Gender‐ and age‐specific risk factors for wheeze from birth through adolescence
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Cross-sectional gender differences in wheeze are well documented, but few studies have examined the gender-specific risk factors for wheeze longitudinally. This study aims to identify gender- and age-specific risk factors for wheeze from birth through adolescence. METHODS: The incidence of wheeze was ascertained every 6 months through age 14 years in a birth cohort consisting of 499 children with a parental history of atopy. Gender- and age-specific risk factors were identified through generalized estimating equations. RESULTS: A total of 454 (91.0%) and 351 (70.3%) children were followed past age 7 and 13 years, respectively. Maternal asthma was a risk factor for wheeze in girls (OR = 2.05, 95% CI 1.44-2.91, P < 0.0001) and boys (OR = 1.79, 1.29-2.48, P = 0.0004) and had a similar effect on wheeze throughout the ages. Paternal asthma (OR = 1.83, 1.38-2.57, P = 0.0005) and infant bronchiolitis (OR = 2.15, 1.47-3.14, P < 0.0001) were risk factors for boys only, with similar effects throughout the ages. CONCLUSION: Using a prospective cohort, we identified gender- and age-specific risk factors for wheeze. The identification of gender-specific early life risk factors may allow for timely interventions and a more personalized approach to the treatment of asthma.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".