Reliability and Longitudinal Course of Itch/Scratch Severity in Adults With Atopic Dermatitis
Bibliographic record
Abstract
BACKGROUND: Itch is a complex and burdensome symptom in atopic dermatitis (AD). Severity of scratching/excoriation (SCORAD-scratch) has been found to be a valid measure of itch in AD. However, little is known about the longitudinal course of scratching/excoriations in AD. METHODS: A prospective, dermatology practice-based study was performed of adults with AD (N = 399). The patients were assessed at baseline and approximately 6, 12, 18, and 24 months. RESULTS: Severity of excoriations correlated best with the Numerical Rating Scale-worst itch (Spearman correlation, ρ = 0.50), followed by a Patient-Reported Outcome Measurement Information System Itch Questionnaire-scratching behavior T score (ρ = 0.48), Numerical Rating Scale-average itch (ρ = 0.41), relative frequency of itch (ρ = 0.36), and frequency of itch from eczema (ρ = 0.29, all P < 0.0001). Scratching severity showed good reliability (intraclass correlation coefficient range = 0.62-0.69). Overall, 30.6% and 5.5% had moderate (2) or severe (3) SCORAD-scratch scores. Among patients with baseline moderate (2) or severe (3) SCORAD-scratch scores, 18.9% and 13.6% continued to have moderate or severe scores at 1 or more follow-up visits. In repeated-measures regression models, persistent SCORAD-scratch scores were associated with baseline severity of excoriations (adjusted β [95% confidence interval] = 0.51 [0.37 to 0.65]), Medicaid insurance (-0.35 [-0.65 to -0.04]), and Eczema Area and Severity Index scores (0.03 [0.02 to 0.04]). CONCLUSIONS: Adult AD patients had a heterogeneous longitudinal course with fluctuating severity of excoriations.
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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 | 0.003 | 0.010 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 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".