Juvenile‐onset and adult‐onset demodicosis in dogs in the UK: prevalence and breed associations
Bibliographic record
Abstract
OBJECTIVES: To explore epidemiological features of demodicosis relevant to UK veterinary general practitioners. Breed risk factors were proposed as distinct between juvenile-onset and adult-onset disease. MATERIALS AND METHODS: The study used anonymised clinical data on dogs under primary veterinary care at practices enrolled in the UK VetCompass Programme. Case inclusion required recording of a final demodicosis diagnosis for a dermatological condition that was present during the 2013 study period. Risk factor analysis used multivariable logistic regression modelling. RESULTS: In dogs aged <2 years (juvenile-onset), the 1-year period prevalence was 0.48% (95% confidence interval: 0.45 to 0.52). Compared with crossbred dogs, seven breeds showed increased odds of diagnosis with demodex: British bulldog, Staffordshire bull terrier, Chinese shar-pei, dogue de Bordeaux, pug, French bulldog and boxer. Additionally, six breeds showed reduced odds of juvenile demodicosis: Lhasa apso, bichon frise, Labrador retriever, German shepherd dog, shih-tzu and Chihuahua. In dogs aged >4 years (adult-onset), the 1-year period prevalence was 0.05% (95% confidence interval: 0.0.04 to 0.06). Six breeds showed increased odds of demodicosis compared with crossbred dogs: Chinese shar-pei, shih-tzu, West Highland white terrier, pug, boxer and Border terrier. CLINICAL SIGNIFICANCE: Juvenile-onset demodicosis is much more common (about 10 times higher) than the adult-onset form. Knowledge of the predisposed breeds for these two presentations can assist with diagnosis and support the concept of distinct aetiopathogenetic phenotypes.
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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 | 0.002 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".