Effect of free versus constant pace on performance and oxygen kinetics in running

Prognostic Value of Pace Variability, a Novel 6MWT-Derived Feature, in Patients with Chronic Obstructive Pulmonary Disease

Purpose

The 6-minute walk test (6MWT) is often used to evaluate chronic obstructive pulmonary disease (COPD) patients' functional capacity, with 6-minute walk distance (6MWD) and related measures being linked to mortality and hospitalizations. This study investigates the prognostic value of pace variability, a significant indicator in sports medicine, during the 6MWT for COPD patients.

Patients and Methods

We retrospectively screened consecutive COPD patients who had been prospectively enrolled in a pay-for-performance program from January 2019 to May 2020 to determine their eligibility. Patient characteristics, including demographics, exacerbation history, and 6MWT data, were analyzed to investigate their potential associations with prognosis. The primary outcome was a composite of adverse events, including overall mortality or hospitalizations due to exacerbations during a 1-year follow-up period. To analyze the 6MWT data, we divided it into three 2-minute epochs and calculated the average walk speed for each epoch. We defined pace variability as the difference between the maximum and minimum average speed in a single 2-minute epoch, divided by the average speed for the entire 6-minute walk test.

Results

A total of 163 patients with COPD were included in the study, and 19 of them (12%) experienced the composite adverse outcome. Multivariable logistic regression analyses revealed that two predictors were independently associated with the composite outcome: % predicted 6MWD <72 (adjusted odds ratio [aOR] 7.080; 95% confidence interval [CI] 1.481-33.847) and pace variability ≥0.39 (aOR 9.444; 95% CI 2.689-33.170). Patients with either of these adverse prognostic features had significantly worse composite outcome-free survival, with both log-rank P values less than 0.005. Notably, COPD patients with both adverse features experienced an especially poor outcome after 1 year.

Conclusion

Patients with COPD who exhibited greater pace variability during the 6MWT had a significantly higher risk of overall mortality and COPD-related hospitalizations, indicating a worse prognosis.

Marathon Performance Depends on Pacing Oscillations between Non Symmetric Extreme Values

A marathon was recently run in less than 2 h by a man who ran the three fastest marathons ever recorded in a span of three years—Eliud Kipchoge—in the Tokyo Olympic games. Here, we demonstrate that the best marathons were run according to a pace distribution that is statistically not constant and with negative asymmetry. The concept of mirror race enables us to show that the sign of asymmetry is not due to sampling fluctuations. We show that marathon performance depends on pacing oscillations between extreme values, and that even the best marathons ever run differ and can be improved upon. The utilization of extreme values and oscillations allows for recovery and optimization of the complementary aerobic and anaerobic metabolisms. Our findings suggest new ways to approach the pacing for optimizing endurance performance.

Pace Controlled by a Steady-State Physiological Variable Is Associated with Better Performance in a 3000 M Run

This paper aims to test the hypothesis whereby freely chosen running pace is less effective than pace controlled by a steady-state physiological variable. Methods Eight runners performed four maximum-effort 3000 m time trials on a running track. The first time trial (TT1) was freely paced. In the following 3000 m time trials, the pace was controlled so that the average speed (TT2), average V˙O2 (TT3) or average HR (TT4) recorded in TT1 was maintained throughout the time trial. Results: Physiologically controlled pace was associated with a faster time (mean ± standard deviation: 740 ± 34 s for TT3 and 748 ± 33 s for TT4, vs. 854 ± 53 s for TT1; p < 0.01), a lower oxygen cost of running (200 ± 5 and 220 ± 3 vs. 310 ± 5 mLO2·kg-1·km-1, respectively; p < 0.02), a lower cardiac cost (0.69 ± 0.08 and 0.69 ± 0.04 vs. 0.86 ± 0.09 beat·m-1, respectively; p < 0.01), and a more positively skewed speed distribution (skewness: 1.7 ± 0.9 and 1.3 ± 0.6 vs. 0.2 ± 0.4, p < 0.05). Conclusion: Physiologically controlled pace (at the average V˙O2 or HR recorded in a freely paced run) was associated with a faster time, a more favorable speed distribution and lower levels of physiological strain, relative to freely chosen pace. This finding suggests that non-elite runners do not spontaneously choose the best pace strategy.

