Remote physiologic monitoring (RPM) of heart failure (HF) patients with a virtual platform is well established in adult care. However, this technology remains untested in pediatrics and care continues to rely on a hospital-based model which presents challenges in providing equitable access to care for those with lower socio-economic status or living remotely. Telemonitoring technology tailored for children with machine-based algorithms to predict deterioration is needed to facilitate the equitable provision of safe, home-based care, especially in vulnerable populations.

This study will enroll 100 pediatric outpatients with or at risk of deteriorating HF from 4 tertiary pediatric heart failure care centres in Canada. We will use a wearable Bluetooth enabled textile (Skiin device), developed by Myant Inc (Toronto, ON), that can monitor heart rate, heart rhythm, respiratory rate and activity, together with additional home-based monitoring of blood pressure (BP), oxygen saturations and weight. The smart textile will be paired to an RPM platform, SphygmoTM (mmHG Inc).

The goal of this project is to assess the feasibility and acceptability of RPM in pediatrics and validate a RPM-based risk prediction model for pediatric HF patients.

Remote physiologic monitoring (RPM) refers to utilizing non-invasive medical devices to obtain physiologic data, such as pulse oximetry, blood pressure, weight, and electrocardiography at home. Recent advances in RPM have facilitated improved home-based care, reduced hospitalizations, and improved quality of life in adult heart failure populations. Additionally, the integration of multiple physiologic variables acquired through remote physiologic monitoring into machine learning algorithms has been shown to predict hospitalization for heart failure. Previous paediatric studies have demonstrated the utility of incorporating multiple physiologic variables into risk prediction algorithms for cardiac events. This is particularly important in heart failure cohorts where limits of acceptability are often nuanced and patient specific. The use of multiple physiologic parameters creates a more comprehensive insight into the complex pathophysiologic changes in heart failure.

However, the use of RPM devices in children remains limited due to a lack of validated devices and uncertainty about the acceptability and uptake of such interventions. This is partly due to challenges developing devices that can be easily applied, and digital platforms suited to the wider range and variability in body sizes and physiologic parameters. Thus, care of children with heart failure continues to rely on hospital-based models, where tertiary heart failure centers serve large geographically and socio-economically diverse populations. A validated paediatric virtual home monitoring system using RPM to predict clinical deterioration could safely facilitate earlier discharge, reduce the need for outpatient hospital visits, and potentially improve outcomes while minimizing family social disruption and school absence.

The overarching goal of this project is to assess the feasibility of RPM in paediatrics and validate a RPM based risk prediction model for paediatric patients with or at-risk of heart failure, with a view to facilitating safe home-based care across geographically and socially diverse urban, rural, and remote communities. To achieve this goal, this study proposes to utilize a wearable Bluetooth enabled textile (Skiin Device) that can monitor heart rate and rhythm, respiratory rate and activity, together with additional home-based monitoring of blood pressure, oxygen saturations and weight. The textile, developed by Myant (Toronto, ON) has completed pilot testing at SickKids to assess its validity in an outpatient setting (NCT04305340). The Skiin textile will be paired to its software solution, the Myant Health Platform (MHP), which comprises the Skiin Connected Life App (phone application), the Myant Back End (cloud storage of data) and the Myant Virtual Clinical Portal (internet browser visualization of data collected). The Skiin Connected Life App will be used for collection of ECG, heart rate, body temperature, and physical activity throughout the day, and can generate the following average metric for each night when the device is used: resting heart rate, respiratory rate, resting heart rate variability, sleep duration, body temperature.

The MHP will be paired with another RPM platform, SphygmoTM (mmHG Inc). The Sphygmo™ platform consists of a smartphone App (Android, iOS), which can be linked with Bluetooth-compatible devices for automated uploading of measurements to a clinician portal. This platform, originally developed for adults, has the ability to connect with blood pressure, heart rate, weight, and oxygen saturation devices. This platform will be used for collection of additional physiologic data as above and is currently under study at Stollery Children's Hospital. The two systems will have a single-sign on feature allowing their integrated use by the patient, their families, and the research team. We will leverage descriptive and predictive analytics to augment clinician monitoring by defining trajectories and longitudinally predicting risk of key adverse outcomes.

Study Objectives Primary Objectives

1. To investigate the feasibility of a remote physiological monitor using a textile smart garment (Skiin devices) using the Skiin Connected Life App along with additional standard home monitoring tools (BP monitor, weigh scales) that are paired with a Bluetooth enabled app (SphygmoTM)
2. To test the acceptability of a remote physiological monitor using a textile smart garment (Skiin devices) along with the acceptability of a Bluetooth enabled app (SphygmoTM)

Secondary Objectives

1. To leverage analytical methods to develop descriptive and predictive tools using RPM that augment detection of clinical deterioration in pediatric patients as measured by admission, adverse cardiac events and patient reported outcomes within 6-months post intervention.

Study Duration: Patients will be recruited over a 2-year period.

Inclusion Criteria:

• Patients from 8-18 years of age who are outpatients at time of study enrollment.
• Patients with a chest size of at least 69.85 cm in perimeter/circumference (as measured under the pectoral muscles)
• Patients at-risk for heart failure and with American Heart Association (AHA) Stage B-D Heart Failure will be included in this study irrespective of heart failure medication use.
• HF etiologies include: congenital cardiac malformation with systemic ventricular systolic dysfunction, idiopathic cardiomyopathy, familial/inherited and/or genetic cardiomyopathy, history of myocarditis with persistent ventricular dysfunction, neuromuscular disorder, inborn error of metabolism, mitochondrial disorder, acquired (chemotherapy, iatrogenic, infection, rheumatic, or nutritional), ischemic (e.g., Kawasaki disease and post-operative HF), and left ventricular non-compaction, restrictive cardiomyopathy and HCM with systolic or diastolic dysfunction.

Exclusion Criteria:

• Patients within 3 months of a surgery.
• Patients supported by ventricular assist device at study onset.
• Inability to use technology due to physical or cognitive impairment in the patient or caregiver.
• Non-English speaking.
• Patients who have an implantable cardiac defibrillator or pacemaker
• Patients whose chest size is too large or small to fit available sizes of the Skiin device.

This study will enroll 100 paediatric outpatients (8 to 18 years old) with diagnosis of cardiomyopathy (with systolic or diastolic dysfunction), subjects with congenital heart disease with biventricular or univentricular physiology plus systemic ventricular dysfunction from 4 tertiary heart failure care centres.

To protect participant privacy and confidentiality, no IPD will be shared. Only group trends will be reported.