Padrões de condições clínicas de pacientes brasileiros em idade produtiva com esquema vacinal completo contra a Covid-19 e hospitalizados devido à forma grave da doença de acordo com status de admissão na UTI
##plugins.themes.bootstrap3.article.sidebar##
Publicado
Oct 21, 2022
##plugins.themes.bootstrap3.article.main##
Resumo
Objetivo: Identificar padrões de condições clínicas a partir de dados de pacientes em idade produtiva, com esquema vacinal completo contra a Covid-19, hospitalizados devido à forma grave da doença e com apresentação de status de admissão em Unidade de Terapia Intensiva (UTI). Métodos: Trata-se de um estudo descritivo com o banco de dados OpenDataSUS por meio de Mineração de Regras de Associação (MRA). Resultados: Descreveu-se as informações referentes a 3.470 indivíduos, sendo 53% (n= 1.842) do sexo masculino, 63% (n= 2.187) com comorbidades, 33% (n= 1.137) admitidos em UTI e 23% (n= 796) com registros de evolução a óbito. A admissão na UTI foi associada ao uso de suporte ventilatório invasivo, sexo masculino, presença de comorbidade e óbito. Para os pacientes hospitalizados, mas sem internação na UTI, encontrou-se predominância do status de sobrevivência, ausência de comorbidade, sexo feminino, uso de suporte ventilatório não invasivo e sintomatologia leve a moderada. Conclusão: Os achados reforçam a necessidade de administrar doses de reforço das vacinas contra a Covid-19, mas também de fortalecer as políticas de combate às doenças crônicas não transmissíveis no Brasil.
##plugins.themes.bootstrap3.article.details##
Como Citar
OliveiraT. B. de, SantosW. R. F. dos, RodriguesL. S., HirataM. Y., & MazucheliJ. (2022). Padrões de condições clínicas de pacientes brasileiros em idade produtiva com esquema vacinal completo contra a Covid-19 e hospitalizados devido à forma grave da doença de acordo com status de admissão na UTI. Revista Eletrônica Acervo Saúde, 15(10), e10997. https://doi.org/10.25248/reas.e10997.2022
Seção
Artigos Originais
Copyright © | Todos os direitos reservados.
A revista detém os direitos autorais exclusivos de publicação deste artigo nos termos da lei 9610/98.
Reprodução parcial
É livre o uso de partes do texto, figuras e questionário do artigo, sendo obrigatória a citação dos autores e revista.
Reprodução total
É expressamente proibida, devendo ser autorizada pela revista.
Referências
1. ALRUTHIA Y, et al. Demographic Characteristics and Status of Vaccinated Individuals with a History of Covid-19 Infection Pre-or Post-Vaccination: A Descriptive Study of a Nationally Representative Sample in Saudi Arabia. Vaccines, 2022; 10(2): 323.
2. BAQUI P, et al. Comparing Covid-19 risk factors in Brazil using machine learning: the importance of socioeconomic, demographic and structural factors. Scientific reports, 2021; 11(1): 1-10.
3. BAQUI P, et al. Ethnic and regional variations in hospital mortality from Covid-19 in Brazil: a cross-sectional observational study. The Lancet Global Health, 2020; 8(8): 1018-1026.
4. BECKMAN MF, et al. Comorbidities and Susceptibility to Covid-19: A Generalized Gene Set Data Mining Approach. Journal of clinical medicine, 2021; 10(8): 1666.
5. BORTOLINU GA, et al. Evolution of nutrition actions in primary health care along the 20-year history of the Brazilian National Food and Nutrition Policy. Cadernos de Saúde Pública, 2022; 37.
6. BRAZIL. Coronavirus Panel. 2022. Available in: https://covid.saude.gov.br/. Accessed in: March 15th, 2022.
7. BRAZIL. SRAG 2021 - Severe Acute Respiratory Syndrome Database - including Covid-19 data. 2021a. Available in: https://dados.gov.br/dataset/bd-srag-2021. Accessed in: November 18th, 2021.
8. BRAZIL. Strategic Action Plan to Combat Chronic Diseases and Non-Communicable Diseases in Brazil (2021-2030). 2021b. Available in: https://www.gov.br/saude/pt-br/centrais-de-conteudo/publicacoes/publicacoes-svs/doencas-cronicas-nao-transmissiveis-dcnt/09-plano-de-dant-2022_2030.pdf/. Accessed in: March 25th, 2022.
9. BROSH-NISSIMOV T, et al. BNT162b2 vaccine breakthrough: clinical characteristics of 152 fully vaccinated hospitalized Covid-19 patients in Israel. Clinical Microbiology and Infection, 2021; 27(11): 1652-1657.
