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1.
Cad Saude Publica ; 38(11): e00261921, 2022.
Article in Portuguese | MEDLINE | ID: covidwho-2162689

ABSTRACT

The outcome of SARS-CoV-2 infection is not only associated with age and comorbidities but is also aggravated by social vulnerability. This study aims to analyze - according to social vulnerability - survival and hospital lethality by COVID-19 in the first 100 days from symptoms to death in individuals aged 50 years or older hospitalized in Brazil. This is a retrospective cohort from Epidemiological Week 11 of 2020 to week 33 of 2021. The Influenza Epidemiological Surveillance Information System (SIVEP-Gripe) provided clinical and epidemiological data. The Geographic Index of the Socioeconomic Context for Health and Social Studies (GeoSES) measured social vulnerability. The Kaplan-Meier curve and the adjusted proportional risk model by Cox were used for survival, with hazard ratio (HR) and 95% confidence intervals (95%CI). Among the 410,504 cases, overall lethality was of 42.2% in general and 51.4% in the most vulnerable. We found a higher lethality according to worse socioeconomic status in all categories by age group; the double is registered for 50-59 years. The adjusted Cox model showed a 32% increase in risk of death (HR = 1.32; 95%CI: 1.24-1.42). Moreover, men, older adults, black or indigenous adults, with multiple comorbidities, and subjected to invasive ventilation, have a higher risk of death after hospitalization. Intersectoral policy measures need to be targeted to alleviate the effects of the COVID-19 pandemic aggravated by social vulnerability.


O desfecho da infecção pelo SARS-CoV-2 não se associa apenas à idade e a comorbidades, mas também agrava-se por vulnerabilidade social. Este estudo tem como objetivo analisar, segundo vulnerabilidade social, a sobrevida e a letalidade hospitalar por COVID-19 para os primeiros 100 dias entre sintomas até o óbito em indivíduos de 50 anos ou mais hospitalizados no Brasil. Trata-se de uma coorte retrospectiva das Semanas Epidemiológicas 11, de 2020, a 33, de 2021. O Sistema de Informação de Vigilância Epidemiológica da Gripe (SIVEP-Gripe) forneceu dados clínico-epidemiológicos. O Índice Socioeconômico do Contexto Geográfico para Estudos em Saúde (GeoSES) mensurou vulnerabilidade social. Para sobrevida, utilizou-se a curva de Kaplan-Meier e o modelo ajustado de riscos proporcionais de Cox, com hazard ratio (HR) e intervalos de 95% de confiança (IC95%). Dentre os 410.504 casos, a letalidade geral foi de 42,2%, sendo 51,4% os indivíduos mais vulneráveis. Por faixa etária, registra-se a presença de maior letalidade para os piores status socioeconômicos em todas as categorias; para 50-59 anos, registra-se o dobro. O modelo ajustado de Cox mostrou aumento de 32% de risco para óbito (HR = 1,32; IC95%: 1,24-1,42). Ademais, homens, idosos, pretos ou indígenas, com múltiplas comorbidades e submetidos à ventilação invasiva apresentam maior risco de óbito após hospitalização. É necessário que medidas políticas intersetoriais sejam direcionadas para mitigar os efeitos da pandemia de COVID-19 agravados pela vulnerabilidade social.


El pronóstico de la infección por SARS-CoV-2 no sólo está asociado a la edad y a las comorbilidades, sino que también empeora por la vulnerabilidad social. El presente estudio tiene como objetivo analizar, según la vulnerabilidad social, la supervivencia y la letalidad hospitalaria por COVID-19 durante los primeros 100 días entre los síntomas hasta la muerte en individuos de 50 años o más hospitalizados en Brasil. Se trata de una cohorte retrospectiva desde la Semana Epidemiológica 11 de 2020 hasta la 33 de 2021. El Sistema de Información de Vigilancia Epidemiológica de la Gripe (SIVEP-Gripe) proporcionó datos clínico-epidemiológicos. El Índice Socioeconómico del Contexto Geográfico para los Estudios de Salud (GeoSES) midió la vulnerabilidad social. Para la supervivencia se utilizó la curva de Kaplan-Meier y el modelo ajustado de riesgos proporcionales de Cox, con cociente de riesgos (hazard ratio - HR) e intervalos del 95% de confianza (IC95%). Entre los 410.504 casos la letalidad global fue del 42,2%; el 51,4% en los más vulnerables. Por grupos de edad, se registra la presencia de una mayor letalidad a medida que empeora el estatus socioeconómico en todas las categorías; para 50-59 años es el doble. El modelo de Cox ajustado mostró un aumento del 32% en el riesgo de muerte (HR = 1,32; IC95%: 1,24-1,42). Además, los hombres de edad avanzada, de raza negra o indígena, con múltiples comorbilidades y sometidos a ventilación invasiva tienen un mayor riesgo de muerte tras la hospitalización. Es necesario que las medidas políticas intersectoriales se dirijan a mitigar los efectos de la pandemia de COVID-19 agravada por la vulnerabilidad social.


