Chronic kidney disease (CKD) affects approximately 23 to 26 million people in the United States with estimated increases expected in the coming years because of rising obesity and diabetes rates (20). Many CKD patients are sedentary, which may contribute to their poor health status. Although there is evidence from animal models of CKD that chronic aerobic training preserves kidney function (9,22), the effect of exercise training on kidney function in CKD has not been well studied in humans.
Some experts have questioned the safety of exercise training in CKD patients because renal blood flow is transiently reduced during each bout of exercise and proteinuria has been observed to follow strenuous exercise in some individuals leading to open speculation about the safety of exercise in CKD patients (7). However, Eidemak et al. (7) did not find any evidence of a worsening or improvement of kidney function in a sample of nondiabetic CKD patients after 18 months of exercise training. In contrast, Toyama et al. (30) observed that 12 wks of endurance training led to an improvement in kidney function (i.e., an increase in glomerular filtration rate (GFR)) that was associated with an increase in HDL cholesterol and a decrease in both LDL cholesterol and triacylglycerols (TAG).
In addition, to these changes in plasma lipids, there is some evidence of an important role of the autonomic nervous system (ANS) in kidney function. Early in the development of CKD, researchers have found evidence of sympathetic nervous system (SNS) hyperactivity, which is believed to contribute to the progression of renal disease and is associated with a poor prognosis (21,23,25). The SNS hypersensitivity is thought to be linked to a host of complications in CKD including hypertension, proteinuria, glomerulosclerosis, and accelerated atherosclerosis (25). The measurements of both resting and recovery HR are seen as valid indicators of ANS function (5,15). There is some speculation that interventions that lead to a reduction in SNS activity in patients with CKD may be effective in reducing future cardiovascular events (23). However, studies to test this hypothesis, involving the use of chronic exercise training, have not been performed with CKD patients.
With regard to diet, researchers have observed that a reduction in protein intake is associated with less glomerulosclerosis possibly because of a reduction in intraglomerular hypertension and glomerular hypertrophy in CKD patients (4). Although controversial, some researchers have repoted that low protein intakes, in the range of 0.6–0.75 g·kg−1·d−1, in the absence of malnutrition, may reduce the progression of CKD to end stage renal disease (8,13,18,19). In addition, inflammatory cytokines are also believed to contribute to the progression of CKD to end stage renal disease and to the increased prevalence of cardiovascular disease in this population. Whether lifestyle modifications could affect the levels of these biomarkers has not been well studied in humans. Therefore, the current pilot study was designed to determine the effects of long-term supervised exercise training and modest dietary modification on kidney function and indices of cardiovascular function in a sample of stage 2–4 CKD patients compared with a control group who received the current standard medical care. We hypothesized that the combination of exercise training and dietary modification would favorably alter both kidney and cardiovascular function in a sample of stage 2–4 CKD patients compared with controls.
SUBJECTS AND METHODS
Subjects were recruited from Western New England Renal and Transplant Associates (WNERTA). CKD patients were eligible for the study if they were in stages 2–4 (i.e., estimated GFR (eGFR), 15–89 mL·min−1 per 1.73 m2) and were between the ages of 18 and 70 yr. Patients were excluded if they had any contraindications to exercise as defined by the American College of Sports Medicine (29). Based upon baseline data, subjects were matched on eGFR (modification of diet in renal disease) and aerobic fitness as assessed from a graded exercise test (GXT) and then randomly assigned to either the training group (TG) or usual care group (UC).
Eligible patients attended their first experimental session at Springfield College where they were briefed on study procedures and risks and were asked to read and sign a consent form that had previously been approved by the institutional review board of the college. After sitting for 5 min, resting blood pressures (BP) were taken in duplicate with a 1-min interval between trials using an automated sphygmomanometer (Tango; SunTech Medical, Morrisville, NC). A third reading was taken if either systolic BP (SBP) or diastolic BP (DBP) readings differed by at least 6 mm Hg. The average of the two closer readings was used. After the assessment of resting BP, subjects were given a 24-h BP monitor (90207 ABP monitor; Spacelabs Medical, Issaquah, WA), which was programmed to take readings at 30-min intervals from 6 a.m. until 11 p.m. and at 60-min intervals from 11 p.m. until 6 a.m. Before leaving the laboratory, the monitor was started and the researcher made sure that readings were being recorded properly before the subject was allowed to leave for the day. Subjects were instructed to carry on with their daily routines to keep the arm that bore the cuff, typically the nondominant arm, still while readings were being taken. Subjects would return the monitor after wearing it for 24 h. The data were then downloaded onto a PC with software that computed the appropriate averages after filtering out any spurious readings (Spacelabs Medical).
