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1.
Int. j. cardiovasc. sci. (Impr.) ; 35(5): 635-642, Sept.-Oct. 2022. tab, graf
Article in English | WHO COVID, LILACS (Americas) | ID: covidwho-2325830

ABSTRACT

Abstract Fundament: Telemedicine for follow-up in heart failure (HF) patients is effective in reducing hospitalizations, total and cardiovascular mortality. However, few studies were conducted in low and middle income, where lower access to technology and illiteracy could impact the results. Objective: To assess the effectiveness of associating telemedicine strategies, when compared to usual care, in reducing hospitalizations related to HF in patients discharged from the hospital due to HF. Methods: Controlled, randomized, multicenter, parallel-arm clinical trial, with an allocation ratio of 1:1, blinded to outcome evaluation, in which 340 patients who were discharged from public hospitals in Belo Horizonte due to HF will be randomized. Patients will be followed for 6 months and the intervention group will receive, in addition to the usual care, Structured Telephone Support (STS) from a nurse, a doctor, and an educational program. Counseling will be according to a clinical decision tree. The level of significance in the statistical analysis will be 5%. Expected results: Reduction in the number of hospital readmissions and/or in hospitalization time, in addition to developing a software with a clinical decision tree for remote follow-up and patient education about HF adapted to local culture. Conclusions: The intention of this study is to develop a telemedicine strategy and assess whether or not, in addition to the usual care, it is effective in reducing hospitalizations and mortality from HF. If effective, the aforementioned strategy could reduce costs and hospital needs in the Unified Health System (SUS, in Portuguese) for patients with HF. These results will be even more relevant considering the pandemic of COVID-19.

2.
PLOS global public health ; 2(5), 2022.
Article in English | EuropePMC | ID: covidwho-2259511

ABSTRACT

The purpose of this article is to quantify the amount of misclassification of the Coronavirus Disease-2019 (COVID-19) mortality occurring in hospitals and other health facilities in selected cities in Brazil, discuss potential factors contributing to this misclassification, and consider the implications for vital statistics. Hospital deaths assigned to causes classified as garbage code (GC) COVID-related cases (severe acute respiratory syndrome, pneumonia unspecified, sepsis, respiratory failure and ill-defined causes) were selected in three Brazilian state capitals. Data from medical charts and forensic reports were extracted from standard forms and analyzed by study physicians who re-assigned the underlying cause based on standardized criteria. Descriptive statistical analysis was performed and the potential impact in vital statistics in the country was also evaluated. Among 1,365 investigated deaths due to GC-COVID-related causes, COVID-19 was detected in 17.3% in the age group 0–59 years and 25.5% deaths in 60 years and over. These GCs rose substantially in 2020 in the country and were responsible for 211,611 registered deaths. Applying observed proportions by age, location and specific GC-COVID-related cause to national data, there would be an increase of 37,163 cases in the total of COVID-19 deaths, higher in the elderly. In conclusion, important undercount of deaths from COVID-19 among GC-COVID-related causes was detected in three selected capitals of Brazil. After extrapolating the study results for national GC-COVID-related deaths we infer that the burden of COVID-19 disease in Brazil in official vital statistics was probably under estimated by at least 18% in the country in 2020.

3.
PLOS Glob Public Health ; 2(5): e0000199, 2022.
Article in English | MEDLINE | ID: covidwho-1854952

ABSTRACT

The purpose of this article is to quantify the amount of misclassification of the Coronavirus Disease-2019 (COVID-19) mortality occurring in hospitals and other health facilities in selected cities in Brazil, discuss potential factors contributing to this misclassification, and consider the implications for vital statistics. Hospital deaths assigned to causes classified as garbage code (GC) COVID-related cases (severe acute respiratory syndrome, pneumonia unspecified, sepsis, respiratory failure and ill-defined causes) were selected in three Brazilian state capitals. Data from medical charts and forensic reports were extracted from standard forms and analyzed by study physicians who re-assigned the underlying cause based on standardized criteria. Descriptive statistical analysis was performed and the potential impact in vital statistics in the country was also evaluated. Among 1,365 investigated deaths due to GC-COVID-related causes, COVID-19 was detected in 17.3% in the age group 0-59 years and 25.5% deaths in 60 years and over. These GCs rose substantially in 2020 in the country and were responsible for 211,611 registered deaths. Applying observed proportions by age, location and specific GC-COVID-related cause to national data, there would be an increase of 37,163 cases in the total of COVID-19 deaths, higher in the elderly. In conclusion, important undercount of deaths from COVID-19 among GC-COVID-related causes was detected in three selected capitals of Brazil. After extrapolating the study results for national GC-COVID-related deaths we infer that the burden of COVID-19 disease in Brazil in official vital statistics was probably under estimated by at least 18% in the country in 2020.

