Heart Rate and Oxygen Uptake Kinetics in Type 2 Diabetes Patients – A Pilot Study on the Influence of Cardiovascular Medication on Regulatory Processes

Abstract

The aim of this pilot study was to investigate whether there are differences in heart rate and oxygen uptake kinetics in type 2 diabetes patients, considering their cardiovascular medication. It was hypothesized that cardiovascular medication would affect heart rate and oxygen uptake kinetics and that this could be detected using a standardized exercise test. 18 subjects were tested for maximal oxygen uptake. Kinetics were measured in a single test session with standardized, randomized moderate-intensity work rate changes. Time series analysis was used to estimate kinetics. Greater maxima in cross-correlation functions indicate faster kinetics. 6 patients did not take any cardiovascular medication, 6 subjects took peripherally acting medication and 6 patients were treated with centrally acting medication. Maximum oxygen uptake was not significantly different between groups. Significant main effects were identified regarding differences in muscular oxygen uptake kinetics and heart rate kinetics. Muscular oxygen uptake kinetics were significantly faster than heart rate kinetics in the group with no cardiovascular medication (maximum in cross-correlation function of muscular oxygen uptake vs. heart rate; 0.32±0.08 vs. 0.25±0.06; p=0.001) and in the group taking peripherally acting medication (0.34±0.05 vs. 0.28±0.05; p=0.009) but not in the patients taking centrally acting medication (0.28±0.05 vs. 0.30±0.07; n.s.). It can be concluded that regulatory processes for the achievement of a similar maximal oxygen uptake are different between the groups. The used standardized test provided plausible results for heart rate and oxygen uptake kinetics in a single measurement session in this patient group.

Key words

diabetes - hypertension - obesity

Abbreviations

τ: time constant

ACE: angiotensin-converting enzyme

BMI: body mass index

CCF_lag : lag between maximum of autocorrelation function and cross-correlation function

CCF_max : maximum in cross-correlation function

Q’: cardiac output

ECG: electrocardiography

HR: heart rate

HR_max : maximal heart rate

mBP: mean arterial blood pressure

PRBSs: pseudo-random binary sequences

SV: stroke volume

T2DM: type 2 diabetes mellitus

T2D: type 2 diabetes mellitus patients without treatment with cardiovascular medication

T2D_c : type 2 diabetes mellitus patients treated with centrally acting medication

T2D_p : type 2 diabetes mellitus patients treated with peripherally acting medication

V’O₂max: maximal oxygen uptake

V’O₂musc: muscular oxygen uptake

V’O₂pulm: pulmonary oxygen uptake

WR: work rate

WR_max : maximal work rate

Introduction

Type 2 diabetes mellitus (T2DM) is associated with increased cardiovascular morbidity and mortality. This presents a major challenge to healthcare systems for several aspects [1] [2] [3] [4]. T2DM is often accompanied by comorbidities such as arterial hypertension [5] [6], lipid metabolism disorders [7], overweight or obesity [8]. This cluster of diseases is termed the metabolic syndrome [4].

Centrally acting beta blockers, affecting directly the sympathetic nervous system to decrease heart rate (HR) and consequently cardiac output (Q’), or peripherally acting drugs as angiotensin-converting enzyme (ACE) inhibitors or calcium-channel blockers, influencing the vascular tone, are commonly used to control arterial hypertension in patients with T2DM.

There are indices, that both types of drugs can improve the responses of the cardiovascular, respiratory and metabolic system to changing work rates (WR) at submaximal exercise intensities [9] [10] [11] [12], which can be described with oxygen uptake (V’O₂) kinetics. V’O₂ kinetics give information on the adjustment of the cardiovascular and respiratory and metabolic system and therefore aspects of transport and metabolic processes to changes in WR. Slower V’O₂ kinetics are associated with lower exercise tolerance [13]. Using a circulatory model, considering venous volume and the V’O₂ as well as perfusion of the non-working part of the body, muscular V’O₂ (V’O₂musc) kinetics can be estimated from pulmonary V’O₂ (V’O₂pulm) and HR [14]. This allows for a more detailed analysis of metabolic and circulatory processes.

To the best of our knowledge, no data are available regarding HR kinetics in patients taking cardiovascular drugs. Although faster HR kinetics as indicators for kinetics of Q’ have been considered as a potentially influencing factor for faster V’O₂pulm kinetics [10] [11], they were not yet measured in this context. It was shown that beta blockers increase RR interval variability and vagal tone in patients with former uncomplicated myocardial infarction [15].

