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Introduction: The impact of COVID-19 pandemics on cardiovascular diseases (CVD) may be caused by health system reorganization and/or collapse, or from changes in the behaviour of individuals. In Brazil, municipalities were empowered to define regulatory measures, potentially resulting in diverse effects on CVD morbimortality. Objective: To analyse the impact of COVID-19 pandemics on CVD outcomes in Belo Horizonte (BH), the sixth greater capital city in Brazil, including: mortality, mortality at home, hospitalizations, intensive care unit utilization, and in-hospital mortality; and the differential effect according to sex, age range, social vulnerability, and pandemic’s phase. Methods: Ecological study analysing data from the Mortality and Hospital Information System of BH residents aged ≥30 years. CVD was defined as in Chapter IX from ICD-10. Social vulnerability was classified by a composite socioeconomic index as high, medium and low. The observed age-standardized rates for epidemiological weeks 10–48, 2020, were compared to the expected rates (mean of 2015–2019). Risk ratios (RiR) were analysed and 95% confidence intervals were calculated for all estimates. Population projected to 2020 for BH and its census tracts were used to calculate rates. Results: We found no changes in CVD mortality rates (RiR 1.01, 95%CI 0.96–1.06). However, CVD deaths occurred more at homes (RiR 1.32, 95%CI 1.20–1.46) than in hospitals (RiR 0.89, 95%CI 0.79–0.99), as a result of a substantial decline in hospitalization rates, even though proportional in-hospital deaths increased. The rise in home deaths was greater in older adults and in had an increasing gradient in those more socially vulnerable (RiR 1.45); for high (RiR 1.45), medium (RiR 1.32) and low vulnerability (RiR 1.21). Conclusion: The greater occurrence of CVD deaths at home, in parallel with lower hospitalization rates, suggests that CVD care was disrupted during the COVID-19 pandemics, which more adversely affected older and more socially vulnerable individuals, exacerbating health inequities in BH.

The COVID-19 pandemic may indirectly impact hospitalizations for other natural causes. Belo Horizonte is a city with 2.5 million inhabitants in Brazil, one of the most hardly-hit countries by the pandemic, where local authorities monitored hospitalizations daily to guide regulatory measures. In an ecological, time-series study, we investigated how the pandemic impacted the number and severity of public hospitalizations by other natural causes in the city, during 2020. We assessed the number and proportion of intensive care unit (ICU) admissions and in-hospital deaths for all-natural causes, COVID-19, non-COVID-19 natural causes, and four disease groups: infectious, respiratory, cardiovascular, and neoplasms. Observed data from epidemiological week (EW) 9 (first diagnosis of COVID-19) to EW 48, 2020, was compared to the mean for the same EW of 2015–2019 and differences were tested by Wilcoxon rank-sum test. The five-week moving averages of the studied variables in 2020 were compared to that of 2015–2019 to describe the influence of regulatory measures on the indicators. During the studied period, there was 54,722 hospitalizations by non-COVID-19 natural causes, representing a 28% decline compared to the previous five years (p

Rheumatic Heart Disease Educational Strategies Introduction: The burden of rheumatic heart disease (RHD) is still high in Brazil. Lack of population awareness about the disease limits the efficacy of prevention programs. We aimed to evaluate the effectiveness of education on RHD in schools, comparing the conventional expository teaching method with tablet-based worked examples. Method: A prospective, cluster randomized trial was conducted over eight months in six randomly selected low-income Brazilian public schools. Each class was considered a cluster (total: 90), being randomized 1:1 to receive one of the educational methods. Pre-test evaluated students’ prior knowledge on RHD. Post-tests, 10 days, and three months later, evaluated retention of knowledge. Results: At total 1,301 students (52% female) completed the study, being 63% from high school. Baseline knowledge about RHD was universally low (average score expository classes [G1] 33.9% vs. worked examples [G2] 32.5%, p = 0.23). A significant but similar improvement was observed in both groups in the immediate post-test (pre- vs. post: p < 0.001): G1 57.5% vs. G2 56.7%, p = 0.69. In the late post-test, a significant 20% worsening was observed in both groups and the final scores were again similar: G1 45.0% vs. G2 45.9%, p = 0.87. Highschool students had higher scores (p < 0.001), and girls had better overall performances than boys (p < 0.001). Conclusion: The novel technology of tablet-based worked examples had similar results compared with expository classes for RHD education in schools. Both educational processes resulted in modest gains in knowledge, with low retention. More studies are needed to determine if increased knowledge leads to behavioral changes that could reduce RHD burden. Highlights: In a cluster-randomized trial, two different educational strategies about Rheumatic Heart Disease (RHD) for children – standard expository classes and worked examples based on interactive modules in tablet computers – were compared in public schools of underserved Brazilian neighborhoods. Baseline knowledge was low, and the novel tablet-based technology had similar results compared with traditional teaching for RHD education in schools, with no differences in acquisition and mid-term retention of knowledge. Both educational interventions resulted in similar 71% improvement in the immediate post-test, although with suboptimal retention, with over 20% worsening in three months in both groups. Our data suggests that the optimal strategy for RHD education is yet to be determined, and future studies should be warranted to determine if increased knowledge leads to behavioral changes that could reduce disease burden in endemic areas.

