Disease burden in children with moderate to severe perennial allergic rhinitis and concomitant asthma in Canada, Denmark, and the United Kingdom
Bibliographic record
Abstract
Background: Allergic rhinitis (AR) affects up to 40% of children in the United States and Europe. AR is often associated with asthma and has a negative impact on quality of life for the children and their families. Objective: We investigated the AR burden in children with moderate to severe perennial AR in Canada, Denmark, and the United Kingdom, focusing on the role of concomitant asthma. We assessed the health impact on the children, their receipt of allergy medication and health care services, and the impact on their families. Methods: An online survey was distributed to caregivers of children aged 5 to 17 with moderate to severe perennial AR (both with and without asthma) and to a control group of caregivers of children without allergies. Results: In total, 877 and 855 caregivers of children with perennial AR and without allergies, respectively, completed the survey. Children with AR and asthma, compared with those without asthma, experienced more sleep disturbances (69% vs 58%), schoolwork limitations (33% vs 22%), daily activities restrictions (55% vs 41%), and missed school hours (7.2 vs 4.6 hours per month). Children with AR and asthma had a higher receipt of allergy medication compared with those without asthma, and they also visited their general practitioner more often (4.6 vs 3.5 times a year). Overall, 32% of all caregivers of children with AR expressed dissatisfaction with allergy medication. Conclusion: Perennial AR, especially with concomitant asthma, imposes a substantial disease burden in children and their families, highlighting the need for long-term disease control.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".