Why the study?
It was unclear how the algorithm used to calculate breath-by-breath gas exchange affects kinetic parameters estimated at the onset of moderate-intensity exercise.
Does the 'Independent-breath' algorithm compared to the 'Expiration-only' algorithm affect the estimation of O2 uptake kinetics at the onset of moderate-intensity exercise in healthy volunteers?
Does the 'Independent-breath' algorithm compared to the 'Expiration-only' algorithm affect the estimation of O2 uptake kinetics at the onset of moderate-intensity exercise in healthy volunteers?
The choice of gas exchange calculation algorithm significantly affects the estimation of O2 uptake kinetics, with the 'Independent-breath' algorithm yielding faster mean response times.
Answers are grounded in this paper and cite their sources.
Different algorithms yield discrepant VO2 kinetic estimates; leaves open optimal method for research assessing muscle O2 uptake.
At the start of a moderate‐intensity square‐wave exercise, after a short delay, breath‐by‐breath O 2 uptake at the mouth is approximated to a mono‐exponential function, whose time constant is considered matched to that of the O 2 uptake of the working muscles. We compared the kinetic parameters obtained from the breath‐by‐breath gas exchange data yielded by the ‘Independent‐breath’ algorithm (IND), which accounts for the changes in lung gas stores, with those obtained with the classical ‘Expiration‐only’ algorithm (EXP). The two algorithms were applied on the same flow and gas fraction traces acquired on 10 healthy volunteers, performing 10 times the same moderate‐intensity exercise transition. Repeated O 2 uptake responses were stacked together and the kinetic parameters of a mono‐exponential function were estimated by non‐linear regression, removing the data pertaining to 1‐s progressively longer initial periods (Δ T r ). Independently of Δ T r , the mean response time (time constant + time delay) obtained for the IND data was faster compared to the EXP data (∼43 s vs. ∼47 s, P < 0.001), essentially because of shorter time delays. Between Δ T r = 16 s and Δ T r = 29s, the time constants of the IND data decreased (30.7 s vs. 28.0 s, P < 0.05; drop = 10%), but less than those of the EXP data (32.2 s vs. 26.2 s, P < 0.001; drop = 23%); with the same Δ T r , the time constants of the two algorithms’ data were not different ( P > 0.07). The different decrease in the time constant, together with the different mean response time, suggests that the data yielded by the two algorithms provide a different picture of the phenomena occurring at the beginning of the exercise.
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Francescato et al. (2023) studied this question.
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