ABSTRACT
Aims: Urbanization is related to non-communicable diseases such as congestive heart failure (CHF). Understanding the influence of diverse living environments on physiological variables such as heart rate variability (HRV) in patients with chronic cardiac disease may contribute to more effective lifestyle advice and telerehabilitation strategies. This study explores how machine learning (ML) models can predict HRV metrics, which measure autonomic nervous system responses to environmental attributes in uncontrolled real-world settings. The goal is to validate whether this approach can ascertain and quantify the connection between environmental attributes and cardiac autonomic response in patients with CHF. Methods and results: A total of 20 participants (10 healthy individuals and 10 patients with CHF) wore smartwatches for 3 weeks, recording activities, locations, and heart rate (HR). Environmental attributes were extracted from Google Street View images. Machine learning models were trained and tested on the data to predict HRV metrics. The models were evaluated using Spearman's correlation, root mean square error, prediction intervals, and Bland-Altman analysis. Machine learning models predicted HRV metrics related to vagal activity well (R > 0.8 for HR; 0.8 > R > 0.5 for the root mean square of successive interbeat interval differences and the Poincaré plot standard deviation perpendicular to the line of identity; 0.5 > R > 0.4 for the high frequency power and the ratio of the absolute low- and high frequency power induced by environmental attributes. However, they struggled with metrics related to overall autonomic activity, due to the complex balance between sympathetic and parasympathetic modulation. Conclusion: This study highlights the potential of ML-based models to discern vagal dynamics influenced by living environments in healthy individuals and patients diagnosed with CHF. Ultimately, this strategy could offer rehabilitation and tailored lifestyle advice, leading to improved prognosis and enhanced overall patient well-being in CHF.
ABSTRACT
BACKGROUND: Cardiac rehabilitation in patients with chronic heart failure (CHF) has favourable effects on exercise capacity, the risk at hospital (re-)admission and quality of life. Although cardiac rehabilitation is generally recommended it is still under-utilised in daily clinical practice, particularly in frail elderly patients after hospital admission, mainly due to low referral and patient-related barriers. Cardiac telerehabilitation (CTR) has the potential to partially solve these barriers. The purpose of this study is to evaluate the effects of CTR as compared to standard remote care after hospital admission on physical functional capacity in CHF patients. METHODS: In this randomised controlled trial, 64 CHF patients will be recruited during hospitalisation for acute decompensated heart failure, and randomised to CTR combined with remote patient management (RPM) or RPM alone (1:1). All participants will start with RPM after hospital discharge for early detection of deterioration, and will be up titrated to optimal medical therapy before being randomised. CTR will start after randomisation and consists of an 18-week multidisciplinary programme with exercise training by physical and occupational therapists, supported by a (remote) technology-assisted dietary intervention and mental health guiding by a physiologist. The training programme consists of three centre-based and two home-based video exercise training sessions followed by weekly video coaching. The mental health and dietary programme are executed using individual and group video sessions. A wrist-worn device enables remote coaching by the physical therapist. The web application is used for promoting self-management by the following modules: 1) goal setting, 2) progress tracking, 3) education, and 4) video and chat communication. The primary outcome measure is physical functional capacity evaluated by the Short Physical Performance Battery (SPPB) score. Secondary outcome measures include frailty scoring, recovery after submaximal exercise, subjective health status, compliance and acceptance to the rehabilitation programme, and readmission rate. DISCUSSION: The Tele-ADHF trial is the first prospective randomised controlled trial designed for evaluating the effects of a comprehensive combined RPM and CTR programme in recently hospitalised CHF patients. We hypothesize that this intervention has superior effects on physical functional capacity than RPM alone. TRIAL REGISTRATION: Netherlands Trial Registry (NTR) NL9619, registered 21 July 2021.