Subject(s)
COVID-19 , Male , Humans , Middle Aged , Aged , COVID-19/epidemiology , Retrospective Studies , SARS-CoV-2 , Brazil/epidemiology , Pandemics , Social Vulnerability , Hospitals , Hospitalization
2.
Int J Infect Dis ; 113: 162-165, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1507128

ABSTRACT

OBJECTIVES: To describe the profile of hospital deaths in Brazil according to cause of admission during the pre-pandemic (2019) and pandemic periods (2020). METHODS: Descriptive study based on individual-level records of all hospital admissions with death outcomes reimbursed by the Brazilian National Health System in 2019 and 2020. RESULTS: The number of hospital deaths increased by 16.7% in 2020 compared with 2019 (522,686 vs 609,755). Coronavirus disease 2019 (COVID-19) was associated with 19.5% (118,879) of all hospital deaths in 2020, surpassing diseases of the circulatory system (15.4%, 93,735) and diseases of the respiratory system (14.9%, 91,035). CONCLUSIONS: COVID-19 was the main cause of death in public hospitals in Brazil in 2020.


Subject(s)
COVID-19 , Brazil/epidemiology , Hospitals, Public , Humans , Public Health , SARS-CoV-2
3.
PLoS One ; 16(7): e0254633, 2021.
Article in English | MEDLINE | ID: covidwho-1315889

ABSTRACT

BACKGROUND: Almost 200,000 deaths from COVID-19 were reported in Brazil in 2020. The case fatality rate of a new infectious disease can vary by different risk factors and over time. We analysed the trends and associated factors of COVID-19 case fatality rates in Brazilian public hospital admissions during the first wave of the pandemic. METHODS: A retrospective cohort of all COVID-19-related admissions between epidemiological weeks 10-40 in the Brazilian Public Health System (SUS) was delimited from available reimbursement records. Smoothing time series and survival analyses were conducted to evaluate the trends of hospital case fatality rates (CFR) and the probability of death according to factors such as sex, age, ethnicity, comorbidities, length of stay and ICU use. RESULTS: With 398,063 admissions and 86,452 (21.7%) deaths, the overall age-standardized hospital CFR trend decreased throughout the period, varying from 31.8% (95%CI: 31.2 to 32.5%) in week 10 to 18.2% (95%CI: 17.6 to 18.8%) in week 40. This decreasing trend was observed in all sex, age, ethnic groups, length of stay and ICU admissions. Consistently, later admission (from July to September) was an independent protective factor. Patients 80+ year old had a hazard ratio of 8.18 (95% CI: 7.51 to 8.91). Ethnicity, comorbidities, and ICU need were also associated with the death risk. Although also decreasing, the CFR was always around 40-50% in people who needed an ICU admission. CONCLUSIONS: The overall hospital CFR of COVID-19 has decreased in Brazilian public hospitals during the first wave of the pandemic in 2020. Nevertheless, during the entire period, the CFR was still very high, suggesting the need for improving COVID-19 hospital care in Brazil.


Subject(s)
COVID-19/mortality , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , Brazil , COVID-19/epidemiology , Comorbidity , Female , Hospitals, Public/statistics & numerical data , Humans , Male , Middle Aged , Mortality/trends , Patient Admission/statistics & numerical data , Population Groups/statistics & numerical data , Sex Factors , Socioeconomic Factors
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