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.
Face cooling is associated with autonomic and cardiovascular alterations that accompany an increased blood pressure. Following an exercise heat stress, even minor increases in heart rate and vascular resistance may permit an improved blood pressure control during a simulated hemorrhagic challenge (Lower Body Negative Pressure, LBNP) and improve tolerance. Our aim was to examine whether modest reductions in face skin temperature would improve LBNP tolerance in exercise heat stressed individuals. Ten healthy subjects (Age: 29 ± 13 yrs; Ht: 177 ± 9 cm; Wt: 72.4 ± 8.0 kg) completed two counterbalanced trials (Trial A and Trial B) cycling at 63 ± 6% of their predetermined VO2Max whilst wearing a warm water perfused suit and face mask until core temperature had increased 1.5°C. Participants then underwent LBNP to pre syncope. LBNP tolerance was quantified as cumulative stress index (CSI; mmHg*min). Face skin temperature represents the average of forehead, cheek and chin skin temperatures. Face skin temperature was maintained at exercise heat stress values throughout LBNP in Trial A but was reduced via facial fanning in Trial B after 1 minute of LBNP. Arterial blood pressure (MAP, Penaz method), heart rate (HR, ECG), stroke volume (SV, Pulse Contour Analysis) were continuously measured and total peripheral resistance (TPR) was calculated. Following exercise heat stress, core (38.6 ± 0.2 °C), mean skin (38.2 ± 0.6 °C) and face skin (36.4 ± 0.5 °C) temperatures were elevated relative to baseline (all P < 0.05) and not different between trials (all P > 0.05). Face skin temperature remained elevated throughout LBNP in Trial A (36.1 ± 0.5 °C) but was reduced in Trial B (31.3 ± 1.6°C, P = 0.0001 between trials). Following exercise and prior to LBNP, HR was increased (63 ± 8 to 121 ±15 BPM) while MAP (86 ± 7 to 70 ± 6 mmHg) and TPR (12.5 ± 2.0 to 7.7 ± 1.6 mmHg/L/min) were similarly lowered relative to baseline in both trials (all P < 0.05). Mean arterial pressure was similarly reduced at pre syncope in both trials (54 ± 11 and 57 ± 5 mmHg; P < 0.0001 relative to prior to LBNP). TPR and HR increased during LBNP in both trials relative to baseline (both P < 0.05) but were not different between trials 2 minutes after the onset of LBNP (TPR: 7.8 ± 1.7 vs. 7.8 ± 1.8 mmHg/L/min and HR: 131 ± 17 vs. 137 ± 22 BPM, main effect of trial both P > 0.05). CSI was not different between trials (Trial A: 332 ± 176 vs. Trial B: 393 ± 261 mmHg*min; P = 0.482). LBNP tolerance was not improved by face skin cooling in exercise heat stressed individuals. These results suggest that modest reductions in face skin temperature are not accompanied by an improved blood pressure control during a simulated hemorrhagic challenge in exercise heat stressed individuals.
The study aim was to compare the predictive validity of the often referenced traditional model of human endurance performance (i.e. oxygen consumption, VO2, 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 VO2 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 R2 = .927, F = 294.2, SEE = 71.2, p < .001). Alternatively, the best complete traditional model of performance, including VO2max (L·min−1), %VO2max determined by the ventilatory equivalents method, and cycling economy at 50 W, only explained 76.2% of TTC variance (Adj R2 = .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.
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