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72-h Kinetics of High-Sensitive Troponin T and Inflammatory Markers after Marathon


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Medicine & Science in Sports & Exercise: October 2011 - Volume 43 - Issue 10 - p 1819-1827
doi: 10.1249/MSS.0b013e31821b12eb
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Regular moderate physical activity is a major prevention strategy to improve cardiovascular risk factors, delay cardiovascular disease, and decrease cardiovascular mortality (19,42). In contrast, an increased risk of exercise-related sudden cardiac death during vigorous exercise such as marathon running has been frequently reported (1); however, results are equivocal (34).

Extreme exercise has been shown to increase biomarkers of cardiac strain such as N-terminal pro-brain natriuretic peptide (NT-proBNP) as well as markers of cardiac injury such as cardiac troponins (cTn) (35). In addition, transient functional and persistent structural myocardial alterations (e.g., left and right ventricular dysfunction) as well as the occurrence of a myocardial fibrosis have been described (5,32). The underlying mechanism for these alterations was first addressed as the "cardiac fatigue syndrome" by Douglas et al. (13); however, it is not yet understood (33).

Several hypotheses have been raised to explain this phenomenon of increased cardiac biomarkers after strenuous exercise. First, systemic inflammation or oxidative stress induced by strenuous exercise has been suggested to cause cardiac injury (7). An exercise-induced increase in cytokines such as interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) may lead to cardiomyocyte dysfunction, as observed for severe inflammation or sepsis (26). Second, it has been hypothesized that stretch-related mechanisms mediated by integrins of viable cardiomyocytes may lead to exercise-related release of cTn (20). This hypothesis of minimal membrane leakage and rapid resealing is still discussed controversially (25). Third, on the basis of the finding of structural cardiac damage in older marathon runners, ischemia has been proposed to cause an exercise-induced elevation of cardiac enzymes (5). Whether cell necrosis due to microvascular stenosis with subsequent increase of cTn after strenuous exercise is a potential mechanism for this increase is still under debate. An argument against this hypothesis is that kinetics of cTn after marathon running and after myocardial infarction differ from each other (23,28). Fourth, impaired renal excretion may cause elevated troponin T levels because of decreased renal elimination (10). Likewise, an acute renal tubular dysfunction with transient oliguria caused by long-lasting strenuous exercise has been previously described (22).

Because of the reported differences in the elevation of serum cTn concentrations, the kinetics of their elevation, and the prevalence of their increase per se, as well as the intensity and duration of exercise resulting in increased cTn-values (14,39,40), the underlying mechanisms of the cTn elevation after strenuous exercise remain unclear (38).

Recently, a novel and more specific and sensitive marker of cardiac cell injury called high-sensitive cardiac troponin T (hs-cTnT) has been developed yielding more precise results and permitting analyses of cTn concentrations that are 10-fold lower than determined in previous assays (28). This allows a more precise and sensitive documentation of the chronological sequence of changes in serum cTn. This marker and other more established markers of cardiac ischemia, such as heart-type fatty acid-binding protein (h-FABP), increase during acute myocardial infarction. The latter returns to baseline within 24 h, whereas hs-cTnT remains elevated during days after myocardial injury (44).

To shed more light into the pathophysiology of cardiomyocyte strain and injury induced by long-distance vigorous exercise, we investigated the kinetics of specific cardiac biomarkers (h-FABP, hs-cTnT, NT-proBNP), inflammatory markers (interleukin-10 (IL-10), IL-6, high-sensitive C-reactive protein (hs-CRP), and TNF-α), and a marker of renal dysfunction (cystatin C) before and up to 72 h after a marathon race in a large cohort of otherwise healthy individuals.



Marathon runners were recruited through advertisements in local newspapers, running journals, or Internet announcements as well as through our outpatient clinic, which some of them have visited for general medical screening before their marathon. The first 150 interested and eligible runners were consecutively included in the study.

