Gestational diabetes mellitus and pregnancy outcomes among Chinese and South Asian women in Canada
Bibliographic record
Abstract
OBJECTIVE: To determine the association between Chinese or South Asian ethnicity and adverse neonatal and maternal outcomes for women with gestational diabetes compared to the general population. METHODS: A cohort study was conducted using population-based health care databases in Ontario, Canada. All 35,577 women aged 15-49 with gestational diabetes who had live births between April 2002 and March 2011 were identified. Their delivery hospitalization records and the birth records of their neonates were examined to identify adverse neonatal outcomes and adverse maternal outcomes. RESULTS: Compared to infants of mothers from the general population (55.5%), infants of Chinese mothers had a lower risk of an adverse outcome at delivery (42.9%, adjusted odds ratio 0.63, 95% confidence interval 0.58-0.68), whereas infants of South Asian mothers had a higher risk (58.9%, adjusted odds ratio 1.15, 95% confidence interval 1.07-1.23). Chinese women also had a lower risk of adverse maternal outcomes (32.4%, adjusted odds ratio 0.58, 95% confidence interval 0.54-0.63) compared to general population women (41.2%), whereas the risk for South Asian women was not different (39.4%, adjusted odds ratio 0.94, 95% confidence interval 0.88-1.02) from that of general population women. CONCLUSIONS: The risk of complications of gestational diabetes differs significantly between Chinese and South Asian patients and the general population in Ontario. Tailored interventions for gestational diabetes management may be required to improve pregnancy outcomes in high-risk ethnic groups.
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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 | 0.000 | 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".