Death trends based on autopsy data compared to the beginning of the coronavirus pandemic in Brazil.

The novel Coronavirus disease (COVID-19) is responsible for thousands of deaths worldwide, especially in Brazil, currently one of the leading countries in number of infections and deaths. The beginning of the COVID-19 epidemic in Brazil is uncertain due to the low number of tests done in the country. The excess number of deaths can suggest the beginning of the pandemic in this context. In this article, we used an autoregressive integrated moving average (ARIMA) model to investigate possible excesses in the number of deaths processed by the São Paulo Autopsy Service according to different causes of deaths: all-cause, cardiovascular, and pulmonary causes. We calculated the expected number of deaths using data from 2019 to 2020 (n=17,011), and investigated different seasonal patterns using harmonic dynamic regression with Fourier terms with residuals modeled by an ARIMA method. We did not find any abnormalities in the predicted number of deaths and the real values in the first months of 2020. We found an increase in the number of deaths only by March 20, 2020, right after the first COVID-19 confirmed case in the city of São Paulo, which occurred on March 16, 2020.

Death trends based on autopsy data compared to the beginning of the coronavirus pandemic in Brazil

The novel Coronavirus disease (COVID-19) is responsible for thousands of deaths worldwide, especially in Brazil, currently one of the leading countries in number of infections and deaths. The beginning of the COVID-19 epidemic in Brazil is uncertain due to the low number of tests done in the country. The excess number of deaths can suggest the beginning of the pandemic in this context. In this article, we used an autoregressive integrated moving average (ARIMA) model to investigate possible excesses in the number of deaths processed by the São Paulo Autopsy Service according to different causes of deaths: all-cause, cardiovascular, and pulmonary causes. We calculated the expected number of deaths using data from 2019 to 2020 (n=17,011), and investigated different seasonal patterns using harmonic dynamic regression with Fourier terms with residuals modeled by an ARIMA method. We did not find any abnormalities in the predicted number of deaths and the real values in the first months of 2020. We found an increase in the number of deaths only by March 20, 2020, right after the first COVID-19 confirmed case in the city of São Paulo, which occurred on March 16, 2020.

RAS genes influence exercise-induced left ventricular hypertrophy: an elite athletes study.

PURPOSE: The association of ACE I/D polymorphism with changes in LV mass in response to physical training has been observed, but no association has been found with AT1R A1166C polymorphism. We investigated the ACE I/D, AT1R A1166C, and AT1R CA microsatellite polymorphisms genotype distribution in elite athletes and whether the presence of AT1R C1166 variant, in addition to ACE D allele affects the training-induced LV mass alterations in elite trained athletes. METHODS: The study population comprised 28 healthy players recruited from an Italian elite male soccer team and 155 healthy male subjects. LV mass, LV mass adjusted for body surface area, septal thickness, posterior wall, end-diastolic and end-systolic ventricular dimension, and ejection fraction were determined by echocardiography in pretrained period, at rest and 7 months later during the training. All subjects were genotyped for ACE I/D, AT1R A1166C, and CA microsatellite polymorphisms. RESULTS: Training induced an LV mass increase in all but six athletes. The percentage of athletes in whom an increase of LV mass was found after training was statistically different in relation to the ACE D allele: no increase was observed in three of 24 D allele carriers and in three of four II genotype players (Fisher's exact test, P = 0.02). As AT1R is concerned, no increase was observed in 4 of 15 C allele carriers and in 2 of 13 AA genotype athletes (Fisher's exact test, P > 0.05). The contemporary presence of ACE D and AT1R C allele did not affect the changes after training. No difference has been observed in the CA microsatellite marker allele frequencies between athletes and controls (P = 0.46). CONCLUSION: In this study, we provide the evidence that soccer play does not select athletes on genotype basis. Training-induced LV mass changes in male elite athletes are significantly associated with the presence of ACE D allele, but not of AT1R C allele.