Inclusion criteria for the study were being aged between 20 and 60 yr, a history of at least one successfully finished half marathon, the intention to participate at the Munich Marathon in 2009 (42.195 km), and written informed consent. Exclusion criteria were a former or current cardiac, musculoskeletal, or psychiatric disease and neoplasia; an acute or chronic infection; pharmaceutical treatment for diabetes mellitus or arterial hypertension; and any medication or supplementation known to affect the immune status. The sample size of n = 150 was chosen on the basis of an estimated dropout rate before and during the marathon of 30% and hence a predicted number of complete data sets at all visits of n = 105. For this resulting sample size, bivariate correlations with a correlation coefficient of r > |0.27| were detectable with a power of 80% at a two-sided 0.05 significance level. The study protocol was approved by the ethics committee of the University Hospital Klinikum rechts der Isar, Munich, Germany (approval reference number: 2384/09), and the investigation conforms to the principles outlined in the Declaration of Helsinki. All participants gave written informed consent before enrollment into the study.


Measurements before the race (V1 and V2).

At 4-5 wk before the race, runners were examined for eligibility for study participation (visit V1). Collection of baseline data of participants during the last week before the race (visit V2) included questionnaires assessing training history, a physical examination, anthropometry, clinical chemistry, collection of blood samples for further analyses, ECG (custo cardio 200 with custo diagnostics 3.8.3; custo med GmbH, Ottobrunn, Germany), and echocardiography. Echocardiographical images were taken parasternally for both short and long axes and apical two-, three-, and four-chamber views in a left lateral decubitus position (iE33 imaging system equipped with a broadband S5-1 transducer (frequency transmitted = 1.7 MHz, received = 3.4 MHz); Philips Medical Imaging, Hamburg, Germany).

Because of a potential influence of both nutrition and medication on inflammation, participants were asked to document the medication they currently use (e.g., anti-inflammatory drugs) and were asked to minimize their intake of fatty foods, large doses of vitamins or mineral supplements, and probiotic yogurt during the whole study period. Participants recorded their food intake using a 3-d food diary before visit V2 and before the marathon.

Measurements after the race (V3-V5).

Within 1 h after finishing the race, an ECG was performed, blood samples were collected, and blood pressure was measured (visit V3). Follow-up examinations, i.e., an ECG, collection of blood samples, and measurement of blood pressure, were taken 24 h (visit V4) and 72 h (visit V5) after the marathon under identical settings.

Further parameters recorded extensively as part of the trial protocol but not reported in detail here include other cardiovascular measurements such as diastolic and systolic cardiac function, arteriovenous ratio, and an ECG.

During the marathon, all participants were asked to use an HR monitor to determine the individual exercise intensity. Percent HRmax was calculated as a ratio of mean HR during the marathon and HRmax as calculated by the following formula: HRmax = 208 − 0.7 × age (yr) (41). Seventy-eight participants (77%) wore an HR monitor during the race. Body mass index (BMI) was calculated as the ratio of weight and the square of height (kg·m−2). Total body fat was assessed by skinfold calipers (6). Hypertension was defined as previously reported (8). An elevated cholesterol level was specified as >240 mg·dL−1 (30). Smoking was defined as current smoking or having smoked within the previous year.

Blood samples.

Fasting blood samples were taken from an antecubital vein with subjects in supine position at V1, V2, V4, and V5. Only the blood collection immediately after the race was not in a fasted state. All participants were instructed to refrain from sustained or long runs and strenuous exercise for at least 3 d before the prerace blood draws. Routine complete blood cell counts were performed by a clinical hematology laboratory technician using a Sysmex SF-3000 Automated Hematology Analyzer (Sysmex Deutschland GmbH, Norderstedt, Germany) and provided hemoglobin, hematocrit, and albumin for determination of plasma volume change from before to after the race using the method of Dill and Costill (12). As albumin concentration increased significantly from baseline to follow-up, hs-cTnT and all other dehydration-dependent concentrations were corrected for changes in plasma volume as previously described (12). For this reason, corrected values even below the lower limit of detection (LLD) can occur. Other blood samples were centrifuged in sodium heparin or EDTA tubes, and plasma samples were aliquoted and stored within 1 h at −80°C for further analyses.

High-sensitive troponin T.

High-sensitive cardiac troponin T (hs-cTnT) was measured quantitatively with the new high-sensitive enzyme immunoassay based on electrochemiluminescence technology using the cobas e 411 analyzer (Roche Diagnostics, Penzberg, Germany). The measuring range of this assay is 3-10,000 ng·L−1. The interassay coefficient of variation (CV) under actual routine conditions is 6.5% at a concentration of 27 ng·L−1. The upper reference limit in healthy volunteers is 14 ng·L−1.


