Fatores associados aos óbitos de pacientes com síndrome respiratória aguda grave com diagnóstico de COVID-19
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2023-03-03
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Universidade Estadual Paulista (Unesp)
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Introdução: Por se tratar de uma nova doença no cenário mundial, foi preciso identificar a população mais vulnerável e os fatores de risco prevalentes para o óbito entre indivíduos com Síndrome Respiratória Aguda Grave (SRAG) hospitalizados com diagnostico de COVID-19 durante a primeira onda da doença no município de Bauru/SP. Com a necessidade do monitoramento dos casos hospitalizados no Brasil, todo paciente internado com SRAG suspeito ou confirmado para COVID-19 deve ser notificado no prazo de 24 horas. As informações são digitadas e armazenadas no Sistema de Informação de Vigilância Epidemiológica da Gripe (SIVEP-Gripe) para acompanhamento epidemiológico. Objetivo: investigar os fatores associados à ocorrência de óbitos entre indivíduos com SRAG diagnosticados com COVID-19. Método: estudo de coorte não concorrente, com análise de dados secundários. Os dados foram coletados no SIVEP-Gripe entre os meses de fevereiro a setembro de 2021. Foram considerados todos os indivíduos residentes de Bauru que foram atendidos em hospitais públicos e particulares, notificados com SRAG que tiveram diagnóstico confirmado de COVID-19, no período de um ano a contar a partir de 1 de abril de 2020. Os dados foram analisados hierarquicamente. Primeiramente foram ajustados os modelos de regressão linear simples com resposta Poisson em cada bloco de variáveis independentes. Em seguida, foram ajustados modelos de regressão linear múltipla com resposta Poisson considerando as variáveis dos blocos que associaram-se significativamente com o óbito. O próximo passo foi um processo iterativo de ajuste de modelo, considerando variáveis estatisticamente significativas dos blocos seguintes. Ao final do processo iterativo foi ajustado um novo modelo, mais parcimonioso contendo apenas as variáveis que foram estatisticamente significativas. Em todo o processo foram consideradas associações significativas se p<0,20, incluindo no modelo final somente variáveis com p < 0,05. Resultados: durante o período do estudo, foram notificados 5357 casos. Utilizando os critérios de exclusão a amostra foi de 3558 casos de SRAG em usuários dos serviços de saúde, residentes de Bauru, sendo que 2238 tiveram diagnóstico confirmado de COVID-19, e desses, 581 evoluíram a óbito. Observou-se que com o aumento da idade existe um risco maior para o óbito, aumentando em média 2,9% a cada ano, enquanto os indivíduos internados em uma Unidade de Terapia Intensiva (UTI) apresentaram cinco vezes mais risco de evoluir a óbito. No entanto, os indivíduos internados em serviços particulares, apresentaram risco relativo menor que um, agindo como fator de proteção. Conclusão: os fatores relacionados a ocorrência dos óbitos por SRAG causado pela COVID-19 no município de Bauru durante a primeira onda da doença foram: a idade, internação em UTI e tipo de unidade de internação.
Introduction: with the need to monitor hospitalized cases in Brazil, every patient hospitalized with Severe Acute Respiratory Syndrome (SARS) - suspected or confirmed for COVID-19 has been notified within 24 hours. The information must be entered and stored in the Influenza Epidemiological Surveillance Information System (SIVEP-Flu) for epidemiological monitoring. Objective: to investigate the factors associated with the occurrence of deaths among individuals with SARS diagnosed with COVID-19. Method: retrospective cohort study, with analysis of secondary data regarding reported cases of SARS diagnosed with COVID-19 that occurred in the city of Bauru/SP, from April 1, 2020, to April 1, 2021. Data were collected in the SIVEP-Flu between the months of February and September 2021. All individuals residing in Bauru who were treated at public and private hospitals, hospitalized and notified with SARS who had a confirmed diagnosis of COVID-19, within a period of one year were considered starting from April 1, 2020. Data analysis was performed hierarchically. First, the simple linear regression models with Poisson response were adjusted in each block of independent variables. Then, multiple linear regression models with Poisson response were adjusted considering the block variables that were significantly associated with death. The next step was an iterative process of model fitting, considering statistically significant variables from the following blocks. At the end of the iterative process, a new, more parsimonious model was adjusted, containing only the variables that were statistically significant. Throughout the process, significant associations were considered if p<0.20, including in the final model only variables with p< 0.05. Results: during the study period, 5357 cases were reported. Using the inclusion and exclusion criteria, the sample consisted of 3558 cases of SARS in users residing in Bauru, of which 2238 had a confirmed diagnosis of COVID-19, and of these, 581 died. It was observed that with increasing age there is a greater risk of death, increasing on average by 2.9% each year, while individuals admitted to an Intensive Care Unit (ICU) had a five times greater risk of evolving to death. However, individuals admitted to private services had a relative risk lower than one, acting as a protective factor. Conclusion: the factors related to the occurrence of SARS deaths caused by COVID-19 in the city of Bauru during the first wave of the disease were: age, ICU stay and type of hospitalization unit.
Introduction: with the need to monitor hospitalized cases in Brazil, every patient hospitalized with Severe Acute Respiratory Syndrome (SARS) - suspected or confirmed for COVID-19 has been notified within 24 hours. The information must be entered and stored in the Influenza Epidemiological Surveillance Information System (SIVEP-Flu) for epidemiological monitoring. Objective: to investigate the factors associated with the occurrence of deaths among individuals with SARS diagnosed with COVID-19. Method: retrospective cohort study, with analysis of secondary data regarding reported cases of SARS diagnosed with COVID-19 that occurred in the city of Bauru/SP, from April 1, 2020, to April 1, 2021. Data were collected in the SIVEP-Flu between the months of February and September 2021. All individuals residing in Bauru who were treated at public and private hospitals, hospitalized and notified with SARS who had a confirmed diagnosis of COVID-19, within a period of one year were considered starting from April 1, 2020. Data analysis was performed hierarchically. First, the simple linear regression models with Poisson response were adjusted in each block of independent variables. Then, multiple linear regression models with Poisson response were adjusted considering the block variables that were significantly associated with death. The next step was an iterative process of model fitting, considering statistically significant variables from the following blocks. At the end of the iterative process, a new, more parsimonious model was adjusted, containing only the variables that were statistically significant. Throughout the process, significant associations were considered if p<0.20, including in the final model only variables with p< 0.05. Results: during the study period, 5357 cases were reported. Using the inclusion and exclusion criteria, the sample consisted of 3558 cases of SARS in users residing in Bauru, of which 2238 had a confirmed diagnosis of COVID-19, and of these, 581 died. It was observed that with increasing age there is a greater risk of death, increasing on average by 2.9% each year, while individuals admitted to an Intensive Care Unit (ICU) had a five times greater risk of evolving to death. However, individuals admitted to private services had a relative risk lower than one, acting as a protective factor. Conclusion: the factors related to the occurrence of SARS deaths caused by COVID-19 in the city of Bauru during the first wave of the disease were: age, ICU stay and type of hospitalization unit.
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Infecções por coronavírus, Vírus da SARS, Morte, Serviços de Vigilância Epidemiológica