25-Hydroxyvitamin D supplementation and health-service utilization for upper respiratory tract infection in young children
Bibliographic record
Abstract
Objective: Upper respiratory tract infections (URTI) are the most common and costly condition of childhood. Low vitamin D levels have been hypothesized as a risk factor for URTI. The primary objective was to determine if serum vitamin D levels were associated with health-service utilization (HSU) for URTI including hospital admission, emergency department visits and outpatient sick visits. The secondary objectives were to determine whether oral vitamin D supplementation in pregnancy or childhood was associated with HSU for URTI. Design: Cohort study. HSU was determined by linking each child's provincial health insurance number to health administrative databases. Multivariable quasi Poisson regression was used to evaluate the association between 25-hydroxyvitamin D, vitamin D supplementation and HSU for URTI. Setting: Toronto, Canada. Subjects: Children participating in the TARGet Kids! network between 2008 and 2013. Results: Healthy children aged 0-5 years (n 4962) were included; 52 % were male and mean 25-hydroxyvitamin D was 84 nmol/l (range 11-355 nmol/l). There were 105 (2 %), 721 (15 %) and 3218 (65 %) children with at least one hospital admission, emergency department visit or outpatient sick visit for URTI, respectively. There were no statistically significant associations between 25-hydroxyvitamin D or vitamin D supplementation and HSU for URTI. Conclusions: A clinically meaningful association between vitamin D (continuously and dichotomized at <50 and <75 nmol/l) and HSU for URTI was not identified. While vitamin D may have other benefits for health, reducing HSU for URTI does not appear to be one of them.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".