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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.
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.
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.
All participating patients improved in functional capacity throughout the CR program (
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.
Cardiovascular diseases are the most prevalent noncommunicable diseases worldwide. The American College of Cardiology Foundation, the American Heart Association, and the European Society of Cardiology consider cardiac rehabilitation (CR) to be a key component within current disease management strategies, making millions of cardiac patients eligible for rehabilitation [
The aim of this study was to investigate the difference in cardiac response, a measure of chronotropic response, between patients that showed a clear improvement in functional capacity and patients that only showed a minor improvement following CR therapy. This was done by using data captured with a wearable electrocardiogram (ECG) device during a standardized activity. Moreover, innovative analysis techniques were used to derive digital cardiac biomarkers allowing an in-depth analysis of heart rate behavior during a standardized activity test.
A total of 129 cardiovascular patients, who were enrolled in a multidisciplinary CR program in a single tertiary-care center (Ziekenhuis Oost-Limburg [ZOL], Genk, Belgium) and representative of the typical CR population, were included. Patients over the age of 18 years with heart failure and reduced ejection fraction, with heart failure and preserved ejection fraction, and with a left ventricular ejection fraction less than or equal to 55% were eligible for the study. Patients with an inability to exercise due to orthopedic or neurological limitations were excluded from the study. The goal was to investigate the different levels of response to exercise intervention during a standardized CR program. The 6-minute walking test (6MWT) was used to follow up on the improvement in functional capacity in the course of the CR program. A wearable device was used to collect ECG data during the 6MWT. A descriptive analysis of the longitudinally collected wearable data was performed to identify patterns or trends in the dataset. To distinguish the response to rehabilitation, patients were assessed as being within a low-response and a high-response group based on a median split for the increase in distance walked throughout the CR program. Therefore, two groups with an equal number of patients were created based on the level of improvement in functional capacity measured by the 6-minute walking distance. Patients who increased more than 90 meters after completing the CR were referred to as the high-response group, while the low-response group consisted of patients who increased less than 90 meters. The study complied with the Declaration of Helsinki, and the local ethical committee approved the study protocol. All subjects gave written informed consent prior to study participation.
Patients were referred to the multidisciplinary CR program following a cardiovascular-related hospital admission. The 15-week program consisted of 45 ambulatory rehabilitation sessions at a frequency of three 1-hour sessions per week. Both resistive and aerobic exercises were included in the program. Additionally, dietary sessions, psychological support, and social consultations were included in the multidisciplinary program. By standard, a cardiopulmonary exercise test (CPET) was performed at baseline and at end-of-study to assess functional capacity. A total of 14 low-response group patients out of 45 (31%) and 21 high-response group patients out of 45 (47%) had a CPET at both baseline and end-of-study. The heart rate achieved at 90% of ventilator threshold during the CPET was chosen as the target heart rate during aerobic training. If no CPET data were available, target heart rate was set at 50%-80% of the maximal heart rate. Aerobic training consisted of 30-40 minutes, in total, of aerobic exercise on bicycle, hand bike, treadmill, and/or stepper. Resistive training was performed at 50%-80% of one repetition maximum and consisted of three sets of 15 repetitions on both the leg and arm press. Training intensity was increased every 2 weeks based on patient improvement according to the standard clinical practice of CR in our study center.
Demographics, clinical data, medical therapy, and echocardiography data were collected from the electronic medical record. A 6MWT was performed at baseline (ie, start of rehabilitation program). Four follow-up 6MWTs were performed every 3 weeks, resulting in five 6MWTs in total. The compliance rate with the rehabilitation program between every 6MWT for both groups was calculated. Patients were expected to follow three rehabilitation sessions per week, which is equal to nine rehabilitation sessions between two consecutive 6MWT measurements. If patients attended nine rehabilitation sessions between consecutive 6MWTs, a compliance rate of 100% was obtained. The 6MWT was performed according to a standardized protocol [
The signal was divided into three parts: a 5-minute resting phase, a 6-minute walking phase, and a 5-minute recuperation phase. First, the artefacts present in the ECG signals were automatically detected and removed by means of the algorithm proposed by Varon et al [
The resting heart rate (HRrest) was calculated by taking the mean heart rate during the final 20 seconds of the resting period. The peak heart rate (HRpeak) was calculated by taking the mean heart rate obtained during the final 10 seconds of the walking phase. For the recovery heart rate (HRrec), the mean heart rate during every minute of recuperation following the 6MWT (ie, HRrec1, HRrec2, HRrec3, HRrec4, and HRrec5) was calculated. Moreover, to study whether HRpeak was influenced by the difference in effort among patients, HRpeak was corrected for the distance walked by dividing HRpeak by distance (HRpeak-dist), as described previously [
in which n is the total number of accelerometer sample points considered and Xk is a vector representing the acceleration along the x-axis, while the other axes are represented by Yk and Zk vectors, respectively.