10. CANDIDO DS, et al. Evolution and epidemic spread of SARS-CoV-2 in Brazil. Science, 2020; 369(6508): 1255-1260.
11. CANUTO LE, et al. Estudo da demanda de uma equipe da Estratégia Saúde da Família que utiliza o acesso avançado como modelo de organização da agenda. Revista Brasileira de Medicina de Família e Comunidade, 2021; 16(43): 2378-2378.
12. CASH R, PATEL V. Has Covid-19 subverted global health?. The Lancet, 2020; 395(10238): 1687-1688.
13. DOCHERTY AB, et al. Features of 20 133 UK patients in hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: prospective observational cohort study. BJM, 2020; 369.
14. GIOVANELLA L, et al. The family health strategy coverage in Brazil: what reveal the 2013 and 2019 national health surveys. Ciência & Saúde Coletiva, 2021; 26: 2543-2556.
15. GRASSELLI G, et al. Risk factors associated with mortality among patients with Covid-19 in intensive care units in Lombardy, Italy. JAMA internal medicine, 2020; 180(10): 1345-1355.
16. GUIMARÃES R, et al. Increasing impact of Covid-19 on young adults: evidence from hospitalisations in Brazil. Public Health, 2021; 198: 297-300.
17. HASHLER M, et al. Mining Association Rules and Frequent Itemsets, Package Version, 2022; 17-3. Available in: https://cran.r-project.org/web/packages/arules/index.html. Accessed in: December 20th, 2022.
18. KAHN F, et al. Risk of severe Covid-19 from the Delta and Omicron variants in relation to vaccination status, sex, age and comorbidities–surveillance results from southern Sweden, July 2021 to January 2022. Eurosurveillance, 2022; 27(9): 2200121.
19. KATRAGADDA S, et al. Association mining based approach to analyze Covid-19 response and case growth in the United States. Scientific Reports, 2021; 11(1): 1-12.
20. KIM L, et al. Risk factors for intensive care unit admission and in-hospital mortality among hospitalized adults identified through the US coronavirus disease 2019 (Covid-19)-associated hospitalization surveillance network (Covid-NET). Clinical Infectious Diseases, 2021; 72(9): e206-e214.
21. MALTA DC, et al. Avaliação do alcance das metas do plano de enfrentamento das doenças crônicas não transmissíveis no Brasil, 2011-2022. Anais do Instituto de Higiene e Medicina Tropical, (supl. 1), 2019; 9-16.
22. MASSUDA A. Mudanças no financiamento da Atenção Primária à Saúde no Sistema de Saúde Brasileiro: avanço ou retrocesso?. Ciência & Saúde Coletiva, 2020; 25: 1181-1188.
23. MORENO-PEREZ O, et al. Hospitalized patients with breakthrough Covid-19: Clinical features and poor outcome predictors. International Journal of Infectious Diseases, 2022; 118: 89-94.
24. MOTOS A, et al. Higher frequency of comorbidities in fully vaccinated patients admitted to the ICU due to severe Covid-19: a prospective, multicentre, observational study. European Respiratory Journal, 2022; 59(2).
25. MURAKAMI MN, et al. A reorganização e atuação da Atenção Primária à Saúde em contexto de pandemia de Covid-19: uma revisão narrativa. Brazilian Journal of Development, 2022; 8(2): 12232-12251.
26. PAN AMERICAN HEALTH ORGANIZATION (PAHO). What is primary health care? 2021. Available in: https://www.paho.org/pt/topicos/atencao-primaria-saude. Accessed in: April 25th, 2022.
27. QUEIROZ AF, et al. Impacto da cobertura e da qualidade da atenção básica nas internações por condições sensíveis à Atenção Primária em Sergipe de 2010 a 2019. Research, Society and Development, 2022; 11(1): e42211125099.
28. RAO AB, KIRAN JS. Application of market–basket analysis on healthcare. International Journal of System Assurance Engineering and Management, 2021; 1-6.
29. RAUBER F, et al. Ultra-processed food consumption and risk of obesity: a prospective cohort study of UK Biobank. European journal of nutrition, 2021; 60(4): 2169-2180.
30. REIS CMJ, VANNIER MM, FRANKLIN VT. Análise Epidemiológica da Incidência da Covid-19 nas Regiões Brasileiras. The Brazilian Journal of Infectious Diseases, 2022; 26: 101782.
31. SANDOVAL-INSAUSTI H, et al. Ultra-processed food consumption is associated with abdominal obesity: A prospective cohort study in older adults. Nutrients, 2020; 12(8): 2368.
32. SANTOS SMCD, et al. Avanços e desafios nos 20 anos da Política Nacional de Alimentação e Nutrição. Cadernos de Saúde Pública, 2021; 37.
33. SHADMI E, et al. Health equity and Covid-19: global perspectives. International journal for equity in health, 2020; 19(1): 1-16.
