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In a group of patients with chagasic cardiomyopathy, BNP levels correlated with diastolic function patterns regardless of systolic function. The E/E'ratio (inferior wall) was the only isolated parameter of diastolic function that was independently associated with BNP levels.

HRT indices appear to correlate better with EF than SDNN in Chagas disease. Thus, an analysis based on heart rate transient adaptation seems to perform better than HRV in detecting the autonomic alterations that parallel left ventricular dysfunction in Chagas disease patients. The high number of PVCs observed in these patients further support the use of HRT methodology.

Introduction: The acceleration of new cases is important for the characterization and comparison of epidemic curves. The objective of this study was to quantify the acceleration of daily confirmed cases and death curves using the polynomial interpolation method. Methods: Covid-19 epidemic curves from Brazil, Germany, the United States, and Russia were obtained. We calculated the instantaneous acceleration of the curve using the first derivative of the representative polynomial. Results: The acceleration for all curves was obtained. Conclusions: Incorporating acceleration into an analysis of the Covid-19 time series may enable a better understanding of the epidemiological situation.

Introduction: Recently, we demonstrated that the polynomial interpolation method can be used to accurately calculate the daily acceleration of cases and deaths by Covid-19. The acceleration of new cases is important for the characterization and comparison of epidemic curves. The objective of this work is to measure the diversity of epidemic curves and understand the importance of socioeconomic variables in the acceleration, peak cases and deaths by Covid-19 in Brazilian states. Methods: This is an ecological study with time series analysis of new cases and deaths by Covid-19 in Brazil and its 27 federation units. Using the polynomial interpolation method, we calculated the daily cases and deaths with the measurement of the respective acceleration. We calculated the correlation coefficient between the epidemic curve data and socioeconomic data. Results: The combination of daily data and acceleration determined that the states of Brazil are in different stages of the epidemic. Maximum acceleration of peak cases, peak of cases, maximum acceleration of deaths and peak of deaths are associated with the Gini index and population density, but did not correlate with HDI and per capita income. Conclusion: Brazilian states showed heterogeneous data curves. Densitypopulation and socioeconomic inequality are associated with worse control of the epidemic.