BackgroundCardiovascular disease is the leading cause of mortality worldwide, accounting for 13%-15% of all deaths. Cardiac rehabilitation has poor compliance and adherence. Telerehabilitation has been introduced to increase patients’ participation, access, and adherence with the help of digital technologies. The target group is patients with heart failure. A telerehabilitation program called “Future Patient” has been developed and consists of three phases: (1) titration of medicine (0-3 months), (2) implementation of the telerehabilitation protocols (3 months), and (3) follow-up with rehabilitation in everyday life (6 months). Patients in the Future Patient program measure their blood pressure, pulse, weight, number of steps taken, sleep, and respiration and answer questions online regarding their well-being. All data are transmitted and accessed in the HeartPortal by patients and health care professionals.ObjectiveThe aim of this paper is to describe the research design, outcome measures, and data collection techniques in the clinical test of the Future Patient Telerehabilitation Program for patients with heart failure.MethodsA randomized controlled study will be performed. The intervention group will follow the Future Patient Telerehabilitation program, and the control group will follow the traditional cardiac rehabilitation program. The primary outcome is quality of life measured by the Kansas City Cardiomyopathy Questionnaire. Secondary outcomes are development of clinical data; illness perception; motivation; anxiety and depression; health and electronic health literacy; qualitative exploration of patients’, spouses’, and health care professionals’ experiences of participating in the telerehabilitation program; and a health economy evaluation of the program. Outcomes were assessed using questionnaires and through the data generated by digital technologies.ResultsData collection began in December 2016 and will be completed in October 2019. The study results will be published in peer-reviewed journals and presented at international conferences. Results from the Future Patient Telerehabilitation program are expected to be published by the spring of 2020.ConclusionsThe expected outcomes are increased quality of life, increased motivation and illness perception, reduced anxiety and depressions, improved electronic health literacy, and health economics benefits. We expect the study to have a clinical impact for future telerehabilitation of patients with heart failure.Trial RegistrationClinicalTrials.gov NCT03388918; https://clinicaltrials.gov/ct2/show/NCT03388918International Registered Report Identifier (IRRID)DERR1-10.2196/14517

Background Atrial fibrillation (AF) is the most common cardiac arrhythmia and is predicted to more than double in prevalence over the next 20 years. Tailored patient education is recommended as an important aspect of AF care. Current guidelines emphasize that patients become more active participants in the management of their own disease, yet there are no rehabilitation programs for patients with AF in the Danish health care system. Through participatory design, we developed the Future Patient Telerehabilitation (TR) Programs, A and B, for patients with AF. The 2 programs are based on HeartPortal and remote monitoring, together with educational modules. Objective The aim of this pilot study is to evaluate and compare the feasibility of the 2 programs of TR for patients with AF. Methods This pilot study was conducted between December 2019 and March 2020. The pilot study consisted of testing the 2 TR programs, A and B, in two phases: (1) treatment at the AF clinic and (2) TR at home. The primary outcome of the study was the usability of technologies for self-monitoring and the context of the TR programs as seen from patients’ perspectives. Secondary outcomes were the development of patients’ knowledge of AF, development of clinical data, and understanding the expectations and experiences of patients and spouses. Data were collected through interviews, questionnaires, and clinical measurements from home monitoring devices. Statistical analyses were performed using the IBM SPSS Statistics version 26. Qualitative data were analyzed using NVivo 12.0. Results Through interviews, patients articulated the following themes about participating in a TR program: usefulness of the HeartPortal, feeling more secure living with AF, community of practice living with AF, and measuring heart rhythm makes good sense. Through interviews, the spouses of patients with AF expressed that they had gained increased knowledge about AF and how to support their spouses living with AF in everyday life. Results from the responses to the Jessa AF Knowledge Questionnaire support the qualitative data, as they showed that patients in program B acquired increased knowledge about AF at follow-up compared with baseline. No significant differences were found in the number of electrocardiography recordings between the 2 groups. Conclusions Patients with AF and their spouses were positive about the TR program and they found the TR program useful, especially because it created an increased sense of security, knowledge about mastering their symptoms, and a community of practice linking patients with AF and their spouses and health care personnel. To assess all the benefits of the Future Patient–TR Program for patients with AF, it needs to be tested in a comprehensive randomized controlled trial. Trial Registration ClinicalTrials.gov NCT04493437; https://clinicaltrials.gov/ct2/show/NCT04493437.