NT-proBNP was measured quantitatively with the enhanced electrochemiluminescence immunoassay system method on a cobas e 411 analyzer (Roche Diagnostics). The measuring range of this assay is 5-35,000 ng·L−1. The interassay CV under actual routine conditions is 4.2% at a concentration of 138 ng·L−1. The upper reference limit in healthy volunteers depends on age and sex and is 65 ng·L−1 in 18- to 49-yr-old males, 125 ng·L−1 in 50- to 59-yr-old males, and 194 ng·L−1 in >60-yr-old males.


h-FABP was determined quantitatively using a solid-phase enzyme-linked immunoassay (BioCheck, Inc., Foster City, CA). The measuring range of this assay is 5-500 μg·L−1. Serum samples have a minimum detectability of 5 μg·L−1. The interassay CV is 10.9% at a concentration of 86 μg·L−1. The upper reference limit in healthy volunteers is 19 μg·L−1.

In addition to its cardiac origin, h-FABP is produced and released from the peripheral musculature during strenuous exercise, although to a much smaller extent than from the heart. Hence, the origin of the h-FABP can be discriminated by the myoglobin/h-FABP ratio (with a ratio between 2 and 10 indicating cardiac damage and between 20 and 70 implying muscular injury) (44). After this, we used only participants with a myoglobin/h-FABP ratio between 2 and 10 for the multiple regression analysis.

TNF-α and IL-6 and -10.

TNF-α and IL-6 and -10 were measured using a solid-phase two-site chemiluminescent immunometric assay on the IMMULITE® system (Siemens Healthcare, Eschborn, Germany). Expected values in healthy individuals range from nondetectable to 8.1 ng·L−1 for TNF-α, up to 5.9 ng·L−1 for IL-6, and up to 9.1 ng·L−1 for IL-10. The analytical sensitivity is 1.7 ng·L−1 for TNF-α, 2 ng·L−1 for IL-6, and 1 ng·L−1 for IL-10. The measuring range is up to 1000 ng·L−1 for all measured parameters.


hs-CRP was measured quantitatively with an immune turbidimetric method on an AU 2700 analyzer (Olympus Germany, Beckman Coulter, Krefeld, Germany). The measuring range of this assay is 0.7-800 mg·L−1. The interassay CV under actual routine conditions is 1.4% at a concentration of 13 mg·L−1. The intra-assay CV is 0.74% at a concentration of 5.7 mg·L−1. The upper reference limit in healthy volunteers is <5.0 mg·L−1.

Cystatin C.

For quantitative determination of cystatin C in plasma, a particle-enhanced immunoturbidimetric assay run on a COBAS INTEGRA 800 analyzer (Roche Diagnostics) was used. The measuring range of this assay is 0.4-8.0 mg·L−1. Expected values for healthy adults are between 0.5 and 1.09 mg·L−1.


Data analysis was performed using PASW Statistics 18.0.2 (SPSS, Inc., Chicago, IL). For quantitative data, the mean, SD, and range or, if more appropriate (non-normally distributed data), the median and interquartile range (IQR = 25th-75th percentile) were reported for descriptive purposes. Assumption of normal distribution of data was verified by using descriptive methods (skewness, outliers, and distribution plots) and inferential statistics (Shapiro-Wilk test).

Because of the non-normally skewed distribution of the main outcome parameters, transformation by natural logarithm was applied before parametric data analysis (linear regression). Thus, the relative effects of potential explanatory variables were modeled. Particularly, the back-transformation of regression coefficients (using simple exponential function) gives an estimate for the median relative change of the outcome measure by a one-unit increment of the corresponding explanatory variable. On the basis of evidence of recent literature, the variables age, body composition (24), and FABP (11) were considered as relevant confounding and/or explanatory factors in the multivariable analyses. The variance inflation factor (VIF) was used to assess multicolinearity of multivariable explanation factors. Higher VIF values reflect a stronger dependency of a single predictor variable in association to the remaining explanatory variables included in a regression model.

To evaluate changes in serum biomarkers between two time points, the Wilcoxon signed rank test was used. P < 0.05 was considered statistically significant, and Bonferroni correction of P values was applied variablewise within any multiple comparison. Testing was performed two-sided.


