Symptom control and health-related quality of life in allergic rhinitis with and without comorbid asthma: a multicentre European study
Bibliographic record
Abstract
Background: Allergic rhinitis (AR) is a major non-communicable disease that affects the health-related quality of life (HRQoL) of patients. AR is significantly related to asthma also affecting HRQoL. However, data on HRQoL and symptom control in AR patients with comorbid asthma are lacking. Objective: To assess the differences of symptom control and HRQoL in AR patients with and without comorbid asthma. Methods: In this multicentre, cross-sectional study, patients with AR were screened and administered questionnaires of demographic characteristics and health conditions (symptoms/diagnosis of AR and asthma, disease severity level, and allergic conditions). HRQoL was assessed using a modified version of the RHINASTHMA questionnaire and symptom control was evaluated by a modified version of the Control of Allergic Rhinitis/Asthma Test (CARAT). Results: Out of 643 patients with AR, 500 (78%) had asthma as a comorbidity, and 54% had moderate-severe intermittent AR, followed by moderate-severe persistent AR (34%). Patients with both AR and asthma had significantly higher RHINASTHMA scores than the patients with AR alone (e.g., median RHINASTHMA-total score 84 vs. 48.5, respectively). Conversely, CARAT scores were significantly lower in AR with comorbid asthma than in the patients with AR alone (median CARAT-total score 16.5 vs. 23, respectively). Upon stratifying asthma based on severity, AR patients with severe persistent asthma had worse HRQoL and control than AR patients with mild persistent asthma. Conclusions: Our observation of poorer HRQoL and symptoms control in AR patients with comorbid asthma supports the importance of a comprehensive approach for the management of AR in case of a comorbid allergic condition.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".