Investigating the effect of early life antibiotic use on asthma and allergy risk in over 600 000 Canadian children: a protocol for a retrospective cohort study in British Columbia and Manitoba
Bibliographic record
Abstract
INTRODUCTION: Allergic conditions, such as asthma, hay fever and eczema, are some of the most common conditions impacting children globally. There is a strong incentive to study their determinants to improve their prevention. Asthma, hay fever and eczema are influenced through the same immunological pathway and often copresent in children ('the atopic march'). Increasing evidence shows a link between infant antibiotic use and the risk of childhood atopic conditions, mediated through gut microbial dysbiosis during immune system maturation, however, the potential for confounding remains. This study will investigate the relationship between infant antibiotic use and risk of allergic conditions in British Columbian and Manitoban children born over 10 years, adjusting for relevant confounders. METHODS AND ANALYSIS: Provincial administrative datasets will be linked to perform comparable retrospective cohort analyses, using Population Data BC and the Manitoba Population Research Data Repository. All infants born between 2001 and 2011 in BC and Manitoba will be included (approximately 460 000 and 162 500 infants, respectively), following up to age 7. Multivariable logistic regression will determine the outcome risk by the fifth birthday among children who did and did not receive antibiotics before their first birthday. Clinical, demographic and environmental covariates will be explored, and sensitivity analyses performed to reduce confounding by indication. ETHICS AND DISSEMINATION: The University of British Columbia Research Ethics Board (H19-03255) and University of Manitoba Ethics Board (HS25156 (H2021:328)) have approved this study. Data stewardship committees for all administrative datasets have granted permissions, facilitated by Population Data BC and the Manitoba Centre for Health Policy. Permissions from the Canadian Health Infant Longitudinal Development Study are being sought for breastfeeding data (CP185). Findings will be published in scientific journals and presented at infectious disease and respiratory health conferences. A stakeholder committee will guide and enhance sensitive and impactful communication of the findings to new parents.
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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 | 0.019 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".