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Sportverletz Sportschaden 2015; 29(03): 173-179
DOI: 10.1055/s-0034-1399096
Originalarbeit
© Georg Thieme Verlag KG Stuttgart · New York

Reliabilität ausgewählter Parameter der Fahrradergospirometrie anhand des PowerCube-Ergo-Atemgasanalysators

Reliability of Selected Parameters of Cycling Ergospirometry from the PowerCube-Ergo Respiratory Gas Analyser
M. W. Hoppe
1   Arbeitsbereich Bewegungs- und Trainingswissenschaft, Bergische Universität Wuppertal, Deutschland
,
B. Sperlich
2   Arbeitsbereich Integrative und Experimentelle Trainingswissenschaft, Julius-Maximilians-Universität Würzburg, Deutschland
,
C. Baumgart
1   Arbeitsbereich Bewegungs- und Trainingswissenschaft, Bergische Universität Wuppertal, Deutschland
,
M. Janssen
1   Arbeitsbereich Bewegungs- und Trainingswissenschaft, Bergische Universität Wuppertal, Deutschland
,
J. Freiwald
1   Arbeitsbereich Bewegungs- und Trainingswissenschaft, Bergische Universität Wuppertal, Deutschland
› Author Affiliations
Further Information

Publication History

Publication Date:
24 February 2015 (online)

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Zusammenfassung

Ziel der Studie war es, die Reliabilität 1.) der wichtigsten Größen der Fahrradergospirometrie (maximale Leistung [Pmax] und Sauerstoffaufnahme [V̇O2peak], ventilatorische Schwellen 1 [VT 1] und 2 [VT 2] sowie Radfahrökonomie [CE] und Wirkungsgrad [GE]), 2.) der gebräuchlichsten sekundären Ausbelastungsparameter (maximale Herzfrequenz [HFmax], respiratorischer Quotient [RQmax], Blutlaktatkonzentration [BLAmax] und subjektives Belastungsempfinden [RPEmax]) und 3.) der belastungsinduzierten Verläufe der Atemgase (Sauerstoffaufnahme [V̇O2], Kohlendioxidabgabe [V̇CO2] und Atemminutenvolumen [V̇E]) anhand des PowerCube-Ergo-Atemgasanalysators zu erheben und einheitlich gemäß internationaler Standards der Statistik zu berechnen. 12 Frauen und 12 Männer (28 ± 4 Jahre; 23,2 ± 2,4 kg/m2) absolvierten zwei Fahrradergospirometrien (20 Watt/min) im Abstand von einer Woche. Die Reliabilität wurde anhand der Mittelwertdifferenzen (t-Test und Effektstärken), der Retestkorrelation (Intraklassenkorrelationskoeffizient [ICC]) und der intraindividuellen Variabilität (Standardmessfehler [SEM]) der Messwerte berechnet. Von den wichtigsten Größen der Fahrradergospirometrie sind die Pmax, die V̇O2peak und die VT 1 ausgezeichnet reproduzierbar (ICC ≥ 0,969; p = 0,000) und hoch messgenau (%SEM ≤ 4,6). Von den gebräuchlichsten sekundären Ausbelastungsparametern gilt dies nur für die HFmax (ICC = 0,922; p = 0,000; %SEM = 1,0). Der PowerCube-Ergo ermöglicht ausgezeichnet reproduzierbare Messungen der V̇O2, der V̇CO2 und des V̇E (ICC ≥ 0,991; p = 0,000), wobei die Messgenauigkeit der V̇O2 (SEM = 0,10 l/min) und des V̇E (SEM = 3,13 l/min) den Qualitätsrichtlinien leistungsphysiologischer Labore genügt. Die Ergebnisse sind bei zukünftigen Interventionsstudien für die sichere Unterscheidung zwischen einem tatsächlichen Interventionseffekt und einem Messfehler sowie für die Planung von Stichprobenumfängen von praktischer Bedeutsamkeit.

