Tests of cycling performance

Ischemic preconditioning enhances critical power during a 3 minute all-out cycling test

This study tested the hypothesis that ischemic preconditioning (IPC) would increase critical power (CP) during a 3 minute all-out cycling test. Twelve males completed two 3 minute all-out cycling tests, in a crossover design, separated by 7 days. These tests were preceded by IPC (4 x 5 minute intervals at 220 mmHg bilateral leg occlusion) or SHAM treatment (4 x 5 minute intervals at 20 mmHg bilateral leg occlusion). CP was calculated as the mean power output during the final 30 s of the 3 minute test with W' taken as the total work done above CP. Muscle oxygenation was measured throughout the exercise period. There was a 15.3 ± 0.3% decrease in muscle oxygenation (TSI; [Tissue saturation index]) during the IPC stimulus, relative to SHAM. CP was significantly increased (241 ± 65 W vs. 234 ± 67 W), whereas W' (18.4 ± 3.8 vs 17.9 ± 3.7 kJ) and total work done (TWD) were not different (61.1 ± 12.7 vs 60.8 ± 12.7 kJ), between the IPC and SHAM trials. IPC enhanced CP during a 3 minute all-out cycling test without impacting W' or TWD. The improved CP after IPC might contribute towards the effect of IPC on endurance performance.

Individual Patterns in Blood-Borne Indicators of Fatigue-Trait or Chance

Julian, R, Meyer, T, Fullagar, HHK, Skorski, S, Pfeiffer, M, Kellmann, M, Ferrauti, A, and Hecksteden, A. Individual patterns in blood-borne indicators of fatigue-trait or chance. J Strength Cond Res 31(3): 608-619, 2017-Blood-borne markers of fatigue such as creatine kinase (CK) and urea (U) are widely used to fine-tune training recommendations. However, predictive accuracy is low. A possible explanation for this dissatisfactory characteristic is the propensity of athletes to react to different patterns of fatigue indicators (e.g., predominantly muscular [CK] or metabolic [U]). The aim of the present trial was to explore this hypothesis by using repetitive fatigue-recovery cycles. A total of 22 elite junior swimmers and triathletes (18 ± 3 years) were monitored for 9 weeks throughout 2 training phases (low-intensity, high-volume [LIHV] and high-intensity, low-volume [HILV] phases). Blood samples were collected each Monday (recovered) and Friday (fatigued) morning. From measured values of CK, U, free-testosterone (FT), and cortisol (C) as determined in the rested and fatigued state, respectively, Monday-Friday differences (Δ) were calculated and classified by magnitude before calculation of ratios (ΔCK/ΔU and ΔFT/ΔC). Coefficient of variation (CV) was calculated as group-based estimates of reproducibility. Linear mixed modeling was used to differentiate inter- and intraindividual variability. Consistency of patterns was analyzed by comparing with threshold values (<0.9 or >1.1 for all weeks). Reproducibility was very low for fatigue-induced changes (CV ≥ 100%) with interindividual variation accounting for 45-60% of overall variability. Case-wise analysis indicated consistent ΔCK/ΔU patterns for 7 individuals in LIHV and 7 in HILV; 5 responded consistently throughout. For ΔFT/ΔC the number of consistent patterns was 2 in LIHV and 3 in HILV. These findings highlight the potential value of an individualized and multivariate approach in the assessment of fatigue.

Prediction of Critical Power and W' in Hypoxia: Application to Work-Balance Modelling

Purpose: Develop a prediction equation for critical power (CP) and work above CP (W′) in hypoxia for use in the work-balance (WBAL′) model.

Methods: Nine trained male cyclists completed cycling time trials (TT; 12, 7, and 3 min) to determine CP and W′ at five altitudes (250, 1,250, 2,250, 3,250, and 4,250 m). Least squares regression was used to predict CP and W′ at altitude. A high-intensity intermittent test (HIIT) was performed at 250 and 2,250 m. Actual and predicted CP and W′ were used to compute W′ during HIIT using differential (WBALdiff′) and integral (WBALint′) forms of the WBAL′ model.

Results: CP decreased at altitude (P < 0.001) as described by 3rd order polynomial function (R² = 0.99). W′ decreased at 4,250 m only (P < 0.001). A double-linear function characterized the effect of altitude on W′ (R² = 0.99). There was no significant effect of parameter input (actual vs. predicted CP and W′) on modelled WBAL′ at 2,250 m (P = 0.24). WBALdiff′ returned higher values than WBALint′ throughout HIIT (P < 0.001). During HIIT, WBALdiff′ was not different to 0 kJ at completion, at 250 m (0.7 ± 2.0 kJ; P = 0.33) and 2,250 m (−1.3 ± 3.5 kJ; P = 0.30). However, WBALint′ was lower than 0 kJ at 250 m (−0.9 ± 1.3 kJ; P = 0.058) and 2,250 m (−2.8 ± 2.8 kJ; P = 0.02).

Conclusion: The altitude prediction equations for CP and W′ developed in this study are suitable for use with the WBAL′ model in acute hypoxia. This enables the application of WBAL′ modelling to training prescription and competition analysis at altitude.

Comparison of ergometer- and track-based testing in junior track-sprint cyclists. Implications for talent identification and development

Talent identification (TID) and talent development (TDE) programmes in track sprint cycling use ergometer- and track-based tests to select junior athletes and assess their development. The purpose of this study was to assess which tests are best at monitoring TID and TDE. Ten male participants (16.2 ± 1.1 year; 178.5 ± 6.0 cm and 73.6 ± 7.6 kg) were selected into the national TID squad based on initial testing. These tests consisted of two 6-s maximal sprints on a custom-built ergometer and 4 maximal track-based tests (2 rolling and 2 standing starts) using 2 gear ratios. Magnitude-based inferences and correlation coefficients assessed changes following a 3-month TDE programme. Training elicited meaningful improvements (80-100% likely) in all ergometer parameters. The standing and rolling small gear, track-based effort times were likely and very likely (3.2 ± 2.4% and 3.3 ± 1.9%, respectively) improved by training. Stronger correlations between ergometer- and track-based measures were very likely following training. Ergometer-based testing provides a more sensitive tool than track-based testing to monitor changes in neuromuscular function during the early stages of TDE. However, track-based testing can indicate skill-based improvements in performance when interpreted with ergometer testing. In combination, these tests provide information on overall talent development.