At least 1 d after the first session, subjects returned to the laboratory for their second session during which anthropometric variables were measured using standard laboratory methods. A medically supervised GXT, with ECG monitoring, was administered using the modified Bruce protocol. Oxygen uptake (V˙O2peak) was measured using a computerized metabolic cart (MAXII; Physio-Dyne, Quogue, NY). The test was performed until volitional exhaustion or until the subject exhibited any of the criteria for the termination of an exercise test as recommended by the American College of Sports Medicine (29). Subjects were seated within 1 min of completing the test, and HR and BP measurements were made for 5 min with the subjects quietly seated. Subjects were then fitted with a 24-h BP monitor and asked to wear this for the next 24 h.
Three days to 7 d after the GXT, subjects returned to the laboratory for their third session during which resting BP and HR were recorded after an identical protocol as was used during the first visit. Subjects were fitted with the ambulatory monitor and followed the directions as previously described. Both resting and ambulatory readings taken during the third visit were used as the baseline values for the study.
Kidney function was determined by the assessment of GFR using two different methods: an estimation method using the modification of diet in renal disease equation (eGFR) (16,17) and a direct method, creatinine clearance (CrCl) (28). To determine clearance rates, subjects performed 24-h urine collections the day before visiting the laboratory at WNERTA after an 8- to 10-h fast, to have a blood sample taken. This blood sample was used for the assessment of all blood parameters during the study, including serum creatinine, blood urea nitrogen, total cholesterol (TC), HDL, LDL, TAG, high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), and asymmetric dimethylarginine (ADMA).
Three-day diet analyses were performed at baseline and at weeks 24 and 48 for both groups by a registered dietitian who specializes in kidney disease. Based upon these findings, patients in TG received nutritional counseling. Patients in the training group initially met with the dietitian who provided written and verbal instructions to each participant detailing recommendations for macro- and micronutrient consumption according to standard nutritional care for renal patients. In particular, patients were encouraged to maintain protein intake within the desired range (0.6–0.75 g·kg−1·d−1). Patients in the UC were instructed to follow the advice of their physician and provided with no further nutritional counseling. After the initial counseling session, patients in the TG were contacted via phone at 2-wk intervals, at which time the dietitian completed a 24-h dietary recall from the previous day, and she also selected a weekend day. She used that time to address areas of concern from previous conversations.
After baseline testing and group assignments, the exercise group was expected to attend three supervised exercise sessions per week in the Wellness Center of Springfield College for a total of 48 wk. Graduate students or senior undergraduates with the appropriate academic background (i.e., clinical exercise physiology or applied exercise science majors) and experience were the personal trainers. Each exercise session began with a BP assessment in all subjects, whereas blood glucose levels were assessed in diabetics (either directly or via self-report). If the preexercise value was less than 100 mg·dL−1, the individual was given a drink containing some carbohydrate and was reassessed to make sure that their blood glucose was elevated before they could participate for that day. After these assessments, subjects warmed up for 5 min by walking or cycling at a low intensity. This was followed by a period of static flexibility exercises. Patients were then gradually expected to build up their exercise tolerance to complete 45 min of moderate-intensity (i.e., 50%–60% V˙O2peak) aerobic exercise using a combination of exercise apparati including treadmills, cycle ergometers, elliptical machines, and the Stairmaster, depending upon their preference. The work rate that they used was calculated based upon their most recent performance on the GXT. Throughout each session, HR was monitored via a Polar HR monitor (Polar F4, Polar Electro Oy, Finland) to make sure that each subject stayed within their prescribed intensity range. Furthermore, the RPE was assessed during each exercise session. Subjects started off doing as little as 10 min of continuous exercise, but this was gradually increased to get them working for the desired period (i.e., 45 min). At the completion of each workout, subjects were taken through a cool down procedure involving static stretching. BP was once again assessed, and blood glucose levels were also monitored to make sure that individuals were not hypoglycemic before leaving the facility. The total time completed during the session and an estimate of the total calories expended (based upon the output given by the machines) were recorded after each session. During the study, diabetic subjects who were on insulin had to make adjustments to their insulin dose to minimize the risk of them experiencing hypoglycemic episodes after exercise. These adjustments were made after the patient had consulted with their doctor.