Participants' characteristics.

From the initial 150 runners, a total of 102 were eligible for analysis (Fig. 1). Baseline characteristics are given in Table 1.

low diagram of study participants. The MaGIC (Marathon, Genetics, Inflammation and Cardiovascular system) trial participants with blood samples available at baseline and follow-up visits.
Baseline characteristics of marathon participants, mean ± SD.

Kinetics of hs-cTnT and marathon running.

hs-cTnT was measured in all 102 marathon runners at all five visits. In the premarathon visits, the hs-cTnT concentrations were higher than the LLD in approximately half of the samples (51%). Three days after the marathon race, hs-cTnT concentrations were above the LLD in 43 participants (42%). In the prerace samples, the 99th percentile value for hs-cTnT was 18 ng·L−1. At the first visit, two otherwise healthy participants (2%) had an hs-cTnT concentration above the upper reference limit (values of 18 and 44 ng·L−1). This increase above the clinical threshold of 14 ng·L−1 was observable in 91 participants (89%) immediately after the race, in 27 participants (27%) 24 h after the race, and in 4 participants (4%) 72 h after the race.

Immediately after the marathon, hs-cTnT increased significantly with an average of 10.8-fold (P < 0.001) compared with before the race (V2) (Table 2; Fig. 2). Three days after the marathon race, the levels of hs-cTnT concentrations were increased above prerace levels in most runners (P < 0.001).

Concentrations of biomarkers before (within 1 wk before the marathon), immediately after, and 24 and 72 h after the marathon race.
hs-cTnT concentrations before, immediately after, and 24 and 72 h after the marathon race. #P < 0.001. Boxes represent the IQR, whiskers represent most distant values within a range of 1.5 times the IQR, and horizontal lines represent medians. Seven outliers with values between 100 and 200 ng·L−1 at V3 were excluded from the figure because of better presentability. Outliers (filled circles) represent values within a range between 1.5IQR and 3IQR from the upper quartile. Extreme values (stars) represent measures within a range > 3IQR from the upper quartile.

The five participants with the highest hs-cTnT concentrations immediately after the race (hs-cTnT = 147-631 ng·L−1) were 29-51 yr old, were free of cardiovascular risk factors (nonsmoker, mean BMI = 24.6 kg·m−2, mean blood pressure = 117/78 mm Hg), and have completed between one and five marathon races previously. Their hs-cTnT concentrations showed prolonged elevation over the reference limit in both V4 and V5 (mean hs-cTnTV4 = 52.5 ng·L−1, mean hs-cTnTV5 = 16.5 ng·L−1). Further cardiac examinations of these participants (also after exercise) showed normal results.

Levels of additional myocardial markers.

All additional myocardial markers showed a significant increase immediately and 24 h after the race (all P < 0.001 compared with before the race, Table 2).

Regarding h-FABP, within 72 h after the race, no significant changes were seen compared with before the race (P = 0.09). To discriminate between h-FABP from skeletal muscle and from cardiac origin, the myoglobin/h-FABP ratio was calculated (44). The results regarding the origin of h-FABP are shown in Figure 3.

Origin of h-FABP (percent of participants) at different visits. #P < 0.001 compared with before the race.

Levels of inflammation markers.

There were significant changes in all markers of inflammation between the examination 1 wk before and immediately and 1 d after the race (Table 2). At the prerace visits and the visits 24 and 72 h after the race, cytokines were mainly below the LLD. Only at the examination directly after the race did the majority of participants have measurable cytokine levels with a significant increase immediately after the race (IL-6 and IL-10, P < 0.001).

For TNF-α, significant changes were observed during the race. TNF-α values were below the reference limit at the first visit in 44% of the participants, in the week before the marathon in 37% of the participants, immediately after the race in 7% of the participants, 24 h after the race in 23% of the participants, and 72 h after the race in 31% of the participants. There was a significant increase in TNF-α from before to immediately after the race (Table 2).

The levels of hs-CRP 24 h after the marathon were approximately 10-fold higher compared with before the race (P < 0.001) (Fig. 4; Table 2).

hs-CRP concentrations before, immediately after, and 24 and 72 h after the marathon race. #P < 0.001. Boxes represent the IQR, whiskers represent most distant values within a range of 1.5 times the IQR from the upper quartile, and horizontal lines represent medians. Outliers (empty circles) represent values within a range between 1.5IQR and 3IQR from the upper quartile. Extreme values (stars) represent data within a range > 3IQR from the upper quartile.

