Gestational diabetes care and outcomes for refugee women: a population‐based cohort study
Bibliographic record
Abstract
AIM: To determine the prevalence of adverse clinical outcomes, the rates of healthcare utilization, and the incidence of post-partum Type 2 diabetes in refugees with gestational diabetes (GDM), compared with other immigrants and non-immigrants. METHODS: A population-based cohort study was conducted using healthcare databases in Ontario, Canada. Over 40 000 women with GDM having singleton live births between 2002 and 2014 were identified. We identified GDM adverse outcomes such as macrosomia, pre-eclampsia and respiratory distress syndrome. Antenatal and newborn healthcare utilization were ascertained. Women were then followed for diagnosis of diabetes post-partum. RESULTS: Both refugees and other immigrants had a lower rate than non-immigrants of many adverse GDM outcomes, including pre-eclampsia [relative risk (RR) 0.65, 95% confidence interval (95% CI) 0.44-0.95 and 0.61, 95% CI 0.52-0.72, respectively], preterm birth (RR 0.87, 95% CI 0.75-0.995 and 0.85, 95% CI 0.80-0.91, respectively), and respiratory distress syndrome (RR 0.83, 95% CI 0.70-0.97 and 0.78, 95% CI 0.72-0.84, respectively). However, refugees were less likely to attend well-baby care in time for the first routine vaccination (RR 0.92, 95% CI 0.88-0.95). Incidence of post-partum diabetes was high in all groups, but refugee women were at increased risk (hazard ratio 1.23, 95% CI 1.11-1.37). CONCLUSIONS: Despite different circumstances leading to migration, refugees have a similar 'healthy immigrant effect' to other immigrants, with respect to adverse GDM outcomes. However, newborns of refugees were less likely to have well-baby care, and refugee women were also at especially high risk of developing diabetes post-partum. These are both important public health issues.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".