Validity and Reliability of the PowerCal Device for Estimating Power Output During Cycling Time Trials

Costa, VP, Guglielmo, LGA, and Paton, CD. Validity and reliability of the PowerCal device for estimating power output during cycling time trials. J Strength Cond Res 31(1): 227-232, 2017-This study assessed the validity and reproducibility of the PowerCal device for estimating power output (PO) during cycling hilly time trials (TTs). Twenty-one well-trained men cyclists performed an incremental exercise test and three 20-km TTs (34.1 ± 10.6 years; 73.2 ± 3.2 kg, 176.8 ± 6.2 cm; maximal PO, 334 ± 31 W; maximal oxygen uptake, 61.0 ± 4.2 ml·kg·min). The first TT was used for familiarization, and the tests were separated by at least 72 hours. Mean PO over the 20-km TT was significantly greater for the Velotron (282 ± 27 W) than for the PowerCal (242 ± 28 W). The mean power over each kilometer of the trial ranged from 5.8 to 23.4% greater on the Velotron than on the PowerCal. High within-subject variation between the trials was substantially greater for the PowerCal (4.9%) than for the Velotron (1.8%). High coefficients of variation scores for the Velotron test-retest were found to be concentrated in the beginning and final meters of the TT (∼6.0%), whereas the scores were lower in the middle of the trials (∼3.0%). In contrast, the PowerCal test-retest achieved a high coefficient of variation (∼6.0%) in each km over the TT. Thus, the PowerCal device should be used with caution during cycling activities because it is not reliable and underestimates PO.

Blood-Borne Markers of Fatigue in Competitive Athletes - Results from Simulated Training Camps

Assessing current fatigue of athletes to fine-tune training prescriptions is a critical task in competitive sports. Blood-borne surrogate markers are widely used despite the scarcity of validation trials with representative subjects and interventions. Moreover, differences between training modes and disciplines (e.g. due to differences in eccentric force production or calorie turnover) have rarely been studied within a consistent design. Therefore, we investigated blood-borne fatigue markers during and after discipline-specific simulated training camps. A comprehensive panel of blood-born indicators was measured in 73 competitive athletes (28 cyclists, 22 team sports, 23 strength) at 3 time-points: after a run-in resting phase (d 1), after a 6-day induction of fatigue (d 8) and following a subsequent 2-day recovery period (d 11). Venous blood samples were collected between 8 and 10 a.m. Courses of blood-borne indicators are considered as fatigue dependent if a significant deviation from baseline is present at day 8 (Δfatigue) which significantly regresses towards baseline until day 11 (Δrecovery). With cycling, a fatigue dependent course was observed for creatine kinase (CK; Δfatigue 54±84 U/l; Δrecovery -60±83 U/l), urea (Δfatigue 11±9 mg/dl; Δrecovery -10±10 mg/dl), free testosterone (Δfatigue -1.3±2.1 pg/ml; Δrecovery 0.8±1.5 pg/ml) and insulin linke growth factor 1 (IGF-1; Δfatigue -56±28 ng/ml; Δrecovery 53±29 ng/ml). For urea and IGF-1 95% confidence intervals for days 1 and 11 did not overlap with day 8. With strength and high-intensity interval training, respectively, fatigue-dependent courses and separated 95% confidence intervals were present for CK (strength: Δfatigue 582±649 U/l; Δrecovery -618±419 U/l; HIIT: Δfatigue 863±952 U/l; Δrecovery -741±842 U/l) only. These results indicate that, within a comprehensive panel of blood-borne markers, changes in fatigue are most accurately reflected by urea and IGF-1 for cycling and by CK for strength training and team sport players.

Using micro-sensor data to quantify macro kinematics of classical cross-country skiing during on-snow training

Micro-sensors were used to quantify macro kinematics of classical cross-country skiing techniques and measure cycle rates and cycle lengths during on-snow training. Data were collected from seven national level participants skiing at two submaximal intensities while wearing a micro-sensor unit (MinimaxX™). Algorithms were developed identifying double poling (DP), diagonal striding (DS), kick-double poling (KDP), tucking (Tuck), and turning (Turn). Technique duration (T-time), cycle rates, and cycle counts were compared to video-derived data to assess system accuracy. There was good reliability between micro-sensor and video calculated cycle rates for DP, DS, and KDP, with small mean differences (Mdiff% = -0.2 ± 3.2, -1.5 ± 2.2 and -1.4 ± 6.2) and trivial to small effect sizes (ES = 0.20, 0.30 and 0.13). Very strong correlations were observed for DP, DS, and KDP for T-time (r = 0.87-0.99) and cycle count (r = 0.87-0.99), while mean values were under-reported by the micro-sensor. Incorrect Turn detection was a major factor in technique cycle misclassification. Data presented highlight the potential of automated ski technique classification in cross-country skiing research. With further refinement, this approach will allow many applied questions associated with pacing, fatigue, technique selection and power output during training and competition to be answered.

Five-Kilometers Time Trial: Preliminary Validation of a Short Test for Cycling Performance Evaluation

Background:

The five-kilometer time trial (TT5km) has been used to assess aerobic endurance performance without further investigation of its validity.

Objectives:

This study aimed to perform a preliminary validation of the TT5km to rank well-trained cyclists based on aerobic endurance fitness and assess changes of the aerobic endurance performance.

Materials and Methods:

After the incremental test, 20 cyclists (age = 31.3 ± 7.9 years; body mass index = 22.7 ± 1.5 kg/m²; maximal aerobic power = 360.5 ± 49.5 W) performed the TT5km twice, collecting performance (time to complete, absolute and relative power output, average speed) and physiological responses (heart rate and electromyography activity). The validation criteria were pacing strategy, absolute and relative reliability, validity, and sensitivity. Sensitivity index was obtained from the ratio between the smallest worthwhile change and typical error.

