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Authors: M. Pinto, D. Grass and I. Herrmann
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BACKGROUND: Superficial pyoderma is common in dogs with atopic dermatitis, yet no validated and widely accepted severity scoring system exists. HYPOTHESIS/OBJECTIVES: To develop a predictor for superficial pyoderma severity based on reliable objective lesion quantification combined with a clinician-assigned numerical severity rating. ANIMALS: Sixty client-owned dogs presenting with follicular papules, pustules, epidermal collarettes, and/or yellow crusts were prospectively enrolled. MATERIALS AND METHODS: Six clinicians assessed lesion types, numerical and categorical disease severity, and treatment efficacy at baseline and at up to two follow-up visits. Lesions were quantified by counting individual papules and pustules, and by standardised area measurements for confluent papules/pustules, epidermal collarettes and crusts. Inter- and intra-clinician reliability were evaluated. A predictive model for pyoderma severity was subsequently developed using lesion quantification and clinician-assigned numerical severity scores. RESULTS: Recognition of specific lesion types and categorical severity assessments showed poor agreement between clinicians, indicating limited reliability for severity assessment. By contrast, combined lesion quantification demonstrated good inter- and intra-clinician reliability, and clinician-assigned numerical severity scores showed good inter-clinician reliability. The resulting predictive model demonstrated good agreement with clinician-assigned severity scores, estimating pyoderma severity on a continuous scale from 0 (no pyoderma) to 100 (worst conceivable pyoderma), with a mean absolute error of approximately nine severity points per case. CONCLUSIONS AND CLINICAL RELEVANCE: The proposed scoring system relies on combined lesion quantification without the need for subjective categorical grading. Although further validation is required, it provides a foundation for objective assessment of superficial pyoderma severity and introduces a mathematical model that translates combined lesion burden into clinician-perceived disease severity.
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