Abstract

This study aimed to investigate the reliability of 1) the key parameters of cycling ergospirometry (maximum power output [Pmax] and oxygen uptake [V̇O2peak], ventilatory thresholds 1 [VT 1] and 2 [VT 2], and cycling efficiency [CE] and gross efficiency [GE]), 2) the commonly used parameters to quantify exhaustion (maximum heart rate [HFmax], respiratory quotient [RQmax], blood lactate concentration [BLAmax], and ratings of perceived exhaustion [RPEmax]), and 3) the kinetics of exercise induced gas exchange measurements (oxygen uptake [V̇O2], carbon dioxide output [V̇CO2], and minute ventilation [V̇E]) using the PowerCube-Ergo metabolic system in consideration of international statistical recommendations. 12 women and 12 men (28 ± 4 years; 23.2 ± 2.4 kg/m2) performed two cycling tests (20 watt/min) separated by one week. The reliability was calculated based on differences in means (t test and effect sizes), retest correlation (intraclass correlation coefficient [ICC]), and within-subject variation (standard error of measurement [SEM]). Of the key parameters of cycling ergospirometry, an excellent reliability (ICC ≥ 0.969; p = 0.000) and high accuracy (%SEM ≤ 4.6) were found for Pmax, V̇O2peak, and VT 1. Of the most commonly used parameters to quantify exhaustion, an excellent reliability (ICC = 0.922; p = 0.000) and high accuracy (%SEM = 1.0) existed only for HFmax. The gas exchange measurements (V̇O2, V̇CO2 und V̇E) of the PowerCube-Ergo were all excellently reliable (ICC ≥ 0,991; p = 0.000) and the accuracy of V̇O2 (SEM = 0.10 l/min) and V̇E (SEM = 3.13 l/min) fulfilled the quality guidance of exercise physiology laboratories. For future studies and practical purposes, the results are vital for the decision as to whether a difference between two tests represents a true intervention effect or just a measurement error and for the estimation of required sample sizes.