4.
Rev Soc Bras Med Trop ; 55(suppl 1): e0283, 2022.
Article in English | MEDLINE | ID: covidwho-1674095

ABSTRACT

INTRODUCTION: Excess Mortality by all causes considers deaths directly related to COVID-19 and those attributed to conditions caused by the pandemic. When stratified by social dimensions, such as race/color, it allows for the evaluation of more vulnerable populations. The study estimated the excess mortality by natural causes, separating the white and black populations in 2020. METHODS: Public civil registration data on deaths observed in 2020, corrected for under registration, were used. The expected number of deaths was estimated based on the mortality rates observed in 2019, applied to the estimated population in 2020. The difference between the values expected and observed and the proportion of excess was considered the excess mortality. RESULTS: The present study found an excess of 270,321 deaths (22.2% above the expected) in 2020. Every state of Brazil reported deaths above the corresponding expected figure. The excess was higher for men (25.2%) than for women (19.0%). Blacks showed an excess of 27.8%, as compared to whites at 17.6%. In both sexes and all age groups, excess was higher in the black population, especially in the South, Southeast, and Midwest regions. São Paulo, the largest in population number, had twice as much excess death in the black population (25.1%) than in the white population (11.5%). CONCLUSIONS: The present study showed racial disparities in excess mortality during the COVID-19 pandemic in Brazil. The higher excess found for the black suggests an intrinsic relationship with the socioeconomic situation, further exposing the Brazilian reality, in which social and structural inequality is evident.


Subject(s)
COVID-19 , Black or African American , Brazil/epidemiology , Female , Humans , Male , Pandemics , SARS-CoV-2 , White People
5.
Rev Soc Bras Med Trop ; 55(suppl 1): e0264, 2022.
Article in English | MEDLINE | ID: covidwho-1674094

ABSTRACT

INTRODUCTION: The COVID-19 pandemic has had a great impact on the behavior of individuals and the organization of health systems. This study analyzed the COVID-19 pandemic's effect on public hospitalizations for cardiovascular diseases (CVD) in a large city in Brazil, Belo Horizonte, MG, with approximately 2.5 million inhabitants. METHODS: In a time-series analysis, this study used administrative data from the national "Hospital Information System" from 2010 to February 2020 to estimate the expected number of hospitalizations for CVD by month during the COVID-19 pandemic in Belo Horizonte in 2020 using the Auto-Regressive Integrated Moving Average model. For CVD, this study compared the expected number of hospital admissions, intensive care use, deaths during hospitalization, and mean length of stay with the observed number during the period. RESULTS: There were 6,517 hospitalizations for CVD from March to December 2020, a decrease of 16.3% (95% CI: 4.7-25.3) compared to the projected. The number of intensive care hospitalizations for CVD fell 24.1% (95% CI 13-32.7). The number of deaths also decreased (17.4% [80% CI: 0 - 0.30]), along with the reduction in hospitalizations, as did the length of stay for CVD hospitalizations. These reductions, however, were not significant. CONCLUSIONS: Hospitalizations for CVD were 16.3% lower than expected in a large Brazilian city, possibly due to the fear of getting infected or going to hospitals. Public campaigns informing how to proceed in case of CVD show that prompt urgent attention is essential to mitigate the indirect effects of the pandemic on CVD.


Subject(s)
COVID-19 , Cardiovascular Diseases , Brazil/epidemiology , Cardiovascular Diseases/epidemiology , Hospitalization , Hospitals , Humans , Pandemics , SARS-CoV-2
7.
Rev. bras. epidemiol ; 23:e200061-e200061, 2020.
Article in Portuguese | LILACS (Americas) | ID: grc-741418

ABSTRACT

RESUMO: Objetivos: Descrever as ações realizadas pela vigilância epidemiológica da Secretaria Municipal de Saúde de Belo Horizonte para enfrentamento da epidemia de COVID-19 e avaliar a oportunidade para detecção precoce da transmissão da doença no período compreendido entre 1º de janeiro e 24 de abril de 2020. Métodos: Foram identificadas as fontes de informação utilizadas pela vigilância epidemiológica do município para a COVID-19 e analisadas a distribuição temporal e a oportunidade para detecção dos casos confirmados da doença. Resultados: A vigilância epidemiológica do município utiliza fontes de notificações ambulatoriais, hospitalares, de laboratórios públicos e privados, além de busca ativa com cruzamento de dados laboratoriais na investigação de óbitos suspeitos, sendo os casos confirmados de COVID-19 informados em sistemas de informação oficiais. Foram notificados 1.449 casos internados, sendo o primeiro caso detectado no fim de fevereiro de 2020. Do total de 1.025 amostras laboratoriais de casos internados após a semana epidemiológica 8, confirmaram-se 87 casos (8,5%) por COVID-19. A mediana de tempo entre o início dos sintomas e a liberação dos resultados laboratoriais foi de 12 dias. Conclusão: A vigilância epidemiológica utiliza várias fontes de dados para monitoramento e análise da transmissão da COVID-19. A oportunidade para detecção de casos da doença está comprometida pela demora na liberação dos resultados laboratoriais, sendo um desafio para a vigilância. ABSTRACT: Objectives: This study aims to describe the actions carried out by the epidemiological surveillance system in Belo Horizonte to address the COVID-19 epidemic and the timeless of the data for detecting transmission in 2020. Methods: The sources of information used by the epidemiological surveillance of the municipality for COVID-19 were identified and the temporal distribution and interval for detection of confirmed cases of the disease were analyzed. Results: The city's epidemiological surveillance uses outpatient, hospital, public and private laboratory notifications as data sources. For reporting COVID-19 cases in official information systems, there is also an active search of laboratory results linked to suspected deaths investigated. From January to April 2020, 1,449 hospitalized cases of COVID-19 were reported, the first case being detected in late February 2020. Of the total 1,025 laboratory samples of cases hospitalized after the 8th epidemiological week, 87 (8.5%) of COVID-19 cases were confirmed. The median time between the onset of symptoms and the release of laboratory results was 12 days for the analyzed period. Conclusion: Epidemiological surveillance uses several data sources to monitor and analyze the transmission of COVID-19. The timeliness of this system to detect cases of the disease is compromised by the delay in the release of laboratory results, which has been a considerable challenge for adequate surveillance.

