Effect of maternal vitamin D supplementation on nasal pneumococcal acquisition, carriage dynamics and carriage density in infants in Dhaka, Bangladesh
Bibliographic record
Abstract
BACKGROUND: Invasive pneumococcal disease is a major cause of infant morbidity and death worldwide. Vitamin D promotes anti-pneumococcal immune responses in vitro, but whether improvements in infant vitamin D status modify risks of nasal pneumococcal acquisition in early life is not known. METHODS: This is a secondary analysis of data collected in a trial cohort in Dhaka, Bangladesh. Acute respiratory infection (ARI) surveillance was conducted from 0 to 6 months of age among 1060 infants of women randomized to one of four pre/post-partum vitamin D dose combinations or placebo. Nasal swab samples were collected based on standardized ARI criteria, and pneumococcal DNA quantified by qPCR. Hazards ratios of pneumococcal acquisition and carriage dynamics were estimated using interval-censored survival and multi-state modelling. RESULTS: Pneumococcal carriage was detected at least once in 90% of infants by 6 months of age; overall, 69% of swabs were positive (2616/3792). There were no differences between any vitamin D group and placebo in the hazards of pneumococcal acquisition, carriage dynamics, or carriage density (p > 0.05 for all comparisons). CONCLUSION: Despite in vitro data suggesting that vitamin D promoted immune responses against pneumococcus, improvements in postnatal vitamin D status did not reduce the rate, alter age of onset, or change dynamics of nasal pneumococcal colonization in early infancy. Trial registration Registered in ClinicalTrials.gov with the registration number of NCT02388516 and first posted on March 17, 2015.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".