The influence of sensitisation to pollens and moulds on seasonal variations in asthma attacks
Bibliographic record
Abstract
No large study has described the seasonal variation in asthma attacks in population-based asthmatics in whom sensitisation to allergen has been measured. 2,637 young adults with asthma living in 15 countries reported the months in which they usually had attacks of asthma and had skin-prick tests performed. Differences in seasonal patterns by sensitisation status were assessed using generalised estimating equations. Most young adults with asthma reported periods of the year when their asthma attacks were more common (range: 47% in Sweden to 86% in Spain). Seasonal variation in asthma was not modified by sensitisation to house dust mite or cat allergens. Asthmatics sensitised to grass, birch and Alternaria allergens had different seasonal patterns to those not sensitised to each allergen, with some geographical variation. In southern Europe, those sensitised to grass allergens were more likely to report attacks occurred in spring or summer than in winter (OR March/April 2.60, 95% CI 1.70-3.97; OR May/June 4.43, 95% CI 2.34-8.39) and smaller later peaks were observed in northern Europe (OR May/June 1.25, 95% CI 0.60-2.64; OR July/August 1.66, 95% CI 0.89-3.10). Asthmatics reporting hay fever but who were not sensitised to grass showed no seasonal variations. Seasonal variations in asthma attacks in young adults are common and are different depending on sensitisation to outdoor, but not indoor, allergens.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".