Acute effects of multi-ingredient pre-workout dietary supplement on anaerobic performance in untrained men: a randomized, crossover, single blind study

BACKGROUND

Multi-ingredient pre-workout dietary supplements (MIPS), which are combinations of different ingredients acting on different physiological mechanisms, can have a synergistic effect and improve performance. The aim of the study was to determine the acute effects of a multi-ingredient pre-workout supplement containing: beta-alanine, taurine, caffeine, L-tyrosine, and cayenne pepper (capsaicin) on anaerobic performance.

METHODS

A randomized, crossover, single-blind study was designed. Twelve young, healthy, untrained men aged 22.4 ± 1.44 years participated in the study. The participants performed a supramaximal all-out test (20 s Wingate test) twice, day by day, in random order: test after placebo or MIPS consumption. In both trials, the following variables were measured in the exercise test: total work performed, peak power, mean power, time to reach peak power, and power decrease.

RESULTS

MIPS was found to be effective in improving peak power (p = 0.009, ES = 0.77) and mean power (p = 0.04, ES = 0.62) in the Wingate test. However, the supplement consumption did not affect the amount of total work done (p = 0.10, ES = 0.48) in the test or power decrease (p = 0.07, ES = 0.53). The data indicate, that the improvement in anaerobic power was due to a significant improvement in pedaling speed, which was manifested in a significant improvement (i.e. shortening) in time to peak power (p = 0.003, ES = 0.88).

CONCLUSION

A multi-ingredient pre-workout dietary supplement was found to be effective in improving Wingate (anaerobic) performance.

TRIAL REGISTRATION

NCT06363669, retrospectively registered on 11.04.2024 (ClinicalTrials.gov).

Impact of Anaerobic Exercise Integrated Into Regular Training on Experienced Judo Athletes: Running Vs. Repetitive Throws

ABSTRACT

Kamandulis, S, Dudėnienė, L, Snieckus, A, Kniubaite, A, Mickevicius, M, Lukonaitiene, I, Venckunas, T, Stasiule, L, and Stasiulis, A. Impact of anaerobic exercise integrated into regular training on experienced judo athletes: running vs. repetitive throws. J Strength Cond Res XX(X): 000-000, 2024-Anaerobic training in high-level athletes is of considerable interest to practitioners aiming to optimize performance. This study compared the impact of interval anaerobic training (IAT) sessions consisting of either high-intensity running or throwing that were performed twice a week together with regular judo training on the anaerobic and aerobic performance of experienced judo athletes. Employing a repeated-measures, counterbalancing, research design, 12 national team judo athletes (7 women and 5 men; mean age, 20.4 ± 0.95 years; mean judo training experience, 13.4 ± 1.4 years; competitive level, black belt first and second Dan) performed each IAT modality for 6 weeks, for a full training cycle of 12 weeks. Assessments of their anaerobic fitness (Cunningham and Faulkner Anaerobic Treadmill Test), sport-specific anaerobic fitness (Special Judo Fitness Test [SJFT]), and aerobic capacity (maximal incremental treadmill running test) were performed before, after 6 weeks, and after 12 weeks of training. The uphill running performance improved by 13.1% over the 12-week period (p = 0.047). Simultaneously, there was a 9.0% improvement in the SJFT index and a 6.9% increase in the number of throws (p = 0.011 and p = 0.017, respectively). Although a trend for throwing drills being more effective than interval sprint running was observed, the interaction effect lacked statistical significance (p = 0.074). Moreover, no substantial changes were noted in aerobic endurance markers. In conclusion, this study suggests that incorporating specific and nonspecific high-intensity drills into a routine training regimen may enhance anaerobic capacity among well-trained judo athletes, potentially leading to favorable competitive outcomes.

Reliability of the Maximal Lactate Accumulation Rate in Rowers

The maximal lactate accumulation rate (VLamax) has been linked to lactic anaerobic performance. Hence, accurate and reliable assessment is crucial in sport-specific performance testing. Thus, between-day reliability data of rowing-specific VLamax assessment was examined. Seventeen trained rowers (eight females and nine males; 19.5±5.2 yrs; 1.76±0.08 m; 70.2±8.9 kg; V̇O2max: 54±13 ml/min/kg) performed 20-s sprint tests on two separate days (one week apart) on a rowing ergometer. VLamax, peak lactate concentration, time to peak lactate, and mean rowing power were measured. Good to excellent intraclass correlation coefficients (ICCs), low standard error of measurement (SEM), and acceptable levels of agreement (LoAs; 90% confidence interval) for VLamax (ICC=0.85; SEM=0.02 mmol/L/s; LoA±0.09 mmol/L/s), peak lactate (ICC=0.88; SEM=0.3 mmol/L; LoA±1.4 mmol/l), time to peak lactate (ICC=0.92; SEM=0.1 min; LoA±0.5 min), and mean rowing power (ICC=0.98; SEM=3 W; LoA±39 W) were observed. In addition, VLamax was highly correlated (r=0.96; p≤0.001) to rowing power. Thus, VLamax and sprint performance parameters can be measured highly reliably using this sport-specific sprint test in rowing.

Can Hypoxia Alter the Anaerobic Capacity Measured by a Single Exhaustive Exercise?

The present study aimed to compare the MAODALT in situations of hypoxia and normoxia to confirm the method validity. Seventeen healthy and physically active men participated in this study, aged 25.2±3.2 years. All participants underwent four days of evaluation. The first day was performed a body composition test, an incremental test to exhaustion to determine the maximum oxygen uptake, familiarizing the hypoxia (H) and normoxia (N) situation and the equipment used. On the second, third and fourth days, supramaximal efforts were performed until exhaustion at 110% of maximum oxygen uptake, in a situation of hypoxia (FIO2=14.0%) and normoxia (FIO2=20.9%). The anaerobic capacity was considered the sum of energy supply of the alactic and lactic systens. The absolute or relative anaerobic capacity values were not different (H=3.9±1.1 L, N=3.8±0.9 L, p=0.69), similarly no differences were found for the alactic contribution (H=1.7±0.5 L, N=1.5±0.5 L, p=0.30) and lactic contribution (H=2.3±0.9 L, N=2.3±0.7 L, p=0.85). It can be concluded that the anaerobic capacity measured by a single exhaustive effort is not altered by hypoxia.

