Open AccessImproving biologic predictors of cycling endurance performance with near‐infrared spectroscopy derived measures of skeletal muscle respiration: E pluribus unum
Author(s) -
Batterson Philip M.,
Norton Michael R.,
Hetz Sarah E.,
Rohilla Sachi,
Lindsay Keston G.,
Subudhi Andrew W.,
Jacobs Robert A.
Publication year - 2020
Publication title -
physiological reports
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.918
H-Index - 39
ISSN - 2051-817X
DOI - 10.14814/phy2.14342
Subject(s) - skeletal muscle , cycling , respiration , time trial , ventilatory threshold , exercise physiology , vo2 max , endurance training , oxidative phosphorylation , repeated measures design , analysis of variance , medicine , physical therapy , physical medicine and rehabilitation , chemistry , mathematics , statistics , heart rate , biochemistry , anatomy , blood pressure , archaeology , history
The study aim was to compare the predictive validity of the often referenced traditional model of human endurance performance (i.e. oxygen consumption, VO 2 , or power at maximal effort, fatigue threshold values, and indices of exercise efficiency) versus measures of skeletal muscle oxidative potential in relation to endurance cycling performance. We hypothesized that skeletal muscle oxidative potential would more completely explain endurance performance than the traditional model, which has never been collectively verified with cycling. Accordingly, we obtained nine measures of VO 2 or power at maximal efforts, 20 measures reflective of various fatigue threshold values, 14 indices of cycling efficiency, and near‐infrared spectroscopy‐derived measures reflecting in vivo skeletal muscle oxidative potential. Forward regression modeling identified variable combinations that best explained 25‐km time trial time‐to‐completion (TTC) across a group of trained male participants ( n = 24). The time constant for skeletal muscle oxygen consumption recovery, a validated measure of maximal skeletal muscle respiration, explained 92.7% of TTC variance by itself (Adj R 2 = .927, F = 294.2, SEE = 71.2, p < .001). Alternatively, the best complete traditional model of performance, including VO 2max (L·min −1 ), %VO 2max determined by the ventilatory equivalents method, and cycling economy at 50 W, only explained 76.2% of TTC variance (Adj R 2 = .762, F = 25.6, SEE = 128.7, p < .001). These results confirm our hypothesis by demonstrating that maximal rates of skeletal muscle respiration more completely explain cycling endurance performance than even the best combination of traditional variables long postulated to predict human endurance performance.