Dataset Information

Oxygen kinetics and debt during recovery from expiratory flow-limited exercise in healthy humans.

ABSTRACT: In healthy subjects expiratory flow limitation (EFL) during exercise can lower O(2) delivery to the working muscles. We hypothesized that if this affects exercise performance it should influence O(2) kinetics at the end of exercise when the O(2) debt is repaid. We performed an incremental exercise test on six healthy males with a Starling resistor in the expiratory line limiting expiratory flow to approximately 1 l s(-1) to determine maximal EFL exercise workload (W (max)). In two more square-wave exercise runs subjects exercised with and without EFL at W (max) for 6 min, while measuring arterial O(2) saturation (% SaO(2)), end-tidal pressure of CO(2) (P (ET)CO(2)) and breath-by-breath O(2) consumption VO2 taking into account changes in O(2) stored in the lungs. Over the last minute of EFL exercise, mean P (ET)CO(2) (54.7 +/- 9.9 mmHg) was significantly higher (P < 0.05) compared to control (41.4 +/- 3.9 mmHg). At the end of EFL exercise %SaO(2) fell significantly by 4 +/- 3%. When exercise stopped, EFL was removed, and we continued to measure VO2. During recovery, there was an immediate step increase in [Formula: see text] so that repayment of EFL O(2) debt started at a higher VO2 than control. Recovery VO2 kinetics after EFL exercise was best characterized by a double-exponential function with fundamental and slow time constants of 27 +/- 11 and 1,020 +/- 305 s, compared to control values of 41 +/- 10 and 1,358 +/- 320 s, respectively. EFL O(2) debt was 52 +/- 22% greater than control (2.19 +/- 0.58 vs. 1.49 +/- 0.38 l). We conclude that EFL exercise increases the O(2) debt and leads to hypoxemia in part due to hypercapnia.

SUBMITTER: Vogiatzis I

PROVIDER: S-EPMC1782100 | biostudies-other | 2007 Feb

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:BackgroundIncreasing functional residual capacity (FRC) or tidal volume (VT) reduces airway resistance and attenuates the response to bronchoconstrictor stimuli in animals and humans. What is unknown is which one of the above mechanisms is more effective in modulating airway caliber and whether their combination yields additive or synergistic effects. To address this question, we investigated the effects of increased FRC and increased VT in attenuating the bronchoconstriction induced by inhaled methacholine (MCh) in healthy humans.MethodsNineteen healthy volunteers were challenged with a single-dose of MCh and forced oscillation was used to measure inspiratory resistance at 5 and 19 Hz (R5 and R19), their difference (R5-19), and reactance at 5 Hz (X5) during spontaneous breathing and during imposed breathing patterns with increased FRC, or VT, or both. Importantly, in our experimental design we held the product of VT and breathing frequency (BF), i.e, minute ventilation (VE) fixed so as to better isolate the effects of changes in VT alone.ResultsTripling VT from baseline FRC significantly attenuated the effects of MCh on R5, R19, R5-19 and X5. Doubling VT while halving BF had insignificant effects. Increasing FRC by either one or two VT significantly attenuated the effects of MCh on R5, R19, R5-19 and X5. Increasing both VT and FRC had additive effects on R5, R19, R5-19 and X5, but the effect of increasing FRC was more consistent than increasing VT thus suggesting larger bronchodilation. When compared at iso-volume, there were no differences among breathing patterns with the exception of when VT was three times larger than during spontaneous breathing.ConclusionsThese data show that increasing FRC and VT can attenuate induced bronchoconstriction in healthy humans by additive effects that are mainly related to an increase of mean operational lung volume. We suggest that static stretching as with increasing FRC is more effective than tidal stretching at constant VE, possibly through a combination of effects on airway geometry and airway smooth muscle dynamics.

Project description:Purpose:The present study aimed to determine whether whole-body fat oxidation and muscle deoxygenation kinetics parameters during exercise were related in individuals with different aerobic fitness levels. Methods:Eleven cyclists [peak oxygen uptake ( V.O2?p?e?a?k ): 64.9 ± 3.9 mL?kg-1?min-1] and 11 active individuals ( V.O2?p?e?a?k : 49.1 ± 7.4 mL?kg-1?min-1) performed a maximal incremental cycling test to determine V.O2?p?e?a?k and a submaximal incremental cycling test to assess whole-body fat oxidation using indirect calorimetry and muscle deoxygenation kinetics of the vastus lateralis (VL) using near-infrared spectroscopy (NIRS). A sinusoidal (SIN) model was used to characterize fat oxidation kinetics and to determine the intensity (Fatmax) eliciting maximal fat oxidation (MFO). The muscle deoxygenation response was fitted with a double linear model. The slope of the first parts of the kinetics (a 1) and the breakpoint ([HHb]BP) were determined. Results:MFO (p = 0.01) and absolute fat oxidation rates between 20 and 65% V.O2?p?e?a?k were higher in cyclists than in active participants (p < 0.05), while Fatmax occurred at a higher absolute exercise intensity (p = 0.01). a 1 was lower in cyclists (p = 0.02) and [HHb]BP occurred at a higher absolute intensity (p < 0.001) than in active individuals. V.O2?p?e?a?k was strongly correlated with MFO, Fatmax, and [HHb]BP (r = 0.65-0.88, p ? 0.001). MFO and Fatmax were both correlated with [HHb]BP (r = 0.66, p = 0.01 and r = 0.68, p < 0.001, respectively) and tended to be negatively correlated with a 1 (r = -0.41, p = 0.06 for both). Conclusion:This study showed that whole-body fat oxidation and muscle deoxygenation kinetics were both related to aerobic fitness and that a relationship between the two kinetics exists. Individuals with greater aerobic fitness may have a delayed reliance on glycolytic metabolism at higher exercise intensities because of a longer maintained balance between O2 delivery and consumption supporting higher fat oxidation rates.

Project description:PurposeThe 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.MethodsOverall 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 ([Formula: see text]̇O2peak): 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 [Formula: see text]O2peak. Heart rate (HR), stroke volume (SV) and gas exchange (pulmonary oxygen uptake ([Formula: see text]O2pulm)) were measured beat-to-beat and breath-by-breath, respectively. For estimation of muscle oxygen uptake ([Formula: see text]O2musc) kinetics and for the analysis of kinetic responses of the parameters of interest (perfusion ([Formula: see text] = HR·SV), [Formula: see text]O2pulm, [Formula: see text]O2musc) the approach of Hoffmann et al. (2013) was applied. For calculation of the Fuzzy Kinetics Index [Formula: see text], [Formula: see text]O2pulm, and [Formula: see text]O2musc were used as input variables for the subsequent fuzzy- and defuzzyfication procedures.ResultsFor both absolute and relative [Formula: see text]O2peak 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 [Formula: see text]O2peak (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).ConclusionsThe significant correlations between FKI and [Formula: see text]O2peak 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.

Dataset Information

Oxygen kinetics and debt during recovery from expiratory flow-limited exercise in healthy humans.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets