Chronic urticaria in most patients is poorly controlled
Bibliographic record
Abstract
OBJECTIVES: To translate and linguistically validate the urticaria control test (UCT) to/for Arabic speakers. No Arabic version of the UCT is available to assess disease control in patients with chronic urticaria (CU). Secondary objectives were to assess disease control in Lebanese CU patients and determine influence factors. METHODS: This is a prospective observational study of 178 CU patients diagnosed during their first visit to a private Allergy/Immunology Clinic, Hotel Dieu de France Hospital, Beirut, Lebanon between January and December 2014. RESULTS: Factor analysis showed that all 4 UCT items on the Arabic version converged over a solution of one factor. A high internal consistency was found with a Cronbach's alpha of 0.824. Most patients in this study had chronic spontaneous urticaria (96%), of which 19% also had inducible urticaria. The majority was less than 40 years (67.4%), with disease duration of less than 2 years (70.8%). Most patients used H1-antihistamines, but unfortunately, 34.3% used systemic glucocorticosteroids, of which 24.7% also used H1-antihistamines. The disease was poorly controlled in most patients (79.2%, UCT less than 12). Age, gender, duration, diagnosis, triggers, and/or history of atopy had no influence. CONCLUSION: We developed the first linguistically validated Arabic UCT to improve CU management in Arabic speaking patients. We also found that disease control was poor in most CU patients, and is unaffected by age, disease duration, gender, subtype, triggers, history of atopy, and/or previous treatments.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.004 | 0.001 |
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".