Prevalence and bidirectional association between rhinitis and urticaria: A systematic review and meta-analysis
Bibliographic record
Abstract
Background: Rhinitis, allergic rhinitis in particular, and urticaria are both common atopic problems globally. However, there is controversy regarding the correlation between rhinits and urticaria. Objectives: To examine the accurate association between rhinitis and urticaria. Methods: Three medical databases (PubMed, Embase, and Web of Science) were searched from database inception until January 11, 2022. The prevalence and association between rhinitis and urticaria were estimated by meta-analysis. The Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines were followed, and quality assessment was performed using the Newcastle–Ottawa Scale. Pooled odds ratios (OR) with 95% confidence intervals (95% CI) and pooled prevalence were calculated using random-effects models. Results: Urticaria prevalence in patients with rhinitis was 17.6% (95% CI, 13.2%–21.9%). The pooled prevalence of rhinitis was 31.3% (95% CI, 24.2%–38.4%) in patients with urticaria, and rhinitis prevalence in patients with acute urticaria and chronic urticaria was 31.6% (95% CI, 7.4%–55.8%) and 28.7% (95% CI, 20.4%–36.9%), respectively. Rhinitis occurence was significantly associated with urticaria (OR, 2.67; 95% CI, 2.625–2.715). Limitations: Urticaria and rhinitis were diagnosed based on different criteria possibly resulting in a potential misclassification of these two diseases. Conclusion: Rhinitis and urticaria were significantly correlated. Physicians should be cognizant regarding this relationship and address nasal or skin symptoms in patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".