A computational predictor of the anaerobic mechanical power outputs from a clinical exercise stress test

We previously were able to predict the anaerobic mechanical power outputs using features taken from a maximal incremental cardiopulmonary exercise stress test (CPET). Since a standard aerobic exercise stress test (with electrocardiogram and blood pressure measurements) has no gas exchange measurement and is more popular than CPET, our goal, in the current paper, was to investigate whether features taken from a clinical exercise stress test (GXT), either submaximal or maximal, can predict the anaerobic mechanical power outputs to the same level as we found with CPET variables. We have used data taken from young healthy subjects undergoing CPET aerobic test and the Wingate anaerobic test, and developed a computational predictive algorithm, based on greedy heuristic multiple linear regression, which enabled the prediction of the anaerobic mechanical power outputs from a corresponding GXT measures (exercise test time, treadmill speed and slope). We found that for submaximal GXT of 85% age predicted HRmax, a combination of 3 and 4 variables produced a correlation of r = 0.93 and r = 0.92 with % error equal to 15 ± 3 and 16 ± 3 on the validation set between real and predicted values of the peak and mean anaerobic mechanical power outputs (p < 0.001), respectively. For maximal GXT (100% of age predicted HRmax), a combination of 4 and 2 variables produced a correlation of r = 0.92 and r = 0.94 with % error equal to 12 ± 2 and 14 ± 3 on the validation set between real and predicted values of the peak and mean anaerobic mechanical power outputs (p < 0.001), respectively. The newly developed model allows to accurately predict the anaerobic mechanical power outputs from a standard, submaximal and maximal GXT. Nevertheless, in the current study the subjects were healthy, normal individuals and therefore the assessment of additional subjects is desirable for the development of a test applicable to other populations.

Rowing in Los Angeles: Performance Considerations for the Change to 1500 m at the 2028 Olympic Games

BACKGROUND

World Rowing's decision to support the proposed change from a 2000-m to a 1500-m regatta course at the 2028 Olympic Games in Los Angeles is anticipated to have important implications for athlete preparation and race execution during the 2024-2028 quadrennium.

PURPOSE

This commentary aims to provide insight into the expected implications of the reduction in course length heading into the 2028 Games, focusing on the training and monitoring of high-performance rowers, as well as tactical, technical, and pacing considerations for performance. The reduction in event duration (estimated to be ∼90-120 s across all event classes) will lead to an expected ∼5% to 15% increase in relative contribution of anaerobic metabolism. Consequently, adjustment in training periodization priorities toward higher-intensity interventions may be required, especially in the period immediately prior to the games. The critical-power and anaerobic-power-reserve concepts may become more useful tools for structuring exercise programs, evaluating training outcomes, and determining event suitability through individual physiological profiling. Additionally, the adoption of a more constant (flat) pacing strategy, rather than the commonly used reverse J-shaped approach, might be considered for racing over this new distance. Finally, technical aspects, such as stroke rate and gearing, may require adjustment for optimal performance; however, research is clearly required to explore such effects.

CONCLUSIONS

Our intention is to stimulate discussion and debate, with the provision of practical recommendations that aim to optimize rowers' preparation for and performance at the 2028 Olympic Games.

Dose-response relationship between training load and anaerobic performance in female short-track speed skaters: A prospective cohort study

This study aimed to assess the dose-response relationship (DRR) between measures of training load (TL) and anaerobic performance in female short-track speed skaters. TL data from 22 female short-track speed skaters (mean ± SD; calendar age 20.7 ± 2.01 years, training length 4.18 ± 1.23 years, height 164.20 ± 5.53 cm, weight 52.00 ± 5.58 kg) was collected over a six week period. Participants completed two anaerobic capacity assessments (cycling parameters: total work, maximal anaerobic power [MAnP], power duration indices, maximal blood lactate, fatigue indices, and peak power output [PPO]) pre- and post-training, which included three tests (short-term, intermediate-term, and 120 s maximal anaerobic test). The mean weekly TL measures calculated were total distance, red zone (time spent > 85% of peak heart rate), Edwards training impulse (eTRIMP), Stagno training impulse (gTRIMP), Lucia training impulse, and session ratings of perceived exertion. The gTRIMP identified a curvilinear relationship and explained 79% and 63% of the variance in changes of MAnPⁱ and PPO (R² = 0.79, 95%CI = 0.64 to 1.00, turn point 621AU; R² = 0.63, 95%CI = 0.27 to 1.00, turn point 633AU, respectively). Likewise, The eTRIMP identified a curvilinear relationship and explained 62% and 54% of the variance in changes of MAnPⁱ and PPO (R² = 0.62, 95%CI = 0.11 to 1.00, turn point 485AU; R² = 0.54, 95%CI = 0.07 to 1.00, turn point 515AU, respectively). All other variables exhibited a DRR below moderate. This study investigated a TL strategy to improve the speed endurance of female short-track speed skaters and suggested the superiority of gTRIMP and eTRIMP methods of internal TL.

Anaerobic work capacity in cycling: the effect of computational method

Purpose

To compare the anaerobic work capacity (AnWC, i.e., attributable anaerobic mechanical work) assessed using four different approaches/models applied to time-trial (TT) cycle-ergometry exercise.

Methods

Fifteen male cyclists completed a 7 × 4-min submaximal protocol and a 3-min all-out TT (TTAO). Linear relationships between power output (PO) and submaximal metabolic rate were constructed to estimate TT-specific gross efficiency (GE) and AnWC, using either a measured resting metabolic rate as a Y-intercept (7 + YLIN) or no measured Y-intercept (7-YLIN). In addition, GE of the last submaximal bout (GELAST) was used to estimate AnWC, and critical power (CP) from TTAO (CP3´AO) was used to estimate mechanical work above CP (W’, i.e., “AnWC”).

Results

Average PO during TTAO was 5.43 ± 0.30 and CP was 4.48 ± 0.23 W∙kg−1. The TT-associated GE values were ~ 22.0% for both 7 + YLIN and 7-YLIN and ~ 21.1% for GELAST (both P < 0.001). The AnWC were 269 ± 60, 272 ± 55, 299 ± 61, and 196 ± 52 J∙kg−1 for the 7 + YLIN, 7-YLIN, GELAST, and CP3´AO models, respectively (7 + YLIN and 7-YLIN versus GELAST, both P < 0.001; 7 + YLIN, 7-YLIN, and GELAST versus CP3´AO, all P < 0.01). For the three pair-wise comparisons between 7 + YLIN, 7-YLIN, and GELAST, typical errors in AnWC values ranged from 7 to 11 J∙kg−1, whereas 7 + YLIN, 7-YLIN, and GELAST versus CP3´AO revealed typical errors of 55–59 J∙kg−1.

Conclusion

These findings demonstrate a substantial disagreement in AnWC between CP3´AO and the other models. The 7 + YLIN and 7-YLIN generated 10% lower AnWC values than the GELAST model, whereas 7 + YLIN and 7-YLIN generated similar values of AnWC.

