Key result
A system of quadratic equations utilizing VE/VO2 and VE/VCO2 established lines of best fit (r=0.82), allowing for accurate identification of the ventilatory threshold in highly trained cyclists.
Effect estimate: r=0.82
A quadratic regression model using the crossover point of VE/VO2 and VE/VCO2 can accurately identify the ventilatory threshold in trained cyclists.
May aid ventilatory threshold detection in trained cyclists; hypothesis-generating and requires validation before broader use.
The ventilatory threshold (VT) has been used to measure physiological occurrences in athletes. Models have been created to detect VT with limited accuracy. PURPOSE: The purpose of this study was to establish a mathematical model for detecting the ventilatory threshold utilizing the ventilatory equivalent of carbon dioxide (VE/VCO2) and the ventilatory equivalent of oxygen (VE/VO2). METHODS: The methodology was a mathematical analysis of data archived from the cardio-respiratory laboratory in the Department of Kinesiology at Midwestern State University. Procedures for archived data collection included breath-by-breath gas analysis averaged every 20 seconds (s) measured through open circuit spirometry (ParVo Medics™). A ramp protocol on a cycle ergometer (Velotron™) was used which increased work 25 w·min−1 beginning with 150 watts, until volitional fatigue. Subjects were highly trained cyclists (n=27) from the area with ages ranging from 18 (y) to 50 (y). Prior to testing, all subjects signed an informed consent approved by the university Humans as Subjects Review Committee. Mathematical analyses utilized Microsoft Excel™ spreadsheets to create scatter-plots and regression analyses to establish trend-lines of VE/VO2 and VE/VCO2. RESULTS: A polynomial trend-line along the scatter-plots for VE/VO2 and VE/VCO2 was used with a significant correlation coefficient (r=0.82) of the data and trend-line. The equations derived from the scatter-plots and trend-lines were quadratic in nature due to the fact that they have a polynomial degree of two. The mean (SD) % VO2max of the VT established through the trend-line intersections was .79 (.09). CONCLUSION: A system of equations which were quadratic in nature established the lines of best fit allowing for an accurate identification of VT. The exact point of VE/VO2 and VE/VCO2 crossover, the intersection or solution to the system, was established as the VT with the subsequent increased slope of VE/VCO2 as respiratory compensation.
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Gregg et al. (2008) studied Highly trained cyclists (n=27). Quadratic regression analysis of VE/VCO2 and VE/VO2 was evaluated on Correlation of polynomial trend-line with data for VE/VO2 and VE/VCO2 (r=0.82). A system of quadratic equations utilizing VE/VO2 and VE/VCO2 established lines of best fit (r=0.82), allowing for accurate identification of the ventilatory threshold in highly trained cyclists.
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