Schlüsselwörter

Ausdauer - Laktat - Leistungsdiagnostik - Spiroergometrie - Trainingssteuerung

Key words

endurance - lactate - performance diagnostics - spiroergometry - training
 

  • Literatur

  • 1 Hollmann W, Strüder H, Predel H et al. Spiroergometrie: Kardiopulmonale Leistungsdiagnostik des Gesunden und Kranken. Stuttgart: Schattauer; 2006
    Google Scholar
  • 2 Wasserman K, Hansen JE, Sue DY et al. Principles of exercise testing and interpretation – including pathophysiology and clinical applications. Fourth. Aufl. Phiadelphia: Lippincott Williams & Wilkins; 2005
    Google Scholar
  • 3 Haber P. Lungenfunktion und Spiroergometrie – Interpretation und Befunderstellung unter Einschluss der arteriellen Blutgasanalyse. 3. Aufl. Wien: Springer-Verlag; 2013
    Google Scholar
  • 4 Kroidl RF, Schwarz S, Lehnigk B. Kursbuch Spiroergometrie – Technik und Befundung verständlich gemacht. Stuttgart: Georg Thieme Verlag KG; 2007
    Article in Thieme ConnectGoogle Scholar
  • 5 Bentley DJ, Newell J, Bishop D. Incremental exercise test design and analysis: implications for performance diagnostics in endurance athletes. Sports Med 2007; 37: 575-586
    CrossrefPubMedGoogle Scholar
  • 6 Bassett Jr DR, Howley ET. Limiting factors for maximum oxygen uptake and determinants of endurance performance. Medicine and science in sports and exercise 2000; 32: 70-84
    PubMedGoogle Scholar
  • 7 Coyle EF. Integration of the physiological factors determining endurance performance ability. Exerc Sport Sci Rev 1995; 23: 25-63
    PubMedGoogle Scholar
  • 8 Midgley AW, McNaughton LR, Jones AM. Training to enhance the physiological determinants of long-distance running performance: can valid recommendations be given to runners and coaches based on current scientific knowledge?. Sports Med 2007; 37: 857-880
    CrossrefPubMedGoogle Scholar
  • 9 Joyner MJ, Coyle EF. Endurance exercise performance: the physiology of champions. The Journal of physiology 2008; 586: 35-44
    CrossrefPubMedGoogle Scholar
  • 10 Jones AM, Carter H. The effect of endurance training on parameters of aerobic fitness. Sports Med 2000; 29: 373-386
    CrossrefPubMedGoogle Scholar
  • 11 Meyer T, Lucia A, Earnest CP et al. A conceptual framework for performance diagnosis and training prescription from submaximal gas exchange parameters – theory and application. International journal of sports medicine 2005; 26 (Suppl. 01) S38-S48
    Article in Thieme ConnectPubMedGoogle Scholar
  • 12 Binder RK, Wonisch M, Corra U et al. Methodological approach to the first and second lactate threshold in incremental cardiopulmonary exercise testing. European journal of cardiovascular prevention and rehabilitation: official journal of the European Society of Cardiology, Working Groups on Epidemiology & Prevention and Cardiac Rehabilitation and Exercise Physiology 2008; 15: 726-734
    PubMedGoogle Scholar
  • 13 Ramos RP, Alencar MC, Treptow E et al. Clinical usefulness of response profiles to rapidly incremental cardiopulmonary exercise testing. Pulmonary medicine 2013; 2013: 359021
    PubMedGoogle Scholar
  • 14 Jeukendrup AE, Craig NP, Hawley JA. The bioenergetics of World Class Cycling. Journal of science and medicine in sport/Sports Medicine Australia 2000; 3: 414-433
    CrossrefPubMedGoogle Scholar
  • 15 Lucia A, Hoyos J, Perez M et al. Inverse relationship between VO2max and economy/efficiency in world-class cyclists. Medicine and science in sports and exercise 2002; 34: 2079-2084
    CrossrefPubMedGoogle Scholar
  • 16 Moseley L, Achten J, Martin JC et al. No differences in cycling efficiency between world-class and recreational cyclists. International journal of sports medicine 2004; 25: 374-379
    Article in Thieme ConnectPubMedGoogle Scholar
  • 17 Midgley AW, McNaughton LR, Polman R et al. Criteria for determination of maximal oxygen uptake: a brief critique and recommendations for future research. Sports Med 2007; 37: 1019-1028
    CrossrefPubMedGoogle Scholar
  • 18 Howley ET, Bassett DR Jr, Welch HG. Criteria for maximal oxygen uptake: review and commentary. Medicine and science in sports and exercise 1995; 27: 1292-1301
    PubMedGoogle Scholar
  • 19 Macfarlane DJ. Automated metabolic gas analysis systems: a review. Sports Med 2001; 31: 841-861
    CrossrefPubMedGoogle Scholar
  • 20 Hodges LD, Brodie DA, Bromley PD. Validity and reliability of selected commercially available metabolic analyzer systems. Scandinavian journal of medicine & science in sports 2005; 15: 271-279
    PubMedGoogle Scholar
  • 21 Atkinson G, Davison RC, Nevill AM. Performance characteristics of gas analysis systems: what we know and what we need to know. International journal of sports medicine 2005; 26 (Suppl. 01) S2-S10
    Article in Thieme ConnectPubMedGoogle Scholar
  • 22 Thomas JR, Nelson JK, Silvermann SJ. Research methods in physical activity. Champaign: Human Kinetics 2010;
    PubMedGoogle Scholar
  • 23 Atkinson G, Nevill AM. Statistical methods for assessing measurement error (reliability) in variables relevant to sports medicine. Sports Med 1998; 26: 217-238
    CrossrefPubMedGoogle Scholar
  • 24 Hopkins WG. Measures of reliability in sports medicine and science. Sports Med 2000; 30: 1-15
    CrossrefPubMedGoogle Scholar
  • 25 Weir JP. Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. Journal of strength and conditioning research/National Strength & Conditioning Association 2005; 19: 231-240
    PubMedGoogle Scholar
