Skeletal muscle VO₂ kinetics from cardio-pulmonary measurements: assessing distortions through O₂ transport by means of stochastic work-rate signals and circulatory modelling

Sentinel fall presenting to the emergency department (SeFallED) - protocol of a complex study including long-term observation of functional trajectories after a fall, exploration of specific fall risk factors, and patients' views on falls prevention

BACKGROUND

Falls are a leading cause for emergency department (ED) visits in older adults. As a fall is associated with a high risk of functional decline and further falls and many falls do not receive medical attention, the ED is ideal to initiate secondary prevention, an opportunity generally not taken. Data on trajectories to identify patients, who would profit the most form early intervention and to examine the impact of a fall event, are lacking. To tailor interventions to the individual's needs and preferences, and to address the whole scope of fall risks, we developed this longitudinal study using an extensive assessment battery including dynamic balance and aerobic fitness, but also sensor-based data. Additionally, participative research will contribute valuable qualitative data, and machine learning will be used to identify trips, slips, and falls in sensor data during daily life.

METHODS

This is a mixed-methods study consisting of four parts: (1) an observational prospective study, (2) a randomized controlled trial (RCT) to explore whether a diagnostic to measure reactive dynamic balance influences fall risk, (3) machine learning approaches and (4) a qualitative study to explore patients' and their caregivers' views. We will target a sample size of 450 adults of 60 years and older, who presented to the ED of the Klinikum Oldenburg after a fall and are not hospitalized. The participants will be followed up over 24 months (within four weeks after the ED, after 6, 12 and 24 months). We will assess functional abilities, fall risk factors, participation, quality of life, falls incidence, and physical activity using validated instruments, including sensor-data. Additionally, two thirds of the patients will undergo intensive testing in the gait laboratory and 72 participants will partake in focus group interviews.

DISCUSSION

The results of the SeFallED study will be used to identify risk factors with high predictive value for functional outcome after a sentinel fall. This will help to (1) establish a protocol adapted to the situation in the ED to identify patients at risk and (2) to initiate an appropriate care pathway, which will be developed based on the results of this study.

TRIAL REGISTRATION

DRKS (Deutsches Register für klinische Studien, DRKS00025949 ). Prospectively registered on 4^th November, 2021.

Cardiorespiratory kinetics in exercise physiology: estimates and predictions using randomized changes in work rate

Purpose

Kinetics of cardiorespiratory parameters (CRP) in response to work rate (WR) changes are evaluated by pseudo-random binary sequences (PRBS testing). In this study, two algorithms were applied to convert responses from PRBS testing into appropriate impulse responses to predict steady states values and responses to incremental increases in exercise intensity.

Methods

13 individuals (age: 41 ± 9 years, BMI: 23.8 ± 3.7 kg m⁻²), completing an exercise test protocol, comprising a section of randomized changes of 30 W and 80 W (PRBS), two phases of constant WR at 30 W and 80 W and incremental WR until subjective fatigue, were included in the analysis. Ventilation (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}_{{\text{E}}}$$\end{document}V˙E), O₂ uptake (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2), CO₂ output (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{CO}}_{2}$$\end{document}V˙CO2) and heart rate (HR) were monitored. Impulse responses were calculated in the time domain and in the frequency domain from the cross-correlations of WR and the respective CRP.

Results

The algorithm in the time domain allows better prediction for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{CO}}_{2}$$\end{document}V˙CO2, whereas for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}_{{\text{E}}}$$\end{document}V˙E and HR the results were similar for both algorithms. Best predictions were found for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2 and HR with higher (3–4%) 30 W steady states and lower (1–4%) values for 80 W. Tendencies were found in the residuals between predicted and measured data.

Conclusion

The CRP kinetics, resulting from PRBS testing, are qualified to assess steady states within the applied WR range. Below the ventilatory threshold, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2 and HR responses to incrementally increasing exercise intensities can be sufficiently predicted.

Influence of the fitting window on the O2 uptake kinetics at the onset of moderate intensity exercise

The O₂ uptake (V̇o₂) data at the onset of an exercise are usually fitted with a mono-exponential function, after removal of the data pertaining to a conventional initial time period (ΔTr) lasting ∼20 s. We performed a thorough quantitative analysis on the effects of removing data pertaining to different ΔTr, aiming at identifying an objective method to establish the appropriate ΔTr. Breath-by-breath O₂ uptake responses, acquired from 25 healthy adults performing a step moderate-intensity exercise, and 10⁴ simulated biexponential responses, were analyzed. For all the responses, the kinetic parameters of a mono-exponential function and the corresponding asymptotic standard errors (ASEs) were estimated by nonlinear regression, removing the data pertaining to progressively longer initial periods (1 s each) up to 60 s. Four methods to establish objectively ΔTr were compared. The minimum estimated τ was obtained for ΔTr ≅ 35 s in both the V̇o₂ and simulated data, that was about 30% lower compared with that obtained for ΔTr ≅ 0s. The average ASE values remained quite constant up to ΔTr ≅ 35 s, thereafter they increased remarkably. The τ used to generate the simulated response fell within the confidence intervals of the estimated τ in ∼85% of cases for ΔTr = 20 s ("20 s-w" method); this percentage increased to ∼92% of cases when ΔTr was established according to both the minimum τ and its narrowest confidence interval ("Mixed" method). In conclusion, the effects of removing V̇o₂ data pertaining to different ΔTr are remarkable. The "Mixed" method provided estimated parameters close to those used to generate the simulated responses and is thus endorsed.NEW & NOTEWORTHY We propose a method to objectively establish the initial time period to be removed from the fitting window when, using a mono-exponential model, the kinetics of the fundamental component is determined on breath-by-breath O₂ uptake data collected at the onset of a moderate-intensity exercise. Innovative statistical parameters ("Coverage" and "Concordance_5%," applicable on simulated responses) were used to compare its performance with that of other three methods. The proposed method yielded the best "Coverage" and "Concordance_5%."

