Evidence map›Paper›PMID 42429301›Full record

ArticleVeterinary dermatology2026

Standardising Assessment of Superficial Pyoderma in Dogs: Proposal of a Severity Score.

Mickaël Pinto, David Grass, Ina Herrmann

Abstract read
In one paragraph

Article in Veterinary dermatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Mickaël PintoDepartment of Clinical Sciences, College of Veterinary Medicine, North Carolina State University, Raleigh, North Carolina, USA.ORCID https://orcid.org/0009-0008-6215-7704
David GrassDepartment of Chemistry, Duke University, Durham, North Carolina, USA.ORCID https://orcid.org/0000-0003-1781-0969
Ina HerrmannDepartment of Clinical Sciences, College of Veterinary Medicine, North Carolina State University, Raleigh, North Carolina, USA.ORCID https://orcid.org/0000-0003-2772-9144

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSuperficial pyoderma is common in dogs with atopic dermatitis, yet no validated and widely accepted severity scoring system exists. HYPOTHESIS/

objectivesTo 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

methodsSix 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.

resultsRecognition 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.

Indexed as

Dog DiseasesPyodermaSeverity of Illness IndexAnimalsDogsFemaleMaleObserver VariationProspective StudiesReproducibility of Resultscanine superficial pyodermaoutcome measurespredictor modelseverity scorevalidation

Identifiers

PMID42429301
PMCPMC13569156

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.