MétaCan
Menu
Back to cohort
Record W2753449397 · doi:10.1038/s41598-017-11432-5

Impact of maternal obesity on the incidence of pregnancy complications in France and Canada

2017· article· en· W2753449397 on OpenAlexafffundabout
F. Fuchs, Marie‐Victoire Sénat, Évelyne Rey, Jacques Balayla, Nils Chaillet, Jean Bouyer, François Audibert

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsCentre Hospitalier Universitaire Sainte-Justine
FundersCentre de recherche du CHU Sainte-JustineCollège National des Gynécologues et Obstétriciens Français
KeywordsIncidence (geometry)ObesityPregnancyObstetricsMedicineGynecologyBiologyInternal medicineGenetics

Abstract

fetched live from OpenAlex

The aim of our study was to compare the impact of maternal obesity on the incidence of medical complications of pregnancy in France and Canada. We performed a prospective comparative cohort study using French data, retrieved from a prospective cohort of singleton deliveries, and Canadian data retrieved from QUARISMA, a cluster-randomized controlled trial conducted in Quebec, both between 2009 and 2011. Outcomes studied included, hypertensive disorders of pregnancy (HDP), venous thromboembolism, stillbirth, caesarean delivery and macrosomia. The impact of obesity across both cohorts was studied using univariate and multivariate logistic regression analyses, adjusting for relevant confounders. The French and Canadian databases included 26,973 and 22,046 deliveries respectively, with obesity rates of 9.1% and 16% respectively (p < 0.001). In both cohorts, obesity was significantly associated with an increased rate of HDP, cesarean delivery, and macrosomia. However, in both cohorts the relationship between increasing body mass index and the incidence of medical complication of pregnancy was the same, regardless the outcome studied. In conclusion, obesity is a risk factor for adverse maternal and fetal outcomes in both cohorts. Similar trends of increased risk were noted in both cohorts even though obesity is more prevalent in Canada.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.140
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.317
Teacher spread0.295 · 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

Citations60
Published2017
Admission routes3
Has abstractyes

Explore more

Same venueScientific ReportsSame topicGestational Diabetes Research and ManagementFrench-language works237,207