Confinement, partial sleep deprivation and defined physical activity-influence on cardiorespiratory regulation and capacity

INTRODUCTION

Adequate cardiorespiratory fitness is of utmost importance during spaceflight and should be assessable via moderate work rate intensities, e.g., using kinetics parameters. The combination of restricted sleep, and defined physical exercise during a 45-day simulated space mission is expected to slow heart rate (HR) kinetics without changes in oxygen uptake ([Formula: see text]) kinetics.

METHODS

Overall, 14 crew members (9 males, 5 females, 37 ± 7 yrs, 23.4 ± 3.5 kg m^-2) simulated a 45-d-mission to an asteroid. During the mission, the sleep schedule included 5 nights of 5 h and 2 nights of 8 h sleep. The crew members were tested on a cycle ergometer, using pseudo-random binary sequences, changing between 30 and 80 W on day 8 before (MD-8), day 22 (MD22) and 42 (MD42) after the beginning and day 4 (MD + 4) following the end of the mission. Kinetics information was assessed using the maxima of cross-correlation functions (CCF_max). Higher CCF_max indicates faster responses.

RESULTS

CCF_max(HR) was significantly (p = 0.008) slower at MD-8 (0.30 ± 0.06) compared with MD22 (0.36 ± 0.06), MD42 (0.38 ± 0.06) and MD + 4 (0.35 ± 0.06). Mean HR values during the different work rate steps were higher at MD-8 and MD + 4 compared to MD22 and MD42 (p < 0.001).

DISCUSSION

The physical training during the mission accelerated HR kinetics, but had no impact on mean HR values post mission. Thus, HR kinetics seem to be sensitive to changes in cardiorespiratory fitness and may be a valuable parameter to monitor fitness. Kinetics and capacities adapt independently in response to confinement in combination with defined physical activity and sleep.

The Fuzzy Kinetics Index: an indicator conflating cardiorespiratory kinetics during dynamic exercise

Purpose

The aim of the present study was to develop a novel index using fuzzy logic procedures conflating cardiorespiratory and pulmonary kinetics during dynamic exercise as a representative indicator for exercise tolerance.

Methods

Overall 69 data sets were re-analyzed: (age: 29 ± 1.2 y [mean ± SEM], height: 179 ± 1.0 cm; body mass: 78 ± 1.4 kg; peak oxygen uptake (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot {\text{V}}$$\end{document}V˙˙O_2peak): 48 ± 1.1 ml·min⁻¹·kg⁻¹), that comprised pseudo random binary sequence work rate (WR) changes between 30 and 80 W on a cycle ergometer, with additional voluntary exhaustion to estimate \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot {\text{V}}$$\end{document}V˙O_2peak. Heart rate (HR), stroke volume (SV) and gas exchange (pulmonary oxygen uptake (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot {\text{V}}$$\end{document}V˙O_2pulm)) were measured beat-to-beat and breath-by-breath, respectively. For estimation of muscle oxygen uptake (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot {\text{V}}$$\end{document}V˙O_2musc) kinetics and for the analysis of kinetic responses of the parameters of interest (perfusion (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot {\text{Q}}$$\end{document}Q˙ = HR·SV), \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot {\text{V}}$$\end{document}V˙O_2pulm, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot {\text{V}}$$\end{document}V˙O_2musc) the approach of Hoffmann et al. (2013) was applied. For calculation of the Fuzzy Kinetics Index \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot {\text{Q}}$$\end{document}Q˙, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot {\text{V}}$$\end{document}V˙O_2pulm, and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot {\text{V}}$$\end{document}V˙O_2musc were used as input variables for the subsequent fuzzy- and defuzzyfication procedures.

Results

For both absolute and relative \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot {\text{V}}$$\end{document}V˙O_2peak a significant correlation has been observed with FKI, whereas the correlation coefficient is higher for relative (r = 0.430; p < 0.001; n = 69) compared to absolute \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot {\text{V}}$$\end{document}V˙O_2peak (r = 0.358; p < 0.01; n = 69). No significant correlations have been found between FKI and age, height or body mass (p > 0.05 each).

Conclusions

The significant correlations between FKI and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot {\text{V}}$$\end{document}V˙O_2peak represent a physiological connection between the regulatory and the capacitive system and its exercise performance. In turn, the application of FKI can serve as an indicator for healthy participants to assess exercise tolerance and sport performance.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00421-021-04611-w.

Time-series analysis of heart rate and blood pressure in response to changes in work rate before and after 60 days of 6° head down tilt bed rest

Purpose

Cardiovascular regulation during exercise, described using time series analysis, is expected to be attenuated after bed rest (BR) and this effect will be dampened by a reactive jumps countermeasure.

