Application of Principal Component Analysis as a Prediction Model for Feline Sporotrichosis

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorPontifícia Universidade Católica do Paraná (PUCPR)-
Autor(es): dc.creatorPegoraro, Franco Bresolin-
Autor(es): dc.creatorMangrich-Rocha, Rita Maria Venâncio-
Autor(es): dc.creatorWeber, Saulo Henrique-
Autor(es): dc.creatorde Farias, Marconi Rodrigues-
Autor(es): dc.creatorSchmidt, Elizabeth Moreira dos Santos-
Data de aceite: dc.date.accessioned2025-08-21T21:32:00Z-
Data de disponibilização: dc.date.available2025-08-21T21:32:00Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2024-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.3390/vetsci12010032-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/299981-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/299981-
Descrição: dc.descriptionSporotrichosis is a worldwide zoonotic disease that is spreading and causing epidemics in large urban centers. Cats are the most susceptible species to develop the disease, which could cause significant systemic lesions. The aim was to investigate and to identify predictive indicators of disease progression by correlations between the blood profile (hematological and biochemical analytes) and cutaneous lesion patterns of 70 cats diagnosed with Sporothrix brasiliensis. The higher occurrence in male cats in this study could be related to being non-neutered and having access to open spaces. Principal component analysis (PCA) with two principal components, followed by binary logistic regression, and binary logistic regression analysis, with independent variables and backward elimination modeling, were performed to evaluate hematological (n = 56) and biochemical (n = 34) analytes, including red blood cells, hemoglobin, hematocrit, leukocytes, segmented neutrophils, band neutrophils, eosinophils, lymphocytes, monocytes, total plasma protein, albumin, urea, creatinine, and alanine aminotransferase. Two logistic regression models (PCA and independent variables) were employed to search for a predicted model to correlate fixed (isolated) and disseminated cutaneous lesion patterns. Total plasma protein concentration may be assessed during screening diagnosis as it has been recognized as an independent predictor for the dissemination of cutaneous lesion patterns, with the capability of serving as a predictive biomarker to identify the progression of cutaneous lesions induced by S. brasiliensis infections in cats.-
Descrição: dc.descriptionSchool of Veterinary Medicine and Animal Science (FMVZ) São Paulo State University (UNESP), Campus Botucatu-
Descrição: dc.descriptionSchool of Medicine and Life Sciences Pontifícia Universidade Católica do Paraná (PUCPR), PR-
Descrição: dc.descriptionGraduate Program in Animal Science School of Medicine and Life Sciences Pontifícia Universidade Católica do Paraná (PUCPR), PR-
Descrição: dc.descriptionSchool of Veterinary Medicine and Animal Science (FMVZ) São Paulo State University (UNESP), Campus Botucatu-
Idioma: dc.languageen-
Relação: dc.relationVeterinary Sciences-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectcats-
Palavras-chave: dc.subjectfungus-
Palavras-chave: dc.subjectplasma proteins-
Palavras-chave: dc.subjectpredictive function-
Palavras-chave: dc.subjectSporothrixspp-
Título: dc.titleApplication of Principal Component Analysis as a Prediction Model for Feline Sporotrichosis-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

Não existem arquivos associados a este item.