Pacing and Positioning Strategies During an Elite Fixed-Gear Cycling Criterium

Fixed-gear cycling performance during criteriums predominantly involves the aerobic system. Whether pacing is another important factor for performance is unknown. The purpose of the present study was to explore pacing and/or positioning strategies of fixed-gear riders during criteriums. Race results of an international fixed-gear criterium were analyzed (20 laps for women and 28 laps for men; laps = 1,270 m). Statistics were conducted on individuals lap time and positioning during the finals. Race pattern in women (n = 35) and men (n = 53) revealed that the faster laps (P < 0.05) were in the middle and at the end of the race and the slower laps (P < 0.05) were at the end of the race (laps 17–18 for women and lap 26 for men). The final ranking was significantly correlated with the mean race position (Kendall's tau = 0.664 and 0.689 for women and men, respectively). A coefficient of variation >50% revealed an important positioning variability. The best riders are mostly amongst the first during the race. However, the others exhibited larger mean position variations during the first half of the race. Our results demonstrated variable pacing strategies during fixed-gear criteriums. Although some riders had economical drafting strategies during the first half of the race, riding placed ahead during the whole race seemed to be an essential performance factor.

Cycling performance is superior for time-to-exhaustion versus time-trial in endurance laboratory tests

Time-to-exhaustion (TTE) trials are used in a laboratory setting to measure endurance performance. However, there is some concern with their ecological validity compared with time-trials (TT). Consequently, we aimed to compare cycling performance in TTE and TT where the duration of the trials was matched. Seventeen trained male cyclists completed three TTE trials at 80, 100 and 105% of maximal aerobic power (MAP). On a subsequent visit they performed three TT over the same duration as the TTE. Participants were blinded to elapsed time, power output, cadence and heart rate (HR). Average TTE was 865 ± 345 s, 165 ± 98 s and 117 ± 45 s for the 80, 100 and 105% trials respectively. Average power output was higher for TTE (294 ± 44 W) compared to TT (282 ± 43 W) at 80% MAP (P < 0.01), but not at 100 and 105% MAP (P > 0.05). There was no difference in cadence, HR, or RPE for any trial (P > 0.05). Critical power (CP) was also higher when derived from TTE compared to TT (P < 0.01). It is concluded that TTE results in a higher average power output compared to TT at 80% MAP. When determining CP, TTE rather than TT protocols appear superior.

Clinical Impact of Speed Variability to Identify Ultramarathon Runners at Risk for Acute Kidney Injury

BACKGROUND

Ultramarathon is a high endurance exercise associated with a wide range of exercise-related problems, such as acute kidney injury (AKI). Early recognition of individuals at risk of AKI during ultramarathon event is critical for implementing preventative strategies.

OBJECTIVES

To investigate the impact of speed variability to identify the exercise-related acute kidney injury anticipatively in ultramarathon event.

METHODS

This is a prospective, observational study using data from a 100 km ultramarathon in Taipei, Taiwan. The distance of entire ultramarathon race was divided into 10 splits. The mean and variability of speed, which was determined by the coefficient of variation (CV) in each 10 km-split (25 laps of 400 m oval track) were calculated for enrolled runners. Baseline characteristics and biochemical data were collected completely 1 week before, immediately post-race, and one day after race. The main outcome was the development of AKI, defined as Stage II or III according to the Acute Kidney Injury Network (AKIN) criteria. Multivariate analysis was performed to determine the independent association between variables and AKI development.