Methods

Twenty subjects (29 ± 6 years, 23.6 ± 1.7 kg m⁻²) were tested on a cycle ergometer 9 days (BDC-9) before the beginning of BR as well as 2 (R + 2) and 13 days (R + 13) after the end of BR, applying moderate pseudo-random binary (PRBS) work rate changes. Heart rate (HR) and mean arterial blood pressure (mBP) were measured beat-to-beat and interpolated to 1 s intervals. HR and mBP were cross-correlated [CCF(HR-mBP)] during the PRBS. Eleven subjects participated in a reactive jump countermeasure (JUMP) during the BR period, the other part of the group served as control group (CTRL).

Results

In the CTRL group, significantly lower CCF(HR-mBP) values during BDC-9 were observed compared to R + 2 during the lags 20–25 s and significantly higher values during the lags − 39 s to − 35 s. In the JUMP group, significantly lower CCFs were only observed at R + 2 compared with BDC-9 during the lags 23 s and 24 s, whereas the CCFs for BDC-9 were significantly higher at several lags compared with R + 13.

Conclusion

Attenuations in the regulation of the cardiovascular system during cycling exercise after BR were found in the CTRL group of the RSL study. Cardiovascular regulation in the JUMP group was improved compared to values before the beginning of BR, suggesting the effectiveness of the reactive jumps countermeasure to mitigate the deleterious effects of prolonged BR.

Relationship between maximal aerobic power with aerobic fitness as a function of signal-to-noise ratio

Efforts to better understand cardiorespiratory health are relevant for the future development of optimized physical activity programs. We aimed to explore the impact of the signal quality on the expected associations between the ability of the aerobic system in supplying energy as fast as possible during moderate exercise transitions with its maximum capacity to supply energy during maximal exertion. It was hypothesized that a slower aerobic system response during moderate exercise transitions is associated with a lower maximal aerobic power; however, this relationship relies on the quality of the oxygen uptake data set. Forty-three apparently healthy participants performed a moderate constant work rate (CWR) followed by a pseudorandom binary sequence (PRBS) exercise protocol on a cycle ergometer. Participants also performed a maximum incremental cardiopulmonary exercise testing (CPET). The maximal aerobic power was evaluated by the peak oxygen uptake during the CPET, and the aerobic fitness was estimated from different approaches for oxygen uptake dynamics analysis during the CWR and PRBS protocols at different levels of signal-to-noise ratio. The product moment correlation coefficient was used to evaluate the correlation level between variables. Aerobic fitness was correlated with maximum aerobic power, but this correlation increased as a function of the signal-to-noise ratio. Aerobic fitness is related to maximal aerobic power; however, this association appeared to be highly dependent on the data quality and analysis for aerobic fitness evaluation. Our results show that simpler moderate exercise protocols might be as good as maximal exertion exercise protocols to obtain indexes related to cardiorespiratory health.NEW & NOTEWORTHY Optimized methods for cardiorespiratory health evaluation are of great interest for public health. Moderate exercise protocols might be as good as maximum exertion exercise protocols to evaluate cardiorespiratory health. Pseudorandom or constant workload moderate exercise can be used to evaluate cardiorespiratory health.

Effect of Lower Body Negative Pressure on Phase I Cardiovascular Responses at Exercise Onset

We hypothesised that vagal withdrawal and increased venous return interact in determining the rapid cardiac output (CO) response (phase I) at exercise onset. We used lower body negative pressure (LBNP) to increase blood distribution to the heart by muscle pump action and reduce resting vagal activity. We expected a larger increase in stroke volume (SV) and smaller for heart rate (HR) at progressively stronger LBNP levels, therefore CO response would remain unchanged. To this aim ten young, healthy males performed a 50 W exercise in supine position at 0 (Control), −15, −30 and −45 mmHg LBNP exposure. On single beat basis, we measured HR, SV, and CO. Oxygen uptake was measured breath-by-breath. Phase I response amplitudes were obtained applying an exponential model. LBNP increased SV response amplitude threefold from Control to −45 mmHg. HR response amplitude tended to decrease and prevented changes in CO response. The rapid response of CO explained that of oxygen uptake. The rapid SV kinetics at exercise onset is compatible with an increased venous return, whereas the vagal withdrawal conjecture cannot be dismissed for HR. The rapid CO response may indeed be the result of two independent yet parallel mechanisms, one acting on SV, the other on HR.

Cardiovascular regulation: associations between exercise and head-up tilt

It was hypothesized that faster cardiorespiratory kinetics during exercise are associated with higher orthostatic tolerance. Cardiorespiratory kinetics of 14 healthy male subjects (30 ± 4 years, 179 ± 8 cm, 79 ± 8 kg) were tested on a cycle ergometer during exercise with changing work rates of 30 and 80 W. Pulmonary oxygen uptake ( ) was measured breath-by-breath and heart rate (HR), mean arterial blood pressure (MAP), and total peripheral resistance (TPR) were measured beat-to-beat. Muscular oxygen uptake ( ) was estimated from HR and . Kinetic parameters were determined by time-series analysis, using cross-correlation functions (CCF_max(x)) between the parameter and the work rate. Cardiovascular regulations of MAP, HR, and TPR during orthostatic stress were measured beat-to-beat on a tilt seat. Changes between the minima and maxima during the 6° head-down tilt and the 90° head-up tilt positions were calculated for each parameter (Δ_tilt-up). correlated significantly with ΔTPR_tilt-up (r = 0.790, p ≤ 0.001). CCF_max(HR) was significantly correlated with ΔHR_tilt-up (r = -0.705, p = 0.002) and the amplitude in HR from 30 to 80 W (r_SP = -0.574, p = 0.016). The observed correlations between cardiorespiratory regulation in response to exercise and orthostatic stress during rest might allow for a more differential analysis of the underlying mechanisms of orthostatic intolerance in, for example, patient groups.

