Literature DB >> 21735217

Evidence of break-points in breathing pattern at the gas-exchange thresholds during incremental cycling in young, healthy subjects.

Troy J Cross1, Norman R Morris, Donald A Schneider, Surendran Sabapathy.   

Abstract

The present study investigated whether 'break-points' in breathing pattern correspond to the first ([Formula: see text]) and second gas-exchange thresholds ([Formula: see text]) during incremental cycling. We used polynomial spline smoothing to detect accelerations and decelerations in pulmonary gas-exchange data, which provided an objective means of 'break-point' detection without assumption of the number and shape of said 'break-points'. Twenty-eight recreational cyclists completed the study, with five individuals excluded from analyses due to low signal-to-noise ratios and/or high risk of 'pseudo-threshold' detection. In the remaining participants (n = 23), two separate and distinct accelerations in respiratory frequency (f (R)) during incremental work were observed, both of which demonstrated trivial biases and reasonably small ±95% limits of agreement (LOA) for the [Formula: see text] (0.2 ± 3.0 ml O(2) kg(-1) min(-1)) and [Formula: see text] (0.0 ± 2.4 ml O(2) kg(-1) min(-1)), respectively. A plateau in tidal volume (V (T)) data near the [Formula: see text] was identified in only 14 individuals, and yielded the most unsatisfactory mean bias ±LOA of all comparisons made (-0.4 ± 5.3 ml O(2) kg(-1) min(-1)). Conversely, 18 individuals displayed V (T)-plateau in close proximity to the [Formula: see text] evidenced by a mean bias ± LOA of 0.1 ± 3.1 ml O(2) kg(-1) min(-1). Our findings suggest that both accelerations in f (R) correspond to the gas-exchange thresholds, and a plateau (or decline) in V (T) at the [Formula: see text] is a common (but not universal) feature of the breathing pattern response to incremental cycling.

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Year:  2011        PMID: 21735217     DOI: 10.1007/s00421-011-2055-4

Source DB:  PubMed          Journal:  Eur J Appl Physiol        ISSN: 1439-6319            Impact factor:   3.078


  44 in total

1.  Breathing pattern in highly competitive cyclists during incremental exercise.

Authors:  A Lucía; A Carvajal; F J Calderón; A Alfonso; J L Chicharro
Journal:  Eur J Appl Physiol Occup Physiol       Date:  1999-05

2.  A refined technique for determining the respiratory gas exchange responses to anaerobic metabolism during progressive exercise - repeatability in a group of healthy men.

Authors:  Anita G M Wisén; Björn Wohlfart
Journal:  Clin Physiol Funct Imaging       Date:  2004-01       Impact factor: 2.273

3.  Occurrence of electromyographic and ventilatory thresholds in professional road cyclists.

Authors:  F Hug; D Laplaud; B Savin; L Grélot
Journal:  Eur J Appl Physiol       Date:  2003-09-24       Impact factor: 3.078

4.  Prognostic usefulness of the functional aerobic reserve in patients with heart failure.

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Journal:  Am Heart J       Date:  2010-11       Impact factor: 4.749

5.  Fitting piecewise linear regression functions to biological responses.

Authors:  E Vieth
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Review 6.  Physiological mechanisms dissociating pulmonary CO2 and O2 exchange dynamics during exercise in humans.

Authors:  Brian J Whipp
Journal:  Exp Physiol       Date:  2006-12-21       Impact factor: 2.969

7.  Ventilatory constraints during exercise in patients with chronic heart failure.

Authors:  B D Johnson; K C Beck; L J Olson; K A O'Malley; T G Allison; R W Squires; G T Gau
Journal:  Chest       Date:  2000-02       Impact factor: 9.410

8.  Respiratory compensation point during incremental exercise as related to hypoxic ventilatory chemosensitivity and lactate increase in man.

Authors:  N Takano
Journal:  Jpn J Physiol       Date:  2000-08

9.  Breathing He-O2 attenuates the slow component of O2 uptake kinetics during exercise performed above the respiratory compensation threshold.

Authors:  Troy J Cross; Surendran Sabapathy; Donald A Schneider; Luke J Haseler
Journal:  Exp Physiol       Date:  2009-08-28       Impact factor: 2.969

10.  Detecting outliers when fitting data with nonlinear regression - a new method based on robust nonlinear regression and the false discovery rate.

Authors:  Harvey J Motulsky; Ronald E Brown
Journal:  BMC Bioinformatics       Date:  2006-03-09       Impact factor: 3.169

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  2 in total

1.  Respiratory Frequency during Exercise: The Neglected Physiological Measure.

Authors:  Andrea Nicolò; Carlo Massaroni; Louis Passfield
Journal:  Front Physiol       Date:  2017-12-11       Impact factor: 4.566

2.  Estimation of Respiratory Frequency in Women and Men by Kubios HRV Software Using the Polar H10 or Movesense Medical ECG Sensor during an Exercise Ramp.

Authors:  Bruce Rogers; Marcelle Schaffarczyk; Thomas Gronwald
Journal:  Sensors (Basel)       Date:  2022-09-21       Impact factor: 3.847

  2 in total

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