In an effort to avoid boredom, from weeks 24 to 48, in addition to the aerobic training already described, subjects were also allowed to perform some resistance exercise twice per week. Subjects were taught how to perform six exercises in good form using machine weights (leg press, leg curl, compound row, chest press, triceps push down, and lat pulldown). Subjects initially performed one set of 10–15 repetitions of these six different exercises. As time progressed, some subjects added a second set.
Serum creatinine, blood urea nitrogen, and total protein were assessed using standard methods. All analytes were monitored at WNERTA’s laboratory to within 2 SDI and 2.0 CVR of peer groups using Bio-Rad (Hercules, CA) Unity quality assurance program. The laboratory at WNERTA has been certified with COLA ID# 018067 and CLIA accredited #22D0861308.
All lipids, with the exception of the LDL particle sizes, along with glucose, phosphorus, and calcium, were analyzed at the laboratory at WNERTA using standard methods. The Lipoprint LDL system (Lipoprint LDL System; Quantimetrix, Redondo Beach, CA) was used to determine LDL particle size and pattern via nongradient, high-resolution PAGE (11). Blood samples were analyzed for hs-CRP (MP Biomedicals, Orangeburg, NY) and IL-6 (Thermo Scientific, Pierce Biotechnology, Rockford, IL) using enzyme-linked immunosorbent assays with sensitivities of 0.1 mg·L−1 and <1 pg·mL−1, respectively. ADMA was determined by enzyme-linked immunosorbent assays kits (Euroimmun US, Boonton Twp, NJ) with a sensitivity of 0.05 μmol·L−1. All analyses were performed in duplicate, and specific analytes were assayed at the same time to reduce interassay variability. With the exception of hs-CRP (<20%), the coefficient of variability was less than 10% for all variables.
Data are presented as means ± SD. A regression equation was used to determine the average change in GFR per month over the course of the study. For each subject, GFR data were used to calculate a regression equation using time to predict GFR levels. Time was converted to months (0, 5.5, and 11 months) to create slopes that indicated changes in GFR per month. Average slopes for each of the methods for UC and TG were compared using an independent samples t-test. Physical characteristics of the subjects who completed the study were compared using an independent samples t-test. All other variables were analyzed using ANCOVA with baseline value as a covariate. All statistical analyses were performed using the Statistical Package for Social Sciences 17 for Windows (SPSS, Inc., Chicago, IL). Significance was determined as P < 0.05.
Twenty-one out of a total of 40 potential subjects completed the study. Fifteen patients were excluded; 13 of whom were unwilling or found it inconvenient, one could not exercise, and another did not have transportation. Therefore, 25 subjects were enrolled, 14 to the TG and 11 to the UC. Four individuals from the TG dropped out (one started dialysis, two lost interest, and one had hip surgery); consequently, we were able to analyze data from 10 subjects in the TG and 11 from the UC. The mean age of the subjects was 57.5 ± 11.5 yr (TG) and 52.5 ± 10.6 yr (UC), P > 0.05. The etiology of CKD and the medications taken by the subjects during the study are described in Table 1. The anthropometric measurements taken on the subjects during the study are listed in Table 2. There were no differences in these parameters between groups during the study.
Subject compliance, defined as the total number of training sessions attended as a proportion of the total possible number of sessions during the 48 wk (i.e., 144), was 83.8% ± 18.6%, whereas the average weekly caloric expenditure was 654 ± 287 kcal. At baseline, the V˙O2peaks (mL·kg−1·min−1) of the two groups did not differ (18.1 ± 7.8 TG vs 18.8 ± 4.5 UC); however, by week 48, the TG had improved to 19.5 ± 4.6 mL·kg−1·min−1, and this was significantly higher (P = 0.04) than UC (17.0 ± 3.1 mL·kg−1·min−1). At baseline, the measured V˙O2peaks represented 58.2% ± 23.3% (TG) and 53.4% ± 10.4 % (UC) of the estimated normal value for each group. The normal values for each group were the 50% percentile score from published standards (29). By the completion of the study, the V˙O2peak of the TG represented a significantly higher percentage of their age and sex-specific predicted normal value than the UC (61.8% ± 17.5% in TG vs 43.5% ± 16.3 % in UC), P < 0.05, but the value was still below normal. The time (s) to complete the treadmill protocol did not differ between groups at baseline (678.6 ± 194.3 TG, 645.7 ± 157 UC) but was significantly longer in the TG than the UC after 48 wk (743.4 ± 311 TG, 629.3 ± 155, P = 0.002) (Table 3).