Four different models were used to study the heart rate behavior during a standardized activity for both patient subgroups: one-term, two-term, two-term with added coefficient, and quadratic polynomial models. The goodness of fit was determined by calculating the coefficient of determination (R-squared). The model with the best fit was used to study the heart rate behavior. The coefficients of the best fits—the digital cardiac biomarkers—were studied for differences between both groups.
This study focused on investigating the difference in cardiac response, reflected by changes in commonly used heart rate parameters and digital cardiac biomarkers, between patients with a clear increased functional capacity and patients with only a minor improvement after completing CR.
Continuous variables are expressed as mean (SD), if normally distributed, or as median (IQR), if nonnormally distributed, and dichotomous data are expressed as n (%). Normality was checked by the Shapiro-Wilk statistic. Categorical data were expressed as numbers and percentages and compared with the Fisher exact test. Continuous variables were compared between groups with the Student
Of the 129 patients that consented to participate, 89 (69.0%) completed the total study protocol. Out of 129 patients, 40 (31.0%) were excluded from analysis upon failure to complete the CR program due to health-related problems, lack of motivation, and work or family commitment (see
Patients showed an increase in functional capacity based on both the results of the CPET measurements and the results of the 6MWTs. Only 14 patients out of 44 in the low-response group (32%) and 21 patients out of 45 in the high-response group (47%) performed both a CPET at baseline and at end-of-study. Although not statistically significant, an increase of 2.23 mL kg-1 min-1 in peak VO2 was seen between baseline and end-of-study for the low-response group (14/44, 32%,
Baseline characteristics.
Variable | Low-response groupa (n=45) | High-response groupb (n=44) | ||
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Gender (male), n (%) | 30 (67) | 35 (80) | .23 |
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Age (years), mean (SD) | 64 (9) | 63 (10) | .83 |
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Height (m), mean (SD) | 1.72 (0.09) | 1.73 (0.09) | .44 |
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Body surface area (m²), mean (SD) | 1.96 (0.19) | 1.93 (0.19) | .45 |
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Active smoker, n (%) | 12 (27) | 6 (14) | .19 |
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Left ventricle ejection fraction (%), mean (SD) | 47 (12) | 44 (14) | .18 |
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Cardiac resynchronization therapy, n (%) | 2 (4) | 2 (5) | >.99 |
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Myocardial infarction | 14 (31) | 9 (20) | .33 |
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Heart failure | 11 (24) | 10 (23) | >.99 |
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Coronary artery bypass grafting | 6 (13) | 8 (18) | .57 |
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Percutaneous coronary intervention | 4 (9) | 2 (5) | .68 |
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Atrial fibrillation | 10 (22) | 12 (27) | .63 |
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Hypertension | 16 (36) | 22 (50) | .20 |
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Dyslipidemia | 20 (44) | 19 (43) | >.99 |
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Diabetes | 11 (24) | 1 (2) | .004 |
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Class I | 11 (24) | 14 (32) | .62 |
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Class II | 24 (53) | 20 (45) |
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Class III | 9 (20) | 10 (23) |
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Angiotensin converting enzyme inhibitor | 25 (56) | 25 (57) | >.99 |
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Beta-blocker | 33 (73) | 32 (73) | >.99 |
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Diuretics | 19 (42) | 20 (45) | .83 |
Baseline CPETc peak VO2d (mL/kg∙min), mean (SD) | 17.2 (5.3) | 16.8 (4.9) | .72 | |
Baseline 6MWTe distance (m), mean (SD) | 496 (95) | 473 (97) | .25 | |
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.99 | |
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Baseline to first measurement | 88.0 (17.0) | 85.5 (13.9) |
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First to second measurement | 87.7 (18.5) | 85.7 (14.1) |
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Second to third measurement | 84.5 (17.9) | 81.9 (20.6) |
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Third to end-of-study measurement | 85.4 (21.8) | 83.5 (24.9) |
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aThis group consisted of patients who improved less than 90 meters throughout the cardiac rehabilitation.
bThis group consisted of patients who improved more than 90 meters throughout the cardiac rehabilitation.
cCPET: cardiopulmonary exercise test.
dVO2: peak oxygen uptake.
e6MWT: 6-minute walking test.
To study the difference in cardiac response between the two subgroups, commonly used heart rate parameters were derived from the ECG data. Hereto, HRrest, HRpeak, and HRrec were analyzed. For these parameters, the differences between the two subgroups for every session and the differences in progression throughout CR were studied.
Secondly, the evolution in HRpeak across five sessions and, more specifically, the difference between both subgroups was investigated.