Results:

The TT5km showed high absolute (coefficient of variation < 3%) and relative (intraclass coefficient correlation > 0.95) reliability of performance variables, whereas it presented low reliability of physiological responses. The TT5km performance variables were highly correlated with the aerobic endurance indices obtained from incremental test (r > 0.70). These variables showed adequate sensitivity index (> 1).

Conclusions:

TT5km is a valid test to rank the aerobic endurance fitness of well-trained cyclists and to differentiate changes on aerobic endurance performance. Coaches can detect performance changes through either absolute (± 17.7 W) or relative power output (± 0.3 W.kg^-1), the time to complete the test (± 13.4 s) and the average speed (± 1.0 km.h^-1). Furthermore, TT5km performance can also be used to rank the athletes according to their aerobic endurance fitness.

Comparison of power output during ergometer and track cycling in adolescent cyclists

The aim of this study is to establish the level of agreement between test performance of young elite cyclists in a laboratory and a track field-based trial. Fourteen adolescent cyclists (age: 14.8 ± 1.1 years; (Equation is included in full-text article.): 63.5 ± 5.6 ml·min(-1)·kg(-1)) performed 3 tests of 10 seconds, 1 minute, and 3 minutes on an air-braked ergometer (Wattbike) and on a 250-m track using their own bikes mounted with mobile power meters (SRM). The agreement between the maximum and mean power output (Pmax and Pmean) measured on the Wattbike and SRM was assessed with the 95% limits of agreement (LoA). Power output was strongly correlated between Wattbike and SRM for all tests (r = 0.94-0.96; p < 0.001). However, power output was significantly higher on the Wattbike compared with track cycling during all tests. The bias and 95% LoA were 76 ± 78 W (8.8 ± 9.5%; p = 0.003, d = 0.38) for Pmax10s and 82 ± 55 W (10.9 ± 7.9%; p < 0.001, d = 0.46) for Pmean10s. During the 1- and 3-minute test, the bias and 95% LoA were 72 ± 30 W (17.9 ± 7.1%; p < 0.001, d = 0.84) and 28 ± 20 W (9.6 ± 6.1%; p < 0.001, d = 0.51), respectively. Laboratory tests, as assessed using a stationary ergometer, resulted in maximal and mean power output scores that were consistently higher than a track field-based test using a mobile ergometer. These results might be attributed to the technical ability of the riders and their experience to optimize gearing and cadence to maximize performance. Prediction of field-based testing on the track from laboratory tests should be used with caution.

Heliox breathing equally influences respiratory mechanics and cycling performance in trained males and females

In this study we tested the hypothesis that inspiring a low-density gas mixture (helium-oxygen; HeO2) would minimize mechanical ventilatory constraints and preferentially increase exercise performance in females relative to males. Trained male (n = 11, 31 yr) and female (n = 10, 26 yr) cyclists performed an incremental cycle test to exhaustion to determine maximal aerobic capacity (V̇o2max; male = 61, female = 56 ml·kg(-1)·min(-1)). A randomized, single-blinded crossover design was used for two experimental days where subjects completed a 5-km cycling time trial breathing humidified compressed room air or HeO2 (21% O2:balance He). Subjects were instrumented with an esophageal balloon for the assessment of respiratory mechanics. During the time trial, we assessed the ability of HeO2 to alleviate mechanical ventilatory constraints in three ways: 1) expiratory flow limitation, 2) utilization of ventilatory capacity, and 3) the work of breathing. We found that HeO2 significantly reduced the work of breathing, increased the size of the maximal flow-volume envelope, and reduced the fractional utilization of the maximal ventilatory capacity equally between men and women. The primary finding of this study was that inspiring HeO2 was associated with a statistically significant performance improvement of 0.7% (3.2 s) for males and 1.5% (8.1 s) for females (P < 0.05); however, there were no sex differences with respect to improvement in time trial performance (P > 0.05). Our results suggest that the extent of sex-based differences in airway anatomy, work of breathing, and expiratory flow limitation is not great enough to differentially affect whole body exercise performance.

Prediction of maximal or peak oxygen uptake from ratings of perceived exertion

Maximal or peak oxygen uptake (V˙O2 max and V˙O2 peak , respectively) are commonly measured during graded exercise tests (GXTs) to assess cardiorespiratory fitness (CRF), to prescribe exercise intensity and/or to evaluate the effects of training. However, direct measurement of CRF requires a GXT to volitional exhaustion, which may not always be well accepted by athletes or which should be avoided in some clinical populations. Consequently, numerous studies have proposed various sub-maximal exercise tests to predict V˙O2 max or V˙O2 peak . Because of the strong link between ratings of perceived exertion (RPE) and oxygen uptake (V˙O2), it has been proposed that the individual relationship between RPE and V˙O2 (RPE:V˙O2) can be used to predict V˙O2 max (or V˙O2 peak) from data measured during submaximal exercise tests. To predict V˙O2 max or V˙O2 peak from these linear regressions, two procedures may be identified: an estimation procedure or a production procedure. The estimation procedure is a passive process in which the individual is typically asked to rate how hard an exercise bout feels according to the RPE scale during each stage of a submaximal GXT. The production procedure is an active process in which the individual is asked to self-regulate and maintain an exercise intensity corresponding to a prescribed RPE. This procedure is referred to as a perceptually regulated exercise test (PRET). Recently, prediction of V˙O2max or V˙O2 peak from RPE:V˙O2 measured during both GXT and PRET has received growing interest. A number of studies have tested the validity, reliability and sensitivity of predicted V˙O2 max or V˙O2 peak from RPE:V˙O2 extrapolated to the theoretical V˙O2 max at RPE20 (or RPE19). This review summarizes studies that have used this predictive method during submaximal estimation or production procedures in various populations (i.e., sedentary individuals, athletes and pathological populations). The accuracy of the methods is discussed according to the RPE:V˙O2 range used to plot the linear regression (e.g., RPE9–13 versus RPE9–15 versus RPE9–17 during PRET), as well as the perceptual endpoint used for the extrapolation (i.e., RPE19 and RPE20). The V˙O2 max or V˙O2 peak predictions from RPE:V˙O2 are also compared with heart rate-related predictive methods. This review suggests that V˙O2 max (or V˙O2 peak ) may be predicted from RPE:V˙O2 extrapolated to the theoretical V˙O2 max (or V˙O2 peak) at RPE20 (or RPE19). However, it is generally preferable to (1) extrapolate RPE:V ˙ O 2 to RPE19 (rather than RPE20); (2) use wider RPE ranges (e.g. RPE ≤ 17 or RPE9–17) in order to increase the accuracy of the predictions; and (3) use RPE ≤ 15 or RPE9–15 in order to reduce the risk of cardiovascular complications in clinical populations.