One participant in UC did not have complete data for eGFR and was excluded from this analysis. The rate of change of eGFR (mL·min−1 per 1.73 m2 per month) was not different between the two groups (0.07 ± 0.66 TG, 0.45 ± 1.2 UC), P > 0.05, effect size (d) = 0.39. The same result was seen when GFR was directly assessed using CrCl (-0.36 ± 0.86 TG, 0.05 ± 3.09 UC; P > 0.05, d = 0.18). Furthermore, 24-h urine protein excretions were not different between groups at any point during the study.
Resting and ambulatory BP and HR
The intervention had no significant effect upon either resting or ambulatory BP (Table 3). However, the intervention led to significant reductions in both resting and ambulatory HR. At week 48, the resting HR of individuals in UC was 71.5 ± 15.7 bpm, whereas the HR of those in TG was lower (68.1 ± 6.7), P = 0.01, with an effect size (f) of 0.65. A similar pattern was observed with the ambulatory HR data. At baseline, HR did not differ between groups at baseline, but by week 48, the ambulatory HR (bpm) of those in TG (68.7 ± 6.5) was lower than those in UC (75.3 ± 12.9), P = 0.03 (Fig. 1). We also observed that the 1-min HR recovery value (bpm) after a GXT was similar at baseline (18.4 ± 10.6 TG vs 15.5 ± 8.3 UC), but by week 48, there was a statistically significant difference (19.5 ± 7.3 TG vs 11.0 ± 6.0 UC, P < 0.05 ) between the groups.
One subject in UC had extreme values of several lipid levels (baseline cholesterol >580) and was excluded from the analyses. At baseline, none of the lipid parameters differed between TG and UC. At week 24, the TC (mg·dL−1) was statistically higher in TG (193.9 ± 35.4) and UC (145.2 ± 24.4), P = 0.003, and these values continued to differ at 48 wk (187.9 ± 31.2 vs 147.5 ± 11.8, P = 0.001). LDL (mg·dL−1) was also higher in the treatment group at both week 24 (106.2 ± 30.2 vs 79.0 ± 17.4, P = 0.001) and week 48 (111.1 ± 28.3 vs 80.3 ± 11.3, P = 0.001). The TAG levels differed at 24 wk between TG (192.7 ± 51.2) and UC (113.9 ± 43.2), P = 0.01, but there was no statistically significant difference detected at 48 wk. HDL cholesterol levels did not differ between the two groups at any time point during the 48-wk study (Table 4).
After the observation of an increase in LDL in TG, we decided to further investigate this finding by analyzing our samples for the LDL particle sizes, which were measured only at baseline and week 48. Baseline values did not differ between groups for any of the particle sizes analyzed. By week 48, LDL-3 (mg·dL−1) in TG (3.9 ± 3.8) was higher than that in UC (1.7 ± 1.5), P = 0.02, whereas LDL size (Å) was lower (269.1 ± 4.3) in TG compared with UC (270.6 ± 2.7), P = 0.02. (Table 5).
Inflammatory and vascular markers
There were no statistically significant differences in IL-6, hs-CRP, and ADMA levels between the study groups at any time point of the study (Table 4).
The total caloric intake (kcal) of the subjects was not different between the two groups at baseline (1350.3 ± 225.6 TG, 1886.9 ± 666.5 UC) or after 48 wk of training (1301.2 ± 190 TG, 1907.4 ± 149.4 UC). The protein intake (g·kg−1) at baseline was 0.70 ± 0.15 (TG) versus 0.76 ± 0.24 (UC), P > 0.05. By the end of the study, the protein intakes for the two groups were 0.68 ± 0.15 (TG) and 0.65 ± 0.10 (UC), P > 0.05. Sodium (mg) (2063.9 ± 673.9 TG, 2769.2 ± 917.0 UC, baseline; 1948.8 ± 618.6 TG, 3544.3 ± 1085.7 UC, week 48) and phosphorus (mg) (792.7 ± 127.5 TG, 704.5 ± 197.9 UC, baseline; 510.2 ± 36.8 TG, 575.4 ± 79.5 UC, week 48) intakes were not different between the groups at any time point but were within the normal ranges.
