Dadelszen, Wessel Ganzevoort, Joost Akkermans, Sally Kerry, Ben W Mol and 4 more

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
6.5field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 1 synthesis or guideline pooled it, 70 citations in OpenAlex.

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  11. Evaluating the ability of fullPIERS calculator to predict adverse maternal outcomes in pre-eclampsia at Charlotte Maxeke Johannesburg Academic Hospital.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 4 institutions in 3 countries.

Shakila ThangaratinamWomen's Health Research Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
John AlloteyWomen's Health Research Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK. j.allotey@qmul.ac.uk.ORCID 0000-0003-4134-6246
Nadine MarlinPragmatic Clinical Trials Unit, Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University London, London, UK.
Julie DoddsWomen's Health Research Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Fiona Cheong-SeeWomen's Health Research Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Peter von DadelszenInstitute of Cardiovascular and Cell Sciences, St George's, University of London, London, UK.
Wessel GanzevoortDepartments of Obstetrics and Gynecology, University of Amsterdam, Academic Medical Center, Amsterdam, The Netherlands.
Joost AkkermansDepartment of Obstetrics, Leiden University Medical Center, Leiden, The Netherlands.
Sally KerryPragmatic Clinical Trials Unit, Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University London, London, UK.
Ben W MolThe Robinson Research Institute, School of Paediatrics and Reproductive Health, University of Adelaide, Adelaide, Australia.
Karl G M MoonsJulius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands.
Richard D RileyResearch Institute for Primary Care and Health Sciences, Keele University, Keele, Staffordshire, UK.
Khalid S KhanWomen's Health Research Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
PREP Collaborative Network
Queen Mary University of London · GBSt George's, University of London · GBUniversity Medical Center Utrecht · NLLeiden University Medical Center · NL

Funding

Department of Health 09/22/163
6 · The paper itself

Abstract

backgroundUnexpected 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.

methodWomen 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.

resultsA 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.

conclusionsPREP 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 registrationISRCTN40384046 , retrospectively registered.

Indexed as

AdultFemaleGestational AgeHumansInfant, NewbornLogistic ModelsPre-EclampsiaPregnancyPrenatal DiagnosisPrognosisProspective StudiesRisk AssessmentRisk FactorsUnited KingdomComplicationsEarly-onsetMaternalPre-eclampsiaPrognostic models

Identifiers

PMID28356148
PMCPMC5372261
OpenAlexW2603626049

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.