Effects of high-intensity intermittent priming on physiology and cycling performance

The pre-event warm-up or "priming" routine for optimising cycling performance is not well-defined or uniform to a specific event. We aimed to determine the effects of varying the intensity of priming on 3 km cycling performance. Ten endurance-trained male cyclists completed four 3 km time-trials (TT) on four separate occasions, each preceded by a different priming strategy including "self-selected" priming and three intermittent priming strategies incorporating 10 min of constant-load cycling followed by 5 × 10 s bouts of varying relative intensity (100% and 150% of peak aerobic power, Wpeak, and all-out priming). The self-selected priming trial (379 ± 44 W) resulted in similar mean power during the 3 km TT to intermittent priming at 100% (376 ± 45 W; -0.7%; unclear) and 150% (374 ± 48 W; -1.5%, unclear) of Wpeak, but significantly greater than all-out priming (357 ± 45 W; -5.8%, almost certainly harmful). Differences between intermittent and self-selected priming existed with regards to heart rate (6.2% to 11.5%), blood lactate (-22.9% to 125%) and VO2 kinetics (-22.9% to 8.2%), but these were not related to performance outcomes. In conclusion, prescribed intermittent priming strategies varying in intensity did not substantially improve 3 km TT performance compared to self-selected priming.

Validity and reliability of the look Keo power pedal system for measuring power output during incremental and repeated sprint cycling

Power meters have traditionally been integrated into the crank set, but several manufacturers have designed new systems located elsewhere on the bike, such as inside the pedals.

PURPOSE

This study aimed to determine the validity and reliability of the Keo power pedals during several laboratory cycling tasks.

METHODS

Ten active male participants (mean ± SD age 34.0 ± 10.6 y, height 1.77 ± 0.04 m, body mass 76.5 ± 10.7 kg) familiar with laboratory cycling protocols completed this study. Each participant was required to complete 2 laboratory cycling trials on an SRM ergometer (SRM, Germany) that was also fitted with the Keo power pedals (Look, France). The trials consisted of an incremental test to exhaustion followed by 10 min rest and then three 10-s sprint tests separated by 3 min of cycling at 100 W.

RESULTS

Over power ranges of 75 to 1147 W, the Keo power-pedal system produced typical error values of 0.40, 0.21, and 0.21 for the incremental, sprint, and combined trials, respectively, compared with the SRM. Mean differences of 21.0 and 18.6 W were observed between trials 1 and 2 with the Keo system in the incremental and combined protocols, respectively. In contrast, the SRM produced differences of 1.3 and 0.6 W for the same protocols.

CONCLUSIONS

The power data from the Keo power pedals should be treated with some caution given the presence of mean differences between them and the SRM. Furthermore, this is exacerbated by poorer reliability than that of the SRM power meter.

Reliability of a 2-Bout Exercise Test on a Wattbike Cycle Ergometer

Purpose:

To determine the intraday and interday reliability of a 2 × 4-min performance test on a cycle ergometer (Wattbike) separated by 30 min of passive recovery (2 × 4MMP).

Methods:

Twelve highly trained cyclists (mean ± SD; age = 20 ± 2 y, predicted VO2max = 59.0 ± 3.6 mL · kg−1 · min−1) completed six 2 × 4MMP cycling tests on a Wattbike ergometer separated by 7 d. Mean power was measured to determine intraday (test 1 [T1] to test 2 [T2]) and interday reliability (weeks 1–6) over the repeated trials.

Results:

The mean intraday reliabilities of the 2 × 4MMP test, as expressed by the typical error of measurement (TEM, W) and coefficient of variation (CV, %) over the 6 wk, were 10.0 W (95% confidence limits [CL] 8.2–11.8), and 2.6% (95%CL 2.1–3.1), respectively. The mean interday reliability TEM and CV for T1 over the 6 wk were 10.4 W (95%CL 8.7–13.3) and 2.7% (95%CL 2.3–3.5), respectively, and 11.7 W (95%CL 9.8–15.1) and 3.0% (95%CL 2.5–3.9) for T2.

Conclusion:

The testing protocol performed on a Wattbike cycle ergometer in the current study is reproducible in highly trained cyclists. The high intraday and interday reliability make it a reliable method for monitoring cycling performance and for investigating factors that affect performance in cycling events.

Effects of Music Tempo on Performance, Psychological, and Physiological Variables during 20 Km Cycling in Well-Trained Cyclists

Few studies have investigated the effects of music on trained athletes during high intensity endurance tasks. Therefore, this study investigated the effects of different music tempi on performance, psychological, and physiological responses of well-trained cyclists to time trial cycling. 10 male road cyclists ( M age = 35 yr., SD = 7), with a minimum of three years racing experience, performed four 20-km time trials on a Computrainer™ Pro 3D indoor cycle trainer over a period of four weeks. The time-trials were spaced one week apart. The music conditions for each trial were randomised between fast-tempo (140 bpm), medium-tempo (120 bpm), slow-tempo (100 bpm), and no music. Performance (completion time, power output, average speed and cadence), physiological (heart rate, oxygen consumption, breathing frequency and respiratory exchange ratio), psychophysical (RPE), and psychological (mood states) data were collected for each trial. Results indicated no significant changes in performance, physiological, or psychophysical variables. Total mood disturbance and tension increased significantly in the fast-tempo trial when compared with medium and no-music conditions.