Impact of venous return on pulmonary oxygen uptake kinetics during dynamic exercise: in silico time series analyses from muscles to lungs

The aim of the present study was to investigate whether a single-compartment (SCM) and a multi-compartment (MCM) venous return model will produce significantly different time-delaying and distortive effects on pulmonary oxygen uptake (V̇o2pulm) responses with equal cardiac outputs (Q̇) and muscle oxygen uptake (V̇o2musc) inputs. For each model, 64 data sets were simulated with alternating Q̇ and V̇o2musc kinetics—time constants (τ) ranging from 10 to 80 s—as responses to pseudorandom binary sequence work rate (WR) changes. Kinetic analyses were performed by using cross-correlation functions (CCFs) between WR with V̇o2pulm and V̇o2musc. Higher maxima of the CCF courses indicate faster system responses—equal to smaller τ values of the variables of interest (e.g., τV̇o2musc). The models demonstrated a highly significant relationship for the resulting V̇o2pulm responses ( r = 0.976, P < 0.001, n = 64). Both models showed significant differences between V̇o2pulm and V̇o2musc kinetics for τV̇o2musc ranging from 10 to 30 s ( P < 0.05 each). In addition, a significant difference in V̇o2pulm kinetics ( P < 0.05) between the models was observed for very fast V̇o2musc kinetics (τ = 10 s). The combinations of fast Q̇ dynamics and slow V̇o2musc kinetics yield distinct deviations in the resultant V̇o2pulm responses compared with V̇o2musc kinetics. Therefore, the venous return models should be used with care and caution if the aim is to infer V̇o2musc by means of V̇o2pulm kinetics. Finally, the resultant V̇o2pulm responses seem to be complex and most likely unpredictable if no cardiodynamic measurements are available in vivo.

NEW & NOTEWORTHY A single-compartment and a multi-compartment venous return model were tested to see whether they result in different pulmonary oxygen uptake (V̇o2pulm) kinetics from equal cardiac output and muscle oxygen uptake (V̇o2musc) kinetics. To infer V̇o2musc kinetics by means of V̇o2pulm kinetics, both models should only be used for V̇o2musc time constants ranging from 40 to 80 s. The resultant V̇o2pulm responses seem to be complex and most likely unpredictable if no cardiodynamic measurements are available.

Impact of 60 days of 6° head down tilt bed rest on muscular oxygen uptake and heart rate kinetics: efficacy of a reactive sledge jump countermeasure

PURPOSE

The effects of 60 days of head down tilt bed rest (HDBR) with and without the application of a reactive jump countermeasure were investigated, using a method which enables to discriminate between pulmonary ([Formula: see text]O₂pulm) and muscular ([Formula: see text]O₂musc) oxygen uptake kinetics to control for hemodynamic influences.

METHODS

22 subjects were randomly allocated to either a group performing a reactive jumps countermeasure (JUMP; n = 11, male, 29 ± 7 years, 23.9 ± 1.3 kg m^- 2) or a control group (CTRL; n = 11, male, 29 ± 6 years, 23.3 ± 2.0 kg m^- 2). Heart rate (HR) and [Formula: see text]O₂pulm were measured in response to repeated changes in work rate between 30 and 80 W before (BDC-9) and two times after HDBR (R+ 2, R+ 13). Kinetic responses of HR, [Formula: see text]O₂pulm, and [Formula: see text]O₂musc were assessed applying time series analysis. Higher maxima in cross-correlation functions (CCF_max(x)) between work rate and the respective parameter indicate faster kinetics responses. Statistical analysis was performed applying multifactorial analysis of variance.

RESULTS

CCF_max([Formula: see text]O₂musc) and CCF_max([Formula: see text]O₂pulm) were not significantly different before and after HDBR (P > 0.05). CCF_max(HR) decreased following bed rest (JUMP: BDC-9: 0.30 ± 0.09 vs. R+ 2: 0.28 ± 0.06 vs. R+13: 0.28 ± 0.07; CTRL: 0.35 ± 0.09 vs. 0.27 ± 0.06 vs. 0.33 ± 0.07 P = 0.025). No significant differences between the groups were observed (P > 0.05). Significant alterations were found for CCF_max of mean arterial blood pressure (mBP) after HDBR (JUMP: BDC-9: 0.21 ± 0.07 vs. R+ 2: 0.30 ± 0.13 vs. R+ 13: 0.28 ± 0.08; CTRL: 0.25 ± 0.07 vs. 0.38 ± 0.13 vs. 0.28 ± 0.08; P = 0.008).