  • 26 Meyer K, Hajric R, Westbrook S et al. Ventilatory and lactate threshold determinations in healthy normals and cardiac patients: methodological problems. European journal of applied physiology and occupational physiology 1996; 72: 387-393
    PubMedGoogle Scholar
  • 27 Amann M, Subudhi AW, Walker J et al. An evaluation of the predictive validity and reliability of ventilatory threshold. Medicine and science in sports and exercise 2004; 36: 1716-1722
    CrossrefPubMedGoogle Scholar
  • 28 Lucia A, Pardo J, Durantez A et al. Physiological differences between professional and elite road cyclists. International journal of sports medicine 1998; 19: 342-348
    Article in Thieme ConnectPubMedGoogle Scholar
  • 29 Granja Filho PCN, Pompeu FAMS, de Souza eSilva PPR. Accuracy of VO2max and anaerobic threshold determination. Rev Bras Med Esporte 2005; 11: 162-165
    PubMedGoogle Scholar
  • 30 Beaver WL, Wasserman K, Whipp BJ. A new method for detecting anaerobic threshold by gas exchange. Journal of applied physiology 1986; 60: 2020-2027
    PubMedGoogle Scholar
  • 31 Saunders PU, Pyne DB, Telford RD et al. Factors affecting running economy in trained distance runners. Sports Med 2004; 34: 465-485
    CrossrefPubMedGoogle Scholar
  • 32 Moseley L, Jeukendrup AE. The reliability of cycling efficiency. Medicine and science in sports and exercise 2001; 33: 621-627
    PubMedGoogle Scholar
  • 33 Fletcher JR, Esau SP, Macintosh BR. Economy of running: beyond the measurement of oxygen uptake. J Appl Physiol (1985) 2009; 107: 1918-1922
    CrossrefPubMedGoogle Scholar
  • 34 Cohen J. Statistical power analysis for the behavioral sciences. New York: Academic Press; 1969
    Google Scholar
  • 35 Shrout PE, Fleiss JL. Intraclass correlations: uses in assessing rater reliability. Psychological bulletin 1979; 86: 420-428
    CrossrefPubMedGoogle Scholar
  • 36 Höner O, Roth K. Klassische Testtheorie: Die Gütekriterien sportwissenschaftlicher Erhebungsmethoden. In: Singer R, Willimczik K, Hrsg. Sozialwissenschaftliche Forschungsmethoden in der Sportwissenschaft. Hamburg: Czwalina; 2002: 67-97
    Google Scholar
  • 37 Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; 1: 307-310
    PubMedGoogle Scholar
  • 38 Zhou S, Weston SB. Reliability of using the D-max method to define physiological responses to incremental exercise testing. Physiological measurement 1997; 18: 145-154
    CrossrefPubMedGoogle Scholar
  • 39 Fontana P, Boutellier U, Toigo M. Reliability of measurements with Innocor during exercise. International journal of sports medicine 2009; 30: 747-753
    Article in Thieme ConnectPubMedGoogle Scholar
  • 40 Skinner JS, Wilmore KM, Jaskolska A et al. Reproducibility of maximal exercise test data in the HERITAGE family study. Medicine and science in sports and exercise 1999; 31: 1623-1628
    CrossrefPubMedGoogle Scholar
  • 41 Aunola S, Rusko H. Reproducibility of aerobic and anaerobic thresholds in 20–50 year old men. European journal of applied physiology and occupational physiology 1984; 53: 260-266
    CrossrefPubMedGoogle Scholar
  • 42 Weston SB, Gabbett TJ. Reproducibility of ventilation of thresholds in trained cyclists during ramp cycle exercise. Journal of science and medicine in sport/Sports Medicine Australia 2001; 4: 357-366
    CrossrefPubMedGoogle Scholar
  • 43 Hopkins WG, Schabort EJ, Hawley JA. Reliability of power in physical performance tests. Sports Med 2001; 31: 211-234
    CrossrefPubMedGoogle Scholar
  • 44 Kuipers H, Verstappen FT, Keizer HA et al. Variability of aerobic performance in the laboratory and its physiologic correlates. International journal of sports medicine 1985; 6: 197-201
    Article in Thieme ConnectPubMedGoogle Scholar
  • 45 Katch VL, Sady SS, Freedson P. Biological variability in maximum aerobic power. Medicine and science in sports and exercise 1982; 14: 21-25
    CrossrefPubMedGoogle Scholar
  • 46 Busse MW, Scholz J, Maassen N. Plasma potassium and ventilation during incremental exercise in humans: modulation by sodium bicarbonate and substrate availability. European journal of applied physiology and occupational physiology 1992; 65: 340-346
    CrossrefPubMedGoogle Scholar
  • 47 Whipp BJ. Ventilatory control during exercise in humans. Annual review of physiology 1983; 45: 393-413
    CrossrefPubMedGoogle Scholar
  • 48 Hug F, Laplaud D, Savin B et al. Occurrence of electromyographic and ventilatory thresholds in professional road cyclists. European journal of applied physiology 2003; 90: 643-646
    CrossrefPubMedGoogle Scholar
  • 49 Ward SA. Control of the exercise hyperpnoea in humans: a modeling perspective. Respiration physiology 2000; 122: 149-166
    CrossrefPubMedGoogle Scholar
  • 50 Perkins CD, Pivarnik JM, Green MR. Reliability and validity of the VmaxST portable metabolic analyzer. Journal of Physical Activity and Health 2004; 413-422
    PubMedGoogle Scholar
  • 51 Faude O, Meyer T. Methodische Aspekte der Laktatbestimmung. Dtsch Z Sportmed 2008; 59: 305-309
    PubMedGoogle Scholar
  • 52 Meyer T, Georg T, Becker C et al. Reliability of gas exchange measurements from two different spiroergometry systems. International journal of sports medicine 2001; 22: 593-597
    Article in Thieme ConnectPubMedGoogle Scholar
  • 53 Tanner RK, Gore CJ. Quality assurance in exercise physiology laboratories. In: Tanner RK, Gore CJ, Hrsg. Physiological tests for elite athletes. Second. Aufl. Champaign: Human Kinetics; 2013
    Google Scholar