Validation of the Urticaria Control Test (UCT) in Children with Chronic Urticaria
Bibliographic record
Abstract
ABSTRACT Background No validated tools exist to evaluate chronic urticaria (CU) control in children. While the Urticaria Control Test (UCT) exhibits favourable clinometric properties in adult CU, it is not yet validated in children. Therefore, we sought to evaluate the validity of the UCT for the assessment of pediatric CU. Methods Children presenting with CU were consecutively recruited. Participants completed both the UCT and the Children’s Dermatology Life Quality Index (CDLQI). We assessed the internal consistency, convergent and known-groups validity, and screening accuracy of the UCT at study entry and at follow-up. Results A total of 52 children with CU were recruited. The UCT exhibited respectable internal consistency in the evaluation of CU (Cronbach’s α=0.73 [95%CI: 0.62, 0.85]). UCT and CDLQI scores strongly correlated (r=-0.74, P<0.01). The UCT distinguished between different strata of disease severities established by the CDLQI (P<0.01). Screening accuracy of the UCT was excellent in the discrimination of poorly controlled CU (area under the curve=0.82). An optimal cut-off of ≤10 was determined for defining poorly controlled CU (sensitivity=95.5%, specificity=63.3%). Data at follow-up were consistent with data at study entry. Conclusion The UCT is a valid tool for the assessment of pediatric CU and CSU, as evidenced by acceptable internal consistency, convergent and known-groups validity, and screening accuracy at multiple time points.
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".