Canadian Practical Guide for the Treatment and Management of Atopic Dermatitis
Bibliographic record
Abstract
BACKGROUND: Atopic dermatitis is a common condition, with a lifetime prevalence of approximately 10% to 20% among the Canadian population. A clear, practical, Canadian guideline for the management of these patients has been lacking. OBJECTIVE: To provide primary-care physicians, pediatricians and dermatologists with the first practical and comprehensive set of Canadian recommendations for the management of atopic dermatitis. METHODS: A group of Canadian dermatologists convened to review the current issues of diagnosis, treatment and international guidelines and adapt them to the Canadian context. The reviewers used the latest clinical trial data on atopic dermatitis, complemented by clinical experience, to develop the consensus recommendations found in this review. RESULTS: In the present report, following a brief review of the epidemiology of and clinical diagnosis criteria for atopic dermatitis, the recommendations for treatment and management are detailed. These recommendations, which are intended to provide clinicians with a useful and valuable tool to help manage their patients with atopic dermatitis, are divided into the following sections: epidemiology, diagnosis, general measures/skin care, acute management of atopic dermatitis, long-term management/disease control, adjunct therapies, and considerations for switching between antiinflammatory therapies/handling treatment failure. General measures discussed include hydration with bathing and the use of moisturizers. Management strategies discussed include topical corticosteroids, topical calcineurin inhibitors, antihistamines and anti-infectives. A management algorithm is also presented.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.030 | 0.016 |
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".