Apparently, no data have been published that show the influence of different cardiovascular drugs on HR and V’O₂ kinetics in patients with T2DM. Subjects with medication were either excluded from the analysis [16] [17] [18] [19], no detailed information was provided [20], or patients were included in the study (except patients taking beta blockers) but not analyzed seperately [21] [22].

The aim of the present pilot study is to investigate differences in HR and V’O₂ kinetics between T2DM patients, considering their cardiovascular medication.

The following hypotheses were tested:

• 1) The kinetics responses of V’O₂musc and HR are faster in T2DM patients taking centrally acting medication compared with T2DM patients not taking cardiovascular medication.

• 2) T2DM patients taking mainly peripherally acting medication show faster V’O₂musc and HR kinetics compared with T2DM patients not taking cardiovascular medication.

Materials and Methods

Subjects

18 male subjects participated in the study. All subjects declared that they were not diagnosed with diabetic nephropathy, retinopathy, neuropathy, and/or other cardiovascular complications other than arterial hypertension. None of the subjects performed regular physical activity, and no contraindications for participation in exercise testing were evident. The subjects were selected for 3 subgroups, according to their medication: 6 patients were diagnosed with T2DM and did not take any cardiovascular medication, 6 subjects were diagnosed with T2DM and took mainly centrally acting antihypertensive medication (T2D_c, 2 of these subjects had dyslipidemia); and 6 patients were T2DM patients treated with mainly peripherally acting drugs (T2D_p, one subject had dyslipidemia). One subject taking the calcium-channel-blocker ‘verapamil’ was included in the T2D_c group, because this drug is known to act at heart level. Anthropometric data and differentiation of the subgroups are specified in [Table 1].

Table 1  Anthropometric data of all subjects divided into subgroups.

Group (N=18)		Age [years]	BMI [kg·m−2]	Group of cardiovascular medication	Cardiovascular agent	Duration of type 2 diabetes mellitus since diagnosis [years]
T2D (n=6)	Mean	60	33.0	−	−	3.5
	SD	8	5.9			3.1
T2D p (n=6)	Mean	56	32.8	ACE inhibitors, angiotensin 1 blockers, calcium-channel blockers	Ramipril, enalapril, irbesartan, amlodipine	8.0
	SD	10	4.0			7.2
T2D c (n=6)	Mean	61	32.6	ß-blockers or any combination of ß-blockers and other antihypertensive drugs	Bisoprolol, verapamil, combination of bisoprolol or verapamil with other antihypertensive drugs	4.3
	SD	9	8.0			3.9

BMI: body mass index; SD: standard deviation; T2D: subjects with type 2 diabetes mellitus not taking additional medication; T2D_p: subjects with type 2 diabetes mellitus taking peripherally acting medication; T2D_c: subjects with type 2 diabetes mellitus taking centrally acting medication

Considering the subjects’ anti-diabetic treatment, 4 of the T2D subjects took metformin and 2 did not take any medication. In the T2D_c group 3 subjects took metformin, one took sitagliptin and 2 did not take anti-diabetic drugs. 5 of the T2D_p subjects took metformin and one did not take any anti-diabetic medication. Subjects visited the laboratory twice: The first time, anthropometric measurements, resting electrocardiography (ECG), and a V’O₂max test were performed. Given that no contraindications in the ECG and during V’O₂max test were identified, the subjects returned to the laboratory a second time for a cardiorespiratory kinetics test.

A positive vote of the ethics committee of the German Sport University Cologne, in accordance with the Declaration of Helsinki (1964 including the amendments until 2013), was available before the beginning of the tests. All subjects gave their written informed consent prior to the testing procedures.

V’O₂max testing

The subjects were tested using the protocol recommended by the World Health Organization in a seated position on a cycle ergometer (Ergoline ER 900, Ergoline GmbH, Bitz, Germany). WR was increased by 25 W every 2 min until subjective exhaustion or the occurrence of one of the common reasons for test termination (e. g., ST segment depression or couplets of premature heart contractions).

