Fetal Sex and the Natural History of Maternal Risk of Diabetes During and After Pregnancy
Bibliographic record
Abstract
CONTEXT: It has recently emerged that carrying a male fetus is associated with poorer maternal β-cell function in pregnancy and an increased risk of gestational diabetes mellitus (GDM). β-cell dysfunction is the central pathophysiologic defect underlying both GDM and subsequent postpartum progression to type 2 diabetes mellitus (T2DM). OBJECTIVE: This was a retrospective cohort study that aimed to determine whether fetal sex influences the natural history of maternal risk of diabetes after delivery and in a subsequent pregnancy. SETTING: The study was conducted using population-based administrative databases in Ontario, Canada. PATIENTS: All women with a singleton live-birth first pregnancy between April 2000 and March 2010 (n = 642 987) were included. EXPOSURE: Fetal sex was the exposure of interest (313 280 delivered a girl; 329 707 delivered a boy). MAIN OUTCOME MEASURE: Development of T2DM or a second pregnancy were the main outcome measures. Glucose tolerance in each pregnancy was classified as either GDM or non-GDM. RESULTS: The population was followed for a median of 3.8 years. Carrying a boy yielded a higher risk of GDM in both the first pregnancy (odds ratio [OR] =1.03; 95% confidence interval [CI], 1.0002-1.054) and second pregnancy (OR =1.04, 95% CI, 1.01-1.08). For women with GDM in the first pregnancy, the likelihood of developing T2DM before a second pregnancy was higher if they delivered a girl (OR = 1.07; 95% CI, 1.01-1.12). Recurrence of GDM was not affected by fetal sex (P = .7). However, among women with a non-GDM first pregnancy while carrying a girl, having a boy in their second pregnancy predicted an increased risk of GDM (OR = 1.07, 95% CI, 1.01-1.14). CONCLUSIONS: Fetal sex is a previously unrecognized factor that is associated with maternal diabetic risk both after delivery and in a subsequent pregnancy.
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 | 0.001 | 0.005 |
| 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 | 0.000 |
| 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".