Assessing predictive factors of COVID-19 outcomes: a case-control study in the metropolitan region of São Paulo (Brazil)

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Autor(es): dc.creatorAmato, Juliana Neide-
Autor(es): dc.creatorCastelo, Paula Midori-
Autor(es): dc.creatorCirino, Ferla Maria Simas Bastos-
Autor(es): dc.creatorMeyer, Guilherme-
Autor(es): dc.creatorPereira, Luciano José-
Autor(es): dc.creatorSartori, Luís Cláudio-
Autor(es): dc.creatorAderaldo, Natália Simões-
Autor(es): dc.creatorSilva, Fernando Capela e-
Data de aceite: dc.date.accessioned2026-02-09T12:09:45Z-
Data de disponibilização: dc.date.available2026-02-09T12:09:45Z-
Data de envio: dc.date.issued2022-05-30-
Data de envio: dc.date.issued2022-05-30-
Data de envio: dc.date.issued2021-10-06-
Fonte completa do material: dc.identifierhttps://repositorio.ufla.br/handle/1/50050-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1155653-
Descrição: dc.descriptionBackground and objectives: the aim of this retrospective cohort study was to search individual, sociodemographic and environmental predictors of COVID-19 outcomes. Materials and methods: a convenience sample of 1036 COVID-19 confirmed patients (3–99 years, mean 59 years; 482 females) who sought treatment at the emergency units of the public health system of Diadema (Brazil; March-October 2020) was included. Primary data were collected from medical records: sex, age, occupation/education, onset of symptoms, presence of chronic diseases/treatment and outcome (death and non-death). Secondary socioeconomic and environmental data were provided by the Department of Health. Results: the mean time spent between COVID-19 symptom onset and admission to the health system was 7.4 days. Principal component analysis summarized secondary sociodemographic data, and a Poisson regression model showed that the time between symptom onset and health system admission was higher for younger people and those from the least advantaged regions (availability of electricity, a sewage network, a water supply and garbage collection). A multiple logistic regression model showed an association of age (OR = 1.08; 1.05–1.1), diabetes (OR = 1.9; 1.1–3.4) and obesity (OR = 2.9; 1.1–7.6) with death outcome, while hypertension and sex showed no significant association. Conclusion: the identification of vulnerable groups may help the development of health strategies for the prevention and treatment of COVID-19.-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Publicador: dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)-
Direitos: dc.rightsAttribution 4.0 International-
Direitos: dc.rightsAttribution 4.0 International-
Direitos: dc.rightsacesso aberto-
Direitos: dc.rightshttp://creativecommons.org/licenses/by/4.0/-
Direitos: dc.rightshttp://creativecommons.org/licenses/by/4.0/-
???dc.source???: dc.sourceMedicina-Lithuania-
Palavras-chave: dc.subjectSARS-CoV-2-
Palavras-chave: dc.subjectCOVID-19-
Palavras-chave: dc.subjectSocial determinants of health-
Palavras-chave: dc.subjectDiabetes mellitus-
Palavras-chave: dc.subjectObesity-
Título: dc.titleAssessing predictive factors of COVID-19 outcomes: a case-control study in the metropolitan region of São Paulo (Brazil)-
Tipo de arquivo: dc.typeArtigo-
Aparece nas coleções:Repositório Institucional da Universidade Federal de Lavras (RIUFLA)

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