JMIR Publications

ABSTRACT

Background:

Cardiac rehabilitation (CR) is known for its beneficial effects on functional capacity and is therefore highly recommended as a secondary prevention measure in cardiovascular diseases. 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, being able to personalize CR could open up the possibility to achieve an optimal increase in functional capacity in every patient. Before treatment can be personalized, first, the differences in response of patients in terms of cardiac adaptation to exercise should be understood. In addition, digital biomarkers to steer CR need to be identified. To our knowledge, this is the first study to describe the longitudinal follow-up of a CR patient population using wearable sensor technology during a repeated standardized sub-maximal activity test.

Objective:

Investigating the difference in cardiac response, reflected by changes in commonly used HR parameters and digital cardiac biomarkers, between patients with a clear increased functional capacity, compared to patients with only a minor improvement after completing CR.

Methods:

129 patients in CR performed a six-minute walking test (6MWT) at baseline and during four consecutive short-term follow-up tests while being equipped with a wearable ECG device. The 6MWTs were used to evaluate functional capacity. Patients were divided into a high and low response group, based on the improvement in functional capacity during the CR program. Commonly used HR parameters and cardiac digital biomarkers representative for the HR behavior during the 6MWT and their evolvement over time were investigated.

Results:

All participating patients improved in functional capacity throughout the CR program (P <.0001). The HR parameters, that are commonly used in practice, evolved differently for both groups throughout CR. The HRmax from patients in the high response group increased significantly throughout CR, while no change was observed in the low response group (F (4,92) = 8.321, P < .0005). Similar results were obtained for the HRrec values that increased significantly over time for the high response group (HRrec1: P = .000, HRrec2: P =.000, HRrec3: P = .000, HRrec4: P = .000, HRrec5: P = .021). The digital biomarkers showed that the evolvement of HR 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 response.

Conclusions:

The current study showed that using wearable sensor technology the differences in response of patients to CR can be characterized by means of commonly used HR parameters and digital biomarkers that are representative for 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.