Efficiency of cycling exercise: Quantification, mechanisms, and misunderstandings

The energetics of cycling represents a well-studied area of exercise science, yet there are still many questions that remain. Efficiency, broadly defined as the ratio of energy output to energy input, is one key metric that, despite its importance from both a scientific as well as performance perspective, is commonly misunderstood. There are many factors that may affect cycling efficiency, both intrinsic (e.g., muscle fiber type composition) and extrinsic (e.g., cycling cadence, prior exercise, and training), creating a complex interplay of many components. Due to its relative simplicity, the measurement of oxygen uptake continues to be the most common means of measuring the energy cost of exercise (and thus efficiency); however, it is limited to only a small proportion of the range of outputs humans are capable of, further limiting our understanding of the energetics of high-intensity exercise and any mechanistic bases therein. This review presents evidence that delta efficiency does not represent muscular efficiency and challenges the notion that the slow component of oxygen uptake represents decreasing efficiency. It is noted that gross efficiency increases as intensity of exercise increases in spite of the fact that fast-twitch fibers are recruited to achieve this high power output. Understanding the energetics of high-intensity exercise will require critical evaluation of the available data.

Effect of Computational Method on Accumulated O2 Deficit

The aim of this study was to examine how relationships between exercise intensity and the rate of energy release established in different ways, affect the calculated O2 deficit accumulated during strenuous exercise. Aerobic energy release is readily measured by the O2 uptake, while anaerobic energy release is by definition independent of O2. The latter is not easily measured during strenuous exercise, but it can be estimated using the accumulated O2 deficit principle. We have calculated it using nine different approaches. Thirteen moderately trained persons (three women) volunteered to serve as subjects for cycle ergometry. Their maximal O2 uptake was 2.9 ± 0.6 mmol s−1 (x̄ ± s; 3.9 ± 0.8 LSTPD min−1). Our reference method (M0) is based on measuring the steady state O2 uptake at the end of at least ten bouts of 10 min of exercise at constant intensity, varying between 30 and 40% of that corresponding to the maximal O2 uptake and up to a power &gt;90% of the maximal O2 uptake, which is a rather time-consuming method. The outcomes of eight different simpler approaches have been compared with those of the reference method. The main result is that the accumulated O2 deficit calculated depends a great deal on the relationship used to calculate it. A protocol of stepwise increases in exercise intensity every 4 min appeared to work well. A gross efficiency method showed the poorest performance. Another important result is that at constant power the O2 uptake continued to increase beyond 4 min of exercise at all powers examined, also at powers well-below those corresponding to the lactate threshold. Finally, the O2 uptake during loadless pedaling was considerably higher than resting O2 uptake, and it appeared to follow a cubic function of the pedaling frequency. In conclusion, to obtain reliable values of the anaerobic energy release using the accumulated O2 deficit principle, reliable relationships between exercise intensity and O2 demand must be established.

Physical fitness characteristics and performance in single-handed dinghy and 470 classes sailors

The purpose of this study was to investigate the differences in the physical fitness characteristics of Chinese single-handed dinghy and 470 sailors, predict the single-handed dinghy sailors' physical factors on the performance by equation to guide the training. The sample of this study consisted of one hundred and sixty-seven Chinese sailors who participated in the 2020 China National Sailing Championships, K Independent Samples Test was used to analyze the differences of different classes sailors, and the performance of Laser and Laser Radial sailors were analyzed by step multivariate linear regression. The results showed that the 470 helmsmen are shorter, lighter and have a lower BMI, 470 crew are similar in height to the single-handed dinghy sailors, but lower in weight and BMI. Laser sailors have better strength and flexibility than the ones of male 470. There is no significant difference in the physical fitness characteristics between the Laser Radial sailors and the female 470 crew, they both had better upper and lower body strength than female 470 helmsmen. The regression equation is possible to explain 65.5% of the performance of the sailors in Laser = 90.963-1.33 × sailing experience-0.461 × bench press-0.018 × cycling peak power out; The regression equation is possible to explain 76.7% of the performance of the sailors in Laser Radial = 27.433-0.391 × sailing experience+0.351 × vertical jump-0.329 × pull-up-0.027 × cycling peak power out. Performance in laser and Laser Radial sailors will be determined by the technique and tactics (sailing experience) as well as physical fitness.

Anaerobic Capacity in Running: The Effect of Computational Method

Introduction

To date, no study has compared anaerobic capacity (AnC) estimates computed with the maximal accumulated oxygen deficit (MAOD) method and the gross energy cost (GEC) method applied to treadmill running exercise.

Purpose

Four different models for estimating anaerobic energy supply during treadmill running exercise were compared.

Methods

Fifteen endurance-trained recreational athletes performed, after a 10-min warm-up, five 4-min stages at ∼55-80% of peak oxygen uptake, and a 4-min time trial (TT). Two linear speed-metabolic rate (MR) regression models were used to estimate the instantaneous required MR during the TT (MR _{TT_req} ), either including (5+Y _LIN ) or excluding (5-Y _LIN ) a measured Y-intercept. Also, the average GEC (GEC _AVG ) based on all five submaximal stages, or the GEC based on the last submaximal stage (GEC _LAST ), were used as models to estimate the instantaneous MR _{TT_req} . The AnC was computed as the difference between the MR _{TT_req} and the aerobic MR integrated over time.

Results

The GEC remained constant at ∼4.39 ± 0.29 J⋅kg^-1⋅m^-1 across the five submaximal stages and the TT was performed at a speed of 4.7 ± 0.4 m⋅s^-1. Compared with the 5-Y _LIN , GEC _AVG , and GEC _LAST models, the 5+Y _LIN model generated a MR _{TT_req} that was ∼3.9% lower, with corresponding anaerobic capacities from the four models of 0.72 ± 0.20, 0.74 ± 0.16, 0.74 ± 0.15, and 0.54 ± 0.14 kJ⋅kg^-1, respectively (F _1.07,42 = 13.9, P = 0.002). The GEC values associated with the TT were 4.22 ± 0.27 and 4.37 ± 0.30 J⋅kg^-1⋅m^-1 for 5+Y _LIN and 5-Y _LIN , respectively (calculated from the regression equation), and 4.39 ± 0.28 and 4.38 ± 0.27 J⋅kg^-1⋅m^-1 for GEC _AVG and GEC _LAST , respectively (F _1.08,42 = 14.6, P < 0.001). The absolute typical errors in AnC ranged between 0.03 and 0.16 kJ⋅kg^-1 for the six pair-wise comparisons and the overall standard error of measurement (SEM) was 0.16 kJ⋅kg^-1.

