Increased incidence of glucose disorders during pregnancy is not explained by pre-pregnancy obesity in London, Canada
Bibliographic record
Abstract
BACKGROUND: The increasing incidence of impaired glucose tolerance (IGT), gestational diabetes (GDM) and type 2 diabetes (T2D) during pregnancy was hypothesized to be associated with increases in pre-pregnancy body mass index (BMI). The aims were to 1) determine the prevalence of IGT/GDM/T2 D over a 10 year period; 2) examine the relationship between maternal overweight/obesity and IGT/GDM/T2D; and 3) examine the extent to which maternal metabolic complications impact maternal and fetal pregnancy outcomes. METHODS: Data arose from a perinatal database which contains maternal characteristics and perinatal outcome for all singleton infants born in London, Canada between January 1, 2000 and December 31, 2009. Univariable and multivariable odds ratios (OR) were estimated using logistic regression with IGT/GDM/T2 D being the outcome of interest. RESULTS: A total of 36,597 women were included in the analyses. Population incidence of IGT, GDM and T2 D rose from 0.7%, 2.9% and 0.5% in 2000 to 1.2%, 4.2% and 0.9% in 2009. The univariable OR for IGT, GDM and T2 D were 1.65, 1.52 and 2.06, respectively, over the ten year period. After controlling for maternal age, parity and pre-pregnancy BMI the OR did not decrease. Although there was a positive relationship between pre-pregnancy BMI and prevalence of IGT/GDM/T2 D, this did not explain the time trends in the latter. Diagnosis of IGT/GDM/T2 D increased the risk of having an Apgar score <7 at 5 minutes, which was partially explained by gestational hypertension, high placental ratio, gestational age and large for gestational age babies. CONCLUSIONS: We found a significant increase in the incidence of IGT/GDM/T2 D for the decade between 2000-2009 which was not explained by rising prevalence of maternal overweight/obesity.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".