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The risk of unexplained antepartum stillbirth in second pregnancies following caesarean section in the first pregnancy

2008· article· en· W2094712768 on OpenAlexaffabout
SL Wood, S Chen, Sue Ross, Reg Sauvé

Bibliographic record

VenueBJOG An International Journal of Obstetrics & Gynaecology · 2008
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsAlberta Health ServicesCalgary General HospitalFoothills Medical CentreUniversity of Calgary
Fundersnot available
KeywordsCaesarean sectionObstetricsMedicinePregnancyAntepartum haemorrhageLogistic regressionPopulationRetrospective cohort studyGynecologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine if a previous caesarean section increases the risk of unexplained antepartum stillbirth in second pregnancies. STUDY DESIGN: Retrospective cohort study. SETTING: Large Canadian perinatal database. POPULATION: 158 502 second births. METHODS: Data were obtained from a large perinatal database, which supplied data on demographics, pregnancy complications, maternal medical conditions, previous caesarean section and pregnancy outcomes. MAIN OUTCOME MEASURES: Total and unexplained stillbirth. RESULTS: The antepartum stillbirth rate was 3.0/1000 in the previous caesarean section group compared with 2.7/1000 in the previous vaginal delivery group (P= 0.46). Multivariate logistic regression modelling, including terms for maternal age (polynomial), weight >91 kg, smoking during pregnancy, pre-pregnancy hypertension and diabetes, did not document an association between previous caesarean section and unexplained antepartum stillbirth (OR 1.27, 95% CI 0.92-1.77). CONCLUSION: Caesarean section in the first birth does not increase the risk of unexplained antepartum stillbirth in second pregnancies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.009
Threshold uncertainty score0.313

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.310
Teacher spread0.282 · 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 teacher head, 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

Citations44
Published2008
Admission routes2
Has abstractyes

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