The risk for childhood malignancies in the offspring of mothers with previous gestational diabetes mellitus: a population-based cohort study
Bibliographic record
Abstract
The hyperglycemic intrauterine environment has been shown to have long-term effects on offspring. We aimed to evaluate its effect on the long-term risk of childhood malignancies. This was a population-based cohort analysis comparing the risk for long-term childhood malignancies (≤18 years) in children born to mothers with and without gestational diabetes mellitus (GDM). Childhood malignancies were diagnosed by physicians and recorded in hospital medical files according to predefined codes based on ICD-9. Deliveries occurred between the years 1991 and 2014 in a tertiary medical center. Children to mothers with pre-GDM, with fetal congenital malformations, and with benign tumors were excluded from the analysis. Kaplan-Meier survival curve was constructed to compare cumulative oncological morbidity in both groups over time. Cox proportional hazards model was used to control for confounders. During the study period, 236 893 infants met the inclusion criteria; 10 294 (4.3%) of whom were born to mothers with GDM. Hospitalizations involving malignancy diagnoses were comparable between the groups (0.11 vs. 0.12%; P=0.424), as were the cumulative incidences of total oncological morbidity using a Kaplan-Meier survival curve (log-rank P=0.820). In the Cox regression model, maternal GDM was not associated with increased childhood oncological hospitalizations while controlling for maternal age, gestational age, and hypertensive disorders (adjusted hazard ratio: 1.02, 95% confidence interval: 0.58-1.82, P=0.932). Exposure to intrauterine hyperglycemic environment due to maternal GDM does not increase the risk for childhood malignancies.
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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 | 0.002 | 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".