Background Chagas disease is a neglected and preventable tropical disease that causes significant cardiac morbidity and mortality in Latin America. Our objective in this study was to describe cardiac findings among inhabitants of rural communities of the Bolivian Chaco. Methods The cardiac study drew participants from an epidemiologic study in 7 indigenous Guarani communities. All infected participants 10 years or older were asked to undergo a brief physical examination and 12-lead electrocardiogram. A subset had echocardiograms (ECGs). ECGs and echocardiograms were read by one or more cardiologists. Results Of 1137 residents 10 years or older, 753 (66.2%) had T. cruzi infection. Cardiac evaluations were performed for 398 infected participants 10 years or older. Fifty-five (13.8%) participants had one or more ECG abnormality suggestive of Chagas cardiomyopathy. The most frequent abnormalities were bundle branch blocks in 42 (11.3%), followed by rhythm disturbances or ventricular ectopy in 13 (3.3%) and atrioventricular blocks (AVB) in 10 (2.6%) participants. The prevalence of any abnormality rose from 1.1% among those 10-19 years old to 14.2%, 17.3% and 26.4% among those 20-39, 40-59 and older than 60 years, respectively. First degree AVB was seen most frequently in participants 60 years or older, but the 4 patients with 3rd degree AVB were all under 50 years old. Eighteen and two participants had a left ventricular ejection fraction of 40-54% and <40%, respectively. An increasing number of ECG abnormalities was associated with progressively larger left ventricular end-diastolic dimensions and lower left ventricular ejection fraction. Conclusions We found a high prevalence of ECG abnormalities and substantial evidence of Chagas cardiomyopathy. Programs to improve access to basic cardiac care (annual ECGs, antiarrhythmics, pacemakers) could have an immediate impact on morbidity and mortality in these highly endemic communities.

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The phenomenon of non-linearity is the main problem of a DC motor and optimum performance cannot be obtained by the calculation of the controller's parameters using conventional methods. However, a DC motor is considered an extremely common device by the low-cost and effective dynamic response in various applications. Thus, it has been a subject for research studies to take advantage of its maximum performance. This manuscript proposes an experimental methodology that consists of the following: The DC motor's characterization method for finding the ideal frequency. The design of the Firmware-based Pulse Width Modulation (PWM) generating module and the P, PD, PID controller's implementation in an own FPGA-based programmable microprocessor to obtain almost the same performance as a servo-amplifier commercial of direct-drive. The PWM is a technique widely used to regulate the speed of rotation of a DC motor, in this case, the duty cycle of the PWM is used to provide the torque necessary to the mechanics of the system in order to look for a linear relationship but using the right frequency of the characterized DC motor. Finally, based on a built prototype of a micro-positioning system using the characterized motors, and the mathematical model, in both cases the three controllers were applied in order to establish the comparison between the responses, seeking to observe if the experimental results show a great difference with respect to the simulation results. The main aim of this study is to show that the proposed methodology works. However, since there was no significant difference in both results, motors used in the closed-loop control present approximately the same linear response as that of the motor model used in the simulation.

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Background The COVID-19 pandemic has collapsed the health system, making it necessary to identify factors that help to predict and stratify the risk of patients on admission. Many factors have been used in clinical practice, but the scientific evidence available to date is limited. Purpose The objective of this study was to identify clinical and analytical predictors of 30-day mortality in SARS-CoV- 2 infection. Methods A total of 1708 consecutive patients hospitalized in our centre between 18th and 23rd March 2020 and 22nd August and 9th January 2021 with a confirmed microbiological diagnosis of COVID-19 by PCR were prospectively included. Cox regression analysis was performed to assess whether sex and race, smoking habit, chronic kidney disease, D-dimer, heart disease (defined as a history of acute myocardial infarction, heart failure, atrial fibrillation) and troponin at admission (cTnI levels greater than the 99th percentile of a healthy population) were related to the 30-day mortality of these patients. Results Baseline characteristic are shown in the table 1. Median hospital length of stay was 9 days (IQR 5 to 16). A total of 338 patients (19.8%) died within 30 days and 153 (9.0%) were admitted to the ICU. Furthermore, 52.1% of patients developed ARDS and 9.3% required non-invasive ventilation. A troponin at admission greater than the 99th percentile of a healthy population (HR 1.9, 95% CI 1.4–2.5, p&lt;0.001) and a Charlson Comorbidity Index above 4 (HR 2.6, 95% CI 1.9–3.6, p&lt;0.001) were independent predictors of 30-day mortality in patients admitted due to COVID- 19 infection. Conclusions At admission time, troponin values and patient comorbidity (Charlson Comorbidity Index ≥4) can be useful as prognostic markers of SARS-CoV-2 infection. FUNDunding Acknowledgement Type of funding sources: Public hospital(s). Main funding source(s): Hospital Ramon y Cajal