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A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
Published on: April 19, 2019
Using Biosensors and Digital Biomarkers to Assess Response to Cardiac Rehabilitation: Observational Study
Hélène De Cannière1,2, Christophe J P Smeets1,2,3, Melanie Schoutteten1,2
1Mobile Health Unit, Limburg Clinical Research Center (LCRC), Faculty of Medicine and Life Sciences, Hasselt University (UHasselt), Diepenbeek, Belgium.
Insights
Cardiac rehabilitation (CR) response varies among patients. Wearable sensors and digital biomarkers can identify differences in cardiac adaptation to exercise, enabling personalized CR strategies for better outcomes.
Area of Science:
- Cardiology
- Exercise Physiology
- Digital Health
Background:
- Cardiac rehabilitation (CR) improves functional capacity and clinical outcomes in cardiovascular disease management.
- Patient response to CR varies, necessitating a tailored approach for optimal results.
- Understanding individual cardiac adaptation to exercise and identifying digital biomarkers are crucial for personalized CR.
Purpose of the Study:
- To investigate differences in cardiac response between high- and low-response groups in CR based on functional capacity improvement.
- To identify digital biomarkers that reflect cardiac adaptation during exercise in CR patients.
Main Methods:
- 129 CR patients underwent a 6-minute walking test (6MWT) with wearable ECG monitoring at baseline and follow-up.
- Patients were categorized into high- and low-response groups based on functional capacity gains.
- Analysis focused on heart rate parameters and digital biomarkers during the 6MWT and their temporal evolution.
Main Results:
- All patients showed improved functional capacity (P<.001).
- High-response patients exhibited a significant increase in peak heart rate (HRpeak) and recovery heart rate (HRrec) throughout CR, unlike low-response patients.
- Digital biomarkers revealed distinct heart rate behaviors during standardized activity, offering deeper insights into patient cardiac responses.
Conclusions:
- Wearable sensor technology and digital biomarkers can characterize patient response variability in CR.
- These innovative biomarkers provide in-depth insights into cardiac adaptation to exercise during CR.
- Findings support the development of optimized, patient-tailored CR strategies to enhance outcomes.
Background:
Cardiac rehabilitation (CR) is known for its beneficial effects on functional capacity and is a key component within current cardiovascular disease management strategies. In addition, a larger increase in functional capacity is accompanied by better clinical outcomes. However, not all patients respond in a similar way to CR. Therefore, a patient-tailored approach to CR could open up the possibility to achieve an optimal increase in functional capacity in every patient. Before treatment can be optimized, the differences in response of patients in terms of cardiac adaptation to exercise should first be understood. In addition, digital biomarkers to steer CR need to be identified.
Objective:
The aim of the study was to investigate the difference in cardiac response between patients characterized by a clear improvement in functional capacity and patients showing only a minor improvement following CR therapy.
Methods:
A total of 129 patients in CR performed a 6-minute walking test (6MWT) at baseline and during four consecutive short-term follow-up tests while being equipped with a wearable electrocardiogram (ECG) device. The 6MWTs were used to evaluate functional capacity. Patients were divided into high- and low-response groups, based on the improvement in functional capacity during the CR program. Commonly used heart rate parameters and cardiac digital biomarkers representative of the heart rate behavior during the 6MWT and their evolution over time were investigated.
Results:
All participating patients improved in functional capacity throughout the CR program (P<.001). The heart rate parameters, which are commonly used in practice, evolved differently for both groups throughout CR. The peak heart rate (HRpeak) from patients in the high-response group increased significantly throughout CR, while no change was observed in the low-response group (F4,92=8.321, P<.001). Similar results were obtained for the recovery heart rate (HRrec) values, which increased significantly over time during every minute of recuperation, for the high-response group (HRrec1: P<.001, HRrec2: P<.001, HRrec3: P<.001, HRrec4: P<.001, and HRrec5: P=.02). The other digital biomarkers showed that the evolution of heart rate behavior during a standardized activity test differed throughout CR between both groups. These digital biomarkers, derived from the continuous measurements, contribute to more in-depth insight into the progression of patients' cardiac responses.
Conclusions:
This study showed that when using wearable sensor technology, the differences in response of patients to CR can be characterized by means of commonly used heart rate parameters and digital biomarkers that are representative of cardiac response to exercise. These digital biomarkers, derived by innovative analysis techniques, allow for more in-depth insights into the cardiac response of cardiac patients during standardized activity. These results open up the possibility to optimized and more patient-tailored treatment strategies and to potentially improve CR outcome.
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