CONCLUSIONS

Despite hemodynamic changes, [Formula: see text]O₂ kinetics seem to be preserved for a longer period of HDBR, even without the application of a countermeasure.

Temporal dissociation between muscle and pulmonary oxygen uptake kinetics: influences of perfusion dynamics and arteriovenous oxygen concentration differences in muscles and lungs

PURPOSE

The aim of the study was to test whether or not the arteriovenous oxygen concentration difference (avDO₂) kinetics at the pulmonary (avDO₂pulm) and muscle (avDO₂musc) levels is significantly different during dynamic exercise.

METHODS

A re-analysis involving six publications dealing with kinetic analysis was utilized with an overall sample size of 69 participants. All studies comprised an identical pseudorandom binary sequence work rate (WR) protocol-WR changes between 30 and 80 W-to analyze the kinetic responses of pulmonary ([Formula: see text]) and muscle ([Formula: see text]) oxygen uptake kinetics as well as those of avDO₂pulm and avDO₂musc.

RESULTS

A significant difference between [Formula: see text] (0.395 ± 0.079) and [Formula: see text] kinetics (0.330 ± 0.078) was observed (p < 0.001), where the variables showed a significant relationship (r_SP = 0.744, p < 0.001). There were no significant differences between avDO₂musc (0.446 ± 0.077) and avDO₂pulm kinetics (0.451 ± 0.075), which are highly correlated (r = 0.929, p < 0.001).

CONCLUSION

It is suggested that neither avDO₂pulm nor avDO₂musc kinetic responses seem to be responsible for the differences between estimated [Formula: see text] and measured [Formula: see text] kinetics. Obviously, the conflation of avDO₂ and perfusion ([Formula: see text] ) at different points in time and at different physiological levels drive potential differences in [Formula: see text] and [Formula: see text] kinetics. Therefore, [Formula: see text] should, in general, be considered whenever oxygen uptake kinetics are analyzed or discussed.

Kinetic analysis of oxygen dynamics under a variable work rate

Measurements of oxygen uptake are central to methods for the assessment of physical fitness and endurance capabilities in athletes. Two important parameters extracted from such data of incremental exercise tests are the maximal oxygen uptake and the critical power. A commonly accepted model of the dynamics of oxygen uptake during exercise at a constant work rate comprises a constant baseline oxygen uptake, an exponential fast component, and another exponential slow component for heavy and severe work rates. We have generalized this model to variable load protocols with differential equations that naturally correspond to the standard model for a constant work rate. This provides the means for predicting the oxygen uptake response to variable load profiles including phases of recovery. The model parameters have been fitted for individual subjects from a cycle ergometer test, including the maximal oxygen uptake and critical power. The model predictions have been validated by data collected in separate tests. Our findings indicate that the oxygen kinetics for a variable exercise load can be predicted using the generalized mathematical standard model. Such models can be applied in the field where the constant work rate assumption generally is not valid.

Sex differences in the oxygen delivery, extraction, and uptake during moderate-walking exercise transition

Previous studies in children and older adults demonstrated faster oxygen uptake (V̇O2) kinetics in males compared with females, but young healthy adults have not been studied. We hypothesized that young men would have faster aerobic system dynamics in response to the onset of exercise than women. Interactions between oxygen supply and utilization were characterized by the dynamics of V̇O2, deoxyhemoglobin (HHb), tissue saturation index (TSI), cardiac output (Q̇), and calculated arteriovenous O2 difference (a–vO2diff) in women and men. Eighteen healthy active young women and men (9 of each sex) with similar aerobic fitness levels volunteered for this study. Participants performed an incremental cardiopulmonary treadmill exercise test and 3 moderate-intensity treadmill exercise tests (at 80% V̇O2 of gas exchange threshold). Data related to the moderate exercise were submitted to exponential data modelling to obtain parameters related to the aerobic system dynamics. The time constants of V̇O2, a–vO2diff, HHb, and TSI (30 ± 6, 29 ± 1, 16 ± 1, and 15 ± 2 s, respectively) in women were statistically (p < 0.05) faster than the time constants in men (42 ± 10, 49 ± 21, 19 ± 3, and 20 ± 4 s, respectively). Although Q̇ dynamics were not statistically different (p = 0.06) between groups, there was a trend to slower Q̇ dynamics in men corresponding with the slower V̇O2 kinetics. These results indicated that the peripheral and pulmonary oxygen extraction dynamics were remarkably faster in women. Thus, contrary to the hypothesis, V̇O2 dynamics measured at the mouth at the onset of submaximal treadmill walking were faster in women compared with men.

Mean Normalized Gain: A New Method for the Assessment of the Aerobic System Temporal Dynamics during Randomly Varying Exercise in Humans

The temporal dynamics of the oxygen uptake ([Formula: see text]) during moderate exercise has classically been related to physical fitness and a slower [Formula: see text] dynamics was associated with deterioration of physical health. However, methods that better characterize the aerobic system temporal dynamics remain challenging. The purpose of this study was to develop a new method (named mean normalized gain, MNG) to systematically characterize the [Formula: see text] temporal dynamics. Eight healthy, young adults (28 ± 6 years old, 175 ± 7 cm and 79 ± 13 kg) performed multiple pseudorandom binary sequence cycling protocols on different days and time of the day. The MNG was calculated as the normalized amplitude of the [Formula: see text] signal in frequency-domain. The MNG was validated considering the time constant τ obtained from time-domain analysis as reference. The intra-subject consistency of the MNG was checked by testing the same participant on different days and times of the day. The MNG and τ were strongly negatively correlated (r = -0.86 and p = 0.005). The MNG measured on different days and periods of the day was similar between conditions. Calculations for the MNG have inherent filtering characteristics enhancing reliability for the evaluation of the aerobic system temporal dynamics. In conclusion, the present study successfully validated the use of the MNG for aerobic system analysis and as a potential complementary tool to assess changes in physical fitness.

