Remote monitoring platforms based on advanced health sensors have the potential to become important tools during the COVID-19 pandemic, supporting the reduction in risks for affected populations such as the elderly. Current commercially available wearable devices still have limitations to deal with heart rate variability (HRV), an important health indicator of human aging. This study analyzes the role of a remote monitoring system designed to support health services to older people during the complete course of the COVID-19 pandemic in Brazil, since its beginning in Brazil in March 2020 until November 2021, based on HRV. Using different levels of analysis and data, we validated HRV parameters by comparing them with reference sensors and tools in HRV measurements. We compared the results obtained for the cardiac modulation data in time domain using samples of 10 elderly people’s HRV data from Fitbit Inspire HR with the results provided by Kubios for the same population using a cardiac belt, with the data divided into train and test, where 75% of the data were used for training the models, with the remaining 25% as a test set for evaluating the final performance of the models. The results show that there is very little difference between the results obtained by the remote monitoring system compared with Kubios, indicating that the data obtained from these devices might provide accurate results in evaluating HRV in comparison with gold standard devices. We conclude that the application of the methods and techniques used and reported in this study are useful for the creation and validation of HRV indicators in time series obtained by means of wearable devices based on photoplethysmography sensors; therefore, they can be incorporated into remote monitoring processes as seen during the pandemic.

Introduction Sarcopenia is a highly prevalent muscle dysfunction among older adults and is associated with adverse events. The periodic monitoring enables an early screening of patients at risk and control of the progression of muscle impairment. Wearable devices have been used as clinical support for sarcopenia detection. Therefore, this review aims to identify how wearable devices have been used to screen sarcopenia. Methods and analyses Searches will be conducted from August 2023 on PubMed, CINHAL, Embase, Web of Science and SciELO databases. We will include cross-sectional and/or baseline data from prospective studies reporting the use of wearable devices to investigate sarcopenia. Studies that discuss only the development of algorithms or applications for the assessment of sarcopenia or unavailable full texts will be excluded. The main reviewer will conduct the initial search and exclusion of duplicates, while two independent reviewers will select studies, extract data and assess the methodological quality using the Appraisal tool for Cross-sectional Studies. Ethics and dissemination No previous ethical approval is required for this review. The findings of this review will be submitted to a scientific journal and disclosed at international scientific conferences. PROSPERO registration number CRD42022356040.

BACKGROUND Countries have focused research on developing strategies to fight COVID-19, prevent hospitalizations, and maintain economic activities. OBJECTIVE This study aimed to establish a survival analysis and identify risk factors for patients with COVID-19 in a upper middle-income city in Brazil. METHODS We performed a retrospective cohort study with 280 hospitalized patients with COVID-19. The eCOVID platform provided data used to monitor COVID-19 cases and help communication between professionals. RESULTS Survival analysis showed that age ≥ 65 years was associated with decreased survival (54.8%). Females had lower survival rate than males (p=0.01). Regarding risk factors, urea concentration (p<0.001), hospital LOS (p=0.002), oxygen concentration (p=0.005), and age (p=0.02) were associated with death. CONCLUSION Age, hospital LOS, high blood urea concentration, and low oxygen concentration were associated with death by COVID-19 in the studied population. These findings corroborate with studies conducted in research centers worldwide. Key Findings Some parameters assessed during hospital admission may identify patients with COVID-19 with high risk of progressing to severe conditions and early identification of risk factors and continuous monitoring of laboratory tests may prevent progression to severe disease. Key Implications Knowledge regarding main signs and symptoms of COVID-19 and associated risk factors helps the population manage and monitor the disease at home and identify early signs of severity. Also, more information about COVID-19, such as prevalence, specific characteristics in certain regions, and treatments, must become public to encourage the population to participate in the control and contingency of the pandemic.