HR was measured continuously via 12-lead ECG (GE Medical Systems, Information Technologies, Munich, Germany) and recorded by an AMEDTEC ECGpro^® V.3.66 (MedizintechnikAue GmbH, Aue, Germany). Pulmonary data were assessed breath by breath via a ZAN 600 (ZAN Messgeräte GmbH, Oberthulba, Germany) including the algorithms of Beaver et al. [23]. All instruments were calibrated according to the manufacturer’s suggestions before all tests. For maximal oxygen uptake (V’O₂max) the highest 30 s averaged value of the highest achieved WR was determined as the maximum value. The Achievement of true V’O₂max was assumed, if a plateau in V’O₂ (increase in V’O₂≤2.1 ml kg⁻¹·min⁻¹) despite an increase in WR (as the primary criterion) appeared. When no plateau occurred, V’O₂max was assumed when HR_max was higher than 200 beats min⁻¹ minus the years of age [24] and the maximal respiratory exchange ratio was not lower than 1.06 [25] [26]. All subjects included in this study achieved V’O₂max according to the predefined criteria, which was then normalized to body mass.

Cardiorespiratory kinetics test

Subjects were tested on a semi-recumbent cycle ergometer (Cardiac Stress Table, Lode B.V., Netherlands; backrest at 45°, legs at 42°, relative to ground level). Pseudo-random binary sequences (PRBSs) were used as the WR protocol. The protocol consisted of 180 s of rest; 200 s of 30 W, as low steady state (Low); followed by two 300 s periods of PRBS (PRBS1 and PRBS2), with changing WRs between 30 and 80 W; and ended with 200 s of 80 W, as high steady state (High) ([Fig. 1a]). The cadence was maintained at 60 rpm. HR was assessed beat to beat via electrocardiography; stroke volume (SV) was measured beat to beat via impedance cardiography (Task Force^® Monitor, CNSystems Medizintechnik AG, Graz, Austria). Pulmonary gas exchange data were determined breath by breath (ZAN 680, ZAN Meßgeräte GmbH, Oberthulba, Germany), incorporating the algorithms of Beaver et al. [23]. From SV and HR, Q’ was calculated. The instruments were calibrated before each measurement, according to the manufacturer’s guidelines. For reduction of noise, data were filtered with a low-pass filter (0.1 Hz). Data were synchronized via trigger signals and interpolated to 1 s intervals for homogeneous sampling [27].

Fig. 1 Demonstration of data acquisition and analysis. a: Data acquisition during the work rate protocol; b: Data after time series analysis. The arrows indicate the respective maximum of the cross-correlation course (CCF_max). Lag: lag of cross-correlation function; ACF: autocorrelation function; CCF: cross-correlation function; HR: heart rate; V’O₂musc: muscular oxygen uptake; V’O₂pulm: pulmonary oxygen uptake; Rest: resting period; Low: 30 W constant phase; PRBS: pseudo-random binary sequence; High: 80 W constant phase; Recovery: recovery phase.

For analysis of cardiorespiratory kinetics, time series analysis was applied and V’O₂musc kinetics were estimated from HR and V’O₂pulm [14]. Briefly, the PRBS WR protocol was auto-correlated, which resulted in a triangular shape and each parameter was cross-correlated with the WR protocol ([Fig. 1b]). The autocorrelation can be approximated as a WR impulse. The cross-correlation function was interpreted as the response of the respective parameter to this impulse. The kinetics of the parameters were summarized by the maximum in cross-correlation function (CCF_max, compare [Fig. 1b]) and the related lag (CCF_lag). Higher CCF_max indicate faster response times of the particular parameter. From CCF_max, the time constant τ can be estimated. Further, V’O₂musc and the corresponding kinetics were calculated using the backward calculation method. This method is based on a circulatory model with 2 compartments (working and remainder part). V’O₂musc was estimated considering a certain venous blood volume between muscle and mouth, as well as V’O_2, and perfusion of the remainder of the body (see [14] for further details on the method). This method makes it possible to distinguish between V’O₂musc and V’O₂pulm, which leads to a more detailed analysis of the cardiorespiratory and metabolic regulation considering transport processes. For kinetics comparisons, V’O₂musc and HR kinetics have been considered.

