Clinical Manifestations of Allergic Rhinitis
Bibliographic record
Abstract
Objective: To provide a concise review of the classification, nasal manifestations, non-nasal manifestations, and quality of life impact of allergic rhinitis.Data sources: MEDLINE (PubMed) search using the terms allergic rhinitis, combined with the terms perennial, seasonal, non-nasal, symptoms and quality of life.Study selection: Human studies and reviews published in the English language.Results: The prevalence of allergic rhinitis is increasing worldwide.Symptoms include rhinorrhea, sneezing, obstruction of the nasal passages, and may be underestimated by patients.Traditionally, allergic rhinitis has been classified as perennial or seasonal; however, the Allergic Rhinitis and its Impact on Asthma (ARIA) classification may provide a better description of individual symptoms.Complications of allergic rhinitis include nasal polyps and bacterial sinusitis and comorbid conditions include asthma, allergic conjunctivitis and atopic dermatitis.The list of potential differential diagnoses is extensive, but important not to miss are the rare presentations of nasopharyngeal tumors, Wegener's Granulomatosis and sarcoidosis.Epidemiological studies have shown a reduction in quality of life in patients suffering from allergic rhinitis and new tools have allowed for better assessments of the impact of illness on patient's lives. Conclusion:Patients with allergic rhinitis can experience a wide range of troublesome clinical symptoms, which are often under recognized and underreported causing a delay in seeking medical attention and subsequent reduction in health related quality of life.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 | 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".