The dose-response relationship between pseudoephedrine ingestion and exercise performance

OBJECTIVES

The purpose of the present study was to examine a possible dose-response between pre-exercise pseudoephedrine intake and cycling time trial performance.

DESIGN

Randomised, double-blind, crossover trial.

METHODS

Ten trained male endurance cyclists (26.5 ± 6.2 years, 75.1 ± 5.9 kg, 70.6 ± 6.8 mL kg(-1)min(-1)) undertook three cycling time trials in which a fixed amount of work (7 kJ kg(-1) body mass) was completed in the shortest possible time. Sixty minutes before the start of exercise, subjects orally ingested either 2.3 mg kg(-1) or 2.8 mg kg(-1) body mass of pseudoephedrine or a placebo in a randomised and double-blind manner. Venous blood was sampled at baseline, pre- and post-warm up and post-exercise for the analysis of pH and lactate and glucose concentrations; plasma catecholamine and pseudoephedrine concentrations were measured at all times except post-warm up.

RESULTS

Cycling time trial performance (∼ 30 min) was not enhanced by pseudoephedrine ingestion. Plasma pseudoephedrine concentration increased from pre-warm up to post-exercise in both treatment conditions, with the 2.8 mg kg(-1) body mass dose producing the highest concentration at both time points (2.8 mg kg(-1)>2.3 mg kg(-1)>placebo; p<0.001).

CONCLUSIONS

There was large individual variation in plasma pseudoephedrine concentration between subjects following pseudoephedrine administration. A number of factors clearly influence the uptake and appearance of pseudoephedrine in the blood and these are not yet fully understood. Combined with subsequent differences in plasma pseudoephedrine between individuals, this may partially explain the present findings and also the inconsistencies in performance following pseudoephedrine administration in previous studies.

Field-based physiological testing of wheelchair athletes

The volume of literature on field-based physiological testing of wheelchair sports, such as basketball, rugby and tennis, is considerably smaller when compared with that available for individuals and team athletes in able-bodied (AB) sports. In analogy to the AB literature, it is recognized that performance in wheelchair sports not only relies on fitness, but also sport-specific skills, experience and technical proficiency. However, in contrast to AB sports, two major components contribute towards 'wheeled sports' performance, which are the athlete and the wheelchair. It is the interaction of these two that enable wheelchair propulsion and the sporting movements required within a given sport. Like any other athlete, participants of wheelchair sports are looking for efficient ways to train and/or analyse their technique and fitness to improve their performance. Consequently, laboratory and/or field-based physiological monitoring tools used at regular intervals at key time points throughout the year must be considered to help with training evaluation. The present review examines methods available in the literature to assess wheelchair sports fitness in a field-based environment, with special attention on outcome variables, validity and reliability issues, and non-physiological influences on performance. It also lays out the context of field-based testing by providing details about the Paralympic court sports and the impacts of a disability on sporting performance. Due to the limited availability of specialized equipment for testing wheelchair-dependent participants in the laboratory, the adoption of field-based testing has become the preferred option by team coaches of wheelchair athletes. An obvious advantage of field-based testing is that large groups of athletes can be tested in less time. Furthermore, athletes are tested in their natural environment (using their normal sports wheelchair set-up and floor surface), potentially making the results of such testing more relevant than laboratory testing. However, given that many tests, such as the multistage fitness test and the Yo-Yo intermittent test, have originally been developed for AB games players, the assumption that these can also be used for wheelchair athletes may be erroneous. With the array of AB aerobic and anaerobic field tests available, it is difficult to ascertain which ones may be best suited for wheelchair athletes. Therefore, new, wheelchair sport-specific tests have been proposed and validated. Careful selection of tests to enable coaches to distinguish between disability classifications, wheelchair proficiency and actual performance improvements is paramount as this will not only enhance the value of field-based testing, but also help with the development of meaningful normative data.

Peak power output provides the most reliable measure of performance in prolonged intermittent-sprint cycling

The aims of this study were to determine the reliability of an intermittent-sprint cycling protocol and to determine the efficacy of one practice session on main trials. Eleven men, moderately trained team-sport athletes, completed three visits to the laboratory involving a graded-exercise test and practice session and two trials of a cycling intermittent-sprint Protocol separated by three days. Data for practice and main trials were analysed using typical error of measurement, intra-class correlation and least-products regression to determine reliability. Typical error of measurement (expressed as a coefficient of variation) and intra-class correlation for peak power output from all 20 sprints for trial 1 and trial 2 were 2.9 ± 12.8% (95% confidence interval: 2.0-5.0%) and 0.96 (95% confidence interval: 0.85-0.99), respectively. Typical errors of measurement and intra-class correlation for mean power output for all 20 sprints for trials 1 and 2 were 4.2 ± 11.9% (95% confidence interval: 2.9-7.4%) and 0.90 (95% confidence interval: 0.66-0.97), respectively. The results suggest that peak power output provides a more reliable measure than mean power output. The Cycling Intermittent-Sprint Protocol provides reliable measures of intermittent-sprint performance.

Time-variant modelling of heart rate responses to exercise intensity during road cycling

The aim of this study was to determine if heart rate responses to training intensity during road cycling could be modelled with compact time-variant mathematical model structures. The model performance was evaluated in terms of model order (complexity), number of inputs and parameter estimation methods used (time-invariant vs. time-variant). Thirteen male cyclists performed two identical cycling tests of 27 km on the road. Uphill sections were introduced to induce dynamic variations in heart rate. The heart rate and training intensity, represented by power output and road inclination, were measured in real-time. Taking only power as system input allowed to explain the variations in heart rate in an accurate way R2 T = 0.86 ± 0.08, since adding the road inclination as an additional input did not significantly improve the modelling performance R2 T = 0.87 ± 0.08, P = 0.32. Furthermore, we demonstrated that models with first-order dynamics accurately describes the heart rate responses to power variations R2 T = 0.86 ± 0.08, but that more complex second-order model structures R2 T = 0.88 ± 0.08 were significantly better than the first-order model structures (P = 0.028). Finally, the heart rate dynamics appeared to be time-variant, since the time-variant model structures R2 T = 0.89 ± 0.07 were significantly better than the time-invariant model structures R2 T = 0.84 ± 0.08, P = 0.0002. So, compact time-variant second-order model structures could be used to model the heart rate response to training intensity as a basis for training optimisation.