Resting heart rate (HRrest) for each group throughout cardiac rehabilitation.
Maximum heart rate (HRpeak) for each group throughout cardiac rehabilitation. *denotes a significant change over time.
The two-way mixed ANOVA showed that the evolution of HRpeak throughout CR differed between the high- and low-response groups (F4,216=3.3,
The change in HRrec1 after the 6MWT throughout CR is shown in
Peak heart rate corrected for distance (HRpeak-dist) for each group throughout cardiac rehabilitation. *denotes a significant change over time.
Heart rate recovery during the first minute (HRrec1) after the 6-minute walking test for each group throughout cardiac rehabilitation. *denotes a significant change over time; **denotes a significant difference in HRrec1 during a measurement session between both groups.
Results from the two-way, mixed-model, analysis of variance (ANOVA) for the heart rate recovery (HRrec) during the first 5 minutes after the 6-minute walking test (6MWT).
HRreca | dfmainb | dferrorc | Fd | Partial η²e | ||
HRrec1 | 4 | 212 | 5.172 | .089 | .001 | <.001 |
HRrec2 | 4 | 212 | 7.288 | .121 | <.001 | <.001 |
HRrec3 | 4 | 212 | 6.634 | .111 | <.001 | <.001 |
HRrec4 | 4 | 212 | 6.092 | .103 | <.001 | <.001 |
HRrec5 | 4 | 208 | 3.967 | .071 | .03 | .002 |
aHRrec: heart rate recovery; each number in this column represents every minute of recuperation following the 6MWT.
bdfmain: degrees of freedom for the simple main effect.
cdferror: degrees of freedom for the error term.
dIndicates that we are comparing to an F distribution.
ePartial η²: a measure of effect size.
fSignificance level for the hypothesis of no time effect × group effect.
gSignificance level for the hypothesis of no time effect.
The HRrec during every minute of recuperation increased throughout CR for the high-response group, while no change was observed in the low-response group (HRrec1:
The dynamic behavior of heart rate during a standardized exercise and subsequent recovery phase were investigated to further understand the difference in cardiac response between the groups. Hereto, four different models were fitted to the heart rate data. The quadratic polynomial fit obtained the best goodness of fit and was extracted from the heart rate data; the resulting coefficients, apoly and bpoly, were analyzed. Both coefficients determine the shape and steepness of the curve, thereby characterizing the speed of heart rate increase during the 6MWT and, thus, the response of the heart to exercise. These innovative digital cardiac biomarkers were studied for differences between the groups during every session, as well as for the difference in their progression throughout CR.
Mean quadratic polynomial fit to the changes in heart rate (HR) during all sessions while walking. The line represents the mean fit and the shadows represent the SD. bpm: beats per minute.
The behavior of heart rate during the subsequent recovery phase was analyzed for both groups (see
Mean quadratic polynomial fit to the changes in heart rate (HR) during all sessions while recuperating. The line represents the mean fit and the shadows represent the SD. bpm: beats per minute.
The findings of this observational study indicate that cardiac response to exercise in patients following a CR program plays a role in the level of their response to training in terms of distance walked. 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, submaximal activity test. Our 3-month follow-up period allows for novel in-depth insights into the cardiac response at rest, during exercise, and during recovery. Cardiac response is one of the possible confounders affecting the response to CR in patients. Therefore, investigating this cardiac response in a typical CR program aids in understanding the mechanisms behind different response rates. The wearable sensor technology enabled continuous monitoring of heart rate to derive both traditional heart rate parameters, commonly used in practice, and innovatively derived parameters that can function as digital cardiac biomarkers. The descriptive analysis of this longitudinally collected dataset investigated the difference in cardiac response between two patient populations following CR, who are respectively characterized by low and high improvement in functional capacity during CR.
Previous research showed that the response to training depends on the cardiac output or chronotropic response, as this determines the increase in muscle blood flow during exercise [
HRpeak is a cardiac biomarker that evolves differently throughout CR for both response groups. The high-response group showed an increase in HRpeak, while the low-response group showed no significant change. At a first glance, these results might appear to be opposite of the results from previous research [
The difference between the two groups in heart rate recovery, as captured by HRrec, was investigated. According to Qiu et al, HRrec measured after the 6MWT is considered to be a powerful prognostic indicator in cardiovascular disease [
To summarize, these heart rate parameters show that the effect of CR on the different response groups is also reflected in differences in cardiac response. The cardiac system of the high-response group adapts better to exercise throughout CR compared to the low-response group.