Conclusion

These findings demonstrate a generally high disagreement in estimated anaerobic capacities between models and show that the inclusion of a measured Y-intercept in the linear regression (i.e., 5+Y _LIN ) is likely to underestimate the MR _{TT_req} and the GEC associated with the TT, and hence the AnC during maximal 4-min treadmill running.

The Dynamics of the Anaerobic Energy Contribution During a Simulated Mass-Start Competition While Roller-Ski Skating on a Treadmill

The purposes of this study were: 1) to investigate the anaerobic energy contribution during a simulated cross-country (XC) skiing mass-start competition while roller-ski skating on a treadmill; 2) to investigate the relationship between the recovery of the anaerobic energy reserves and performance; and 3) to compare the gross efficiency (GE) method and maximal accumulated oxygen deficit (MAOD) to determine the anaerobic contribution. Twelve male XC skiers performed two testing days while roller skiing on a treadmill. To collect submaximal data necessary for the GE and MAOD method, participants performed a resting metabolism measurement, followed by low-intensity warm up, 12 submaximal 4-min bouts, performed using three different skating sub-techniques (G2 on a 12% incline, G3 on 5% and G4 on 2%) on three submaximal intensities on day 1. On day 2, participants performed a 21-min simulated mass-start competition on varying terrain to determine the anaerobic energy contribution. The speed was fixed, but when participants were unable to keep up, a 30-s rest bout was included. Performance was established by the time to exhaustion (TTE) during a sprint at the end of the 21-min protocol. Skiers were ranked based on the number of rest bouts needed to finish the protocol and TTE. The highest GE of day 1 for each of the different inclines/sub-techniques was used to calculate the aerobic and anaerobic contribution during the simulated mass start using the GE method and two different MAOD approaches. About 85–90% of the required energy during the simulated mass-start competition (excluding downhill segments) came from the aerobic energy system and ~10–15% from the anaerobic energy systems. Moderate to large Spearman correlation coefficients were found between recovery of anaerobic energy reserves and performance rank (r_s = 0.58–0.71, p < 0.025). No significant difference in anaerobic work was found between methods/approaches (F_(1.2,8.5) = 3.2, p = 0.10), while clear individual differences existed. In conclusion, about 10–15% of the required energy during the periods of active propulsion of a 21-min simulated mass-start competition came from the anaerobic energy systems. Due to the intermittent nature of XC skiing, the recovery of anaerobic energy reserves seems highly important for performance. To assess the anaerobic contribution methods should not be used interchangeably.

The Aerobic and Anaerobic Contribution During Repeated 30-s Sprints in Elite Cyclists

Although the ability to sprint repeatedly is crucial in road cycling races, the changes in aerobic and anaerobic power when sprinting during prolonged cycling has not been investigated in competitive elite cyclists. Here, we used the gross efficiency (GE)-method to investigate: (1) the absolute and relative aerobic and anaerobic contributions during 3 × 30-s sprints included each hour during a 3-h low-intensity training (LIT)-session by 12 cyclists, and (2) how the energetic contribution during 4 × 30-s sprints is affected by a 14-d high-volume training camp with (SPR, n = 9) or without (CON, n = 9) inclusion of sprints in LIT-sessions. The aerobic power was calculated based on GE determined before, after sprints, or the average of the two, while the anaerobic power was calculated by subtracting the aerobic power from the total power output. When repeating 30-s sprints, the mean power output decreased with each sprint (p < 0.001, ES:0.6-1.1), with the majority being attributed to a decrease in mean anaerobic power (first vs. second sprint: -36 ± 15 W, p < 0.001, ES:0.7, first vs. third sprint: -58 ± 16 W, p < 0.001, ES:1.0). Aerobic power only decreased during the third sprint (first vs. third sprint: -17 ± 5 W, p < 0.001, ES:0.7, second vs. third sprint: 16 ± 5 W, p < 0.001, ES:0.8). Mean power output was largely maintained between sets (first set: 786 ± 30 W vs. second set: 783 ± 30 W, p = 0.917, ES:0.1, vs. third set: 771 ± 30 W, p = 0.070, ES:0.3). After a 14-d high-volume training camp, mean power output during the 4 × 30-s sprints increased on average 25 ± 14 W in SPR (p < 0.001, ES:0.2), which was 29 ± 20 W more than CON (p = 0.008, ES: 0.3). In SPR, mean anaerobic power and mean aerobic power increased by 15 ± 13 W (p = 0.026, ES:0.2) and by 9 ± 6 W (p = 0.004, ES:0.2), respectively, while both were unaltered in CON. In conclusion, moderate decreases in power within sets of repeated 30-s sprints are primarily due to a decrease in anaerobic power and to a lesser extent in aerobic power. However, the repeated sprint-ability (multiple sets) and corresponding energetic contribution are maintained during prolonged cycling in elite cyclists. Including a small number of sprints in LIT-sessions during a 14-d training camp improves sprint-ability mainly through improved anaerobic power.

The Metabolic Relevance of Type of Locomotion in Anaerobic Testing: Bosco Continuous Jumping Test Versus Wingate Anaerobic Test of the Same Duration

PURPOSE

To evaluate the metabolic relevance of type of locomotion in anaerobic testing by analyzing and comparing the metabolic profile of the Bosco Continuous Jumping Test (CJ30) with the corresponding profile of the Wingate Anaerobic Test (WAnT).

METHODS

A total of 11 well-trained, male team-sport athletes (age = 23.7 [2.2] y, height = 184.1 [2.8] cm, weight = 82.4 [6.4] kg) completed a CJ30 and WAnT each. During the WAnT, power data and revolutions per minute were recorded, and during the CJ30, jump height and jumping frequency were recorded. In addition, oxygen uptake and blood lactate concentration were assessed, and metabolic profiles were determined via the PCr-LA-O2 method.

RESULTS

In the CJ30, metabolic energy was lower (109.3 [18.0] vs 143.0 [13.1] kJ, P < .001, d = -2.302), while peak power (24.8 [4.4] vs 11.8 [0.5] W·kg-1, P < .001, d = 3.59) and mean power (20.8 [3.6] vs 9.1 [0.5] W·kg-1, P < .001, d = 4.14) were higher than in the WAnT. The metabolic profiles of the CJ30 (aerobic energy = 20.00% [4.7%], anaerobic alactic energy [WPCr] = 45.6% [4.5%], anaerobic lactic energy = 34.4% [5.2%]) and the WAnT (aerobic energy = 16.0% [3.0%], anaerobic alactic WPCr = 34.5% [5.0%], anaerobic lactic energy = 49.5% [3.3%]) are highly anaerobic. Absolute energy contribution for the CJ30 and WAnT was equal in WPCr (49.9 [11.1] vs 50.2 [11.2] kJ), but anaerobic lactic energy (37.7 [7.7] vs 69.9 [5.3] kJ) and aerobic energy (20.6 [5.7] vs 23.0 [4.0] kJ) were higher in the WAnT. Mechanical efficiency was substantially higher in the CJ30 (37.9% [4.5%] vs 15.6% [1.0%], P < .001, d = 6.86), while the fatigue index was lower (18.5% [3.8%] vs 23.2% [3.1%], P < .001, d = -1.38) than in the WAnT.