Quercetin and endurance exercise capacity: a systematic review and meta-analysis

Quercetin is a dietary flavonoid purported to improve human endurance exercise capacity. However, published findings are mixed.

PURPOSE

The study's purpose was to perform a systematic review of the literature and meta-analysis to examine whether quercetin ingestion increases endurance exercise capacity.

METHODS

A search of the literature was conducted using the key words quercetin, performance, exercise, endurance, and aerobic capacity. Eleven studies were identified as meeting the inclusion criteria providing data on 254 human subjects. Across all studies, subject presupplementation VO(2max) ranged from 41 to 64 mL·kg(-1)·min(-1) (median = 46), and median treatment duration was 11 d with a median dosage of 1000 mg·d(-1). Effect sizes (ES) were calculated as the standardized mean difference, and meta-analyses were completed using a random-effects model.

RESULTS

The ES calculated for all studies combining VO(2max) and endurance performance measures indicates a significant effect favoring quercetin over placebo (ES = 0.15, P = 0.021, 95% confidence interval = 0.02-0.27), but the magnitude of effect is considered between trivial and small, equating to a ∼2% [corrected] improvement of quercetin over placebo. Using a subgroup meta-analysis comparing quercetin's effect on endurance exercise performance versus VO(2max), no significant difference was found (P = 0.69). Meta-regression of study ES relative to subjects' fitness level or plasma quercetin concentration achieved by supplementation was also not significant.

CONCLUSIONS

On average, quercetin provides a statistically significant benefit in human endurance exercise capacity (VO(2max) and endurance exercise performance), but the effect is between trivial and small. Experimental factors that explain the between-study variation remain to be elucidated.

Pack hike test finishing time for Australian firefighters: pass rates and correlates of performance

The pack hike test (PHT, 4.83 km hike wearing a 20.4-kg load) was devised to determine the job readiness of USA wildland firefighters. This study measured PHT performance in a sample of Australian firefighters who currently perform the PHT (career land management firefighters, LMFF) and those who do not (suburban/regional volunteer firefighters, VFF). The study also investigated the relationships between firefighters' PHT performance and their performance across a range of fitness tests for both groups. Twenty LMFF and eighteen age-, body mass-, and height-matched VFF attempted the PHT, and a series of muscular endurance, power, strength and cardiorespiratory fitness tests. Bivariate correlations between the participants' PHT finishing time and their performance in a suite of different fitness tests were determined using Pearson's product moment correlation coefficient. The mean PHT finishing time for LMFF (42.2 ± 2.8 min) was 9 ± 14% faster (p = 0.001) than for VFF (46.1 ± 3.6 min). The pass rate (the percentage of participants who completed the PHT in under 45 min) for LMFF (90%) was greater than that of VFF (39%, p = 0.001). For LMFF, VO(2peak) in L min(-1)(r = -0.66, p = 0.001) and the duration they could sustain a grip 'force' of 25 kg (r = -0.69, p = 0.001) were strongly correlated with PHT finishing time. For VFF, VO(2peak) in mL kg(-1) min(-1)(r = -0.75, p = 0.002) and the duration they could hold a 1.2-m bar attached to 45.5 kg in a 'hose spray position' (r = -0.69, p = 0.004) were strongly correlated with PHT finishing time. This study shows that PHT fitness-screening could severely limit the number of VFF eligible for duty, compromising workforce numbers and highlights the need for specific and valid firefighter fitness standards. The results also demonstrate the strong relationships between PHT performance and firefighters' cardiorespiratory fitness and local muscular endurance. Those preparing for the PHT should focus their training on these fitness components in the weeks and months prior to undertaking the PHT.

Fructose-maltodextrin ratio in a carbohydrate-electrolyte solution differentially affects exogenous carbohydrate oxidation rate, gut comfort, and performance

Solutions containing multiple carbohydrates utilizing different intestinal transporters (glucose and fructose) show enhanced absorption, oxidation, and performance compared with single-carbohydrate solutions, but the impact of the ratio of these carbohydrates on outcomes is unknown. In a randomized double-blind crossover, 10 cyclists rode 150 min at 50% peak power, then performed an incremental test to exhaustion, while ingesting artificially sweetened water or one of three carbohydrate-salt solutions comprising fructose and maltodextrin in the respective following concentrations: 4.5 and 9% (0.5-Ratio), 6 and 7.5% (0.8-Ratio), and 7.5 and 6% (1.25-Ratio). The carbohydrates were ingested at 1.8 g/min and naturally (13)C-enriched to permit evaluation of oxidation rate by mass spectrometry and indirect calorimetry. Mean exogenous carbohydrate oxidation rates were 1.04, 1.14, and 1.05 g/min (coefficient of variation 20%) in 0.5-, 0.8-, and 1.25-Ratios, respectively, representing likely small increases in 0.8-Ratio of 11% (90% confidence limits; ± 4%) and 10% (± 4%) relative to 0.5- and 1.25-Ratios, respectively. Comparisons of fat and total and endogenous carbohydrate oxidation rates between solutions were unclear. Relative to 0.5-Ratio, there were moderate improvements to peak power with 0.8- (3.6%; 99% confidence limits ± 3.5%) and 1.25-Ratio (3.0%; ± 3.7%) but unclear with water (0.4%; ± 4.4%). Increases in stomach fullness, abdominal cramping, and nausea were lowest with the 0.8- followed by the 1.25-Ratio solution. At high carbohydrate-ingestion rate, greater benefits to endurance performance may result from ingestion of 0.8- to 1.25-Ratio fructose-maltodextrin solutions. Small perceptible improvements in gut comfort favor the 0.8-Ratio and provide a clearer suggestion of mechanism than the relationship with exogenous carbohydrate oxidation.

