Effect of vitamin D supplementation during pregnancy and lactation on the development of infants born to Tanzanian women living with HIV: a secondary analysis of a randomised controlled trial
Bibliographic record
Abstract
BACKGROUND: Infants born to pregnant women living with HIV (WLHIV) are at greater risk for morbidity and mortality and may also have poorer developmental outcomes as compared with infants who are not exposed to HIV. Nutrition interventions in pregnancy may affect developmental outcomes. OBJECTIVES: This study evaluated the effect of maternal vitamin D supplementation on infant development outcomes. DESIGN: We conducted a secondary analysis of a randomised, triple-blind, placebo-controlled trial of maternal vitamin D supplementation from June 2015 to October 2019. SETTING: Antenatal care clinics in Dar es Salaam, Tanzania. PARTICIPANTS: Pregnant WLHIV and their offspring. INTERVENTIONS: or placebo supplements taken during pregnancy and lactation. OUTCOME MEASURES: Infants were assessed for cognitive, language and motor development at 1 year of age with the Caregiver Reported Early Development Instruments (CREDI). RESULTS: A total of 2167 infants were eligible, and 1312 of them completed CREDI assessments at 1 year of age. Vitamin D supplementation had no effect on overall CREDI z-scores (standardised mean difference (SMD) 0.03, 95% CI -0.09, 0.15, p value 0.66). There was also no evidence of a difference between vitamin D and placebo groups in language (SMD 0.06, 95% CI -0.08, 0.21, p value 0.40), motor (SMD 0.02, 95% CI -0.09, 0.14, p value 0.69) or cognitive domain z-scores (SMD 0.05, 95% CI -0.08, 0.17, p 0.48). CONCLUSIONS: Maternal vitamin D supplementation during pregnancy and lactation did not affect infant development outcomes. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov identifier: NCT02305927.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".