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
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)
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
- 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.