RESULTS

26 ultramarathon runners were analyzed in the study. The overall incidence of AKI (in all Stages) was 84.6% (22 in 26 runners). Among these 22 runners, 18 runners were determined as Stage I, 4 runners (15.4%) were determined as Stage II, and none was in Stage III. The covariates of BMI (25.22 ± 2.02 vs. 22.55 ± 1.96, p = 0.02), uric acid (6.88 ± 1.47 vs. 5.62 ± 0.86, p = 0.024), and CV of speed in specific 10-km splits (from secondary 10 km-split (10th - 20th km-split) to 60th - 70th km-split) were significantly different between runners with or without AKI (Stage II) in univariate analysis and showed discrimination ability in ROC curve. In the following multivariate analysis, only CV of speed in 40th - 50th km-split continued to show a significant association to the development of AKI (Stage II) (p = 0.032).

CONCLUSIONS

The development of exercise-related AKI was not infrequent in the ultramarathon runners. Because not all runners can routinely receive laboratory studies after race, variability of running speed (CV of speed) may offer a timely and efficient tool to identify AKI early during the competition, and used as a surrogate screening tool, at-risk runners can be identified and enrolled into prevention trials, such as adequate fluid management and avoidance of further NSAID use.

The effect of endpoint knowledge on perceived exertion, affect, and attentional focus during self-paced running

The purpose of this study was to determine the effect of endpoint knowledge on psychophysiological variables. Twenty-two runners (11 men and 11 women) participated in 2 conditions: a run with an unknown endpoint and a run to the same distance with knowledge of the endpoint. Rating of perceived exertion (RPE), affect, heart rate, and attentional focus were assessed during testing. Subjects ran faster when the endpoint was known (p < 0.01) but no differences in RPE, affect, or heart rate between conditions were present (p > 0.05). There were differences in attentional focus between conditions (p = 0.034) and subjects reported more associative thoughts in the known endpoint condition. Cardiorespiratory fitness was a significant predictor of attentional focus in the known endpoint condition. In sum, when the endpoint was known, subjects used more associative strategies as RPE increased, and those with higher fitness levels used more associative strategies overall.

Factors influencing pacing in triathlon

Triathlon is a multisport event consisting of sequential swim, cycle, and run disciplines performed over a variety of distances. This complex and unique sport requires athletes to appropriately distribute their speed or energy expenditure (ie, pacing) within each discipline as well as over the entire event. As with most physical activity, the regulation of pacing in triathlon may be influenced by a multitude of intrinsic and extrinsic factors. The majority of current research focuses mainly on the Olympic distance, whilst much less literature is available on other triathlon distances such as the sprint, half-Ironman, and Ironman distances. Furthermore, little is understood regarding the specific physiological, environmental, and interdisciplinary effects on pacing. Therefore, this article discusses the pacing strategies observed in triathlon across different distances, and elucidates the possible factors influencing pacing within the three specific disciplines of a triathlon.

Determinants of performance in 1,500-m runners

Our aim was to investigate the relationship between physiological variables (not previously studied) and performance in elite 1,500-m runners. We assessed eight male athletes with an average personal best time of 233.3 ± 6.9 s (110% of the world record) for the 1,500-m race. Ventilatory measurements, maximal oxygen consumption VO2max maximal vastus lateralis muscle deoxygenation (∆[deoxy(Hb+Mb)])max via near-infrared spectroscopy (NIRS), and maximal velocity (V (max)) were obtained during an incremental treadmill test. During subsequent constant-speed exercise at Vmax, we determined the time to exhaustion (Tlim), end-exercise blood lactate concentration ([La]b(max)), VO2 and ∆[deoxy(Hb+Mb)] kinetics parameters. The mean VO2max, [La]b(max) and Vmax were 70.2 ± 3.9 mL kg(-1) min(-1), 12.7 ± 2.4 mmol L(-1), 21.5 ± 0.5 km h(-1), respectively. VO2 at Vmax showed a significant negative correlation with Tlim, whereas [La]b(max) was positively correlated with Tlim. Race speed was found to significantly correlate with ∆[deoxy(Hb+Mb)](max) (79% of maximal value obtained during a transient limb ischemia), ∆[deoxy(Hb+Mb)] slow component (22.9 ± 9.3% of total amplitude) and [La]b(max) at Vmax. [La]b(max) at Vmax was also significantly correlated with ∆[deoxy(Hb+Mb)] slow component, suggesting a greater release of oxygen from the hemoglobin due to the Bohr effect. We conclude that both the maximal capacity of muscle to extract O2 from the blood and the end-exercise blood lactate accumulation are important predictors of best performance in 1,500-m runners.

