History of mood or anxiety disorders and risk of gestational diabetes mellitus in a population‐based cohort
Bibliographic record
Abstract
AIM: To examine the association between mood and anxiety disorders and the development of gestational diabetes mellitus in a retrospective population-based cohort study. METHODS: Clinical data from a provincial perinatal health registry were linked to physician claims, hospitalization records and emergency visits to identify any diagnoses of mood or anxiety disorders in the 2 years prior to pregnancy and a subsequent diagnosis of gestational diabetes during pregnancy. The study population included all singleton pregnancies in the Canadian province of Alberta from 1 April 2000 to 31 March 2010. Generalized estimating equations were used to determine the adjusted odds ratio of gestational diabetes, comparing women with and without a history of mood or anxiety disorders. RESULTS: Among 373 674 pregnancies from 253 911 women, 25.7% had a history of mood or anxiety disorders, and 3.8% developed gestational diabetes. The multivariate-adjusted odds of developing gestational diabetes were higher among women with a history of mood or anxiety disorders (odds ratio 1.10, 95% CI 1.06-1.14). CONCLUSIONS: Women with a history of mood or anxiety disorders had a moderately increased risk of developing gestational diabetes.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".