Statistical analysis

Between-group comparisons for the factors ‘CCF_max(V’O₂musc)’ and ‘CCF_max(HR)’ (‘Parameter x Group’) were performed via 2-factorial ANOVA. The following post hoc comparisons were implemented via LSD test. For the means of HR, mean arterial blood pressure (mBP), V’O₂pulm, V’O₂musc, SV and Q’ during the different steps (Low, PRBS1, PRBS2, High) of the PRBS protocol, 2-factorial ANOVA (‘Step x Group’) were applied. Since each group included only 6 subjects, Kruskal-Wallis tests were used to compare V’O₂max, HR_max, maximal WR (WR_max), body mass index (BMI), age, resting mBP, fasting blood glucose and glycosylated hemoglobin (HbA_1c) between the groups. When applicable, post hoc tests were adjusted via Bonferroni correction.

Results

Anthropometric data as well as cardiorespiratory and metabolic capacities are shown in [Table 2].

Table 2  Means and standard deviations of anthropometric and glycemic data, and parameters of cardiorespiratory capacities.

Group (N=18)		V’O2max [ml·min−1·kg−1]	WRmax [Watt]	HRmax [min−1]	Fasting blood glucose [mg·dl−1]	HbA1c [% (mmol·mol−1)]	Resting mBP [mmHg]
T2D (n=6)	Mean	21.3	146	146	160	7.1 (54)	108
	SD	5.2	25	12	81	1.9 (21)	7
TD2 p (n=6)	Mean	23.0	158	153	150	7.2 (56)	105
	SD	6.7	34	25	29	1 (11)	7
TD2 c (n=6)	Mean	19.2	133	131	140	6.4 (47)	97
	SD	5.1	13	17	24	1.4 (15)	9

V’O₂max: maximum oxygen uptake; WR_max: maximum work rate; HR_max: maximum heart rate; HbA1c: glycosylated hemoglobin; mBP: mean arterial blood pressure; T2D: subjects with type 2 diabetes mellitus not taking additional medication; T2D_c: subjects with type 2 diabetes mellitus taking centrally acting medication; T2D_p: subjects with type 2 diabetes mellitus taking peripherally acting medication

No significant differences between groups were observed regarding V’O₂max, WR_max, HR_max, resting mBP, fasting blood glucose or HbA1_c.

For the absolute values of HR during the WR protocol, a significant between-group effect was found (p=0.01). T2D_c was significantly different to both T2D (p=0.014) and T2D_p (p=0.005), which did not differ. These group differences for HR were found for all analyzed phases. For all other parameters, no statistical group differences were found, as listed in [Table 3].

Table 3  Analyses of cardiorespiratory parameters of all WR steps.

Group (N=18)	WR step	HR [min−1]		V’O2pulm [L·min−1]		V’O2musc [L·min−1]		mBP [mmHg]		SV [mL]		Q’ [L·min−1]
		Mean	SD	Mean	SD	Mean	SD	Mean	SD	Mean	SD	Mean	SD
T2D (n=6)	Low	96	8	1.0	0.1	0.7	0.1	115	11	85.0	24.8	8.1	1.8
	PRBS1	103	8	1.3	0.1	0.9	0.1	117	10	86.8	21.7	8.7	2.0
	PRBS2	105	9	1.4	0.1	1.0	0.1	116	6	86.2	19.4	8.9	2.0
	High	116	10	1.6	0.2	1.2	0.2	122	11	84.4	12.6	9.8	2.4
T2D p (n=6)	Low	98	10	1.1	0.1	0.7	0.1	112	8	85.7	28.0	8.4	2.0
	PRBS1	106	11	1.3	0.1	1.0	0.1	114	10	86.7	26.7	9.1	2.1
	PRBS2	108	11	1.3	0.1	1.0	0.1	112	10	89.7	32.6	9.2	2.1
	High	119	15	1.6	0.1	1.3	0.1	117	12	90.8	35.4	10.2	2.2
T2D c (n=6)	Low	80*	12	1.1	0.2	0.7	0.1	106	9	101.6	16.5	8.1	1.9
	PRBS1	86*	12	1.3	0.2	0.9	0.1	111	7	99.7	12.2	8.6	1.9
	PRBS2	88*	11	1.3	0.2	1.0	0.1	111	8	98.1	14.3	8.8	2.0
	High	96*	12	1.6	0.2	1.2	0.1	114	8	98.0	22.3	9.7	2.1

