Análise das hospitalizações por Covid-19 no Estado do Espírito Santo

• Autor(a) principal: Garbin, Juliana Rodrigues Tovar
• Data de Publicação: 2023
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Repositório Institucional da Universidade Federal do Espírito Santo (riUfes)
• Texto Completo: http://repositorio.ufes.br/handle/10/12307
• topic: Saúde Coletiva; Infecções por coronavírus; COVID-19; SARS-CoV-2; Sobrevivência; Hospitalização; Vigilância em Saúde Pública

Introduction: For about three years, the world experienced the pandemic of a disease caused by the new coronavirus (SARS-CoV-2): COVID-19, which has become one of the greatest health challenges on a global scale in this century. Aim: To analyze hospitalizations due to COVID-19 in the State of Espírito Santo from 2020 to 2021. Methodology: for the three articles, we chose to use the analytical, retrospective type of study. In article 1, survival analysis was used, where the dependent variable of interest was the time elapsed from the first day of hospitalization until the onset of death from COVID-19. The second article analyzed the mean length of hospitalization for COVID-19 in different waves and the third analyzed the risk factors associated with long-term hospitalization in patients with COVID-19. The analysis began by organizing the databases in the Microsoft Excel version 10 program, and later IBM SPSS Statistics version 24 and STATA version 14 were used. For article 1, multiple logistic regression was performed with the selection method of forward variables, Log-rank test and Cox regression. In article 2, to analyze the distribution of hospitalizations according to waves, the non-parametric Kruskal-Wallis test was used. In article 3, bivariate analyzes were performed using the chi-square test for heterogeneity. Subsequently, the crude and adjusted Odds / Odds Ratio (RO/OR) and their respective 95% confidence intervals were calculated using the logistic regression model. The alpha level of significance used in all analyzes was 5%. The present study was submitted for approval by the Secretary of State for Health of Espírito Santo and the research ethics committee, through the brasil platform under the consubstantiated opinion number 5.180.941 of December 20, 2021. Results: In article 1, the mean age of the group was 58 years (SD ± 18.3) and the mean length of hospital stay was 10.5 days (SD ± 11.8).p < 0.001, age group of 60 to 79 years (HR: 1.62; p < 0.001) and 80 years or older (HR = 2.56; p < 0.001), presence of chronic cardiovascular disease (HR = 1.18; p = 0.028), chronic chronic kidney disease (HR = 1.5; p = 0.004), smoking (HR = 1.41; p < 0.001), obesity (HR = 2.28; p < 0.001), neoplasms (HR = 1.81; p < 0.001) and chronic neurological disease (HR = 1.68; p< 0.001). In article 2, the average length of stay in the hospital was associated with the following characteristics of the patients: age groups up to 59 years old and from 60 to 79 years old, high school and higher education, white and non-white race, female and male gender and resident from the urban area (p<0.05). With regard to the presence of comorbidities, there was a statistically significant difference for the mean days of hospitalization among patients with chronic cardiovascular disease, diabetes mellitus and obesity (p<0.05). In article 03, regarding the associated factors, in the first wave, the chance of having a long hospitalization was greater in elderly patients (OR = 1.67; 95%CI 1.35-2.06, p<0.001), in individuals with 10 or more symptoms (OR=2.03; 95%CI 1.04-3.94, p<0.05), obese (OR=2.0; 95%CI 1.53- 2.74) and with two or more more comorbidities (OR= 2.22; 95%CI 1.71-2.89, p<0.05). In the second wave, in individuals aged 60 years or more (OR=2.04; 95% CI 1.58-2.62, p<0.001) and with two or more comorbidities (OR= 1.77; 95% CI 1.29-2.41, p<0.001). Individuals with 8 to 11 years of education were 36% less likely (OR= 0.64; 95% CI 0.46 to 0.90) than individuals with 12 years or more. As for the third wave, in individuals aged 60 years or more (OR= 1.89; 95%CI 1.65- 2.17, p<0.001), with five to nine symptoms (OR= 1.52; 95%CI 1, 20-1.92, p<0.001), obese (OR= 2.2; 95% CI 1.78-2.73, p<0.001) and with one/two or more comorbidities (OR= 1.45; CI 95 %: 1.22-1.72 and OR= 2.0, 95%CI: 1.69-2.45, p<0.001). Conclusion: Taking into account that diseases do not occur by chance, as they are guided by social and health determinants, and that the pandemic caused by the new coronavirus reached different groups of society, the present study is of great relevance for Collective Health , as it allowed the identification of priority groups, being able to direct the implementation of more specific prevention and control strategies, such as those that protect the elderly, pregnant women, people with low education, with comorbidities and prioritize testing for early detection of positive cases.