Physiological demand and pacing strategy during the new combined event in elite pentathletes

To evaluate the physiological demands and effects of different pacing strategies on performance during the new combined event (CE) of the modern pentathlon (consisting of three pistol shooting sessions interspersed by three 1-km running legs). Nine elite pentathletes realised five tests: a free-paced CE during an international competition; an incremental running test to determine [Formula: see text] and its related velocity ([Formula: see text]) and three experimental time-trial CE, where the pacing strategy was manipulated (CE(ref), CE(100%), CE(105%)). CE(ref) reproduced the international competition strategy with a 170-m fast running start within the first 2 km. CE(100%) and CE(105%) imposed a constant strategy over km-1 and km-2 with a velocity of 100 and 105% of the mean speed adopted over the same sections during the international competition, respectively. Km-3 was always self-paced. The subjects ran CE(ref) at 99 ± 4% of [Formula: see text] and reached 100 ± 5, 100 ± 7, 99 ± 8% of [Formula: see text] at the end of kilometres 1, 2 and 3, respectively ([Formula: see text]: 72 ± 6 mL O(2) min(-1) kg(-1)), with a peak blood lactate concentration of 13.6 ± 1.5 mmol L(-1). No significant differences in overall performance were found between the pacing conditions (753 ± 30, 770 ± 39, 768 ± 27 s for CE(ref), CE(100%) and CE(105%), respectively, p = 0.63), but all of the shooting performance parameters were only stable in CE(ref). Completion of CE by elite pentathletes elicits a maximal aerobic contribution coupled with a high glycolytic supply. Manipulating the mean running speed over km-1 and km-2 had strong influence on the overall pacing strategy and induced minor differences in shooting performance, but it did not affect overall performance.

Performance factors in the new combined event of modern pentathlon

The aims of this study were to determine (1) the individual tactics employed by elite modern pentathletes within each discipline of the new combined running-shooting event, and (2) the consequences of these strategies on overall performance. For 36 male pentathletes competing in a World Cup event, we measured running velocity, transition time, shooting time, shooting accuracy, and delay per shot. Performances of the top third of athletes, middle third of athletes, and the bottom third of athletes in the combined event were compared. The difference in overall performance between the top third and middle/bottom thirds was predominately associated with better shooting accuracy (79 +/- 13%, 68 +/- 12%, and 64 +/- 10% success rate for top, middle, and bottom third, respectively) and faster shooting time (86 +/- 16 s, 109 +/- 19 s, and 117 +/- 23 s for top, middle, and bottom third, respectively). No significant differences in running velocity, transition time or delay per shot were observed among the three groups. All the competitors started significantly faster over the first 200 m of each of the three 1-km running stages. The last third of the approximately 3-km race was completed significantly faster by all athletes (P < 0.05). The main finding was that the best performers of the combined event distinguished themselves due to their greater shooting accuracy.

Pacing strategy during the initial phase of the run in triathlon: influence on overall performance