CONCLUSIONS

Although the anaerobic share in both tests is similar and predominant, the CJ30 primarily taxes the WPCr system, while the WAnT more strongly relies on the glycolytic pathway. Thus, the 2 tests should not be used interchangeably, and the type of locomotion seems crucial when choosing an anaerobic test for a specific sport.

The Inclusion of Sprints in Low-Intensity Sessions During the Transition Period of Elite Cyclists Improves Endurance Performance 6 Weeks Into the Subsequent Preparatory Period

PURPOSE

To investigate the effects of including repeated sprints in a weekly low-intensity (LIT) session during a 3-week transition period on cycling performance 6 weeks into the subsequent preparatory period (PREP) in elite cyclists.

METHODS

Eleven elite male cyclists (age = 22.0 [3.8] y, body mass = 73.0 [5.8] kg, height = 186 [7] cm, maximal oxygen uptake [VO2max] = 5469 [384] mL·min-1) reduced their training load by 64% and performed only LIT sessions (CON, n = 6) or included 3 sets of 3 × 30-second maximal sprints in a weekly LIT session (SPR, n = 5) during a 3-week transition period. There was no difference in the reduction in training load during the transition period between groups. Physiological and performance measures were compared between the end of the competitive period and 6 weeks into the PREP.

RESULTS

SPR demonstrated a 7.3% (7.2%) improvement in mean power output during a 20-minute all-out test at PREP, which was greater than CON (-1.3% [4.6%]) (P = .048). SPR had a corresponding 7.0% (3.6%) improvement in average VO2 during the 20-minute all-out test, which was larger than the 0.7% (6.0%) change in CON (P = .042). No change in VO2max, gross efficiency, or power output at blood lactate concentration of 4 mmol·L-1 from competitive period to PREP occurred in either group.

CONCLUSION

Including sprints in a weekly LIT session during the transition period of elite cyclists provided a performance advantage 6 weeks into the subsequent PREP, which coincided with a higher performance VO2.

Superior Physiological Adaptations After a Microcycle of Short Intervals Versus Long Intervals in Cyclists

PURPOSE

To compare the effects of a 1-week high-intensity aerobic-training shock microcycle composed of either 5 short-interval sessions (SI; n = 9, 5 series with 12 × 30-s work intervals interspersed with 15-s recovery and 3-min recovery between series) or 5 long-interval sessions (LI; n = 8, 6 series of 5-min work intervals with 2.5-min recovery between series) on indicators of endurance performance in well-trained cyclists.

METHODS

Before and following 6 days with standardized training loads after the 1-week high-intensity aerobic-training shock microcycle, both groups were tested in physiological determinants of endurance performance.

RESULTS

From pretraining to posttraining, SI achieved a larger improvement than LI in maximal oxygen uptake (5.7%; 95% confidence interval, 1.3-10.3; P = .015) and power output at a blood lactate concentration of 4 mmol·L-1 (3.8%; 95% confidence interval, 0.2-7.4; P = .038). There were no group differences in changes of fractional use of maximal oxygen uptake at a workload corresponding to a blood lactate concentration of 4 mmol·L-1, gross efficiency, or the 1-minute peak power output from the maximal-oxygen-uptake test.

CONCLUSION

The SI protocol may induce superior changes in indicators of endurance performance compared with the LI protocol, indicating that SI can be a good strategy during a 1-week high-intensity aerobic-training shock microcycle in well-trained cyclists.

Oxygen Demand, Uptake, and Deficits in Elite Cross-Country Skiers during a 15-km Race

PURPOSE

This study aimed to quantify the repeated oxygen deficits attained during intermittent endurance exercise by measuring oxygen consumption (V˙O2) and oxygen demand (V˙O2) throughout a simulated roller ski race.

METHODS

Eight male elite cross-country skiers (V˙O2peak, 77.4 ± 4.4 mL·kg⋅min) raced a 13.5-km roller ski time trial on a World Cup course. On two additional days, athletes completed (i) six submaximal loads (~5 min) and ~4-min maximal trial to establish athlete-specific estimates of skiing economy, V˙O2peak, and maximal ΣO2 (MAOD); and (ii) a simulation of the time trial on a roller skiing treadmill. During the simulation, external work rate (Pprop) and skiing speed (v) were adjusted to match the Pprop and v measured during the time trial, and pulmonary V˙O2 was measured breath by breath. V˙O2 and ΣO2 were calculated using an athlete-specific model for skiing economy throughout the treadmill simulation.

RESULTS

During the treadmill simulation, V˙O2 was on average 0.77 V˙O2peak, and active V˙O2 (i.e., excluding the time in simulated downhill) was on average 1.01 V˙O2peak. The athletes repeatedly attained substantial oxygen deficits in individual uphill sections of the treadmill simulation, but the deficits were typically small compared with their MAOD (average 14%, range ~0%-50%). However, the ΣO2 summed over all periods of active propulsion was on average 3.8 MAOD.

CONCLUSION

Athletes repeatedly attain substantial oxygen deficits in the uphill segments of a distance cross-country ski race. Furthermore, the total accumulated oxygen deficit of all these segments is several times higher than the athletes' MAOD. This suggests that the rapid recovery of the energy stores represented by the oxygen deficit is necessary during downhill sections, and that this might be an important determinant of distance skiing performance.

