Maternal diabetes during pregnancy and carotid intima-media thickness in children
Bibliographic record
Abstract
Abstract Background Cardiovascular risk over the life course may be related to intrauterine risk factors, for instance, the exposure to maternal diabetes. Our objective was to systematically review studies that assessed the association of maternal diabetes during pregnancy and carotid-intima media thickness (CIMT), a marker of cardiovascular risk, in children. Methods We followed methods outlined in a published protocol for a systematic review on risk factors and determinants of CIMT in children (PROSPERO registration: CRD42017075169). Standardized mean differences in CIMT between offspring of women with and without diabetes during pregnancy were computed. Random effects meta-analyses were performed. The reliability of CIMT measurements was assessed. Funding SNSF 32003B-163240. Results Three observational studies involving 658 children were retained. Two studies were conducted in Europe and one in Australia. Age at CIMT assessment ranged from 2 days to 8 years. Two studies evaluated gestational diabetes during pregnancy and found no difference in CIMT among exposed children compared to controls (0.00 (95% CI: -0.41 to 0.41); 0.00 (95% CI; -0.28 to 0.28)). One study, that did not specify the type of diabetes evaluated, identified a higher CIMT (0.46 (95% CI; -0.07 to 1.00)). The pooled standardized mean difference in CIMT between offspring of women with and without diabetes during pregnancy was 0.08 (95% CI: -0.16 to 0.33; I2: 17.1%). Conclusions Overall, there is no clear association between maternal diabetes during pregnancy and offspring's CIMT. The degree of confidence in results is limited by the low number of studies, with relatively small sample sizes and a low number of participants exposed to maternal diabetes. Key messages Children exposed to maternal diabetes have no substantial alterations in vascular structure. More research is needed to inform primordial prevention of cardiovascular disease among these children.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".