Measuring submaximal performance parameters to monitor fatigue and predict cycling performance: a case study of a world-class cyclo-cross cyclist

Recently a novel submaximal test, known as the Lamberts and Lambert submaximal cycle test (LSCT), has been developed with the purpose of monitoring and predicting changes in cycling performance. Although this test has been shown to be reliable and able to predict cycling performance, it is not known whether it can measure changes in training status. Therefore, the aim of this study was to determine whether the LSCT is able to track changes in performance parameters, and objective and subjective markers of well-being. A world class cyclo-cross athlete (31 years) volunteered to participate in a 10-week observational study. Before and after the study, a peak power output (PPO) test with respiratory gas analysis (VO(2max)) and a 40-km time trial (40-km TT) test were performed. Training data were recorded in a training logbook with a daily assessment of well-being, while a weekly LSCT was performed. After the training period all performance parameters had improved by a meaningful amount (PPO +5.2%; 40-km TT time -2.5%; VO(2max) +1.4%). Increased training loads during weeks 2 and 6 and the subsequent training-induced fatigue was reflected in the increased well-being scores. Changes during the LSCT were most clearly notable in (1) increased power during the first minute of third stage, (2) increased rating of perceived exertion during second and third stages, and (3) a faster heart rate recovery after the third stage. In conclusion, these data suggest that the LSCT is able to track changes in training status and detect the consequences of sharp increases in training loads which seem to be associated with accumulating fatigue.

The analysis and utilization of cycling training data

Most mathematical models of athletic training require the quantification of training intensity and quantity or 'dose'. We aim to summarize both the methods available for such quantification, particularly in relation to cycle sport, and the mathematical techniques that may be used to model the relationship between training and performance. Endurance athletes have used training volume (kilometres per week and/or hours per week) as an index of training dose with some success. However, such methods usually fail to accommodate the potentially important influence of training intensity. The scientific literature has provided some support for alternative methods such as the session rating of perceived exertion, which provides a subjective quantification of the intensity of exercise; and the heart rate-derived training impulse (TRIMP) method, which quantifies the training stimulus as a composite of external loading and physiological response, multiplying the training load (stress) by the training intensity (strain). Other methods described in the scientific literature include 'ordinal categorization' and a heart rate-based excess post-exercise oxygen consumption method. In cycle sport, mobile cycle ergometers (e.g. SRM and PowerTap) are now widely available. These devices allow the continuous measurement of the cyclists' work rate (power output) when riding their own bicycles during training and competition. However, the inherent variability in power output when cycling poses several challenges in attempting to evaluate the exact nature of a session. Such variability means that average power output is incommensurate with the cyclist's physiological strain. A useful alternative may be the use of an exponentially weighted averaging process to represent the data as a 'normalized power'. Several research groups have applied systems theory to analyse the responses to physical training. Impulse-response models aim to relate training loads to performance, taking into account the dynamic and temporal characteristics of training and, therefore, the effects of load sequences over time. Despite the successes of this approach it has some significant limitations, e.g. an excessive number of performance tests to determine model parameters. Non-linear artificial neural networks may provide a more accurate description of the complex non-linear biological adaptation process. However, such models may also be constrained by the large number of datasets required to 'train' the model. A number of alternative mathematical approaches such as the Performance-Potential-Metamodel (PerPot), mixed linear modelling, cluster analysis and chaos theory display conceptual richness. However, much further research is required before such approaches can be considered as viable alternatives to traditional impulse-response models. Some of these methods may not provide useful information about the relationship between training and performance. However, they may help describe the complex physiological training response phenomenon.

Effect of intermittent hypoxic training on 20 km time trial and 30 s anaerobic performance

This study aimed to verify whether the "live low, train high" approach is beneficial for endurance and/or anaerobic cycling performance. Sixteen well-trained athletes completed 90 min of endurance training (60-70% of heart rate reserve), followed by two 30-s all-out sprints (Wingate test), daily, for 10 consecutive days. Nine subjects [intermittent hypoxic training (IHT) group] trained with an F(I)O(2) set to produce arterial oxygen saturations of approximately 88-82%, while seven subjects (placebo group) trained while breathing a normal gas mixture (F(I)O(2)=0.21). Four performance tests were conducted at sea level including a familiarization and baseline trial, followed by repeat trials at 2 and 9 days post-intervention. Relative to the placebo group, the mean power during the 30-s Wingate test increased by 3.0% (95% confidence limits, CL +/- 3.5%) 2 days, and 1.7% (+/- 3.8%) 9 days post-IHT. Changes in other performance variables (30 s peak power, 20 km mean power and 20 km oxygen cost) were unclear. During the time trial, the IHT participants' blood lactate concentration, respiratory exchange ratio, and SpO(2), relative to the placebo group, was substantially increased at 2 days post-intervention. The addition of IHT to the normal training program of well-trained athletes produced worthwhile gains in 30 s sprint performance possibly through enhanced glycolysis.

Effects of high-intensity training by heart rate or power in well-trained cyclists

The aim of this study was to determine whether the performance of cyclists after 4 weeks of high-intensity training improved similarly using either heart rate or power to prescribe training. Twenty-one well-trained men cyclists (age, 32 +/- 6 years; peak power output, 371 +/- 46 W) were randomly assigned to a power-based (GPOWER) or heart rate-based (GHEART) high-intensity training (HIT) group or a control group (GCONTROL). Training consisted of 8 repetitions of 4 minutes at either 80% of peak power output (GPOWER) or at the heart rate coinciding with 80% of peak power output (GHEART), with rest periods of 90 seconds. A 40-km time trial and VO2max test were performed before and after 8 training sessions. There were significant improvements (p < 0.05) in peak power output (GPOWER = 3.5%; GHEART = 5.0%) and 40-km time trial performance (GPOWER = 2.3%; GHEART = 2.1%) for both of the high-intensity groups. Although there were no significant differences between groups for these variables, when the data were analyzed using magnitude-based effects, the GHEART group showed greater probability of a "beneficial" effect for peak power output. The current general perception that prescribing training based only on power is more effective than prescribing training based on heart rate was not supported by the data from this study. Coaches who are unable to monitor progress frequently should prescribe training based on heart rate, when intervals are performed under stable conditions, because this may provide an additional advantage over prescribing training using power.

