Introduction
Parkinson’s disease (PD) is the second most common neurodegenerative disorder, affecting approximately 6 million people worldwide (Rocca
2018). The cardinal signs of PD are tremor and motor disturbance due to bradykinesia which affects gait, postural control, and motor function (Draoui et al.
2020). Non-motor symptoms such as cognitive impairment, fatigue, and impaired autonomic nervous system (ANS) are also common and debilitating (Santos-Garcia & de la Fuente-Fernandez
2013). Levels of physical activity are low in people with PD even in early disease (Lord et al.
2013) which in turn increases the risk of developing comorbidities (Liguori et al.
2022). While there is no cure for the disease, dopaminergic replacement therapies and structured exercise programs are the mainstay of management and are tailored to meet individual needs as the disease progresses (Fox et al.
2018; Gamborg et al.
2022).
ANS symptomatology is commonly reported in PD during the prodromal phase and as the disease progresses (Stankovic et al.
2019). Chronotropic incompetence (CI), defined as the inability to increase heart rate (HR) in response to an increase in demand during exercise testing despite attaining maximum effort (Brubaker and Kitzman
2011), is a feature associated with ANS dysfunction in PD (Palma et al.
2013). The prevalence of CI in PD is high with estimates around 50% (Kanegusuku et al.
2016; Penko et al.
2021) and it can be evident prior to disease onset (Palma et al.
2013; Palma and Kaufmann
2014). CI is often undetected in clinical practice and neglected in PD studies, despite its association with cardiovascular diseases (CVD), increased risk of mortality, and poor aerobic capacity reported in other conditions (Brubaker and Kitzman
2011; Herbsleb et al.
2018; Myers et al.
2007).
Although recent evidence suggests reduced aerobic capacity at submaximal and maximal intensity in people with PD (Kanegusuku et al.
2016; Mavrommati et al.
2017; Penko et al.
2021), this is not a universal finding (DiFrancisco-Donoghue et al.
2009; Protas et al.
1996). These studies mostly recruited sedentary and low physically active PD participants and did not stratify for presence of CI. In addition, there is limited knowledge regarding HR and metabolic responses in people with PD with CI using key submaximal physiologic markers (first (VT1) and second (VT2) ventilatory thresholds). Understanding these responses is crucial as they represent the physiologic points at which exercise intensity transitions from light to moderate (VT1) and from moderate to high (VT2) exercise intensities (Anselmi et al.
2021; Mezzani et al.
2013). Incorporating these thresholds into aerobic exercise training has shown greater effectiveness compared to traditional intensity measures (Anselmi et al.
2021; Meyler et al.
2021; Pymer et al.
2020).
Scant data are currently available on HR and metabolic response at submaximal (VT1 and VT2) and maximal intensities in people with PD with CI. This exploratory study aims to examine HR and metabolic responses during cardiopulmonary exercise test (CPET) in people with PD with and without CI to understand its effect on key physiologic markers and thereby enhance precision in setting exercise intensity parameters for aerobic exercise in this population.
Statistical analysis
Demographic data were analyzed using ANOVA to observe differences across groups. Post hoc tests using Tukey’s Honestly Significant Difference were conducted to identify specific variations between groups. In the case of PD-specific variables such as years living with PD, levodopa equivalent, and UPDRS, T-tests were used to compare means, assuming independent observations and equal variances.
For CPET data, linear regression and mixed linear regression were used to evaluate the relationship between outcomes and independent variables. All models were adjusted for gender, age, height, years living with PD, levodopa dosage, IPAQ_sit, IPAQ_walk, IPAQ_mod, and IPAQ_vig. Body mass index (BMI) was included in the models for HR, %HR, RPE, DBP, SBP, and VO2/HR. Linear regression analysis was used for variables measured at a single time point (RER, SBP, DPB, VO2/WR slope, and VO2/HR) and included Group as the categorical variable. Mixed linear regression analysis was used for variables measured at multiple time points (HR, %HR, WR/Kg, VO2, % VO2, and RPE) and included a full interaction between Group and Time as the categorical variables. Mixed linear regression analysis was also used for HR/WR slope and included a full interaction between Group as a categorical variable and %WR as a continuous variable. We evaluated the suitability of fitting straight lines or curvilinear natural splines using Akaike’s information criterion. We also fitted correlated participant-wise random intercepts and slopes across %WR.
