Compliance Challenges in a Longitudinal COVID-19 Cohort Using Wearables for Continuous Monitoring: Observational Study.

BACKGROUND: The WEAICOR (Wearables to Investigate the Long Term Cardiovascular and Behavioral Impacts of COVID-19) study was a prospective observational study that used continuous monitoring to detect and analyze biometrics. Compliance to wearables was a major challenge when conducting the study and was crucial for the results. OBJECTIVE: The aim of this study was to evaluate patients' compliance to wearable wristbands and determinants of compliance in a prospective COVID-19 cohort. METHODS: The Biostrap (Biostrap USA LLC) wearable device was used to monitor participants' biometric data. Compliance was calculated by dividing the total number of days in which transmissions were sent by the total number of days spent in the WEAICOR study. Univariate correlation analyses were performed, with compliance and days spent in the study as dependent variables and age, BMI, sex, symptom severity, and the number of complications or comorbidities as independent variables. Multivariate linear regression was then performed, with days spent in the study as a dependent variable, to assess the power of different parameters in determining the number of days patients spent in the study. RESULTS: A total of 122 patients were included in this study. Patients were on average aged 41.32 years, and 46 (38%) were female. Age was found to correlate with compliance (r=0.23; P=.01). In addition, age (r=0.30; P=.001), BMI (r=0.19; P=.03), and the severity of symptoms (r=0.19; P=.03) were found to correlate with days spent in the WEAICOR study. Per our multivariate analysis, in which days spent in the study was a dependent variable, only increased age was a significant determinant of compliance with wearables (adjusted R2=0.1; ß=1.6; P=.01). CONCLUSIONS: Compliance is a major obstacle in remote monitoring studies, and the reasons for a lack of compliance are multifactorial. Patient factors such as age, in addition to environmental factors, can affect compliance to wearables.

Studying the Effect of Long COVID-19 Infection on Sleep Quality Using Wearable Health Devices: Observational Study.

BACKGROUND: Patients with COVID-19 have increased sleep disturbances and decreased sleep quality during and after the infection. The current published literature focuses mainly on qualitative analyses based on surveys and subjective measurements rather than quantitative data. OBJECTIVE: In this paper, we assessed the long-term effects of COVID-19 through sleep patterns from continuous signals collected via wearable wristbands. METHODS: Patients with a history of COVID-19 were compared to a control arm of individuals who never had COVID-19. Baseline demographics were collected for each subject. Linear correlations among the mean duration of each sleep phase and the mean daily biometrics were performed. The average duration for each subject's total sleep time and sleep phases per night was calculated and compared between the 2 groups. RESULTS: This study includes 122 patients with COVID-19 and 588 controls (N=710). Total sleep time was positively correlated with respiratory rate (RR) and oxygen saturation (SpO2). Increased awake sleep phase was correlated with increased heart rate, decreased RR, heart rate variability (HRV), and SpO2. Increased light sleep time was correlated with increased RR and SpO2 in the group with COVID-19. Deep sleep duration was correlated with decreased heart rate as well as increased RR and SpO2. When comparing different sleep phases, patients with long COVID-19 had decreased light sleep (244, SD 67 vs 258, SD 67; P=.003) and decreased deep sleep time (123, SD 66 vs 128, SD 58; P=.02). CONCLUSIONS: Regardless of the demographic background and symptom levels, patients with a history of COVID-19 infection demonstrated altered sleep architecture when compared to matched controls. The sleep of patients with COVID-19 was characterized by decreased total sleep and deep sleep.

A cardiovascular clinic patients' survey to assess challenges and opportunities of digital health adoption during the COVID-19 pandemic.

BACKGROUND: COVID-19 boosted healthcare digitalization and personalization in cardiology. However, understanding patient attitudes and engagement behaviors is essential to achieve successful acceptance and implementation of digital health technologies in personalized care. OBJECTIVE: This study aims to understand current and future trends in wearable device and telemedicine use in the cardiology clinic patient population, recognize patients' attitude towards digital health before and after COVID-19, and identify potential socioeconomic and racial/ethnic differences in adoption of digital health tools in a New Orleans patient population. METHODS: A cross-sectional survey was distributed to Tulane Cardiology Clinic patients between September 2020 and January 2021. Basic demographic information, medical comorbidities, device usage, and opinions on digital health tools were collected. RESULTS: Survey responses from 299 participants (average age = 54 years, 50.8% female, 24.4% African American) showed that digital health use was more prevalent in younger, healthier, and more educated individuals. Wearable use was also higher among White patients compared to African American patients. Patients cited costs and technology knowledge as primary deterrents for using wearables, despite being more inclined to use wearables for disease monitoring (41%). While wearable use did not increase after COVID-19 (36.6% pre-COVID vs 35.4% post-COVID, P = .77), telemedicine use rose significantly (10.8% pre-COVID vs 24.3% during COVID, P < .0001). Patients mostly noted telemedicine's effectiveness in overcoming difficult healthcare access barriers. Additionally, most patients are in support of wearables and telemedicine either complementing or replacing routine tests and traditional clinical visits. CONCLUSION: Demographic and socioeconomic disparities negatively impact wearable health device and telemedicine adoption within cardiovascular clinic patients. Although telemedicine use increased after COVID-19, this effect was not observed for wearables, reflecting significant economic and digital literacy challenges underlying wearable acceptance.