Demographics, prevalence and outcomes of diabetes in pregnancy in NW Ontario
Bibliographic record
Abstract
INTRODUCTION: Diabetes in pregnancy confers increased risk. This study examines the prevalence and birth outcomes of diabetes in pregnancy at the Sioux Lookout Meno Ya Win Health Centre (SLMHC) and other small Ontario hospitals. METHODS: This was a retrospective study of maternal profile: age, parity, comorbidities, mode of delivery, neonatal birth weight, APGARS and complications. Data were compared to other Ontario hospitals offering an equivalent level of obstetrical services. RESULTS: Type 2 diabetes mellitus in pregnancy is far more prevalent in mothers who deliver at SLMHC (relative risk [RR]: 20.9, 95% confidence interval [CI]: 16.0-27.2); the rates of gestational diabetes (GDM) are double (RR: 2.0, 95% CI: 1.7-2.3). SLMHC mothers with diabetes were on average 5 years younger and of greater parity with increased substance use. Neonates largely had equivalent outcomes except for increased macrosomia, neonatal hypoglycaemia and hyperbilirubinaemia in GDM pregnancies. CONCLUSION: Patients with diabetes in pregnancy at SLMHC differ substantially from mothers delivering at Ontario hospitals with a comparable level of service. Programming and resources must meet the service needs of these patients.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".