Assumptions of normality and homogeneity of variance for model residuals were evaluated with QQ plots and fitted-values VS residuals plots. Multicollinearity was evaluated with a variance inflation factor (VIF) and variables with VIF greater than 10 were excluded from the models. Means and slopes estimated from the models were reported along with 95% confidence intervals. The threshold for statistical significance was set at 0.05. Data were analyzed in R environment for statistical computing (Bates et al.
2015).
The sample size was determined for t-tests (GPower 3.1.9.7) with a 0.05 significance level and 80% power. Based on data from a previous study (Kanegusuku et al.
2016), 8 participants per group were required for the primary outcome (HRmax), while 28 participants per group were needed for the secondary outcome (
VO
2 peak). To ensure adequate representation, a minimum sample size of 16 PD was set for the primary outcome, based on an estimated prevalence of CI in PD of around 50%. However, due to COVID-19, budget, and time constraints, the required sample size of 56 individuals with PD for the secondary outcome could not be achieved.
Discussion
To our knowledge, this is the first study to examine HR and metabolic responses to an incremental increase in workload in a group of people with PD classified according to the presence of CI. Our key finding was that people with PD with CI had blunted HR responses which were evident at high (VT2) and maximal intensity exercise but not at rest or during moderate intensity (VT1). This brings into question the accuracy of age-predicted equations for exercise intensity prescription for this subgroup of PD. Our secondary finding was that this subgroup also presented lower aerobic capacity at VT2, and peak exercise compared to PD non-CI and controls.
Our findings show that CI was present in 46.4% of PD (H&Y 1–3) participants, in line with previous studies reporting a prevalence of 40–62.2% (H&Y 2–3), and, comparable to our results, also showing an inability to reach 85% of their age-predicted maximum HR (Bryant et al.
2016; Penko et al.
2021; Werner et al.
2006). These results differ from Katzel et al. (
2011) who reported that only 7 (11%) of 63 participants with PD (H&Y 1.5–3) were able to achieve 85% of their age-predicted maximum HR. Contrasting findings may be due to differences in CPET test modality and criteria for attainment of maximum effort. Participants from Katzel et al. (
2011) were tested on the treadmill and attained an RER below 1.05, while participants from our study were tested on the cycle ergometer and presented an RER above the recommended threshold of 1.10 (Robergs et al.
2010).
PDCI exhibited significantly lower changes in HR compared to other groups at higher workload intensities despite having a similar HR at rest and moderate intensity (VT1) compared to controls. Werner et al. (
2006) also reported similar HR at rest and at moderate intensities (stage 2 of the Modified Bruce Protocol), and lower HR at the termination of the test in a subgroup of PD who were not able to attain 85% of their age-predicted maximum HR compared to controls. Evaluation of heart rate variability (HRV) was beyond the scope of this study, but our own findings and those from the literature suggest that the mechanisms contributing to a slow rate of change in HR in PD are likely to be linked to a reduced-sympathetic nervous system (SNS) drive. In healthy individuals, at high intensities, an increase in HR is primarily driven by the SNS yielding a rise in norepinephrine (DiFrancisco-Donoghue et al.
2009; White and Raven
2014). This contrasts with lower levels of norepinephrine, which is also associated with CI (Grosman-Rimon et al.
2023), found at peak exercise in people with PD both on and off medication (DiFrancisco-Donoghue et al.
2009).
