Chronic Hand Eczema Guidelines From an Expert Panel of the International Eczema Council
Bibliographic record
Abstract
BACKGROUND: Assessment of chronic hand eczema (CHE) is complex and warrants standardization. OBJECTIVE: We sought to guide clinicians on the assessment of CHE. METHODS: An electronic questionnaire regarding the diagnosis and assessment of CHE was completed by councilors (n=45) of the International Eczema Council, an international group of clinicians and researchers with expertise in CHE. The survey consisted of 52 statements for consensus. RESULTS: Overall, nine statements (17.3%) had strong, twenty-three (44.2%) moderate, 12 (23.1%) low, and 8 (15.4%) very low levels of agreement. Five statements had considerable disagreement, including the value of conducting a skin biopsy (62.2% disagreement), investigating for possible type 1 reactions (60.0%), conducting a fungal culture (44.4%), finding no history of relevant allergens and/or irritants (31.1%) in most or all cases, and performing patch testing irrespective of lesion location and morphology (28.9%). Agreement was generally highest among respondents from Europe (28.6-77.8% agreement), followed by Asia (7.1%-35.7% agreement), North America (0%-35.5% agreement), and other (0%-13.3% agreement). CONCLUSIONS: There were substantial differences of agreement, suggesting there are many knowledge and/or practice gaps with respect to CHE. Future research is needed to inform evidence-based and/or consensus guidelines for CHE.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.045 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".