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Record W2019113075 · doi:10.1136/bmj.d1875

Clinical risk prediction for pre-eclampsia in nulliparous women: development of model in international prospective cohort

2011· article· en· W2019113075 on OpenAlexaff
R A North, Lesley McCowan, G.A. Dekker, Lucilla Poston, E. H. Y. Chan, A. W. Stewart, Michael A. Black, Rennae S. Taylor, James J. Walker, Philip N. Baker, Louise C. Kenny

Bibliographic record

VenueBMJ · 2011
Typearticle
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsUniversity of Alberta
FundersDirectorate for Biological SciencesGuy's and St Thomas' CharityTommy'sAuckland District Health BoardBiotechnology and Biological Sciences Research CouncilGovernment of South AustraliaNational Institute for Health and Care ResearchAustralian GovernmentHealth Research Board
KeywordsMedicineObstetricsEclampsiaPregnancyProspective cohort studyGestationMiscarriageBlood pressureHELLP syndromeCohortBirth weightGynecologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To develop a predictive model for pre-eclampsia based on clinical risk factors for nulliparous women and to identify a subgroup at increased risk, in whom specialist referral might be indicated. DESIGN: Prospective multicentre cohort. SETTING: Five centres in Auckland, New Zealand; Adelaide, Australia; Manchester and London, United Kingdom; and Cork, Republic of Ireland. PARTICIPANTS: 3572 "healthy" nulliparous women with a singleton pregnancy from a large international study; data on pregnancy outcome were available for 3529 (99%). MAIN OUTCOME MEASURE: Pre-eclampsia defined as ≥ 140 mm Hg or diastolic blood pressure ≥ 90 mm Hg, or both, on at least two occasions four hours apart after 20 weeks' gestation but before the onset of labour, or postpartum, with either proteinuria or any multisystem complication. Preterm pre-eclampsia was defined as women with pre-eclampsia delivered before 37(+0) weeks' gestation. In the stepwise logistic regression the comparison group was women without pre-eclampsia. RESULTS: Of the 3529 women, 186 (5.3%) developed pre-eclampsia, including 47 (1.3%) with preterm pre-eclampsia. Clinical risk factors at 14-16 weeks' gestation were age, mean arterial blood pressure, body mass index (BMI), family history of pre-eclampsia, family history of coronary heart disease, maternal birth weight, and vaginal bleeding for at least five days. Factors associated with reduced risk were a previous single miscarriage with the same partner, taking at least 12 months to conceive, high intake of fruit, cigarette smoking, and alcohol use in the first trimester. The area under the receiver operating characteristics curve (AUC), under internal validation, was 0.71. Addition of uterine artery Doppler indices did not improve performance (internal validation AUC 0.71). A framework for specialist referral was developed based on a probability of pre-eclampsia generated by the model of at least 15% or an abnormal uterine artery Doppler waveform in a subset of women with single risk factors. Nine per cent of nulliparous women would be referred for a specialist opinion, of whom 21% would develop pre-eclampsia. The relative risk for developing pre-eclampsia and preterm pre-eclampsia in women referred to a specialist compared with standard care was 5.5 and 12.2, respectively. CONCLUSIONS: The ability to predict pre-eclampsia in healthy nulliparous women using clinical phenotype is modest and requires external validation in other populations. If validated, it could provide a personalised clinical risk profile for nulliparous women to which biomarkers could be added. Trial registration ACTRN12607000551493.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.061
GPT teacher head0.361
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations424
Published2011
Admission routes1
Has abstractyes

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