Effects of Eight Interval Training Sessions in Hypoxia on Anaerobic, Aerobic, and High Intensity Work Capacity in Endurance Cyclists

Aim: This study aimed to determine if eight sessions of supramaximal but steady-state, set duration interval training in hypoxia enhanced measured anaerobic capacity and work performed during high intensity exercise. High Alt Med Biol. 21:370-377, 2020. Materials and Methods: Eighteen cyclists (V̇O_2peak: 57 ± 7 ml·kg^-1·min^-1) were pair-matched for anaerobic capacity determined by maximal accumulated oxygen deficit (MAOD) and allocated to a 4-week interval training in hypoxia (IHT; FiO₂ = 14.7% ± 0.5%, n = 9) or interval training in normoxia (NORM; FiO₂ = 20.6% ± 0.3%, n = 9). Cyclists completed twice weekly interval training (8 × 1 minutes: ∼120% V̇O_2peak, 5 minutes recovery: ∼50% V̇O_2peak) in addition to their habitual training. Before and after the intervention, a constant work rate supramaximal time to fatigue and a graded exercise test were used to determine changes in anaerobic capacity/supramaximal work performed and aerobic capacity/peak aerobic power output, respectively. Results: No interaction or main effects were observed. Using indirect calorimetry, anaerobic capacity was not significantly different in either group pre- to postintervention using MAOD (IHT: 4% ± 15%; NORM: -5% ± 12%) or gross efficiency methods (IHT: 7% ± 14%; NORM: -2% ± 9%), and VO_2peak was unchanged (IHT: 1% ± 6%; NORM: 1% ± 4%). However, within-group analysis shows that supramaximal work performed improved with IHT (14% ± 13%; p = 0.02; d = 0.42) but not NORM (1% ± 22%), and peak aerobic power output increased with IHT (5% ± 7%; p = 0.04; d = 0.32) but not NORM (2% ± 4%). Conclusion: Steady-state, set duration supramaximal interval training in hypoxia appears to provide a small beneficial effect on work capacity during supramaximal and high intensity exercise.

The Effect of 30-Second Sprints During Prolonged Exercise on Gross Efficiency, Electromyography, and Pedaling Technique in Elite Cyclists

BACKGROUND

Cycling competitions are often of long duration and include repeated high-intensity efforts.

PURPOSE

To investigate the effect of repeated maximal sprints during 4 hours of low-intensity cycling on gross efficiency (GE), electromyography patterns, and pedaling technique compared with work-matched low-intensity cycling in elite cyclists.

METHODS

Twelve elite, male cyclists performed 4 hours of cycling at 50% of maximal oxygen uptake either with 3 sets of 3 × 30-second maximal sprints (E&S) during the first 3 hours or a work-matched cycling without sprints (E) in a randomized order. Oxygen uptake, electromyography, and pedaling technique were recorded throughout the exercises.

RESULTS

GE was reduced from start to the end of exercise in both conditions (E&S: 19.0 [0.2] vs 18.1 [0.2], E: 19.1% [0.2%] vs 18.1% [0.2%], both P = .001), with no difference in change between conditions (condition × time interaction, P = .8). Integrated electromyography increased from start to end of exercise in m. vastus lateralis and m. vastus medialis (m. vastus medialis: 9.9 [2.4], m. vastus lateralis: 8.5 [4.0] mV, main effect of time: P < .001 and P = .03, respectively) and E&S increased less than E in m. vastus medialis (mean difference -3.3 [1.5] mV, main effect of condition: P = .03, interaction, P = .06). The mechanical effectiveness only decreased in E&S (E&S: -2.2 [0.7], effect size = 0.24 vs E: -1.3 [0.8] percentage points: P = .04 and P = .8, respectively). The mean power output during each set of 3 × 30-second sprints in E&S did not differ (P = .6).

CONCLUSIONS

GE decreases as a function of time during 4 hours of low-intensity cycling. However, the inclusion of maximal repeated sprinting does not affect the GE changes, and the ability to sprint is maintained throughout the entire session.

Decrescent intensity training concurrently improves maximal anaerobic power, maximal accumulated oxygen deficit, and maximal oxygen uptake

This study aimed to investigate the effects of a gradually decreasing intensity training from that corresponding to maximal anaerobic power (MAnP) to that of near maximal oxygen uptake ([Formula: see text]) (decrescent intensity training) on MAnP, maximal accumulated oxygen deficit (MAOD), and [Formula: see text] in untrained young men. Seventeen untrained young men were randomly divided into either a training (TR; n = 9) group or a control (CON; n = 8) group. The TR group performed the decrescent intensity training, whereas the CON group did not perform any exercises. The mean training time per session throughout the training period was 275 ± 135 s. There was a Group × Time interaction for both absolute and relative (p < 0.01) values of [Formula: see text], MAOD, and MAnP. The TR group had significantly increased values for all variables after the 8-week training program, and the relative values of all variables were significantly higher in the TR group than in the CON group. Muscle thicknesses in the anterior and posterior aspects of the thigh and maximal isokinetic knee extension and flexion strengths improved only in the TR group (p < 0.05). A single-exercise training with gradually decreasing intensity from that corresponding to the MAnP to that of approximately 100% [Formula: see text] improves MAnP, MAOD, and [Formula: see text] concurrently, despite the short training time per session.

Prediction of the Wingate anaerobic mechanical power outputs from a maximal incremental cardiopulmonary exercise stress test using machine-learning approach

The Wingate Anaerobic Test (WAnT) is a short-term maximal intensity cycle ergometer test, which provides anaerobic mechanical power output variables. Despite the physiological significance of the variables extracted from the WAnT, the test is very intense, and generally applies for athletes. Our goal, in this paper, was to develop a new approach to predict the anaerobic mechanical power outputs using maximal incremental cardiopulmonary exercise stress test (CPET). We hypothesized that maximal incremental exercise stress test hold hidden information about the anaerobic components, which can be directly translated into mechanical power outputs. We therefore designed a computational model that included aerobic variables (features), and used a new computational \ predictive algorithm, which enabled the prediction of the anaerobic mechanical power outputs. We analyzed the chosen predicted features using clustering on a network. For peak power (PP) and mean power (MP) outputs, the equations included six features and four features, respectively. The combination of these features produced a prediction model of r = 0.94 and r = 0.9, respectively, on the validation set between the real and predicted PP/MP values (P< 0.001). The newly predictive model allows the accurate prediction of the anaerobic mechanical power outputs at high accuracy. The assessment of additional tests is desired for the development of a robust application for athletes, older individuals, and/or non-healthy populations.

A Comparison between Different Methods of Estimating Anaerobic Energy Production

Purpose: The present study aimed to compare four methods of estimating anaerobic energy production during supramaximal exercise.

Methods: Twenty-one junior cross-country skiers competing at a national and/or international level were tested on a treadmill during uphill (7°) diagonal-stride (DS) roller-skiing. After a 4-minute warm-up, a 4 × 4-min continuous submaximal protocol was performed followed by a 600-m time trial (TT). For the maximal accumulated O₂ deficit (MAOD) method the V.O₂-speed regression relationship was used to estimate the V.O₂ demand during the TT, either including (4+Y, method 1) or excluding (4-Y, method 2) a fixed Y-intercept for baseline V.O₂. The gross efficiency (GE) method (method 3) involved calculating metabolic rate during the TT by dividing power output by submaximal GE, which was then converted to a V.O₂ demand. An alternative method based on submaximal energy cost (EC, method 4) was also used to estimate V.O₂ demand during the TT.