8.
Heart ; 106(24): 1898-1905, 2020 12.
Article in English | MEDLINE | ID: covidwho-873558

ABSTRACT

INTRODUCTION: During the COVID-19 pandemic, excess mortality has been reported, while hospitalisations for acute cardiovascular events reduced. Brazil is the second country with more deaths due to COVID-19. We aimed to evaluate excess cardiovascular mortality during COVID-19 pandemic in 6 Brazilian capital cities. METHODS: Using the Civil Registry public database, we evaluated total and cardiovascular excess deaths, further stratified in specified cardiovascular deaths (acute coronary syndromes and stroke) and unspecified cardiovascular deaths in the 6 Brazilian cities with greater number of COVID-19 deaths (São Paulo, Rio de Janeiro, Fortaleza, Recife, Belém, Manaus). We compared observed with expected deaths from epidemiological weeks 12-22 of 2020. We also compared the number of hospital and home deaths during the period. RESULTS: There were 65 449 deaths and 17 877 COVID-19 deaths in the studied period and cities for 2020. Cardiovascular mortality increased in most cities, with greater magnitude in the Northern capitals. However, while there was a reduction in specified cardiovascular deaths in the most cities, the Northern capitals showed an increase of these events. For unspecified cardiovascular deaths, there was a marked increase in all cities, which strongly correlated to the rise in home deaths (r=0.86, p=0.01). CONCLUSION: Excess cardiovascular mortality was greater in the less developed cities, possibly associated with healthcare collapse. Specified cardiovascular deaths decreased in the most developed cities, in parallel with an increase in unspecified cardiovascular and home deaths, presumably as a result of misdiagnosis. Conversely, specified cardiovascular deaths increased in cities with a healthcare collapse.


Subject(s)
COVID-19/mortality , Cardiovascular Diseases/mortality , Urban Health/trends , Brazil/epidemiology , COVID-19/diagnosis , Cardiovascular Diseases/diagnosis , Cause of Death , Databases, Factual , Hospital Mortality , Humans , Registries , Retrospective Studies , Time Factors
9.
Rev Bras Epidemiol ; 23: e200061, 2020.
Article in English, Portuguese | MEDLINE | ID: covidwho-713147

ABSTRACT

OBJECTIVES: This study aims to describe the actions carried out by the epidemiological surveillance system in Belo Horizonte to address the COVID-19 epidemic and the timeless of the data for detecting transmission in 2020. METHODS: The sources of information used by the epidemiological surveillance of the municipality for COVID-19 were identified and the temporal distribution and interval for detection of confirmed cases of the disease were analyzed. RESULTS: The city's epidemiological surveillance uses outpatient, hospital, public and private laboratory notifications as data sources. For reporting COVID-19 cases in official information systems, there is also an active search of laboratory results linked to suspected deaths investigated. From January to April 2020, 1,449 hospitalized cases of COVID-19 were reported, the first case being detected in late February 2020. Of the total 1,025 laboratory samples of cases hospitalized after the 8th epidemiological week, 87 (8.5%) of COVID-19 cases were confirmed. The median time between the onset of symptoms and the release of laboratory results was 12 days for the analyzed period. CONCLUSION: Epidemiological surveillance uses several data sources to monitor and analyze the transmission of COVID-19. The timeliness of this system to detect cases of the disease is compromised by the delay in the release of laboratory results, which has been a considerable challenge for adequate surveillance.


Subject(s)
Coronavirus Infections/epidemiology , Epidemics , Epidemiological Monitoring , Pneumonia, Viral/epidemiology , Population Surveillance , Brazil/epidemiology , COVID-19 , Cities/epidemiology , Coronavirus Infections/mortality , Humans , Pandemics , Pneumonia, Viral/mortality
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