BackgroundWorldwide, it is estimated that over 6 million people are infected with Chagas disease (ChD). It is a neglected disease that can lead to severe heart conditions in its chronic phase. While early treatment can avoid complications, the early-stage detection rate is low. We explore the use of deep neural networks to detect ChD from electrocardiograms (ECGs) to aid in the early detection of the disease.MethodsWe employ a convolutional neural network model that uses 12-lead ECG data to compute the probability of a ChD diagnosis. Our model is developed using two datasets which jointly comprise over two million entries from Brazilian patients: The SaMi-Trop study focusing on ChD patients, enriched with data from the CODE study from the general population. The model's performance is evaluated on two external datasets: the REDS-II, a study focused on ChD with 631 patients, and the ELSA-Brasil study, with 13,739 civil servant patients.FindingsEvaluating our model, we obtain an AUC-ROC of 0.80 (CI 95% 0.79-0.82) for the validation set (samples from CODE and SaMi-Trop), and in external validation datasets: 0.68 (CI 95% 0.63-0.71) for REDS-II and 0.59 (CI 95% 0.56-0.63) for ELSA-Brasil. In the latter, we report a sensitivity of 0.52 (CI 95% 0.47-0.57) and 0.36 (CI 95% 0.30-0.42) and a specificity of 0.77 (CI 95% 0.72-0.81) and 0.76 (CI 95% 0.75-0.77), respectively. Additionally, when considering only patients with Chagas cardiomyopathy as positive, the model achieved an AUC-ROC of 0.82 (CI 95% 0.77-0.86) for REDS-II and 0.77 (CI 95% 0.68-0.85) for ELSA-Brasil.InterpretationThe neural network detects chronic Chagas cardiomyopathy (CCC) from ECG-with weaker performance for early-stage cases. Future work should focus on curating large higher-quality datasets. The CODE dataset, our largest development dataset includes self-reported and therefore less reliable labels, limiting performance for non-CCC patients. Our findings can improve ChD detection and treatment, particularly in high-prevalence areas.

The COVID-19 pandemic may indirectly impact hospitalizations for other natural causes. Belo Horizonte is a city with 2.5 million inhabitants in Brazil, one of the most hardly-hit countries by the pandemic, where local authorities monitored hospitalizations daily to guide regulatory measures. In an ecological, time-series study, we investigated how the pandemic impacted the number and severity of public hospitalizations by other natural causes in the city, during 2020. We assessed the number and proportion of intensive care unit (ICU) admissions and in-hospital deaths for all-natural causes, COVID-19, non-COVID-19 natural causes, and four disease groups: infectious, respiratory, cardiovascular, and neoplasms. Observed data from epidemiological week (EW) 9 (first diagnosis of COVID-19) to EW 48, 2020, was compared to the mean for the same EW of 2015-2019 and differences were tested by Wilcoxon rank-sum test. The five-week moving averages of the studied variables in 2020 were compared to that of 2015-2019 to describe the influence of regulatory measures on the indicators. During the studied period, there was 54,722 hospitalizations by non-COVID-19 natural causes, representing a 28% decline compared to the previous five years (p