Oxygen consumption at VT2 and peak exercise were lower in PDCI compared to PD non-CI and controls, whereas no significant differences were found between PD non-CI and controls. These findings are difficult to compare with earlier studies because PD participants are not usually stratified according to CI. However, it may help explain earlier ambiguous findings, with some studies reporting lower levels of
VO
2 peak in PD compared with controls (Kanegusuku et al.
2016; Katzel et al.
2011; Mavrommati et al.
2017) and others not (DiFrancisco-Donoghue et al.
2009; Protas et al.
1996). The mechanisms causing reduced aerobic capacity in PD with CI are not well understood. A blunted HR response which reduces maximal cardiac output, and malfunctioning of the mitochondria which reduces the arterio-venous oxygen difference (Larsen et al.
2020; Liguori et al.
2022) are both potential factors compromising aerobic capacity in PD (DiFrancisco-Donoghue et al.
2009; Kanegusuku et al.
2016; Penko et al.
2021). Although arterio-venous oxygen difference was not evaluated in this study, our results suggest that failure to achieve the age-predicted maximum HR may be one of the primary factors influencing
VO
2 peak in PDCI, given that the
VO
2/WR slope and oxygen pulse (
VO
2/HR) at peak exercise were similar between groups.
VO
2/HR is an indirect measure of stroke volume and in addition to the
VO
2/WR slope, indicates that PDCI participants were able to efficiently extract oxygen per heartbeat and per unit of work but unable to achieve their age-predicted maximum HR and associated cardiac output at maximal effort (Wasserman
2012).
Similar IPAQ results between PD and control subjects suggest that all participants were physically active and met the minimum recommendations for aerobic training from the ACSM (Liguori et al.
2022). However, the mean
VO
2 peak in the PDCI was on average 5 ml.kg-1 lower than control subjects.
VO
2 peak is an independent predictor of mortality, and a decrease in 1 metabolic equivalent of task (3.5 ml.kg-1) is associated with an increased risk of morbidity and mortality (Ezzatvar et al.
2021). By any means, the
VO
2 peak for PDCI was considerably higher than earlier reports (DiFrancisco-Donoghue et al.
2009; Kanegusuku et al.
2016; Penko et al.
2021), suggesting that involvement in high levels of training may be beneficial for PD but still not enough for PDCI to achieve similar levels of fitness. Improvement in
VO
2 peak is dependent on a variety of biologic and methodological factors (Meyler et al.
2021), limiting the scope of interpretation. Although, blunted-HR has previously been associated with reduced improvement in
VO
2 peak in PD (Penko et al.
2021) and in other clinical populations (Herbsleb et al.
2019), further studies evaluating the effect of aerobic training in PD with CI are required.
Based on our data, to achieve the threshold that represents moderate intensity (VT1), PD with CI need to train at a significantly higher percentage of their HRmax than PD non-CI and control subjects. These findings are consistent with earlier work, for example participants with CVD and a blunted heart rate response achieved 75–85% of their HRmax at VT1 during CPET (Anselmi et al.
2021; Smarz et al.
2021), comparable to our findings. We used CPET to examine response to aerobic exercise and stratify according to CI. Aerobic protocols that use the threshold zone derived from CPET to set and monitor exercise intensity are more accurate than those relying on predicted equations (de Lira et al.
2017; Meyler et al.
2021; Pymer et al.
2020). However, this approach is not readily available to clinicians who instead approximate values.
Alberts and Rosenfeldt (
2020) recommend an intensity of 70–85% of HRmax or an RPE of 14–17 for aerobic training due to the high prevalence of ANS dysfunction in this population, whereas the ACSM recommends a progressive increase in exercise intensity from 60–65% to 80–85% HRmax (Liguori et al.
2022). Our results suggest greater accuracy may be obtained using an RPE of ≥ 18 to indicate that maximum effort has been achieved (Liguori et al.
2022). From this, a more accurate estimate of HRmax can be obtained rather than using predicting equations.
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