Clinical risk factors of ICU & fatal COVID-19 cases in Brazil

  • Juliana Barcellos Mattos Universidade Federal de Pernambuco
  • Eraylson Silva Universidade Federal de Pernambuco
  • Paulo Mattos Neto Universidade Federal de Pernambuco
  • Renato Vimieiro Universidade Federal de Minas Gerais


The Coronavirus disease 2019 (COVID-19) was first detected in China in December 2019. In a few months, the disease got pandemic proportions, overloading health systems all around the world. Risk factors related to the progression and outcome of the disease are still unclear. Moreover, clinical aspects of patients can differ between societies, and other demographic elements may impact survival responses. A better characterisation of local manifestation of COVID-19 is crucial to a better general understanding of the disease, and thus to improve treatment decisions and health systems’ management. In this article, we performed an initial analysis of clinical factors related to admission in ICU or death of SARS-CoV-2 confirmed Brazilian patients, based on 1,138,690 medical records from the Brazilian government. To our knowledge, this study is the first to assess clinical risk factors for disease progression in Brazil. We provide a concise data set of medical registers related to COVID-19 in the whole Brazilian territory, and we describe the baseline comorbidities and symptoms observed in the data collection. Then, we assess the correlation between the manifestation of symptoms/comorbidities and the patients’ survival response through Kaplan-Meier survival estimates. The results here reported are mostly in accordance with findings reported in previous works.

Palavras-chave: Clinical Analysis, COVID-19, Risk factors, SARS-CoV-2, Survival Analysis


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MATTOS, Juliana Barcellos; SILVA, Eraylson; MATTOS NETO, Paulo ; VIMIEIRO, Renato. Clinical risk factors of ICU & fatal COVID-19 cases in Brazil. In: SYMPOSIUM ON KNOWLEDGE DISCOVERY, MINING AND LEARNING (KDMILE), 8. , 2020, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 33-40. ISSN 2763-8944. DOI: