Novel Trial Design: CHIEF-HF.

BACKGROUND: The expense of clinical trials mandates new strategies to efficiently generate evidence and test novel therapies. In this context, we designed a decentralized, patient-centered randomized clinical trial leveraging mobile technologies, rather than in-person site visits, to test the efficacy of 12 weeks of canagliflozin for the treatment of heart failure, regardless of ejection fraction or diabetes status, on the reduction of heart failure symptoms. METHODS: One thousand nine hundred patients will be enrolled with a medical record-confirmed diagnosis of heart failure, stratified by reduced (≤40%) or preserved (>40%) ejection fraction and randomized 1:1 to 100 mg daily of canagliflozin or matching placebo. The primary outcome will be the 12-week change in the total symptom score of the Kansas City Cardiomyopathy Questionnaire. Secondary outcomes will be daily step count and other scales of the Kansas City Cardiomyopathy Questionnaire. RESULTS: The trial is currently enrolling, even in the era of the coronavirus disease 2019 (COVID-19) pandemic. CONCLUSIONS: CHIEF-HF (Canagliflozin: Impact on Health Status, Quality of Life and Functional Status in Heart Failure) is deploying a novel model of conducting a decentralized, patient-centered, randomized clinical trial for a new indication for canagliflozin to improve the symptoms of patients with heart failure. It can model a new method for more cost-effectively testing the efficacy of treatments using mobile technologies with patient-reported outcomes as the primary clinical end point of the trial. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04252287.

Changes in sleep duration, timing, and variability during the COVID-19 pandemic: Large-scale Fitbit data from 6 major US cities.

The COVID-19 pandemic has resulted in societal-level changes to sleep and other behavioral patterns. Objective data would allow for a greater understanding of sleep-related changes at the population level. About 163,524 active Fitbit users from 6 major US cities contributed data, representing areas particularly hard-hit by the pandemic (Chicago, Houston, Los Angeles, New York, San Francisco, and Miami). Sleep variables extracted include nightly and weekly mean sleep duration and bedtime, and variability (standard deviation) of sleep duration and bedtime. Deviation from similar timeframes in 2018 and 2019 were examined, as were changes in these sleep metrics during the pandemic, relationships to changes in resting heart rate, and changes during re-opening in May and June. Overall, compared to 2019, mean sleep duration in 2020 was higher among nearly all groups, mean sleep phase shifted later for nearly all groups, and mean sleep duration and bedtime variability decreased for nearly all groups (owing to decreased weekday-weekend differences). Over the course of January to April 2020, mean sleep duration increased, mean bedtime shifted later, and mean sleep duration variability decreased. Changes in observed resting heart rate correlated positively with changes in sleep and negatively with activity levels. In later months (May and June), many of these changes started to drift back to historical norms.

Validity of a Novel Research-Grade Physical Activity and Sleep Monitor for Continuous Remote Patient Monitoring.

In the midst of the COVID-19 pandemic, Remote Patient Monitoring technologies are highly important for clinicians and researchers. These connected-health technologies enable monitoring of patients and facilitate remote clinical trial research while reducing the potential for the spread of the novel coronavirus. There is a growing requirement for monitoring of the full 24 h spectrum of behaviours with a single research-grade sensor. This research describes a free-living and supervised protocol comparison study of the Verisense inertial measurement unit to assess physical activity and sleep parameters and compares it with the Actiwatch 2 actigraph. Fifteen adults (11 males, 23.4 ± 3.4 years and 4 females, 29 ± 12.6 years) wore both monitors for 2 consecutive days and nights in the free-living study while twelve adults (11 males, 23.4 ± 3.4 years and 1 female, 22 ± 0 years) wore both monitors for the duration of a gym-based supervised protocol study. Agreement of physical activity epoch-by-epoch data with activity classification of sedentary, light and moderate-to-vigorous activity and sleep metrics were evaluated using Spearman's rank-order correlation coefficients and Bland-Altman plots. For all activity, Verisense showed high agreement for both free-living and supervised protocol of r = 0.85 and r = 0.78, respectively. For physical activity classification, Verisense showed high agreement of sedentary activity of r = 0.72 for free-living but low agreement of r = 0.36 for supervised protocol; low agreement of light activity of r = 0.42 for free-living and negligible agreement of r = -0.04 for supervised protocol; and moderate agreement of moderate-to-vigorous activity of r = 0.52 for free-living with low agreement of r = 0.49 for supervised protocol. For sleep metrics, Verisense showed moderate agreement for sleep time and total sleep time of r = 0.66 and 0.54, respectively, but demonstrated high agreement for determination of wake time of r = 0.83. Overall, our results showed moderate-high agreement of Verisense with Actiwatch 2 for assessing epoch-by-epoch physical activity and sleep, but a lack of agreement for activity classifications. Future validation work of Verisense for activity cut-point potentially holds promise for 24 h continuous remote patient monitoring.