Data collection, handling, and fitting strategies to optimize accuracy and precision of oxygen uptake kinetics estimation from breath-by-breath measurements

Phase 2 pulmonary oxygen uptake kinetics (ϕ2 τV̇o_2P) reflect muscle oxygen consumption dynamics and are sensitive to changes in state of training or health. This study identified an unbiased method for data collection, handling, and fitting to optimize V̇o_2P kinetics estimation. A validated computational model of V̇o_2P kinetics and a Monte Carlo approach simulated 2 × 10⁵ moderate-intensity transitions using a distribution of metabolic and circulatory parameters spanning normal health. Effects of averaging (interpolation, binning, stacking, or separate fitting of up to 10 transitions) and fitting procedures (biexponential fitting, or ϕ2 isolation by time removal, statistical, or derivative methods followed by monoexponential fitting) on accuracy and precision of V̇o_2P kinetics estimation were assessed. The optimal strategy to maximize accuracy and precision of τV̇o_2P estimation was 1-s interpolation of 4 bouts, ensemble averaged, with the first 20 s of exercise data removed. Contradictory to previous advice, we found optimal fitting procedures removed no more than 20 s of ϕ1 data. Averaging method was less critical: interpolation, binning, and stacking gave similar results, each with greater accuracy compared with analyzing repeated bouts separately. The optimal procedure resulted in ϕ2 τV̇o_2P estimates for transitions from an unloaded or loaded baseline that averaged 1.97 ± 2.08 and 1.04 ± 2.30 s from true, but were within 2 s of true in only 47-62% of simulations. Optimized 95% confidence intervals for τV̇o_2P ranged from 4.08 to 4.51 s, suggesting a minimally important difference of ~5 s to determine significant changes in τV̇o_2P during interventional and comparative studies.NEW & NOTEWORTHY We identified an unbiased method to maximize accuracy and precision of oxygen uptake kinetics (τV̇o_2P) estimation. The optimum number of bouts to average was four; interpolation, bin, and stacking averaging methods gave similar results. Contradictory to previous advice, we found that optimal fitting procedures removed no more than 20 s of phase 1 data. Our data suggest a minimally important difference of ~5 s to determine significant changes in τV̇o_2P during interventional and comparative studies.

Linear and non-linear contributions to oxygen transport and utilization during moderate random exercise in humans

NEW FINDINGS

What is the central question of this study? The pulmonary oxygen uptake (pV̇O2) data used to study the muscle aerobic system dynamics during moderate-exercise transitions is classically described as a mono-exponential function controlled by a complex interaction of the oxygen delivery-utilization balance. This elevated complexity complicates the acquisition of relevant information regarding aerobic system dynamics based on pV̇O2 data during a varying exercise stimulus. What is the main finding and its importance? The elevated complexity of pV̇O2 dynamics is a consequence of a multiple-order interaction between muscle oxygen uptake and circulatory distortion. Our findings challenge the use of a first-order function to study the influences of the oxygen delivery-utilization balance over the pV̇O2 dynamics. The assumption of aerobic system linearity implies that the pulmonary oxygen uptake (pV̇O2) dynamics during exercise transitions present a first-order characteristic. The main objective of this study was to test the linearity of the oxygen delivery-utilization balance during random moderate exercise. The cardiac output (Q̇) and deoxygenated haemoglobin concentration ([HHb]) were measured to infer the central and local O₂ availability, respectively. Thirteen healthy men performed two consecutive pseudorandom binary sequence cycling exercises followed by an incremental protocol. The system input and the outputs pV̇O2, [HHb] and Q̇ were submitted to frequency-domain analysis. The linearity of the variables was tested by computing the ability of the response at a specific frequency to predict the response at another frequency. The predictability levels were assessed by the coefficient of determination. In a first-order system, a participant who presents faster dynamics at a specific frequency should also present faster dynamics at any other frequency. All experimentally obtained variables (pV̇O2, [HHb] and Q̇) presented a certainly degree of non-linearity. The local O₂ availability, evaluated by the ratio pV̇O2/[HHb], presented the most irregular behaviour. The overall [HHb] kinetics were faster than pV̇O2 and Q̇ kinetics. In conclusion, the oxygen delivery-utilization balance behaved as a non-linear phenomenon. Therefore, the elevated complexity of the pulmonary oxygen uptake dynamics is governed by a complex multiple-order interaction between the oxygen delivery and utilization systems.

Gas exchange kinetics following concentric-eccentric isokinetic arm and leg exercise

PURPOSE

To evaluate the effects of exercise velocity (60, 150, 240deg∙s^-1) and muscle mass (arm vs leg) on changes in gas exchange and arterio-venous oxygen content difference (avDO₂) following high-intensity concentric-eccentric isokinetic exercise.