Background: eHealth literacy (eHL) may be an important factor in the adoption of telerehabilitation. However, little is known about how telerehabilitation affects patients' eHL. The current study evaluated changes over time in eHL for heart failure (HF) patients in a telerehabilitation program (the Future Patient Program) compared to a traditional rehabilitation program. Methods: As part of a randomized controlled trial comparing telerehabilitation with traditional rehabilitation, 137 HF patients completed the eHealth Literacy Questionnaire (eHLQ) at 6 and 12 months of their respective rehabilitation programs.Results: At 6 months, the telerehabilitation group indicated higher levels of 'using technology to process health information' and 'motivated to engage with digital services'. This difference was consistent over time, and we found no other differences between groups or over time with regard to eHL.Conclusions: Providing a digital toolbox for processing health information to HF patients may aid in increasing their eHL, motivation, and ability to engage with digital services in HF patients. Especially, if the technology is designed to support patient needs in terms of the educational content of the program.Preferably technology should be provided early on in the rehabilitation process to ensure optimal outcome.Trial Registration: The study was registered in ClinicalTrials.gov (NCT03388918).

Background Physical activity has been shown to decrease cardiovascular mortality and morbidity. Walking, a simple physical activity which is an integral part of daily life, is a feasible and safe activity for patients with heart failure (HF). A step counter, measuring daily walking activity, might be a motivational factor for increased activity. Objective The aim of this study was to examine the association between walking activity and demographical and clinical data of patients with HF, and whether these associations could be used as predictors of walking activity. Methods A total of 65 patients with HF from the Future Patient Telerehabilitation (FPT) program were included in this study. The patients monitored their daily activity using a Fitbit step counter for 1 year. This monitoring allowed for continuous and safe data transmission of self-monitored activity data. Results A higher walking activity was associated with younger age, lower New York Heart Association (NYHA) classification, and higher ejection fraction (EF). There was a statistically significant correlation between the number of daily steps and NYHA classification at baseline (P=.01), between the increase in daily steps and EF at baseline (P<.001), and between the increase in daily steps and improvement in EF (P=.005). The patients’ demographic, clinical, and activity data could predict 81% of the variation in daily steps. Conclusions This study demonstrated an association between demographic, clinical, and activity data for patients with HF that could predict daily steps. A step counter can thus be a useful tool to help patients monitor their own physical activity. Trial Registration ClinicalTrials.gov NCT03388918; https://clinicaltrials.gov/ct2/show/NCT03388918 International Registered Report Identifier (IRRID) RR2-10.2196/14517

The Multi-Ethnic Study of Atherosclerosis (MESA), begun in 2000, was the first large cohort study to incorporate cardiovascular magnetic resonance (CMR) to study the mechanisms of cardiovascular disease in over 5,000 initially asymptomatic participants, and there is now a wealth of follow-up data over 20 years. However, the imaging technology used to generate the CMR images is no longer in routine use, and methods trained on modern data fail when applied to such legacy datasets. This study aimed to develop a fully automated CMR analysis pipeline that leverages the ability of machine learning algorithms to enable extraction of additional information from such a large-scale legacy dataset, expanding on the original manual analyses. We combined the original study analyses with new annotations to develop a set of automated methods for customizing 3D left ventricular (LV) shape models to each CMR exam and build a statistical shape atlas. We trained VGGNet convolutional neural networks using a transfer learning sequence between two-chamber, four-chamber, and short-axis MRI views to detect landmarks. A U-Net architecture was used to detect the endocardial and epicardial boundaries in short-axis images. The landmark detection network accurately predicted mitral valve and right ventricular insertion points with average error distance &lt;2.5 mm. The agreement of the network with two observers was excellent (intraclass correlation coefficient &gt;0.9). The segmentation network produced average Dice score of 0.9 for both myocardium and LV cavity. Differences between the manual and automated analyses were small, i.e., &lt;1.0 ± 2.6 mL/m2 for indexed LV volume, 3.0 ± 6.4 g/m2 for indexed LV mass, and 0.6 ± 3.3% for ejection fraction. In an independent atlas validation dataset, the LV atlas built from the fully automated pipeline showed similar statistical relationships to an atlas built from the manual analysis. Hence, the proposed pipeline is not only a promising framework to automatically assess additional measures of ventricular function, but also to study relationships between cardiac morphologies and future cardiac events, in a large-scale population study.