Prenatal vitamin D and cord blood insulin-like growth factors in Dhaka, Bangladesh
Bibliographic record
Abstract
Fetal growth restriction is linked to adverse health outcomes and is prevalent in low- and middle-income countries; however, determinants of fetal growth are still poorly understood. The objectives were to determine the effect of prenatal vitamin D supplementation on the insulin-like growth factor (IGF) axis at birth, to compare the concentrations of IGF-I in newborns in Bangladesh to a European reference population and to estimate the associations between IGF protein concentrations and birth size. In a randomized controlled trial in Dhaka, Bangladesh, pregnant women enrolled at 17-24 weeks of gestation were assigned to weekly oral vitamin D3 supplementation from enrolment to delivery at doses of 4200 IU/week, 16,800 IU/week, 28,000 IU/week or placebo. In this sub-study, 559 woman-infant pairs were included for analysis and cord blood IGF protein concentrations were quantified at birth. There were no significant effects of vitamin D supplementation on cord blood concentrations of IGF-I (P = 0.398), IGF-II (P = 0.525), binding proteins (BPs) IGFBP-1 (P = 0.170), IGFBP-3 (P = 0.203) or the molar ratio of IGF-I/IGFBP-3 (P = 0.941). In comparison to a European reference population, 6% of girls and 23% of boys had IGF-I concentrations below the 2.5th percentile of the reference population. IGF-I, IGF-II, IGFBP-3 and the IGF-I/IGFBP-3 ratio were positively associated with at least one anthropometric parameter, whereas IGFBP-1 was negatively associated with birth anthropometry. In conclusion, prenatal vitamin D supplementation does not alter or enhance fetal IGF pathways.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".