Examining the Respiratory Compensation Point with Automated Methods in Recreational Runners Training for a Marathon
2019-05
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Examining the Respiratory Compensation Point with Automated Methods in Recreational Runners Training for a Marathon
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2019-05
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Background: The respiratory compensation point (RC) approximates the lowest intensity of unsustainably difficult exercise, making it an important measure for endurance athletes. Thus, accurate determination of RC is important to athletes. There are many methods to determine RC, but few large studies to date have compared multiple automated methods. Previous studies have shown that rates of detection of RC (i.e. determinate cases) vary. The purpose of this study was to compare four common methods used to detect RC: Jones-Molitoris (JM), Orr, Beaver’s V-slope (Beaver), and the Dmax method. Methods: Recreationally active college students (n = 131, 45 males, 86 females) completed 2-mile time trials and graded exercise tests both before and after training for a marathon. The four methods were used to detect RC (as a % of VO2max) from the VE vs. VCO2 slope. The number of determinate RC cases were recorded for each method at pre and at post. Determinate counts of RC were expressed as a percentage, were compared pre to post with Fisher’s exact tests, and were simulated with bootstrap resampling. Average differences between methods were compare using a linear mixed effects model (LMEM) with data from participants who displayed RC at both pre and post testing for at least one of the four methods. Comparisons between methods and with 2-mile performance were also compared by correlations and with limits of agreement (LOA) plots. Results: The order of determinate rates from highest to lowest was JM, Dmax, Orr, and Beaver. Fisher’s exact tests produced odds ratios significantly higher than 1 for all but Beaver. Histograms of bootstrap resampling showed large overlap for all but the Beaver method. LMEM analysis showed that JM predicted significantly higher RC than Beaver and Dmax, but not Orr. All methods were significantly correlated with one another at both timepoints. LOA were wide. Conclusions: Beaver detects RC more infrequently than other methods. It is unknown if the higher %VO2max at RC predicted by JM is an overestimate. Although all methods highly and significantly correlate to one another, they have wide LOA. A better automated method may combine the results of several methods.
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University of Minnesota M.S. thesis. May 2019. Major: Kinesiology. Advisor: Li Li Ji. 1 computer file (PDF); vi, 60 pages.
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Hesse, Anton. (2019). Examining the Respiratory Compensation Point with Automated Methods in Recreational Runners Training for a Marathon. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/206173.
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