Results: The GE/EC remained constant across the submaximal stages and the supramaximal TT was performed in 185 ± 24 s. The GE and EC methods produced identical V.O₂ demands and O₂ deficits. The V.O₂ demand was ~3% lower for the 4+Y method compared with the 4-Y and GE/EC methods, with corresponding O₂ deficits of 56 ± 10, 62 ± 10, and 63 ± 10 mL·kg⁻¹, respectively (P < 0.05 for 4+Y vs. 4-Y and GE/EC). The mean differences between the estimated O₂ deficits were −6 ± 5 mL·kg⁻¹ (4+Y vs. 4-Y, P < 0.05), −7 ± 1 mL·kg⁻¹ (4+Y vs. GE/EC, P < 0.05) and −1 ± 5 mL·kg⁻¹ (4-Y vs. GE/EC), with respective typical errors of 5.3, 1.9, and 6.0%. The mean difference between the O₂ deficit estimated with GE/EC based on the average of four submaximal stages compared with the last stage was 1 ± 2 mL·kg⁻¹, with a typical error of 3.2%.

Conclusions: These findings demonstrate a disagreement in the O₂ deficits estimated using current methods. In addition, the findings suggest that a valid estimate of the O₂ deficit may be possible using data from only one submaximal stage in combination with the GE/EC method.

Effect of caffeine ingestion on anaerobic capacity quantified by different methods

We investigated whether caffeine ingestion before submaximal exercise bouts would affect supramaximal oxygen demand and maximal accumulated oxygen deficit (MAOD), and if caffeine-induced improvement on the anaerobic capacity (AC) could be detected by different methods. Nine men took part in several submaximal and supramaximal exercise bouts one hour after ingesting caffeine (5 mg·kg-1) or placebo. The AC was estimated by MAOD, alternative MAOD, critical power, and gross efficiency methods. Caffeine had no effect on exercise endurance during the supramaximal bout (caffeine: 131.3 ± 21.9 and placebo: 130.8 ± 20.8 s, P = 0.80). Caffeine ingestion before submaximal trials did not affect supramaximal oxygen demand and MAOD compared to placebo (7.88 ± 1.56 L and 65.80 ± 16.06 kJ vs. 7.89 ± 1.30 L and 62.85 ± 13.67 kJ, P = 0.99). Additionally, MAOD was similar between caffeine and placebo when supramaximal oxygen demand was estimated without caffeine effects during submaximal bouts (67.02 ± 16.36 and 62.85 ± 13.67 kJ, P = 0.41) or when estimated by alternative MAOD (56.61 ± 8.49 and 56.87 ± 9.76 kJ, P = 0.91). The AC estimated by gross efficiency was also similar between caffeine and placebo (21.80 ± 3.09 and 20.94 ± 2.67 kJ, P = 0.15), but was lower in caffeine when estimated by critical power method (16.2 ± 2.6 vs. 19.3 ± 3.5 kJ, P = 0.03). In conclusion, caffeine ingestion before submaximal bouts did not affect supramaximal oxygen demand and consequently MAOD. Otherwise, caffeine seems to have no clear positive effect on AC.

A comparison of methods to estimate anaerobic capacity: Accumulated oxygen deficit and W' during constant and all-out work-rate profiles

This study investigated (i) whether the accumulated oxygen deficit (AOD) and curvature constant of the power-duration relationship (W') are different during constant work-rate to exhaustion (CWR) and 3-min all-out (3MT) tests and (ii) the relationship between AOD and W' during CWR and 3MT. Twenty-one male cyclists (age: 40 ± 6 years; maximal oxygen uptake [V̇O_2max]: 58 ± 7 ml · kg^-1 · min^-1) completed preliminary tests to determine the V̇O₂-power output relationship and V̇O_2max. Subsequently, AOD and W' were determined as the difference between oxygen demand and oxygen uptake and work completed above critical power, respectively, in CWR and 3MT. There were no differences between tests for duration, work, or average power output (P ≥ 0.05). AOD was greater in the CWR test (4.18 ± 0.95 vs. 3.68 ± 0.98 L; P = 0.004), whereas W' was greater in 3MT (9.55 ± 4.00 vs. 11.37 ± 3.84 kJ; P = 0.010). AOD and W' were significantly correlated in both CWR (P < 0.001, r = 0.654) and 3MT (P < 0.001, r = 0.654). In conclusion, despite positive correlations between AOD and W' in CWR and 3MT, between-test differences in the magnitude of AOD and W', suggest that both measures have different underpinning mechanisms.

Evaluation of energy expenditure in forward and backward movements performed by soccer referees

The aim of this study was to measure the energy expenditure for locomotor activities usually performed by soccer referees during a match (walking, jogging, and running) under laboratory conditions, and to compare forward with backward movements. The sample was composed by 10 male soccer referees, age 29±7.8 years, body mass 77.5±6.2 kg, stature 1.78±0.07 m and professional experience of 7.33±4.92 years. Referees were evaluated on two separate occasions. On the first day, maximal oxygen uptake (VO2max) was determined by a maximal treadmill test, and on the second day, the oxygen consumption was determined in different speeds of forward and backward movements. The mean VO2max was 41.20±3.60 mL·kg-1·min-1 and the mean heart rate achieved in the last stage of the test was 190.5±7.9 bpm. When results of forward and backward movements were compared at 1.62 m/s (walking speed), we found significant differences in VO2, in metabolic equivalents, and in kcal. However, the same parameters in forward and backward movements at jogging velocities (2.46 m/s) were not significantly different, showing that these motor activities have similar intensity. Backward movements at velocities equivalent to walking and jogging are moderate-intensity activities, with energy expenditure less than 9 kcal. Energy expenditure was overestimated by at least 35% when calculated by mathematical equations. In summary, we observed that backward movements are not high-intensity activities as has been commonly reported, and when calculated using equations available in the literature, energy expenditure was overestimated compared to the values obtained by indirect calorimetry.