METHODS

Fourteen subjects (26.9±3.1years) performed a 3×20-repetition isokinetic exercise protocol. Recovery beat-to-beat cardiac output (CO) and breath-by-breath gas exchange were recorded to determine post-exercise half-time (t_1/2) for oxygen uptake (V˙O₂pulm), carbon dioxide output (V˙CO₂pulm), and ventilation (V˙_E).

RESULTS

Significant differences of the t_1/2 values were identified between 60 and 150deg∙s^-1. Significant differences in the t_1/2 values were observed between V˙O₂pulm and V˙CO₂pulm and between V˙CO₂pulm and V˙_E. The time to attain the first avDO₂-peak showed significant differences between arm and leg exercise.

CONCLUSIONS

The present study illustrates, that V˙O₂pulm kinetics are distorted due to non-linear CO dynamics. Therefore, it has to be taken into account, that V˙O₂pulm may not be a valuable surrogate for muscular oxygen uptake kinetics in the recovery phases.

Faster heart rate and muscular oxygen uptake kinetics in type 2 diabetes patients following endurance training

Cardiorespiratory kinetics were analyzed in type 2 diabetes patients before and after a 12-week endurance exercise-training intervention. It was hypothesized that muscular oxygen uptake and heart rate (HR) kinetics would be faster after the training intervention and that this would be detectable using a standardized work rate protocol with pseudo-random binary sequences. The cardiorespiratory kinetics of 13 male sedentary, middle-aged, overweight type 2 diabetes patients (age, 60 ± 8 years; body mass index, 33 ± 4 kg·m^-2) were tested before and after the 12-week exercise intervention. Subjects performed endurance training 3 times a week on nonconsecutive days. Pseudo-random binary sequences exercise protocols in combination with time series analysis were used to estimate kinetics. Greater maxima in cross-correlation functions (CCF_max) represent faster kinetics of the respective parameter. CCF_max of muscular oxygen uptake (pre-training: 0.31 ± 0.03; post-training: 0.37 ± 0.1, P = 0.024) and CCF_max of HR (pre-training: 0.25 ± 0.04; post-training: 0.29 ± 0.06, P = 0.007) as well as peak oxygen uptake (pre-training: 24.4 ± 4.7 mL·kg^-1·min^-1; post-training: 29.3 ± 6.5 mL·kg^-1·min^-1, P = 0.004) increased significantly over the course of the exercise intervention. In conclusion, kinetic responses to changing work rates in the moderate-intensity range are similar to metabolic demands occurring in everyday habitual activities. Moderate endurance training accelerated the kinetic responses of HR and muscular oxygen uptake. Furthermore, the applicability of the used method to detect these accelerations was demonstrated.

The influence of metabolic and circulatory heterogeneity on the expression of pulmonary oxygen uptake kinetics in humans

We examined the relationship amongst baseline work rate (WR), phase II pulmonary oxygen uptake (V̇(O2p)) time constant (τV̇(O2p)) and functional gain (G(P)=ΔV̇(O2p)/ΔWR) during moderate-intensity exercise. Transitions were initiated from a constant or variable baseline WR. A validated circulatory model was used to examine the role of heterogeneity in muscle metabolism (V̇(O2m)) and blood flow (Q̇(m)) in determining V̇(O2p) kinetics. We hypothesized that τV̇(O2p) and G(P) would be invariant in the constant baseline condition but would increase linearly with increased baseline WR. Fourteen men completed three to five repetitions of ∆40 W step transitions initiated from 20, 40, 60, 80, 100 and 120 W on a cycle ergometer. The ∆40 W step transitions from 60, 80, 100 and 120 W were preceded by 6 min of 20 W cycling, from which the progressive ΔWR transitions (constant baseline condition) were examined. The V̇(O2p) was measured breath by breath using mass spectrometry and a volume turbine. For a given ΔWR, both τV̇(O2p) (22-35 s) and G(P) (8.7-10.5 ml min(-1) W(-1)) increased (P < 0.05) linearly as a function of baseline WR (20-120 W). The τV̇(O2p) was invariant (P < 0.05) in transitions initiated from 20 W, but G(P) increased with ΔWR (P < 0.05). Modelling the summed influence of multiple muscle compartments revealed that τV̇(O2p) could appear fast (24 s), and similar to in vivo measurements (22 ± 6 s), despite being derived from τV̇(O2p) values with a range of 15-40 s and τQ̇(m) with a range of 20-45 s, suggesting that within the moderate-intensity domain phase II V̇(O2p) kinetics are slowed dependent on the pretransition WR and are strongly influenced by muscle metabolic and circulatory heterogeneity.

V̇O2 and HR kinetics before and after International Space Station missions

PURPOSE

Heart rate (HR), pulmonary and muscle oxygen uptake ([Formula: see text]O2pulm, [Formula: see text]O2musc) kinetics after changes of work rate (WR) indicate regulatory characteristics related to aerobic metabolism. We analysed whether the kinetics of HR, [Formula: see text]O2pulm and [Formula: see text]O2musc are slowed after missions to the International Space Station (ISS). The changes of the kinetics were correlated with [Formula: see text]O2peak data.

