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New Analysis Software To Evaluate Performance: 3666 Board #113 June 3 8: 00 AM - 9: 30 AM

Pokan, Rochus FACSM1; Allemann, Herwig1; Philip, Seiler1; Hausharter, Maria1; Weber, Christoph2; Heber, Stefan1; von Duvillard, Serge P. FACSM3

Medicine & Science in Sports & Exercise: May 2017 - Volume 49 - Issue 5S - p 1049
doi: 10.1249/01.mss.0000519881.76533.9e
G-33 Free Communication/Poster - Research Methods Saturday, June 3, 2017, 7:30 AM - 11:00 AM Room: Hall F

1University of Vienna, Vienna, Austria. 2Technical University of Munich, Munich, Germany. 3University of Salzburg, Salzburg, Austria.

Email: rochus.pokan@univie.ac.at

(No relationships reported)

Vienna CPX-tool is newly developed software that evaluates cardiopulmonary exercise test by assessing the transitions (T) between 3 phases of energy supply, i.e., T1 and T2. We integrated 3 calculation methods (angle, regression and error variance). Each allows for estimation of threshold indicators (IND) of blood lactate turn point 1 (LTP1), first ventilatory threshold 1 (VT1) and ventilatory equivalent of oxygen (VE/VO2) for T1 and LTP2, VT2, VE/VCO2, and heart rate turn point (HRTP) for T2. Since each T is based on a common physiological mechanism, we assume that an accurate calculation method would yield a small range of power output (PO) estimates IND within each T.

PURPOSE: The aim of the present study was to compare the 3 methods via the Vienna CPX-tool.

METHODS: Sixty-five incremental cardiopulmonary exercise tests were analyzed for PO estimates of LTP2, VT2, lowest turn point of VE/VCO2 and the HRTP with any of the three calculation methods. To compare the results with the PO at the maximal lactate steady state (MLSS), the following criterion was used: a valid MLSS prediction was provided if the difference between the PO estimate and the PO at the MLSS was within a range of ± 4% from the maximum PO resulting from the incremental test. Pearson`s chi-square was used to test for the effects. To determine the association between the variables, pairwise comparisons were calculated via Bonferroni-Holm tests.

RESULTS: Prediction frequencies were only significantly different between the angle and regression for LTP2 as well as the angle and regression and regression and error variance in VT2.

CONCLUSION: The implemented calculation methods had a prediction accuracy of ~75-80% using a ± 4% criterion. Based on the present results it is not possible to identify a single best method whereby angel seems to be the most robust variable. To improve calculations and estimations of the above listed variables should be the leading priority for future research endeavors.

© 2017 American College of Sports Medicine