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Revista de la Facultad de Medicina Humana
versão impressa ISSN 1814-5469versão On-line ISSN 2308-0531
Resumo
YUPARI-AZABACHE, Irma et al. COVID - 19 mortality risk factors in hospitalized patients: A logistic regression model. Rev. Fac. Med. Hum. [online]. 2021, vol.21, n.1, pp.19-27. ISSN 1814-5469. http://dx.doi.org/10.25176/rfmh.v21i1.3264.
Introduction:
The population is susceptible to COVID-19 and knowing the most predominant characteristics and comorbidities of those affected is essential to diminish its effects.
Objective:
This study analyzed the biological, social and clinical risk factors for mortality in hospitalized patients with COVID-19 in the district of Trujillo, Peru.
Methods:
A descriptive type of study was made, with a quantitative approach and a correlational, retrospective, cross-sectional design. Data was obtained from the Ministry of Health’s database, with a sample of 64 patients from March to May 2020.
Results:
85,71% of the total deceased are male, the most predominant occupation is Retired with an 28,57% incidence, and an average age of 64,67 years. When it came to symptoms of deceased patients, respiratory distress represents the highest percentage of incidence with 90,48%, then fever with 80,95%, followed by malaise in general with 57,14% and cough with 52,38%. The signs that indicated the highest percentage in deaths were dyspnea and abnormal pulmonary auscultation with 47,62%, in Comorbidities patients with cardiovascular disease were found in 42,86% and 14,29% with diabetes. The logistic regression model to predict mortality in hospitalized patients allowed the selection of risk factors such as age, sex, cough, shortness of breath and diabetes.
Conclusion:
The model is adequate to establish these factors, since they show that a fairly considerable percentage of explained variation would correctly classify 90,6% of the cases.
Palavras-chave : Risk; mortality; COVID-19; Comorbidity; Hospitalization (source: MeSH NLM)..