The primary purpose of the current pilot study was to determine the effect of long-term exercise training on kidney and indices of cardiovascular function as well as several nutritional markers in stage 2–4 CKD patients. We observed that a 48-week training program led to significant improvements in several measures of aerobic fitness and reductions in both resting and ambulatory HR, but it had no discernible effect on kidney function. Biochemical data showed no obvious changes except a statistically significant increase in TC and LDL levels in the exercise intervention group.
The most striking finding in this study was the reduction in both resting and ambulatory HR in the exercise group. Based upon the effect size observed with the resting HR data (d = 0.65), the 48-wk exercise training program had a large effect upon this variable. This striking improvement in resting HR is not consistently observed in studies involving CKD patients but seems to be related to the exercise intensity used because reductions are more likely to be seen after higher-intensity exercise than low-intensity bouts (10). However, it is interesting to note that the changes observed in this study were seen after moderate-intensity exercise. We also observed that the 1-min postexercise HR recovery worsened over time in the UC (going from 15.5 ± 8.3 to 11.0 ± 6.0 beats) but was preserved in the TG (18.4 ± 10.6 to 19.5 ± 7.3 beats), which also indicates that the training program had favorably affected the ANS. The clinical significance of this finding is that a 1-min postexercise HR that differs by less than 12 beats compared with the peak exercise value (as was the case in the UC) is an indicator of poor prognosis (5,15). A recent study by Brotman et al. (3) showed that elevated resting HR and low heart variability are associated with increased risk of end-stage renal disease and CKD-related hospitalization, further signifying the clinical relevance of our findings. Although we cannot determine with certainty the actual mechanisms responsible for our observations, HR is influenced by the ANS, and the reduction in HR that we observed suggests either an increase in parasympathetic tone, a decrease in sympathetic tone, or possibly a combination of both. The HR recovery data suggest an enhancement of parasympathetic tone (15). Regardless of the mechanism, these results are important in CKD because there is evidence of heightened SNS activity in this patient population and represents an intriguing target for intervention (3,25). It is also important to note that there were no differences in the use of medications that could potentially affect the ANS between the two groups.
Unlike HR, the 48-wk program had no effect upon either resting or ambulatory BP. Other researchers have reported evidence for a 4- to 7-mm Hg reduction in systolic and diastolic pressure after 4–6 months of mixed cardiovascular and resistance training in CKD patients (10). We did not observe this possibly because at baseline, the BP of our patients was already very well controlled by antihypertensive medications. In one of the key exercise studies cited that demonstrated a significant reduction in BP after an exercise training program, the initial blood SBP of the subjects was 145 mm Hg, and this decreased to 124 mm Hg (2). In the current study, the initial SBP was 118 in the exercise group. Furthermore, the reduction in BP observed in the Boyce et al. (2) study occurred with no change in body weight over the duration of the study. The fact that we did not observe a change in body weight cannot therefore be suggested as a major reason for the lack of BP-lowering effect of the training program.
We did not find any obvious change in kidney function between the study groups. Eidemak et al. (7) completed an 18- to 20-month unsupervised training study in 30 nondiabetic CKD patients and reported that their unsupervised exercise training program had no effect upon the rate of progression of kidney disease in their sample. The changes in aerobic fitness reported in this study (7.7% ) are very similar to those reported by Eidemak et al. (7) (8%) even though the latter training program was longer and unsupervised. Furthermore, the changes that were observed were achieved with the expenditure of a small average weekly caloric expenditure (approximately 650 kcal), which is on the low end of the recommended effective “dose” of physical activity as defined by the National Physical Activity Guidelines (31). Admittedly, the quantification of the energy expenditure during the training sessions was only an estimate based on values recorded from the exercise machines, but overall, the changes observed were achieved with activity levels within the moderate range.