34. SHIN DP, et al. Association rules mined from construction accident data. KSCE Journal of Civil Engineering, 2018; 22(4): 1027-1039.
35. SOUZA FSH, et al. An overview of Brazilian working age adults vulnerability to Covid-19. Scientific reports, 2022a; 12(1): 1-10.
36. SOUZA SDS, et al. Cobertura vacinal em Santa Catarina-Brasil: uma análise a partir da cobertura populacional da atenção primária. Enfermagem Comunitária, 2022b; 18: e12874-e12874.
37. TANDAN M, et al. Discovering symptom patterns of Covid-19 patients using association rule mining. Computers in biology and medicine, 2021; 131: 104249.
38. TANDON P, et al. The Third Wave: Comparing Seasonal Trends in Covid-19 Patient Data at a Large Hospital System in New York City. Critical care explorations, 2022; 4(3).
39. YEK C, et al. Risk Factors for Severe Covid-19 Outcomes Among Persons Aged≥ 18 Years Who Completed a Primary Covid-19 Vaccination Series—465 Health Care Facilities, United States, December 2020–October 2021. Morbidity and Mortality Weekly Report, 2022; 71(1): 19.
40. ZHU J, et al. Covid-19 pandemic in BRICS countries and its association with socio-economic and demographic characteristics, health vulnerability, resources, and policy response. Infectious Diseases of Poverty, 2021; 10(1): 1-8.
2. BAQUI P, et al. Comparing Covid-19 risk factors in Brazil using machine learning: the importance of socioeconomic, demographic and structural factors. Scientific reports, 2021; 11(1): 1-10.
3. BAQUI P, et al. Ethnic and regional variations in hospital mortality from Covid-19 in Brazil: a cross-sectional observational study. The Lancet Global Health, 2020; 8(8): 1018-1026.
4. BECKMAN MF, et al. Comorbidities and Susceptibility to Covid-19: A Generalized Gene Set Data Mining Approach. Journal of clinical medicine, 2021; 10(8): 1666.
5. BORTOLINU GA, et al. Evolution of nutrition actions in primary health care along the 20-year history of the Brazilian National Food and Nutrition Policy. Cadernos de Saúde Pública, 2022; 37.
6. BRAZIL. Coronavirus Panel. 2022. Available in: https://covid.saude.gov.br/. Accessed in: March 15th, 2022.
7. BRAZIL. SRAG 2021 - Severe Acute Respiratory Syndrome Database - including Covid-19 data. 2021a. Available in: https://dados.gov.br/dataset/bd-srag-2021. Accessed in: November 18th, 2021.
8. BRAZIL. Strategic Action Plan to Combat Chronic Diseases and Non-Communicable Diseases in Brazil (2021-2030). 2021b. Available in: https://www.gov.br/saude/pt-br/centrais-de-conteudo/publicacoes/publicacoes-svs/doencas-cronicas-nao-transmissiveis-dcnt/09-plano-de-dant-2022_2030.pdf/. Accessed in: March 25th, 2022.
9. BROSH-NISSIMOV T, et al. BNT162b2 vaccine breakthrough: clinical characteristics of 152 fully vaccinated hospitalized Covid-19 patients in Israel. Clinical Microbiology and Infection, 2021; 27(11): 1652-1657.
10. CANDIDO DS, et al. Evolution and epidemic spread of SARS-CoV-2 in Brazil. Science, 2020; 369(6508): 1255-1260.
11. CANUTO LE, et al. Estudo da demanda de uma equipe da Estratégia Saúde da Família que utiliza o acesso avançado como modelo de organização da agenda. Revista Brasileira de Medicina de Família e Comunidade, 2021; 16(43): 2378-2378.
12. CASH R, PATEL V. Has Covid-19 subverted global health?. The Lancet, 2020; 395(10238): 1687-1688.
13. DOCHERTY AB, et al. Features of 20 133 UK patients in hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: prospective observational cohort study. BJM, 2020; 369.
14. GIOVANELLA L, et al. The family health strategy coverage in Brazil: what reveal the 2013 and 2019 national health surveys. Ciência & Saúde Coletiva, 2021; 26: 2543-2556.
15. GRASSELLI G, et al. Risk factors associated with mortality among patients with Covid-19 in intensive care units in Lombardy, Italy. JAMA internal medicine, 2020; 180(10): 1345-1355.
16. GUIMARÃES R, et al. Increasing impact of Covid-19 on young adults: evidence from hospitalisations in Brazil. Public Health, 2021; 198: 297-300.
17. HASHLER M, et al. Mining Association Rules and Frequent Itemsets, Package Version, 2022; 17-3. Available in: https://cran.r-project.org/web/packages/arules/index.html. Accessed in: December 20th, 2022.
