Allergic disorders in relation to asthma and spastic bronchitis in children
Bibliographic record
Abstract
Background: Recent studies suggest that a large proportion of children with diagnosed and treated spastic bronchitis, in fact, suffer from undiagnosed asthma. Such a “labeling” effect is well described in Poland and a few other Eastern European countries. Aims and objectives: The aim of the study was to compare the prevalence and associations of allergic conditions in children with asthma and spastic bronchitis. Methods: This was a cross-sectional study of randomly selected children aged 6-15 years living in the town of Chorzow (Southern Poland). Physician-diagnosed respiratory diseases such as asthma and spastic bronchitis as well as allergic disorders including hay fever, eczema, dust, pollen, food, and animal allergy were ascertained using a questionnaire completed by the parents. Results: A total of 3480 children aged 6-15 years participated in the study (response rate=75.7%). Asthma prevalence was 12.9% while spastic bronchitis prevalence was 10.5%. Any allergy was present in 71.6% of children with asthma and in 26.6% of children with spastic bronchitis (p<0.05). After controlling for age and gender, the odds ratio for asthma and any allergic condition was 17.5 (95%CI:13.4-22.9) while for any allergic condition and spastic bronchitis it was 1.33 (95%CI: 0.9-2.0). Such differences in prevalence (p<0.05) and similar associations (ORs) were observed between each individual allergic condition with asthma and spastic bronchitis. Conclusions: Our findings revealed that allergic conditions are more frequent and are more strongly associated with asthma than with spastic bronchitis. It indirectly shows that in our study children with asthma and spastic bronchitis may suffer from two different conditions.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 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".