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Record W4415827725 · doi:10.1016/j.jcjd.2025.10.176

Lowering the Diagnostic Threshold for Gestational Diabetes: A Comparison of 2 Centres

2025· article· en· W4415827725 on OpenAlexafffundvenueabout
Sanaz Azizi, Agnieszka Majdan, Rachel Bond, Natasha Garfield, S. J. Meltzer, Shaun Eintracht, Julia Ma, Kaberi Dasgupta, Tricia M. Peters

Bibliographic record

VenueCanadian Journal of Diabetes · 2025
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsMcGill UniversityMD Precision (Canada)Group for Research in Decision AnalysisMcGill University Health CentreJewish General Hospital
FundersJewish General HospitalDiabète Québec
KeywordsAffect (linguistics)Gestational agePregnancyFetusGestation

Abstract

fetched live from OpenAlex

OBJECTIVE: In this study, we compared 2 gestational diabetes mellitus (GDM) diagnostic thresholds in relation to large-for-gestational-age (LGA) status and secondary adverse pregnancy outcomes. METHODS: This retrospective cohort study examined 840 pregnant women who underwent 2-step GDM screening at 2 hospital centres in Montréal that use distinct GDM diagnostic thresholds. At the second step of GDM screening, one centre used glucose thresholds suggested by the Diabetes Canada preferred approach and the other centre used the lower International Association of Diabetes and Pregnancy Study Groups thresholds. We defined mild hyperglycemia (MH) as having intermediate glucose values that were diagnostic of GDM at one centre but not the other (fasting plasma glucose [PG] 5.1 to 5.2 mmol/L, 1-hour PG 10 to 10.5 mmol/L, or 2-hour PG 8.5 to 8.9 mmol/L). We conducted multivariable linear and logistic regression analyses to evaluate outcomes for women with untreated or treated MH compared to those diagnosed with GDM by higher glucose thresholds within the same centre, and we also explored differences between centres. RESULTS: The odds of LGA offspring were 3-fold higher (adjusted odds ratio [OR] 3.01, 95% confidence interval [CI] 1.47 to 6.19) among women with untreated MH compared with women treated for GDM at the same centre. Also, the odds of macrosomia were over 2-fold higher when comparing treated MH with GDM. In addition, untreated compared with treated MH had lower odds of induction of labour (adjusted OR 0.28, 95% CI 0.11 to 0.70). CONCLUSION: Failure to optimally treat MH during pregnancy is associated with fetal overgrowth and may affect obstetrical management.

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)0.007
metaresearch head score (Gemma)0.037
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 score0.023
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.302
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 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
Published2025
Admission routes4
Has abstractyes

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