Renal function.

Cystatin C increased significantly immediately after the marathon race (Table 2).

Multiple regression analysis.

Multiple regression analysis revealed significant associations of increment in hs-cTnT concentration (before vs immediately after the race) and hs-cTnT before the race (n-fold change per one-unit increment = 1.11, confidence interval (CI) = 1.04-1.19, P = 0.003), pre- to postrace difference in IL-6 concentration (n-fold change per 10-unit increment = 1.06, CI = >1.00-1.12, P = 0.046), age (n-fold change per 10-yr increment: 0.70, CI = 0.59-0.83, P < 0.001), body fat (n-fold change per one-unit increment = 1.04, CI = >1.00-1.08, P = 0.034), and pre- to postrace difference in h-FABP (n-fold change per 10-unit increment = 1.06, CI = 1.02-1.11, P = 0.005). In total, 32% of the change in hs-cTnT concentration was explained by this multivariable model (adjusted R2 = 0.29). These results were in accordance with a weak positive correlation observed between changes in IL-6 and hs-cTnT from before to immediately after the race (Spearman ρ = +0.27, P = 0.006). Solely the effect of body fat changed considerably within the multivariable analysis when compared with the result of the univariable analysis (n-fold change of hs-cTnT per one-unit increment in body fat = 1.01, CI = 0.97-1.05, P = 0.645). This difference in effect sizes is explained by the high intercorrelation of body fat and the other explanation factors considered in the multivariable analysis, which is reflected by the comparable high VIF for body fat of 1.64 (VIF for all other clinical parameters < 1.10).

In further bivariate correlation analyses, we found no statistically significant association between renal dysfunction (represented by cystatin C), markers of cardiac stretch (such as NT-proBNP), training history (e.g., previously finished marathon races or training workload), finishing time, or individual exercise intensity during the marathon (measured by %HRmax) and the increase of hs-cTnT immediately after compared with before the race (all P values > 0.05).


Several hypotheses have been raised to explain the phenomenon of increased cardiac markers particularly cTnT after prolonged strenuous exercise. To our knowledge, this study is the first to describe an elevation of the novel hs-cTnT in a large cohort of marathon runners and to simultaneously measure numerous other biochemical markers that have been proposed to be of pathophysiological significance (38). These include markers of inflammation (interleukins, TNF-α, hs-CRP), left ventricular strain (NT-proBNP), renal dysfunction (cystatin C), and ischemia (h-FABP). Although all of these parameters significantly increased during the marathon, their kinetics revealed no clear evidence for permanent structural injury or necrosis of cardiac muscle fibers induced by marathon running.

Kinetics of serum cTn concentration released during irreversible myocyte necrosis is characterized by a steep increase and prolonged elevation for at least 4-7 d. This pattern is significantly different after prolonged strenuous exercise with a distinctively faster decrease (2). This is explained by the relatively long clinical half-life of cTn in serum of ≥20 h due to persistent leaking of troponin from necrotic cardiac cells. In contrast to this relatively long clinical half-life, because of rapid elimination, the true half-life of cTn in the circulation is rather short (approximately 2 h [16]). If ischemia fails to induce necrosis, this short true half-life results in a pattern of cTn, as also seen in exercise-induced alteration. In our study, we observed the latter pattern with cTnT concentrations peaking immediately after the race followed by a rapid decrease within 24 h. Mingels et al. (28) observed a similar pattern in their study investigating 85 marathon runners before and after strenuous exercise. The brief peak within 24 h might be explained by a transient injury of the cell membrane seen in reversible ischemia and myocyte metabolism alteration (decreased adenosine triphosphate availability or altered cytosolic calcium homeostasis). In this case, cTn, of which approximately 5%-8% are unbound and soluble in the cytosol (4), may be released due to loss of membrane integrity and shed into the bloodstream increasing systemic levels of cTn (37). Furthermore, this mechanism seems to be evident in a clinical setting of early reperfusion after ischemia in which the troponin release is of cytoplasmic origin (21,23). Although still hypothetical, the cTn kinetics pattern after strenuous exercise as described in a previous publication (43) as well as in our study (Table 2; Fig. 2) might be explained by this mechanism. This is in accordance with a recently published review (38) and confirmed by cardiac imaging failing to show cardiac damage by cardiac magnetic resonance (e.g., neither evidence of myocardial edema in T2-weighted imaging nor findings of delayed enhancement within the left ventricular myocardium) (29,43). Findings of myocardial injury, as seen in older marathon runners (5), are probably independent of marathon running but rather related to cardiovascular disease or risk factors, particularly smoking.

