MétaCan
Menu
← Back to cohort
Record W4407695031 · doi:10.1016/j.jogc.2025.102792

Twin Birth and Hemolysis, Elevated Liver Enzymes, and Low Platelets (HELLP) Syndrome: A Population-Based Study

2025· article· en· W4407695031 on OpenAlexafffundvenue
Sofia Nicolls, Li Qing Wang, Johanna Koegl, Janet Lyons, K.S. Joseph, Sarka Lisonkova

Bibliographic record

VenueJournal of Obstetrics and Gynaecology Canada · 2025
Typearticle
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsBC Children's HospitalUniversity of British ColumbiaWomen's Health Research Institute
FundersUniversity of British ColumbiaBC Children's Hospital
KeywordsMedicineHELLP syndromeElevated liver enzymesHemolysisLiver enzymePlateletPopulationPreeclampsiaPregnancyObstetricsEnzymeInternal medicineBiochemistryEnvironmental healthGenetics

Abstract

fetched live from OpenAlex

OBJECTIVES: Although twin pregnancies are known to have higher rates of preeclampsia, the association between twin pregnancy and Hemolysis, Elevated Liver Enzymes, and Low Platelet Count (HELLP) syndrome has not been adequately studied. We assessed the association between twin pregnancy and HELLP syndrome, and also examined gestational age-specific rates of HELLP syndrome in twin and singleton pregnancies. METHODS: weeks gestation in British Columbia, Canada, from 2008/09 to 2019/20. Data on the demographic and clinical characteristics were obtained from the British Columbia Perinatal Database Registry. Logistic regression was used to estimate adjusted odds ratios and 95% CIs, adjusted for maternal age, body mass index, smoking, and other potential confounders. RESULTS: weeks gestation in singleton pregnancies. CONCLUSIONS: weeks gestation onwards.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.008
GPT teacher head0.227
Teacher spread0.219 · 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

Citations2
Published2025
Admission routes3
Has abstractno

Explore more

Same venueJournal of Obstetrics and Gynaecology Canada→Same topicPregnancy and preeclampsia studies→French-language works237,207→