The clinical burden of allergic rhinitis in five Middle Eastern countries: results of the SNAPSHOT program
Bibliographic record
Abstract
The SNAPSHOT program provides current data on the allergic rhinitis burden in the adult general population of five Middle Eastern countries (Egypt, Turkey, Kuwait, Saudi Arabia and the United Arab Emirates, the latter three grouped into a Gulf cluster). A multi-country, cross-sectional, epidemiological program conducted by telephone in a random sample of the adult general population; quotas were defined per country demographics. Subjects were screened for allergic rhinitis using the Score For Allergic Rhinitis questionnaire. Current prevalence (last 12 months) was estimated. Disease severity and control were assessed using the Allergic Rhinitis and its Impact on Asthma classification and Rhinitis Control Assessment Test respectively. Quality of sleep, impact on daily activities and quality of life were measured using the Epworth Sleepiness Scale, Sheehan Disability Scale and EuroQol Five-Dimension questionnaire respectively. Multivariate logistic regression analyses were used to investigate risk factors and co-morbidities. 1808 of 33,486 subjects enrolled in the SNAPSHOT program fulfilled the case definition for allergic rhinitis. Prevalence was 3.6% [95% CI 3.2–4.0%] in Egypt, 6.4% [95% CI 5.9–6.9%] in Turkey and 6.4% [95% CI 6.0–6.9%] in the Gulf cluster. Risk factors identified were country, co-morbid asthma and income. Subjects with allergic rhinitis reported a significantly lower quality of life compared to the general population ( p < 0.0001). Overall, 55% of allergic rhinitis subjects were moderate/severe and 33% were uncontrolled. Both these groups reported impaired quality of life and quality of sleep and increased impairment of daily activities compared to mild/well-controlled subjects ( p < 0.0001). Although the observed prevalence of allergic rhinitis in these Middle Eastern countries is low compared to western countries, its burden is considerable. Allergic rhinitis in general, and specifically uncontrolled and severe disease, results in a negative impact on quality of life, quality of sleep and daily activities.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".