18. KAHN F, et al. Risk of severe Covid-19 from the Delta and Omicron variants in relation to vaccination status, sex, age and comorbidities–surveillance results from southern Sweden, July 2021 to January 2022. Eurosurveillance, 2022; 27(9): 2200121.
19. KATRAGADDA S, et al. Association mining based approach to analyze Covid-19 response and case growth in the United States. Scientific Reports, 2021; 11(1): 1-12.
20. KIM L, et al. Risk factors for intensive care unit admission and in-hospital mortality among hospitalized adults identified through the US coronavirus disease 2019 (Covid-19)-associated hospitalization surveillance network (Covid-NET). Clinical Infectious Diseases, 2021; 72(9): e206-e214.
21. MALTA DC, et al. Avaliação do alcance das metas do plano de enfrentamento das doenças crônicas não transmissíveis no Brasil, 2011-2022. Anais do Instituto de Higiene e Medicina Tropical, (supl. 1), 2019; 9-16.
22. MASSUDA A. Mudanças no financiamento da Atenção Primária à Saúde no Sistema de Saúde Brasileiro: avanço ou retrocesso?. Ciência & Saúde Coletiva, 2020; 25: 1181-1188.
23. MORENO-PEREZ O, et al. Hospitalized patients with breakthrough Covid-19: Clinical features and poor outcome predictors. International Journal of Infectious Diseases, 2022; 118: 89-94.
24. MOTOS A, et al. Higher frequency of comorbidities in fully vaccinated patients admitted to the ICU due to severe Covid-19: a prospective, multicentre, observational study. European Respiratory Journal, 2022; 59(2).
25. MURAKAMI MN, et al. A reorganização e atuação da Atenção Primária à Saúde em contexto de pandemia de Covid-19: uma revisão narrativa. Brazilian Journal of Development, 2022; 8(2): 12232-12251.
26. PAN AMERICAN HEALTH ORGANIZATION (PAHO). What is primary health care? 2021. Available in: https://www.paho.org/pt/topicos/atencao-primaria-saude. Accessed in: April 25th, 2022.
27. QUEIROZ AF, et al. Impacto da cobertura e da qualidade da atenção básica nas internações por condições sensíveis à Atenção Primária em Sergipe de 2010 a 2019. Research, Society and Development, 2022; 11(1): e42211125099.
28. RAO AB, KIRAN JS. Application of market–basket analysis on healthcare. International Journal of System Assurance Engineering and Management, 2021; 1-6.
29. RAUBER F, et al. Ultra-processed food consumption and risk of obesity: a prospective cohort study of UK Biobank. European journal of nutrition, 2021; 60(4): 2169-2180.
30. REIS CMJ, VANNIER MM, FRANKLIN VT. Análise Epidemiológica da Incidência da Covid-19 nas Regiões Brasileiras. The Brazilian Journal of Infectious Diseases, 2022; 26: 101782.
31. SANDOVAL-INSAUSTI H, et al. Ultra-processed food consumption is associated with abdominal obesity: A prospective cohort study in older adults. Nutrients, 2020; 12(8): 2368.
32. SANTOS SMCD, et al. Avanços e desafios nos 20 anos da Política Nacional de Alimentação e Nutrição. Cadernos de Saúde Pública, 2021; 37.
33. SHADMI E, et al. Health equity and Covid-19: global perspectives. International journal for equity in health, 2020; 19(1): 1-16.
34. SHIN DP, et al. Association rules mined from construction accident data. KSCE Journal of Civil Engineering, 2018; 22(4): 1027-1039.
35. SOUZA FSH, et al. An overview of Brazilian working age adults vulnerability to Covid-19. Scientific reports, 2022a; 12(1): 1-10.
36. SOUZA SDS, et al. Cobertura vacinal em Santa Catarina-Brasil: uma análise a partir da cobertura populacional da atenção primária. Enfermagem Comunitária, 2022b; 18: e12874-e12874.
37. TANDAN M, et al. Discovering symptom patterns of Covid-19 patients using association rule mining. Computers in biology and medicine, 2021; 131: 104249.
38. TANDON P, et al. The Third Wave: Comparing Seasonal Trends in Covid-19 Patient Data at a Large Hospital System in New York City. Critical care explorations, 2022; 4(3).
39. YEK C, et al. Risk Factors for Severe Covid-19 Outcomes Among Persons Aged≥ 18 Years Who Completed a Primary Covid-19 Vaccination Series—465 Health Care Facilities, United States, December 2020–October 2021. Morbidity and Mortality Weekly Report, 2022; 71(1): 19.
40. ZHU J, et al. Covid-19 pandemic in BRICS countries and its association with socio-economic and demographic characteristics, health vulnerability, resources, and policy response. Infectious Diseases of Poverty, 2021; 10(1): 1-8.