HR: heart rate; V’O₂pulm: pulmonary oxygen uptake; V’O₂musc: muscular oxygen uptake; mBP: mean arterial blood pressure; SV: stroke volume; Q’: cardiac output; SD: standard deviation; T2D: subjects with type 2 diabetes mellitus not taking additional medication; T2D_c: subjects with type 2 diabetes mellitus taking centrally acting medication; T2D_p: subjects with type 2 diabetes mellitus taking peripherally acting medication; Low: 30 W low steady state; PRBS1: 53.3 W, mean value of first pseudo-random binary sequence; PRBS2: 53.3 W, mean value of second pseudo-random binary sequence; High: 80 W high steady state; WR: work rate; *indicates significantly different from T2D and T2D_p (p<0.05)

Static linearity, as a prerequisite for the application of time series analysis, was analyzed and proved for all groups. The respective regression functions for HR and V’O₂pulm (during Low, PRBS1, PRBS2 and High; n=4) for each group are shown in [Table 4].

Table 4  Static linearity for HR (heart rate) and V’O₂pulm (pulmonary oxygen uptake) during the PRBS WR protocol.

Group (N=18)	HR			V’O2pulm
	Slope	Intercept	R2	Slope	Intercept	R2
T2D (n=6)	0.40	83.46	0.98	0.017	0.7	0.99
TD2 p (n=6)	0.43	84.76	0.99	0.011	0.74	0.99
TD2 c (n=6)	0.32	70.43	0.98	0.011	0.71	0.99

HR: heart rate; V’O₂pulm: pulmonary oxygen uptake; T2D: subjects with type 2 diabetes mellitus not taking additional medication; T2D_p: subjects with type 2 diabetes mellitus taking peripherally acting medication; T2D_c: subjects with type 2 diabetes mellitus taking centrally acting medication

ANOVA Parameter x Group with repeated measures on CCF_max(HR) and CCF_max(V’O₂musc), presented in [Fig. 2], showed a significant main effect on the Parameter x Group (p=0.004, partial; ŋ²=0.515) and Parameter (p=0.005, partial; ŋ²=0.424). Post hoc tests revealed significant differences between CCF_max(V’O₂musc) and CCF_max(HR) for T2D (p=0.001) and T2D_p (p=0.009) but not for T2D_c. Between groups, no significant differences were identified following ANOVA.

Fig. 2 Means and standard errors for CCF_max of HR and V’O₂ in the T2D, T2D_c and T2D_p group. CCF_max(V’O₂musc) was significantly different from CCF_max(HR) in T2D (p=0.001) and T2D_p (p=0.009) but T2D_c was not. CCF_max: maximum of cross-correlation function; CCF_lag: lag of cross-correlation function; HR: heart rate; V’O₂musc: muscular oxygen uptake. *Significantly different.

For comparisons with data from other publications, CCF_max values of V’O₂musc, V’O₂pulm and HR were converted into time constants (τ) (see [14]). These time constants should be regarded as rough estimates, since they were obtained from CCF_max values [Table 5] .

Table 5  Time constants of HR, V’O₂musc and V’O₂pulm kinetics and model parameters.

Group (N=18)	τHR		τV’O2musc		τV’O2pulm		Vv		Q'rem		V’O2rem
	[s]		[s]		[s]		[ml·min−1]		[ml·min−1]		[L·min−1]
	Mean	SD	Mean	SD	Mean	SD	Mean	SD	Mean	SD	Mean	SD
T2D (n=6)	69.5	28.2	49.7	23.8	66.4	20.3	2816.7	892.0	3111.1	1294.0	0.38	0.06
T2D p (n=6)	53.8	12.7	41.8	10.5	50.9	15.4	2308.3	1081.9	3219.8	1676.5	0.34	0.04
T2D c (n=6)	52.1	17.6	57.1	18.3	58.0	16.9	3100.0	834.9	2386.0	536.8	0.35	0.07

HR: heart rate, V’O₂musc: muscular oxygen uptake; V’O₂pulm: pulmonary oxygen uptake; V_v: venous volume; Q’_rem: perfusion of the remainder of the body; V’O₂rem: oxygen uptake of the remainder of the body; τ: time constant; SD: standard deviation; T2D: subjects with type 2 diabetes mellitus not taking additional medication; T2D_p: subjects with type 2 diabetes mellitus taking peripherally acting medication; T2D_c: subjects with type 2 diabetes mellitus taking centrally acting medication

Discussion

The aim of this study was to investigate differences in HR and V’O₂musc kinetics between groups of patients with T2DM, considering their cardiovascular medication. For comparisons between the groups, a standardized WR protocol was used and V’O₂musc kinetics were estimated from HR and V’O₂pulm applying a circulatory model.