Our findings are different from those reported by Toyama et al. (30), who observed that 12 wk of endurance training led to an improvement in GFR in stage 3 CKD patients with cardiovascular disease. This improvement in GFR was associated with an increase in HDL and a decrease in LDL and TAG. Based upon findings in a rat model, lipids have been implicated in the progression of CKD. Two hours of daily swimming led to a reduction in LDL and TAG (9,22). A curious finding of the current study relates to the observation that TC was higher at week 24 and 48 in the treatment group although nutritional intakes did not differ between the two groups throughout the study. It is notable that our findings are similar to those reported by Eidemak et al. (7) and to other researchers who have studied the CKD population and reported unfavorable changes in lipids with exercise training in this population (10). In the current study, the exercise intervention was not associated with any significant change in body weight. Generally, a reduction in body weight is associated with favorable changes in plasma lipids (6). Unfortunately, the two exercise studies cited involving CKD patients made no mention of body weight changes of their subjects during the study (7,30).
It is also important to note that the antioxidant and anti-inflammatory actions of HDL are altered by CKD (32). Furthermore, we observed that LDL increased in the treatment group. By the end of the study, the LDL particle size had shifted to a more atherogenic profile. Therefore, the effect of exercise training on lipids warrants further investigation particularly in light of the findings of Toyama et al. (30) highlighting the possible role that lipids may play in kidney disease progression.
Our aerobic fitness data are consistent with those reported by others. The measured V˙O2peaks, of the subjects in this study represented approximately 40%–60% of the values for nondiseased age- and sex-matched controls (12). In a recent review, Johansen and Painter (12) report that most researchers who work with stage 3–5 CKD patients report V˙O2peak values that represent 50%–80% of those reported for healthy normals. It is also important to note that despite the improvement in V˙O2peak in the training group, their functional capacity was still substantially below normal compared with an individual without CKD of the same age and sex (12). Interestingly, the UC in our study displayed a slight decline in their functional capacity, which needs to be considered when interpreting the changes in the intervention group.
As further evidence of the effectiveness of the exercise intervention, the time to complete the treadmill protocol was significantly longer after the intervention period compared with baseline. Almost all subjects who completed the exercise intervention showed improvement in this variable.
A period of exercise training has anti-inflammatory effects in healthy individuals (24). However, there has been little work done on the effect of exercise training on inflammatory markers in CKD patients. Our results indicate that a 48-wk exercise intervention had no effect upon any of the pro-inflammatory cytokines, IL-6 or hs-CRP. These cytokines were measured because they are believed to play a role in the progression of CKD (27,34). Our findings are consistent with those of Wilund et al. (33) who demonstrated that 4 months of endurance training had no effect upon cytokine levels in a mouse model of CKD. Similarly, the 48-wk exercise program had no effect on ADMA levels, a putative marker of endothelial function that has been shown to be higher in CKD patients compared with healthy individuals (1,14,26).
There are some limitations to this study. First, the current study is limited by the small sample size. This was a pilot and feasibility study that was designed to look at certain outcomes that are known to require large sample sizes, especially in relation to kidney function. Our data clearly indicated that the intervention was effective in terms of improving aerobic fitness and favorably altering the HR responses of CKD patients. We acknowledge that autonomic function should have been assessed by measuring HR variability, but this was not available to us at the time. Other obvious limitations are the use of surrogate outcomes, limited generalizability of the results, and poor compliance to the dietary intervention. Therefore, these data should be interpreted with caution. Despite the limitations of the study cited above, the results of this study have shown that exercise training does not worsen kidney function in predialysis kidney patients. CKD patients should therefore be encouraged to engage in moderate-intensity exercise programs because such a program will not adversely affect their kidney disease but will benefit some aspects of cardiac function, notably HR.
Long-term aerobic exercise training leads to favorable changes in resting and ambulatory HR without adversely altering kidney function in stage 2–4 CKD patients. The intervention is also associated with increases in total and LDL cholesterol, which requires further examination. There is a need to further investigate the effect of exercise training programs on cardiovascular end points in larger patient cohorts in CKD patients.
This study was supported by grants from Baystate Medical Center Incubator Fund and from the Graduate Research Fund at Springfield College.
We thank the patients who participated in the study and the Springfield Colleges students who worked as personal trainers or assisted with the testing involved in this study. We also thank Dr. Alp Ikizler for his helpful input in the preparation of this manuscript. We also thank the staff at WNERTA for their assistance.
The authors have no conflict of interest to declare.
The results of the present study do not constitute endorsement by the American College of Sports Medicine.
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