Timing, Frequency and Type of Physician-diagnosed Infections in Childhood and Risk for Crohnʼs Disease in Children and Young Adults
Bibliographic record
Abstract
BACKGROUND: Recent experimental data show that exposure to microbes during early childhood can confer immunological tolerance and protect against Crohn's disease (CD). Epidemiological evidence for this link, however, remains controversial. Using prospective data, we examined the link between this hypothesis and risk for CD in children and young adults. METHODS: A case-control study design was used. CD cases (diagnosed before age 20 years) were recruited from a tertiary-care pediatric hospital in Montreal, and population-based controls matched for age, gender and, geographical location were selected. Infection data were ascertained from physician-billing records. These records, which use International Classification of Diseases, Ninth Revision diagnostic codes, were consulted retrospectively but provide prospectively collected diagnostic information. Conditional logistic regression analysis was used to study potential associations. Odds ratios (OR) and 95% confidence intervals (95% CI) were estimated. RESULTS: Four hundred nine cases and 1621 controls were included. Regression analysis adjusting for potential confounding variables suggested that any recorded infection before the diagnosis of CD was associated with reduced risk of CD (OR, 0.67; 95% CI, 0.48-0.93). The protective effect was restricted to infections occurring mainly before 5 years of age, with increasing number of infections resulting in greater protection (1-5 infections: OR, 0.74; ≥6 infections: OR, 0.61; P value for trend = 0.039). Infections affecting the oral and upper respiratory tracts, cellulitis, and, enteric infections seemed most protective. CONCLUSIONS: Our study provides support for the hygiene hypothesis, whereby exposure to infections in early childhood could potentially reduce risks of CD.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".