• 1) Descriptively, HR kinetics, represented by CCF_max, were faster in T2D_c patients, compared with T2D patients not taking cardiovascular medication. V’O₂musc kinetics seemed slower in T2D_c subjects, but the results were not significant.

• 2) V’O₂musc kinetics of the T2D_p patients were slightly faster compared with the T2D patients without cardiovascular medication, but this was not significant. HR kinetics of the T2D_p were slightly faster compared with the T2D groups, but this difference was also not significant.

Although no statistical differences regarding direct group comparisons were identified, a significant main effect for Parameter x Group including V’O₂musc and HR kinetics was found. V’O₂musc kinetics were significantly faster than HR kinetics within the T2D_p and T2D groups, but not within the T2D_c group. For the T2D_c group, V’O₂musc kinetics seemed slower than HR kinetics. For comparison, HR kinetics have been shown to be faster than V’O₂musc kinetics in healthy young subjects [14] [28]. In sedentary aged subjects, V’O₂musc kinetics were faster (but not significantly) than HR kinetics [29]. This is in line with the results of the T2D_p and T2D group, in the present study. Taniguchi et al. [10] showed a positive effect of beta blockers (after one year of treatment) and Dayi et al. [11] for ACE inhibitors (administered shortly before the exercise test) on V’O₂pulm kinetics in hypertensive subjects and in patients with dilated cardiomyopathy. They explained this effect by improved cardiac function (improved left ventricular ejection fraction). Descriptively, the results of this study show this positive effect of the cardiovascular medication on HR kinetics compared with the group not taking cardiovascular medication ([Fig. 2]). Nevertheless, the effect was insignificant and did not result in faster V’O₂musc kinetics compared with the T2D group.

Overall, the disease status of the T2D_c group might have been worse, since some of them were treated with more than one cardiovascular medication ([Table 1]). Between the 3 groups, no obvious differences in V’O₂max were evident. Hence, regulatory processes to achieve the same V’O₂max seem to be different and influenced by cardiovascular medication and/or disease status.

The very slow HR kinetics in the T2D patients (no cardiovascular medication) in the present study were also observed in other studies, comparing T2DM patients with healthy controls [19] [21] [22]. It has been shown, that T2DM influences cardiac mechanoenergetic efficiency and cardiac hypertrophy [30] [31] [32] [33]. The respective medication in the T2D_c and T2D_p group might have improved cardiac function, as has been supposed in previous studies [9] [10] [11]. However, as can be observed in [Fig. 2] this did not lead to faster V’O₂musc kinetics compared to the T2D group.

The patients analyzed in this study were selected for the subgroups, considering the group of cardiovascular medication they were taking ([Table 1]). The possiblity of the underlying disease to influence the obtained results cannot be excluded. Anyway, the applied method showed that differences can be detected between the analyzed patient groups even in a small sample size. Regulatory processes between T2D_c and the other 2 groups were different.

To be comparable with other studies, time constants were calculated as rough estimates from CCF_max. The time constants calculated in this study were within the given ranges from the literature, where values for τV’O₂musc (in the literature represented by the phase 2 τ of V’O₂pulm) as a response to WRs vary from 41 s to 58 s and values for HR vary from 51 s to 81 s for T2DM [16] [17] [19] [20] [21] [22] [34]. Since the applied test delivers plausible results within a single test session, without the need to adjust WR ranges or the need to fit data to an explicit model, the applied test might be relevant for clinical routine.

Conclusion

Even though this study can only be treated as a pilot study, the different effects of the peripherally and centrally acting medication and/or disease conditions on HR and V’O₂musc kinetics without any obvious differences in V’O₂max are worth being considered. In the T2D and T2D_p group, but not the T2D_c group, V’O₂musc kinetics were significantly faster than HR kinetics. This shows that regulatory processes for the achievement of a similar V’O₂max are different between the groups. Future, larger studies analyzing T2DM patients should consider the influence of cardiovascular medication on HR and V’O₂musc kinetics, rather than excluding those patients from analysis.

Conflict of Interest

None.

Acknowledgements

The study was supported by the DLR (Deutsches Zentrum für Luft- und Raumfahrt), Germany (FKZ 50WB1426).

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