Epidermolysis Bullosa and Chronic Wounds
Bibliographic record
Abstract
In Brief PURPOSE: To enhance the learner’s competence with information about a wound bed preparation model of fragile skin for patients with epidermolysis bullosa (EB). TARGET AUDIENCE: This continuing education activity is intended for physicians and nurses with an interest in skin and wound care. OBJECTIVES: After participating in this educational activity, the participant should be better able to: 1. Differentiate between the types and subtypes of EB. 2. Apply EB assessment and treatment strategies to patient care scenarios. Epidermolysis bullosa (EB) is a group of inherited diseases with 4 subtypes. This disorder is a model for fragile skin, with some affected individuals having chronic, difficult-to-heal wounds. The care of wounds in people with EB can be guided by the Wound Bed Preparation paradigm. The treatment of chronic EB wounds is outlined with a quick reference guide of 12 consensus recommendations created by a panel of 11 experts. These recommendations were reviewed by a computer-facilitated modified Delphi process where 15 external reviewers (68.8% of whom reported having 11 or more years’ experience with EB care). Inclusion of recommendations was contingent on 80% agreement from reviewers. This continuing education activity will help clinicians identify and treat epidermolysis bullosa and its subtypes.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".