Gestational diabetes in Manitoba during a twenty-year period
Bibliographic record
Abstract
PURPOSE: This retrospective cohort study was designed to examine the prevalence and risk factors of gestational diabetes mellitus (GDM) in Manitoba. METHODS: A total of 324,605 deliveries by 165,969 women were reported to Manitoba Health in the years 1985-2004. Data on maternal ages, delivery dates, GDM, self-declared First Nation (FN) status, rural or urban residence and previous GDM were collected for the study. Data were analyzed using multivariate logistic regression models. RESULTS: The prevalence of GDM during the 20-year period was 2.9%, which was 2.3% in 1985-1989 and 3.7% in 1999-2004 (P < 0.01). The trend of increase in the prevalence of GDM continued after major modifications on the screening and diagnostic criteria for GDM in 1998. The prevalence of GDM in FN women was 3-times greater than that in non-FN women. Higher prevalence of GDM was detected in FN pregnant women living in rural areas compared to those in urban areas (P < 0.01), which was opposite for non-FN pregnant women living in rural and urban areas. The prevalence of GDM in pregnant women > or =35 yr was 2.3-fold higher than that in those < 35 yr (P < 0.01). The recurrent rate of GDM was 44.4%. Adjusted odds ratios of GDM for FN status, advanced age, a history of GDM and rural living were 2.2, 2.4, 25.1 and 0.8, respectively. CONCLUSIONS: The prevalence of GDM is increased in Manitoba. FN status, advanced age and a history of GDM, but not rural living, are independent predictors for GDM.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".