Monitoring of Cardiovascular Events in Covid 19 Positive Subjects: The Biobeat System

ABSTRACT

Background: Connected health technology can enable healthcare professionals to provide multiple solutions to meet the growing demand of care and control of COVID-19 infected patients, by optimizing economic resources and extending the scope of monitoring beyond the hospital. A connected patient has the ability to monitor his state of health with tools that remotely transmit data to his doctor, help him to perform the right therapy thanks to reminder systems or electronic alerts and identifies cardiovascular alterations predictive of a worsening of the disease. An innovative mobile device, the BioBeat System with an APP that can be downloaded directly to the Smart Phone, is characterized by sensors already validated according to the regulations of the Food and Drug Administration for vital signs, the European Society Hypertension for the detection of blood pressure. Purpose(s) Wearable medical devices and the BioBeat software platform are appropriate for use in different settings for the management of acute, chronic cardiovascular, respiratory and inflammatory pathology, a tool capable of early identification of the instrumental signs of deterioration even before the exclusively clinical recognition that becomes even more difficult if we consider the patients at home. The aim of this study is to test the sensitivity and specificity of the biobeat wearable system applied in patients with paucisymptomatic COVID-19 infection (group A) and in those with previous SARS-COV2 disease discharged from the hospital who still needed post-acute monitoring (group B) and compared with clinical control, managing to determine early the clinical signs of worsening. Method(s) The data recorded by individual patients are systolic and diastolic blood pressure, heart and respiratory rate, peripheral oxygen saturation and body temperature. Thanks to these parameters it is possible to calculate the NEWS by being able to predict any adverse events early with the automatic calculation of the score. The criteria of deterioration or worsening of the clinical condition are represented by the need to hospitalize the patient, alteration of one of the criteria grouped in the ABCDE. Result(s) Table 1 summarises the demographic data of the cases enrolled. We calculated the sensitivity of the methodology related to the alerts detected and the outcome of the patients. Sensitivity was 86.3% with a 95% CI of 0.71 to 1.03 and a specificity of 7.7%. Conclusion(s) Continuous monitoring with biobeat watch showed a high sensitivity in detecting early any alerts predictive of worsening of the disease..