Trends in Incidence of Diabetes in Pregnancy and Serious Perinatal Outcomes: A Large, Population-Based Study in Ontario, Canada, 1996–2010
Bibliographic record
Abstract
OBJECTIVE: Women with diabetes in pregnancy have high rates of pregnancy complications. Our aims were to explore trends in the incidence of diabetes in pregnancy and examine whether the risk of serious perinatal outcomes has changed. RESEARCH DESIGN AND METHODS: We performed a population-based cohort study of 1,109,605 women who delivered in Ontario, Canada, between 1 April 1996 and 31 March 2010. We categorized women as gestational diabetes (GDM) (n = 45,384), pregestational diabetes (pre-GDM) (n = 13,278), or no diabetes (n = 1,050,943). The annual age-adjusted rates of diabetes in pregnancy were calculated, and rates of serious perinatal outcomes were compared between groups and by year using Poisson regression. RESULTS: The age-adjusted rate of both GDM (2.7-5.6%, P < 0.001) and pre-GDM (0.7-1.5%, P < 0.001) doubled from 1996 to 2010. The rate of congenital anomalies declined by 23%, whereas the rate of perinatal mortality did not change significantly. However, compared with women with no diabetes, women with pre-GDM and GDM faced an increased risk of congenital anomalies (relative risk 1.86 [95% CI 1.49-2.33] and 1.26 [1.09-1.45], respectively), and perinatal mortality remained elevated in women with pre-GDM (2.33 [1.59-3.43]). CONCLUSIONS: The incidence of both GDM and pre-GDM in pregnancy has doubled over the last 14 years, and the overall burden of diabetes in pregnancy on society is growing. Although congenital anomaly rates have declined in women with diabetes, perinatal mortality rates remain unchanged, and the risk of both remains significantly elevated compared with nondiabetic women. Increased efforts are needed to reduce these adverse outcomes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".