Sodium bicarbonate supplementation improved MAOD but is not correlated with 200- and 400-m running performances: a double-blind, crossover, and placebo-controlled study

The aim of the study was to investigate the effects of acute supplementation of sodium bicarbonate (NaHCO3) on maximal accumulated oxygen deficit (MAOD) determined by a single supramaximal effort (MAODALT) in running and the correlation with 200- and 400-m running performances. Fifteen healthy men (age, 23 ± 4 years; maximal oxygen uptake, 50.6 ± 6.1 mL·kg−1·min−1) underwent a maximal incremental exercise test and 2 supramaximal efforts at 110% of the intensity associated with maximal oxygen uptake, which was carried out after ingesting either 0.3 g·kg−1 body weight NaHCO3 or a placebo (dextrose) and completing 200- and 400-m performance tests. The study design was double-blind, crossover, and placebo-controlled. Significant differences were found between the NaHCO3 and placebo conditions for MAODALT (p = 0.01) and the qualitative inference for substantial changes showed a very likely positive effect (98%). The lactic anaerobic contribution in the NaHCO3 ingestion condition was significantly higher (p < 0.01) and showed a very likely positive effect (99% chance), similar to that verified for peak blood lactate concentration (p < 0.01). No difference was found for time until exhaustion (p = 0.19) or alactic anaerobic contribution (p = 0.81). No significant correlations were observed between MAODALT and 200- and 400-m running performance tests. Therefore, we can conclude that both MAODALT and the anaerobic lactic metabolism are modified after acute NaHCO3 ingestion, but it is not correlated with running performance.

Effect of work and recovery durations on W' reconstitution during intermittent exercise

PURPOSE

We recently presented an integrating model of the curvature constant of the hyperbolic power-time relationship (W') that permits the calculation of the W' balance (W'BAL) remaining at any time during intermittent exercise. Although a relationship between recovery power and the rate of W' recovery was demonstrated, the effect of the length of work or recovery intervals remains unclear.

METHODS

After determining VO2max, critical power, and W', 11 subjects completed six separate exercise tests on a cycle ergometer on different days, and in random order. Tests consisted of a period of intermittent severe-intensity exercise until the subject depleted approximately 50% of their predicted W'BAL, followed by a constant work rate (CWR) exercise bout until exhaustion. Work rates were kept constant between trials; however, either work or recovery durations during intermittent exercise were varied. The actual W' measured during the CWR (W'ACT) was compared with the amount of W' predicted to be available by the W'BAL model.

RESULTS

Although some differences between W'BAL and W'ACT were noted, these amounted to only -1.6 ± 1.1 kJ when averaged across all conditions. The W'ACT was linearly correlated with the difference between VO2 at the start of CWR and VO2max (r = 0.79, P < 0.01).

CONCLUSIONS

The W'BAL model provided a generally robust prediction of CWR W'. There may exist a physiological optimum formulation of work and recovery intervals such that baseline VO2 can be minimized, leading to an enhancement of subsequent exercise tolerance. These results may have important implications for athletic training and racing.

Intramuscular determinants of the ability to recover work capacity above critical power

PURPOSE

The primary purpose of this investigation was to compare the recovery of the W' to the recovery of intramuscular substrates and metabolites using (31)P- and (1)H-magnetic resonance spectroscopy.

METHODS

Ten healthy recreationally trained subjects were tested to determine critical power (CP) and W' for single-leg-extensor exercise. They subsequently exercised in the bore of a 1.5-T MRI scanner at a supra-CP work rate. Following exhaustion, the subjects rested in place for 1, 2, 5 or 7 min, and then repeated the effort. The temporal course of W' recovery was estimated, which was then compared to the recovery of creatine phosphate [PCr], pH, carnosine content, and to the output of a novel derivation of the W' BAL model.

RESULTS

W' recovery closely correlated with the predictions of the novel model (r = 0.97, p = 0.03). [PCr] recovered faster [Formula: see text] than W' [Formula: see text] The W' available for the second exercise bout was directly correlated with the difference between [PCr] at the beginning of the work bout and [PCr] at exhaustion (r = 0.99, p = 0.005). Nonlinear regression revealed an inverse curvilinear relationship between carnosine concentration and the W' t 1/2 (r (2) = 0.55).

CONCLUSION

The kinetics of W' recovery in single-leg-extensor exercise is comparable to that observed in whole-body exercise, suggesting a conserved mechanism. The extent to which the recovery of the W' can be directly attributed to the recovery of [PCr] is unclear. The relationship of the W' to muscle carnosine content suggests novel future avenues of investigation.

Anaerobic work calculated in cycling time trials of different length

Previous research showed that gross efficiency (GE) declines during exercise and therefore influences the expenditure of anaerobic and aerobic resources.

PURPOSE

To calculate the anaerobic work produced during cycling time trials of different length, with and without a GE correction.

METHODS

Anaerobic work was calculated in 18 trained competitive cyclists during 4 time trials (500, 1000, 2000, and 4000-m). Two additional time trials (1000 and 4000 m) that were stopped at 50% of the corresponding "full" time trial were performed to study the rate of the decline in GE.

RESULTS

Correcting for a declining GE during time-trial exercise resulted in a significant (P<.001) increase in anaerobically attributable work of 30%, with a 95% confidence interval of [25%, 36%]. A significant interaction effect between calculation method (constant GE, declining GE) and distance (500, 1000, 2000, 4000 m) was found (P<.001). Further analysis revealed that the constant-GE calculation method was different from the declining method for all distances and that anaerobic work calculated assuming a constant GE did not result in equal values for anaerobic work calculated over different time-trial distances (P<.001). However, correcting for a declining GE resulted in a constant value for anaerobically attributable work (P=.18).

CONCLUSIONS

Anaerobic work calculated during short time trials (<4000 m) with a correction for a declining GE is increased by 30% [25%, 36%] and may represent anaerobic energy contributions during high-intensity exercise better than calculating anaerobic work assuming a constant GE.

Validation of a novel intermittent w' model for cycling using field data

Recently, an adaptation to the critical-power (CP) model was published, which permits the calculation of the balance of the work capacity available above the CP remaining (W'bal) at any time during intermittent exercise. As the model is now in use in both amateur and elite sport, the purpose of this investigation was to assess the validity of the W'bal model in the field. Data were collected from the bicycle power meters of 8 trained triathletes. W'bal was calculated and compared between files where subjects reported becoming prematurely exhausted during training or competition and files where the athletes successfully completed a difficult assigned task or race without becoming exhausted. Calculated W'bal was significantly different between the 2 conditions (P < .0001). The mean W'bal at exhaustion was 0.5 ± 1.3 kJ (95% CI = 0-0.9 kJ), whereas the minimum W'bal in the nonexhausted condition was 3.6 ± 2.0 kJ (95% CI = 2.1-4.0 kJ). Receiver-operator-characteristic (ROC) curve analysis indicated that the W'bal model is useful for identifying the point at which athletes are in danger of becoming exhausted (area under the ROC curve = .914, SE .05, 95% CI .82-1.0, P < .0001). The W'bal model may therefore represent a useful new development in assessing athlete fatigue state during training and racing.