Trends in Obstetric Intervention and Pregnancy Outcomes of Canadian Women With Diabetes in Pregnancy From 2004 to 2015
Bibliographic record
Abstract
Multiple consensus statements decree that women with diabetes mellitus should have comparable birth outcomes to women without diabetes mellitus; however, there is a scarcity of contemporary population-based studies on this issue. To examine temporal trends in obstetric interventions and perinatal outcomes in a population-based cohort of women with type 1, type 2, or gestational diabetes mellitus compared with a control population. Cross-sectional study. National hospitalization data (Canada except Quebec) from 2004 to 2015. Pregnant women with type 1 (n = 7362), type 2 (n = 11,028), and gestational diabetes mellitus (n = 149,780) and women without diabetes mellitus (n = 2,688,231). Rates of obstetric intervention, maternal morbidity, and neonatal morbidity/mortality. A consistent relationship was generally observed between diabetes mellitus subtype and obstetric outcomes, with women with type 1 diabetes mellitus having the highest rate of intervention and the highest rates of adverse perinatal outcomes followed by women with type 2 diabetes mellitus and women with gestational diabetes mellitus. Rates of severe preeclampsia were 1.2% among women without diabetes mellitus, 2.1% among women with gestational diabetes mellitus, 4.2% among women with type 2 diabetes mellitus, and 7.5% among women with type 1 diabetes mellitus (P < 0.001). The rate of neonatal morbidity ranged from 8.7% in women without diabetes mellitus to 11.0%, 17.4%, and 24.1% in women with gestational, type 2, and type 1 diabetes mellitus, respectively (P < 0.001). In a contemporary obstetric population, women with diabetes mellitus remain at increased risk of adverse pregnancy outcomes compared with women without diabetes mellitus.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".