The aim of the present study was to determine the best pacing strategy to adopt during the initial phase of a short distance triathlon run for highly trained triathletes. Ten highly trained male triathletes completed an incremental running test to determine maximal oxygen uptake, a 10-km control run at free pace and three individual time-trial triathlons (1.5-km swimming, 40-km cycling, 10-km running) in a randomised order. Swimming and cycling speeds were imposed as identical to the first triathlon performed and the first run kilometre was done alternatively 5% faster (Tri-Run(+5%)), 5% slower (Tri-Run(-5%)) and 10% slower (Tri-Run(-10%)) than the control run (C-Run). The subjects were instructed to finish the 9 remaining kilometres as quickly as possible at a free self-pace. Tri-Run(-5%) resulted in a significantly faster overall 10-km performance than Tri-Run(+5%) and Tri-Run(-10%) (p < 0.05) but no significant difference was observed with C-Run (p > 0.05) (2,028 +/- 78 s vs. 2,000 +/- 72 s, 2,178 +/- 121 s and 2,087 +/- 88 s, for Tri-Run(-5%), C-Run, Tri-Run(+5%) and Tri-Run(-10%), respectively). Tri-Run(+5%) strategy elicited higher values for oxygen uptake, ventilation, heart rate and blood lactate at the end of the first kilometre than the three other conditions. After 5 and 9.5 km, these values were higher for Tri-Run(-5%) (p < 0.05). The present results showed that the running speed achieved during the cycle-to-run transition is crucial for the improvement of the running phase as a whole. Triathletes would benefit to automate a pace 5% slower than their 10-km control running speed as both 5% faster and 10% slower running speeds over the first kilometre involved weaker overall performances.

Differential modeling of anaerobic and aerobic metabolism in the 800-m and 1,500-m run

This study examined the hypothesis that running speed over 800- and 1,500-m races is regulated by the prevailing anaerobic (oxygen independent) store (ANS) at each instant of the race up until the all-out phase of the race over the last several meters. Therefore, we hypothesized that the anaerobic power that allows running above the speed at maximal oxygen uptake (V̇o2max) is regulated by ANS, and as a consequence the time limit at the anaerobic power (tlim PAN = ANS/PAN) is constant until the final sprint. Eight 800-m and seven 1,500-m male runners performed an incremental test to measure V̇o2max and the minimal velocity associated with the attainment of V̇o2max ( vV̇o2max), referred to as maximal aerobic power, and ran the 800-m or 1,500-m race with the intent of achieving the lowest time possible. Anaerobic power (PAN) was measured as the difference between total power and aerobic power, and instantaneous ANS as the difference between end-race and instantaneous accumulated oxygen deficits. In 800 m and 1,500 m, tlim PAN was constant during the first 70% of race time in both races. Furthermore, the 1,500-m performance was significantly correlated with tlim PAN during this period ( r = −0.92, P < 0.01), but the 800-m performance was not ( r = −0.05, P = 0.89), although it was correlated with the end-race oxygen deficit ( r = −0.70, P = 0.05). In conclusion, this study shows that in middle-distance races over both 800 m and 1,500 m, the speed variations during the first 70% of the race time serve to maintain constant the time to exhaustion at the instantaneous anaerobic power. This observation is consistent with the hypothesis that at any instant running speed is controlled by the ANS remaining.

Distribution of Power Output During Cycling

We aim to summarise the impact and mechanisms of work-rate pacing during individual cycling time trials (TTs). Unlike time-to-exhaustion tests, a TT provides an externally valid model for examining how an initial work rate is chosen and maintained by an athlete during self-selected exercise. The selection and distribution of work rate is one of many factors that influence cycling speed. Mathematical models are available to predict the impact of factors such as gradient and wind velocity on cycling speed, but only a few researchers have examined the inter-relationships between these factors and work-rate distribution within a TT. When environmental conditions are relatively stable (e.g. in a velodrome) and the TT is >10 minutes, then an even distribution of work rate is optimal. For a shorter TT (< or = 10 minutes), work rate should be increased during the starting effort because this proportion of total race time is significant. For a very short TT (< or = 2 minutes), the starting effort should be maximal, since the time saved during the starting phase is predicted to outweigh any time lost during the final metres because of fatigue. A similar 'time saving' rationale underpins the advice that work rate should vary in parallel with any changes in gradient or wind speed during a road TT. Increasing work rate in headwind and uphill sections, and vice versa, decreases the variability in speed and, therefore, the total race time. It seems that even experienced cyclists naturally select a supraoptimal work rate at the start of a longer TT. Whether such a start can be 'blunted' through coaching or the monitoring of psychophysiological variables is unknown. Similarly, the extent to which cyclists can vary and monitor work rate during a TT is unclear. There is evidence that sub-elite cyclists can vary work rate by +/-5% the average for a TT lasting 25-60 minutes, but such variability might be difficult with high-performance cyclists whose average work rate during a TT is already extremely high (>350 watts). During a TT, pacing strategy is regulated in a complex anticipatory system that monitors afferent feedback from various physiological systems, and then regulates the work rate so that potentially limiting changes do not occur before the endpoint of exercise is reached. It is critical that the endpoint of exercise is known by the cyclist so that adjustments to exercise work rate can be made within the context of an estimated finish time. Pacing strategies are thus the consequence of complex regulation and serve a dual role: they are both the result of homeostatic regulation by the brain, as well as being the means by which such regulation is achieved. The pacing strategy 'algorithm' is sited in the brain and would need afferent input from interoceptors, such as heart rate and respiratory rate, as well as exteroceptors providing information on local environmental conditions. Such inputs have been shown to induce activity in the thalamus, hypothalamus and the parietal somatosensory cortex. Knowledge of time, modulated by the cerebellum, basal ganglia and primary somatosensory cortex, would also input to the pacing algorithm as would information stored in memory about previous similar exercise bouts. How all this information is assimilated by the different regions of the brain is not known at present.