Kinetic patterns, as for hs-cTnT, are similar for biomarkers of ischemia (e.g., h-FABP). However, when calculating the myoglobin/h-FABP ratio to account for the origin of the released h-FABP (cardiac vs peripheral), our analysis revealed that h-FABP after the marathon is primarily released by peripheral muscle and is not of cardiac origin. Also, the increase of markers of ventricular strain such as NT-proBNP was not correlated with the increase of cTn after the marathon, which is in concordance with previous data (25).

In addition to the ischemia hypothesis, inflammation has been considered to be one possible pathophysiological mechanism for the increase of cTn after strenuous exercise. Like the cardiac markers, all of the proinflammatory markers increased during the marathon race (Table 2). However, we could only find a correlation between changes of IL-6 and changes of cardiac markers. None of the other inflammation parameters showed a significant association with the increase of hs-cTnT concentration during the marathon. This is in accordance with the findings of Scharhag et al. (36) who also found no relationship between exercise-induced increases in immune reactions and NT-proBNP.

Of note is that in our study, all potential influencing factors such as nutrition or intake of anti-inflammatory drugs were excluded. Thus, our measures of inflammation were less biased by these cofactors than those in previous studies (35,36).

Circulating cTnT concentration is, in some parts, dependent on renal function and excretion. We observed a distinctive increase in cystatin C, a very sensitive marker of renal function, after marathon and, consecutively, a decrease in glomerular filtration rate, which is in accordance with a prior study (27). However, renal impairment was not significantly linked to the increase of cTnT concentrations, suggesting that renal elimination of cTn is not responsible for the increase in cTn after strenuous exercise.

Other explanations for individual increases of cTn after marathon running are intensity of exercise or training status (15,31). However, neither a previous study investigating increases of cardiac biomarkers in relation to cardiorespiratory fitness (43) nor our data are able to confirm this. Similarly, we did not find any association between finishing time, number of finished marathon runs, or training history and the increase in both cardiac and inflammatory biomarkers. In contrast to our study, prior studies used finishing time as a surrogate parameter for exercise intensity. Because of the varying interindividual physical conditions, this approach seems insufficient to us, so we used a more direct measurement of cardiac strain (mean %HRmax). Remarkably, cTnT concentration was also not dependent on individual exercise intensity during a marathon as investigated for the first time in our study. Therefore, it has to be concluded that inherent vulnerability to exercise-induced cardiac and inflammatory alterations seems to be more important than possible adaptation mechanisms to training.

Although they have increased in sensitivity, results attained using the new hs-cTn assays have been contested on the basis of their supposed reduced diagnostic specificity (3,9). Interestingly, 3 of the 102 marathon runners had baseline hs-cTnT concentrations above 14 ng·L−1, the 99th percentile of the manufacturer's reference. In light of this finding, upper reference limits should be reevaluated because there are also some other nonpathological circumstances associated with increased cTn levels (17,18).


Our results suggest that the increase of cTnT after prolonged strenuous exercise is likely to be caused by transient strain or altered myocyte metabolism rather than irreversible necrosis of cardiomyocytes. Other hypotheses such as increased inflammation, renal dysfunction, or cardiac stretch-related mechanisms seem to be less important. In addition, we observed no significant association between individually measured exercise intensity, training history, or finishing time and changes of hs-cTnT concentration.

The authors thank Jeff Christle and Dr. Désirée Wilks for careful proofreading of the article. S Braun received access to assays from Roche Diagnostics.

The funding organizations played no role in the design of study, choice of enrolled patients, review and interpretation of data, or preparation or approval of the article. Johannes Scherr and Siegmund Braun contributed equally.

There are no other competing interests to declare.

The article's number is NCT00933218.

The results of the present study do not constitute endorsement by the American College of Sports Medicine.


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