Intrapartum Corticosteroid use Significantly Increases the Risk of Gestational Diabetes in Women with Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND AND AIMS: Women with inflammatory bowel disease (IBD) may be at higher risk of adverse pregnancy outcomes. This study compared perinatal outcomes in women with and without IBD. METHODS: The population-based Data Integration, Measurement, and Reporting (DIMR) administrative discharge database was used to identify women (≥18 years of age) in Alberta, Canada, with IBD who delivered a baby between 2006 and 2009 inclusive. Women without IBD were randomly sampled and matched in a 3:1 ratio to IBD cases by age at conception (±1 year). Odds ratios of gestational diabetes, preterm birth, low birth weight, cesarean section, and neonatal intensive care unit admission were calculated. RESULTS: One hundred and sixteen IBD patients were age-matched to 381 pregnant women without IBD. Gestational diabetes, preterm birth, and cesarean section were more common in women with IBD compared with controls (6.9 versus 1.8%, p = 0.03; 12.9 versus 0.3%, p < 0.0001; 43.1 versus 21.0%, p = 0.009, respectively). On multivariate analysis, women with IBD were independently more likely to have gestational diabetes (odds ratio [OR] = 4.3; 95% confidence interval [CI] 1.2-16.3), preterm birth (OR = 19.7, 95% CI 2.2-173.9), and to deliver by cesarean section (OR = 2.7, 95% CI 1.6-4.6) after adjusting for age and smoking status. CONCLUSION: Intrapartum corticosteroid use significantly increases the risk of gestational diabetes in women with IBD. Furthermore, IBD patients are at higher risk of preterm delivery and are more likely to undergo cesarean section compared with a healthy age-matched population. The finding of a higher risk of gestational diabetes is a novel finding not previously reported in the IBD literature.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".