Nonlinear dynamics of heart rate and oxygen uptake in exhaustive 10,000 m runs: influence of constant vs. freely paced

We hypothesized that a freely paced 10,000 m running race would induce a smaller physiological strain (heart rate and oxygen uptake) compared with one performed at the same average speed but with an imposed constant pace. Furthermore, we analyzed the scaling properties with a wavelet transform algorithm computed log2 (wavelet transform energy) vs. log2 (scale) to get slope alpha, which is the scaling exponent, a measure of the irregularity of a time series. HR was sampled beat by beat and V2O, breath by breath. The enforced constant pace run elicited a significantly higher mean VO2 value (53 +/- 4 vs. 48 +/- 5 ml kg(-1) min(-1), P < 0.001), HR (169 +/- 13 vs. 165 +/- 14 bpm, P < 0.01), and blood lactate concentration (6.6 +/- 0.9 vs. 7.5 +/- 1 mM, P < 0.001) than the freely paced run. HR and VO2 signals showed a scaling behavior, which means that the signals have a similar irregularity (a self-similarity) whatever the scale of analysis may be, in both constant and free-paced 10,000 m runs. The scaling exponent was not significantly different according to the type of run (free vs. constant, P > 0.05) and the signal (HR vs. VO2, P > 0.05). The higher metabolic cost of constant vs. free paced run did not affect the self-similarity of HR and VO2, in either run. The HR signal only kept its scaling behavior only with a distance run, no matter the type of run (free or constant). The results suggest that the larger degree of pace variation in freely paced races may be an intentionally chosen strategy designed to minimize the physiological strain during severe exercise and to prevent a premature termination of effort, even if the variability of the heart rate and VO2, are comparable in an enforced constant vs. a freely paced run and if HR keeps the same variability until the arrival.

Factors affecting running economy in trained distance runners

Running economy (RE) is typically defined as the energy demand for a given velocity of submaximal running, and is determined by measuring the steady-state consumption of oxygen (VO2) and the respiratory exchange ratio. Taking body mass (BM) into consideration, runners with good RE use less energy and therefore less oxygen than runners with poor RE at the same velocity. There is a strong association between RE and distance running performance, with RE being a better predictor of performance than maximal oxygen uptake (VO2max) in elite runners who have a similar VO2max). RE is traditionally measured by running on a treadmill in standard laboratory conditions, and, although this is not the same as overground running, it gives a good indication of how economical a runner is and how RE changes over time. In order to determine whether changes in RE are real or not, careful standardisation of footwear, time of test and nutritional status are required to limit typical error of measurement. Under controlled conditions, RE is a stable test capable of detecting relatively small changes elicited by training or other interventions. When tracking RE between or within groups it is important to account for BM. As VO2 during submaximal exercise does not, in general, increase linearly with BM, reporting RE with respect to the 0.75 power of BM has been recommended. A number of physiological and biomechanical factors appear to influence RE in highly trained or elite runners. These include metabolic adaptations within the muscle such as increased mitochondria and oxidative enzymes, the ability of the muscles to store and release elastic energy by increasing the stiffness of the muscles, and more efficient mechanics leading to less energy wasted on braking forces and excessive vertical oscillation. Interventions to improve RE are constantly sought after by athletes, coaches and sport scientists. Two interventions that have received recent widespread attention are strength training and altitude training. Strength training allows the muscles to utilise more elastic energy and reduce the amount of energy wasted in braking forces. Altitude exposure enhances discrete metabolic aspects of skeletal muscle, which facilitate more efficient use of oxygen. The importance of RE to successful distance running is well established, and future research should focus on identifying methods to improve RE. Interventions that are easily incorporated into an athlete's training are desirable.

