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Record W2522110417 · doi:10.1002/uog.16061

OC08.01: Effective screening for pre‐eclampsia by maternal factors and biomarkers at 11–13 weeks' gestation

2016· article· en· W2522110417 on OpenAlexfundno aff
Liona C. Poon, K. H. Nicolaides

Bibliographic record

VenueUltrasound in Obstetrics and Gynecology · 2016
Typearticle
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsnot available
FundersUniversità di BolognaUniversità Cattolica del Sacro CuoreLunds UniversitetSchool of Medicine, New York UniversityYork University
KeywordsMedicineGestationObstetricsEclampsiaUterine arteryPregnancyGestational agePlacental growth factorConfidence intervalPreeclampsiaSmall for gestational ageFetusProspective cohort studyGynecologyInternal medicine

Abstract

fetched live from OpenAlex

The purpose of this study was to develop a competing risk model for pre-eclampsia (PE) based on maternal factors and biomarkers. The data for this study were derived from prospective screening for adverse outcomes in women who attended for their routine first scan at 11–13 weeks gestation in 2 maternity hospitals in England. We screened near 36,948 singleton pregnancies that included 1,058 pregnancies (2.9%) that developed PE. Bayes theorem was used to combine the a priori risk from maternal factors with various combinations of biophysical and biochemical markers multiple of the median values. Five-fold cross validation was used to assess the performance of screening for PE that delivered at <37 weeks gestation (preterm-PE) and ≥37 weeks gestation (term-PE) by models that combined maternal factors with individual biomarkers and their combination with screening by maternal factors alone. In pregnancies that developed PE the values of uterine artery pulsatility index (PI) and mean arterial pressure (MAP) were increased, and the values of serum pregnancy-associated plasma protein-A (PAPP-A), and placental growth factor (PlGF) were decreased. For all biomarkers, the deviation from normal was greater for preterm than term-PE; therefore, the performance of screening was related inversely to the gestational age at which delivery became necessary for maternal and/or fetal indications. Combined screening by maternal factors, uterine artery PI, MAP, and PlGF predicted 75% (95% confidence interval [CI], 70-80%) of preterm-PE and 47% (95% CI, 44-51%) of term-PE, at a false-positive rate of 10%; inclusion of PAPP-A did not improve the performance of screening. Such detection rates are superior to the respective values of 49% (95% CI, 43-55%) and 38% (34-41%) that were achieved by screening with maternal factors alone. Combination of maternal factors and biomarkers provides effective first-trimester screening for preterm-PE.

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)0.004
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.013
GPT teacher head0.265
Teacher spread0.251 · 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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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