To further understand the difference in cardiac response, the dynamic behavior of heart rate during the 6MWT and subsequent recuperation phase was also investigated. This innovative type of heart rate analysis allows in-depth insights by reflecting changes within shorter time spans during a standardized activity test. The heart rate response is representative of the ability of the autonomic nervous system to meet the hemodynamic demands during exercise. The heart rate acceleration at the onset of exercise is often modelled by an exponential curve [
The heart rate behavior during the 6MWT and subsequent recuperation phase evolved differently between the groups throughout CR. The increase in heart rate during the walking phase was steeper in the low-response group at baseline, indicating that in this phase of the CR the autonomous nervous system of these patients is characterized by a superior response to exercise in comparison to the high-response group. In the course of the CR program, the increase in heart rate steepened for the high-response group, eventually catching up with the low-response group. These results are similar to the findings of Schmid et al and Jorde et al, who indicated that the heart rate slope was blunted in subjects with an impaired cardiac response [
To summarize, this study shows novel differences between groups, as the evolution in heart rate changes differently throughout the CR. Continuous measurements using wearable sensor technology enables the collection of traditional, commonly used heart rate parameters, but also of digital cardiac biomarkers representative of heart rate behavior during and after activity. The latter parameters were derived using a polynomial curve fitting technique, which is an innovative approach to capture heart rate evolution. Our research showed that these digital cardiac biomarkers can differentiate between the low- and high-response groups at baseline; hence, they, together with the traditional heart rate–related parameters, are valuable tools to use in short-term follow-up. Moreover, the results contribute to the development toward a more patient-tailored treatment strategy. Future research should focus on the role of these heart rate–related parameters in predicting outcome. The ability to improve and complement short-term follow-up by using these innovative techniques could make it possible to adjust treatment strategy in time and optimize outcome.
This study is an observational study analyzing the characteristics of a typical CR population; as patients were not randomized into different groups, the results should be interpreted as hypothesis generating. A low number of patients received both a baseline and end-of-study CPET measurement. These missing values do not influence the outcome of the study, as a submaximal exercise test is used to determine the progression in functional capacity throughout CR. There are some limitations to performing a median split to divide a patient population into two groups. However, data in this observational study was investigated in the search for trends upon which to base future randomized research. Another point of discussion is that the 6MWT is an effort-dependent test and a greater increase in HRpeak could be a consequence of higher effort. Therefore, effort derived from the data collected by the triaxial accelerometer was used to determine whether the high-response group was characterized by a higher effort in comparison to the low-response group. Hills et al state that acceleration is proportional to the net external force involved in an activity and, therefore, more directly reflects the energy cost associated with movement [
Following CR is, without any doubt, beneficial for cardiovascular patients. However, some patients benefit more from CR as they show a larger improvement in functional capacity in comparison to other patients. This study shows the following:
Continuous measurements using wearable sensor technology during standardized activity give novel insights into cardiac response between different response groups.
Patients showing a larger increase in functional capacity are characterized by a better improvement in cardiac response. This is in contrast to patients showing a low response to exercise intervention.
Innovative analysis approaches allowed us to study the difference in heart rate behavior between the response groups in more detail, showing differences in cardiac response at baseline.
The results from this study can be used in future research to investigate whether the outcome of CR can be predicted in order to adjust treatment strategy. Moreover, it is a first step toward the development of a more patient-tailored CR program.
Flowchart containing the intervention measures, dropout reasons, and number of patients. 6MWT: 6-minute walking test.
6-minute walking test
analysis of variance
cardiopulmonary exercise test
cardiac rehabilitation
degrees of freedom for the error term
degrees of freedom for the simple main effect
electrocardiogram
Research Foundation, Flanders
peak heart rate
peak heart rate corrected for the distance walked
recovery heart rate
resting heart rate
Limburg Clinical Research Program
Limburg Sterk Merk
MUlti SEnsor IC
Hasselt University
Agentschap Innoveren en Ondernemen
peak oxygen uptake
Ziekenhuis Oost-Limburg
This report is part of the Limburg Clinical Research Program (LCRP), Hasselt University (UHasselt)-Ziekenhuis Oost-Limburg (ZOL)-Jessa, supported by the foundation Limburg Sterk Merk (LSM), province of Limburg, Flemish government, UHasselt, ZOL, and Jessa Hospital. We would like to thank the engineers from Holst Centre, imec the Netherlands, for their technical support. We thank the physiotherapists from the cardiac rehabilitation center, ZOL, for their support and guidance during the study. HDC is supported by a doctoral fellowship by the Research Foundation, Flanders (FWO), Belgium (grant number: 1S53616N). SVH is supported by the Flemish Government under the Onderzoeksprogramma Artificiële Intelligentie Vlaanderen program. SVH and CV’s research is supported by Agentschap Innoveren en Ondernemen (VLAIO) (150466-OSA+) and imec funds 2017.
None declared.