Impact of pre-pregnancy diabetes mellitus on congenital anomalies, Canada, 2002–2012
Bibliographic record
Abstract
OBJECTIVE: To examine the impact of pre-pregnancy diabetes mellitus (DM) on the population birth prevalence of congenital anomalies in Canada. METHODS: We carried out a population-based study of all women who delivered in Canadian hospitals (except those in the province of Quebec) between April 2002 and March 2013 and their live-born infants with a birth weight of 500 grams or more and/or a gestational age of 22 weeks or more. Pre-pregnancy type 1 or type 2 DM was identified using ICD-10 diagnostic codes. The association between DM and all congenital anomalies as well as specific congenital anomaly categories was estimated using adjusted odds ratios; the impact was calculated as a population attributable risk percent (PAR%). RESULTS: There were 118,892 infants with a congenital anomaly among 2,839,680 live births (41.9 per 1000). While the prevalence of any congenital anomaly declined from 50.7 per 1000 live births in 2002/03 to 41.5 per 1000 in 2012/13, the corresponding PAR% for a congenital anomaly related to pre-pregnancy DM rose from 0.6% (95% confidence interval [CI]: 0.4-0.8) to 1.2% (95% CI: 0.9-1.4). Specifically, the PAR% for congenital cardiovascular defects increased from 2.3% (95% CI: 1.7-2.9) to 4.2% (95% CI: 3.5-4.9) and for gastrointestinal defects from 0.8% (95% CI: 0.2-1.9) to 1.4% (95% CI: 0.7-2.6) over the study period. CONCLUSION: Although there has been a relative decline in the prevalence of congenital anomalies in Canada, the proportion of congenital anomalies due to maternal pre-pregnancy DM has increased. Enhancement of preconception care initiatives for women with DM is recommended.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".