25‐hydroxyvitamin D and health service utilization for asthma in early childhood
Bibliographic record
Abstract
BACKGROUND: Asthma is the most common chronic illness of childhood and a common reason for hospital admission. Studies suggest that low vitamin D levels may be associated with health service utilization (HSU) for childhood asthma. The primary objective was to determine if vitamin D serum levels in early childhood were associated with HSU for asthma including: a) hospital admissions; b) emergency department visits; and c) outpatient sick visits. Secondary objectives were to determine whether vitamin D supplementation in pregnancy or childhood were associated with HSU for asthma. METHODS: Prospective cohort study of children participating in the TARGet Kids! practice-based research network between 2008 and 2013 in Toronto, Canada. HSU was determined by linking each child's provincial health insurance number to health administrative databases. Multivariable quasi-Poisson and logistic regression were used to evaluate the association between 25-hydroxyvitamin D concentrations, vitamin D supplementation in pregnancy, and childhood and HSU for asthma. RESULTS: A total of 2926 healthy children aged 0-6 years had 25-hydroxyvitamin D data available and were included in the primary analysis. Mean (IQR) 25-hydroxyvitmain D level was 84 nmol/L (65-98 nmol/L), 218 and 1267 children had 25-hydroxyvitamin D concentrations <50 nmol/L and <75 nmol/L, respectively. In the adjusted models, there were no associations between 25-hydroxyvitamin D concentrations (continuously or dichotomized at 50 and 75 nmol/L), vitamin D supplementation in pregnancy or childhood and HSU for asthma. CONCLUSIONS: Vitamin D blood values do not appear to be associated with HSU for asthma in this population of healthy urban 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".