METHODS

10 astronauts [4 females, 6 males, age: 48.0 ± 3.8 years, height: 176 ± 7 cm, mass: 74.5 ± 15.9 kg (mean ± SD)] performed an incremental test to determine [Formula: see text]O2peak (before missions on L-110 days, after return on R+1/+10/+36 days), and a cardio-respiratory kinetics test (CRKT) with randomized 30-80 W WR changes to determine HR, [Formula: see text]O2pulm and [Formula: see text]O2musc kinetics by time-series analysis (L-236/-73, R+6/+21). Kinetics were summarized by maximum and related lag of cross-correlation function (CCFmax, CCFlag) of WR with the analysed parameter.

RESULTS

Statistically, significant changes were also found for CCFmax([Formula: see text]O2musc) between L-236 and R+6 (P = 0.010), L-236 and R+21 (P = 0.030), L-72 and R+6 (P = 0.043). Between pre-to-post mission change in [Formula: see text]O2peak and CCFmax(HR), a correlation was shown (r SP = 0.67, P = 0.017).

CONCLUSION

The [Formula: see text]O2musc kinetics changes indicate aerobic detraining effects which are present up to 21 days following space flight. The correlations between changes in [Formula: see text]O2peak and HR kinetics illustrate the key role of cardiovascular regulation in [Formula: see text]O2peak. The addition of CRKT to ISS flight is recommended to obtain information regarding the potential muscular and cardiovascular deconditioning. This allows a reduction in the frequency of higher intensity testing during flight.

Oxygen uptake and heart rate kinetics during dynamic upper and lower body exercise: an investigation by time-series analysis

PURPOSE

The study compared the kinetic responses of heart rate (HR), pulmonary ([Formula: see text]O2pulm) and muscular oxygen uptake ([Formula: see text]O2musc) for upper (UpBody) and lower body (LoBody) exercise.

METHODS

Eleven healthy men (24 ± 2 years, 184 ± 8 cm, 79 ± 7 kg) performed pseudo-random binary sequence (PRBS) work rate (WR) changes on a semi-recumbent cycle ergometer (30 and 80 W) and an arm cranking exercise device (20 and 50 W); followed by stepwise increases in WR (UpBody: 20 W 5 min(-1); LoBody: 50 W 5 min(-1)). [Formula: see text]O2pulm was measured breath-by-breath and HR beat-to-beat. [Formula: see text]O2musc was estimated by the approach as reported by Hoffmann et al. (Eur J Appl Physiol 113:1745-1754, 2013), accounting for circulatory distortions. Time constants (τ) for HR (τHR), [Formula: see text]O2pulm (τ [Formula: see text]O2pulm) and [Formula: see text]O2musc (τ [Formula: see text]O2musc) were estimated during the PRBS phases by time-series analysis.

RESULTS

Peak oxygen uptake differed significantly between UpBody (37.8 ± 5.0 ml min(-1) kg(-1)) and LoBody exercises (56.1 ± 7.4 mL min(-1) kg(-1); p < 0.001). Significant differences were observed for τ [Formula: see text]O2musc (UpBody: 41.1 ± 11.3 s vs LoBody: 29.5 ± 5.2 s; p < 0.05), but not for τ [Formula: see text]O2pulm (49.1 ± 17.1 s vs 39.6 ± 11.2 s; p > 0.05) and τHR (29.1 ± 15.6 s vs 25.6 ± 8.0 s; p > 0.05).

CONCLUSIONS

Meaningful dissociations between [Formula: see text]O2pulm and [Formula: see text]O2musc kinetics exist for both UpBody and LoBody exercise during rapid work rate changes. Therefore, isolated [Formula: see text]O2pulm kinetic estimations without the consideration of the circulatory distortions may not allow a reliable assessment of [Formula: see text]O2musc kinetics.

A validated model of oxygen uptake and circulatory dynamic interactions at exercise onset in humans

At the onset of muscular exercise, the kinetics of pulmonary O2 uptake (Vo2P) reflect the integrated dynamic responses of the ventilatory, circulatory, and neuromuscular systems for O2 transport and utilization. Muscle O2 uptake (Vo2m) kinetics, however, are dissociated from Vo2P kinetics by intervening O2 capacitances and the dynamics of the circulation and ventilation. We developed a multicompartment computational model (MCM) to investigate these dynamic interactions and optimized and validated the MCM using previously published, simultaneously measured Vo2m, alveolar O2 uptake (Vo2A), and muscle blood flow (Qm) in healthy young men during cycle ergometry. The model was used to show that 1) the kinetics of Vo2A during exercise transients are very sensitive to preexercise blood flow distribution and the absolute value of Qm, 2) a low preexercise Qm exaggerates the magnitude of the transient fall in venous O2 concentration for any given Vo2m kinetics, necessitating a tighter coupling of Qm/Vo2m (or a reduction in the available work rate range) during the exercise transient to avoid limits to O2 extraction, and 3) information regarding exercise-related alterations in O2 uptake and blood flow in nonexercising tissues and their effects on mixed venous O2 concentration is required to accurately predict Vo2A kinetics from knowledge of Vo2m and Qm dynamics. Importantly, these data clearly demonstrate that Vo2A kinetics are nonexponential, nonlinear distortions of Vo2m kinetics that can be explained in a MCM by interactions among circulatory and cellular respiratory control processes before and during exercise.