Reduced work/academic performance and quality of life in patients with allergic rhinitis and impact of allergen immunotherapy
Bibliographic record
Abstract
BACKGROUND: Allergic rhinitis (AR) is characterised by burdensome nasal and/or ocular symptoms. This inflammatory disease can be debilitating and thus result in considerable health-related and economic consequences. METHODS: In a cross-sectional study, adult subjects with AR (N = 683) completed three allergy-specific questionnaires that assessed the impact of AR on the work/academic performance, daily activities, health-related quality of life (HRQOL), and satisfaction with allergen immunotherapy (AIT). Regression analyses were used to examine the associations between several clinical variables and the patient-reported outcomes. RESULTS: Total loss of productivity was 21.0 and 21.2 % for employed and student patients, respectively, whereas the impairment of daily activities was 22.0 %. The mean overall HRQOL score was 1.94 ± 1.29 (on the scale of 0-6 points). Global score for satisfaction with AIT was 65.5 ± 24.8 (on a 0-100 scale). Simple regression analysis found statistically significant associations between loss of work and academic productivity, impairment of daily activities and the type and severity of AR. AIT was a protective factor. The persistent and more severe types of AR and lack of AIT contributed to the worsening of HRQOL. CONCLUSIONS: AR (the persistent and more severe form of the disease) has an impact on functional characteristics of adult patients in Spain. AIT might reduce the effect of this disease on the work/academic performance and HRQOL. Trial registration Retrospectively registered.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| 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".