Energetics of Middle-Distance Running Performances in Male and Female Junior Using Track Measurements

The aim of this study was to determine the energetic factors of middle-distance running performance in junior elite runners according to gender and by using measurements from on-track performances. Fifteen elite runners (8 males and 7 females) were investigated by means of an incremental test and an all-out run over 600 m performed with a 2-d interval. We calculated (1) the aerobic maximal power (E(r max aero), in W kg(-1)), including VO(2 max) and the delay of attainment of VO(2 max) in the 600 m run; (2) the anaerobic power (E(r max anaero)), i.e., the oxygen deficit (J kg(-1)) divided by the duration of the 600 m run. Despite the difference in race duration (87 +/- 3 vs. 102 +/- 2 s), the 600 m run was made at the same relative value of the velocity associated with VO(2 max) (VVO(2 )max) in males and females (121.6 +/- 7 vs. 120 +/- 8% VO(2 max), p = 0.7). E(r max aero) explained most of the variance in the performance (the personal best performed 8 weeks later) between genders: 65 and 79% over 800 m (T(800)) and 1,500 m (T(1,500)). For females, E(r max aero) explained most of the variance of T(1,500) (r(2) = 0.66), and E(r max anaero) improved this prediction (r(2) = 0.84). No energetic factor predicted the performance on 800 m run in males. In elite junior athletes, the energetic model with individual data measured over an all-out 600 m performed on a track, provides an explanation for most of the variance in middle-distance running performances between genders. The distinction between aerobic power and anaerobic power allowed an improvement in the prediction of middle-distance running performances.

The concept of maximal lactate steady state: a bridge between biochemistry, physiology and sport science

The maximal lactate steady state (MLSS) is defined as the highest blood lactate concentration (MLSSc) and work load (MLSSw) that can be maintained over time without a continual blood lactate accumulation. A close relationship between endurance sport performance and MLSSw has been reported and the average velocity over a marathon is just below MLSSw. This work rate delineates the low- to high-intensity exercises at which carbohydrates contribute more than 50% of the total energy need and at which the fuel mix switches (crosses over) from predominantly fat to predominantly carbohydrate. The rate of metabolic adenosine triphosphate (ATP) turnover increases as a direct function of metabolic power output and the blood lactate at MLSS represents the highest point in the equilibrium between lactate appearance and disappearance both being equal to the lactate turnover. However, MLSSc has been reported to demonstrate a great variability between individuals (from 2-8 mmol/L) in capillary blood and not to be related to MLSSw. The fate of enhanced lactate clearance in trained individuals has been attributed primarily to oxidation in active muscle and gluconeogenesis in liver. The transport of lactate into and out of the cells is facilitated by monocarboxylate transporters (MCTs) which are transmembrane proteins and which are significantly improved by training. Endurance training increases the expression of MCT1 with intervariable effects on MCT4. The relationship between the concentration of the two MCTs and the performance parameters (i.e. the maximal distance run in 20 minutes) in elite athletes has not yet been reported. However, lactate exchange and removal indirectly estimated with velocity constants of the individual blood lactate recovery has been reported to be related to time to exhaustion at maximal oxygen uptake.