Treatment of demodicosis in dogs: 2011 clinical practice guidelines
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: These guidelines were written by an international group of specialists with the aim to provide veterinarians with current recommendations for the diagnosis and treatment of canine demodicosis. METHODS: Published studies of the various treatment options were reviewed and summarized. Where evidence in form of published studies was not available, expert consensus formed the base of the recommendations. RESULTS: Demodicosis can usually be diagnosed by deep skin scrapings or trichograms; in rare cases a skin biopsy may be needed for diagnosis. Immune suppression due to endoparasitism or malnutrition in young dogs and endocrine diseases, neoplasia and chemotherapy in older dogs are considered predisposing factors and should be diagnosed and treated to optimize the therapeutic outcome. Dogs with disease severity requiring parasiticidal therapy should not be bred. Secondary bacterial skin infections frequently complicate the disease and require topical and/or systemic antimicrobial therapy. There is good evidence for the efficacy of weekly amitraz rinses and daily oral macrocyclic lactones such as milbemycin oxime, ivermectin and moxidectin for the treatment of canine demodicosis. Weekly application of topical moxidectin can be useful in dogs with milder forms of the disease. There is some evidence for the efficacy of weekly or twice weekly subcutaneous or oral doramectin. Systemic macrocyclic lactones may cause neurological adverse effects in sensitive dogs, thus a gradual increase to the final therapeutic dose may be prudent (particularly in herding breeds). Treatment should be monitored with monthly skin scrapings and extended beyond clinical and microscopic cure to minimize recurrences.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".