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The “independent breath” algorithm: assessment of oxygen uptake during exercise

  • Maria Pia Francescato
  • Valentina Cettolo
Original Article
  • 15 Downloads

Abstract

Purpose

Reduction of noise of breath-by-breath gas-exchange data is crucial to improve measurements. A recently described algorithm (“independent breath”), that neglects the contiguity in time of breaths, was tested.

Methods

Oxygen, carbon dioxide fractions, and ventilatory flow were recorded continuously over 26 min in 20 healthy volunteers at rest, during unloaded and moderate intensity cycling and subsequent recovery; oxygen uptake (\(\dot {V}{{\text{O}}_{\text{2}}}\)) was calculated with the “independent breath” algorithm (IND) and, for comparison, with three other “classical” algorithms. Average \(\dot {V}{{\text{O}}_{\text{2}}}\) and standard deviations were calculated for steady-state conditions; non-linear regression was run throughout the \(\dot {V}{{\text{O}}_{\text{2}}}\) data of the transient phases (ON and OFF), using a mono-exponential function.

Results

Comparisons of the different algorithms showed that they yielded similar average \(\dot {V}{{\text{O}}_{\text{2}}}\) at steady state (p = NS). The standard deviations were significantly lower for IND (post hoc contrasts, p < 0.001), with the slope of the relationship with the corresponding data obtained from “classical” algorithms being < 0.69. For both transients, the overall kinetics (evaluated as time delay + time constant) was significantly faster for IND (post hoc contrasts, p < 0.001). For the ON transient, the asymptotic standard errors of the kinetic parameters were significantly lower for IND, with the slope of the regression line with the corresponding values obtained from the “classical” algorithms being < 0.60.

Conclusion

The “independent breath” algorithm provided consistent average O2 uptake values while reducing the overall noise of about 30%, which might result in the halving of the required number of repeated trials needed to assess the kinetic parameters of the ON transient.

Keywords

Gas exchange Signal-to-noise ratio Mean response time 

Abbreviations

ASE

Asymptotic standard error

AUC

“Auchincloss” approach, i.e., the breath-by-breath alveolar gas-exchange algorithm according to Auchincloss et al. (1966)

BTPS

Body temperature pressure saturated

EXP

“expiration-only” approach, i.e., the breath-by-breath gas-exchange algorithm that uses information obtained during expiration and the Haldane transformation (Roecker et al. 2005; Ward 2018)

FCO2, FN2, FO2

Instantaneous carbon dioxide, non-exchangeable gas at alveolar level (essentially nitrogen) and oxygen fractions

FIO2, FIN2

Inspired oxygen and nitrogen ambient fractions

IND

“independent breath” approach, i.e., the breath-by-breath alveolar gas-exchange algorithm under investigation (Cettolo and Francescato 2018b)

MANOVA

Repeated measures multivariate analysis of variance

MRTON, MRTOFF

Mean response time of the ON and OFF kinetics, respectively

RSS

Residual sum of squares

STPD

Standard temperature pressure dry

t

Time

tdf

t student value for a determined degree of freedom at a certain probability level

TdON, TdOFF

Time delay of the start of the ON and OFF kinetics, respectively

ti, te

Starting times of inspiration and expiration, respectively; defined on the flow trace, where flow changes direction

TON, TOFF

Start time of signal change of the ON and OFF transients, respectively, as obtained by the non-linear regression procedure

\({t_x}\)

Time of the end-expiratory exchanged gas fraction, defined on the FO2 trace

t1, t2

Start and end times of the jth breath for the “independent breath” approach; defined on the FO2/FN2 trace

\(\dot {V}\)

Respiratory flow at the mouth

VL

End-expiratory lung volume

\(\dot {V}{{\text{O}}_2}^{{{\text{IND}}}}\), \(\dot {V}{{\text{O}}_2}^{{{\text{WES}}}}\), \(\dot {V}{{\text{O}}_2}^{{{\text{AUC}}}}\), and \(\dot {V}{{\text{O}}_2}^{{{\text{EXP}}}}\)

Oxygen uptake calculated applying the “independent breath”, the “Wessel”, the “Auchincloss”, and the “expiration-only” approaches, respectively; all the data are expressed in STPD conditions

\(\dot {V}{{\text{O}}_2}^{{\text{r}}}\)

Baseline O2 uptake for the ON kinetic analysis

\(\dot {V}{{\text{O}}_2}^{{{\text{ss}}}}\)

Average steady-state O2 uptake for the OFF kinetic analysis

WES

“Wessel” approach, i.e., the breath-by-breath alveolar gas-exchange algorithm according to Wessel et al. (1979)

\(\Delta \dot {V}{{\text{O}}_2}^{{{\text{rec}}}}\)

Fall of oxygen uptake at the end of recovery

\(\Delta \dot {V}{{\text{O}}_2}^{{{\text{ss}}}}\)

Increase in oxygen uptake at steady state

τON, τOFF

Time constant of the ON and OFF responses, respectively, as obtained by the non-linear regression procedure

Notes

Acknowledgements

Funding was provided by Università degli Studi di Udine—Dpt. of Medicine (2017).

Author contributions

CV and FMP equally contributed in conception and design of the experiments; both performed the experiments, analysed the data, and wrote the paper. Both authors read and approved the final version of the manuscript.

Supplementary material

421_2018_4046_MOESM1_ESM.doc (33 kb)
Supplementary material 1 (DOC 33 KB)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of MedicineUniversity of UdineUdineItaly

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