Effect of age on 16.1-km time-trial performance

In this study, we assessed the performance of trained senior (n = 6) and veteran (n = 6) cyclists (mean age 28 years, s = 3 and 57 years, s = 4 respectively). Each competitor completed two cycling tests, a ramped peak aerobic test and an indoor 16.1-km time-trial. The tests were performed using a Kingcycle ergometer with the cyclists riding their own bicycle fitted with an SRM powermeter. Power output, heart rate, and gas exchange variables were recorded continuously and blood lactate concentration [HLa] was assessed 3 min after the peak ramped test and at 2.5-min intervals during the time-trial. Peak values for power output (RMP(max)), heart rate (HR(peak)), oxygen uptake (VO2(peak)), and ventilation (V(Epeak)) attained during the ramped test were higher in the senior group (P < 0.05), whereas [HLa](peak), RER(peak), V(E): VO2(peak), and economy(peak) were similar between groups (P > 0.05). Time-trial values (mean for duration of race) for power output (W(TT)), heart rate (HR(TT)), VO2 (VO(2TT)), and V(E) (V(ETT)) were higher in the seniors (P < 0.05), but [HLa](TT), RER(TT), V(ETT): VO2(TT), and economy(TT) were similar between the groups (P > 0.05). Time-trial exercise intensity, expressed as %RMP(max), %HR(peak), % VO2(peak), and % V(Epeak), was similar (P > 0.05) for seniors and veterans (W(TT): 81%, s = 2 vs. 78%, s = 8; HR(TT): 96%, s = 4 vs. 94%, s = 4; VO2(TT): 92%, s = 4 vs. 95%, s = 10; V(ETT): 89%, s = 8 vs. 85%, s = 8, respectively). Overall, seniors attained higher absolute values for power output, heart rate, VO2, and V(E) but not blood lactate concentration, respiratory exchange ratio (RER), V(E): VO2, and economy. Veterans did not accommodate age-related declines in time trial performance by maintaining higher relative exercise intensity.

Effect of expiratory muscle fatigue on exercise tolerance and locomotor muscle fatigue in healthy humans

High-intensity exercise (≥90% of maximal O2 uptake) sustained to the limit of tolerance elicits expiratory muscle fatigue (EMF). We asked whether prior EMF affects subsequent exercise tolerance. Eight male subjects (means ± SD; maximal O2 uptake = 53.5 ± 5.2 ml·kg−1·min−1) cycled at 90% of peak power output to the limit of tolerance with (EMF-EX) and without (CON-EX) prior induction of EMF and for a time equal to that achieved in EMF-EX but without prior induction of EMF (ISO-EX). To induce EMF, subjects breathed against an expiratory flow resistor until task failure (15 breaths/min, 0.7 expiratory duty cycle, 40% of maximal expiratory gastric pressure). Fatigue of abdominal and quadriceps muscles was assessed by measuring the reduction relative to prior baseline values in magnetically evoked gastric twitch pressure (Pgatw) and quadriceps twitch force (Qtw), respectively. The reduction in Pgatw was not different after resistive breathing vs. after CON-EX (−27 ± 5 vs. −26 ± 6%; P = 0.127). Exercise time was reduced by 33 ± 10% in EMF-EX vs. CON-EX (6.85 ± 2.88 vs. 9.90 ± 2.94 min; P < 0.001). Exercise-induced abdominal and quadriceps muscle fatigue was greater after EMF-EX than after ISO-EX (−28 ± 9 vs. −12 ± 5% for Pgatw, P = 0.001; −28 ± 7 vs. −14 ± 6% for Qtw, P = 0.015). Perceptual ratings of dyspnea and leg discomfort (Borg CR10) were higher at 1 and 3 min and at end exercise during EMF-EX vs. during ISO-EX ( P < 0.05). Percent changes in limb fatigue and leg discomfort (EMF-EX vs. ISO-EX) correlated significantly with the change in exercise time. We propose that EMF impaired subsequent exercise tolerance primarily through an increased severity of limb locomotor muscle fatigue and a heightened perception of leg discomfort.

Comparison of different theoretical models estimating peak power output and maximal oxygen uptake in trained and elite triathletes and endurance cyclists in the velodrome

The aim of this study was to assess which of the equations that estimate peak power output and maximal oxygen uptake (VO2max) in the velodrome adapt best to the measurements made by reference systems. Thirty-four endurance cyclists and triathletes performed one incremental test in the laboratory and two tests in the velodrome. Maximal oxygen uptake and peak power output were measured with an indirect calorimetry system in the laboratory and with the SRM training system in the velodrome. The peak power output and VO2max of the field test were estimated by means of different equations. The agreement between the estimated and the reference values was assessed with the Bland-Altman method. The equation of Olds et al. (1995) showed the best agreement with respect to the peak power output reference values, and that of McCole et al. (1990) was the only equation to show good agreement with respect to the VO2max reference values. The VO2max values showed a higher coefficient of determination with respect to maximal aerobic speed when they were expressed in relative terms. In conclusion, the equations of Olds et al. (1995) and McCole et al. (1990) were best at estimating peak power output and VO2max in the velodrome, respectively.

Incremental Exercise Test Design and Analysis

Physiological variables, such as maximum work rate or maximal oxygen uptake (VO2max), together with other submaximal metabolic inflection points (e.g. the lactate threshold [LT], the onset of blood lactate accumulation and the pulmonary ventilation threshold [VT]), are regularly quantified by sports scientists during an incremental exercise test to exhaustion. These variables have been shown to correlate with endurance performance, have been used to prescribe exercise training loads and are useful to monitor adaptation to training. However, an incremental exercise test can be modified in terms of starting and subsequent work rates, increments and duration of each stage. At the same time, the analysis of the blood lactate/ventilatory response to incremental exercise may vary due to the medium of blood analysed and the treatment (or mathematical modelling) of data following the test to model the metabolic inflection points. Modification of the stage duration during an incremental exercise test may influence the submaximal and maximal physiological variables. In particular, the peak power output is reduced in incremental exercise tests that have stages of longer duration. Furthermore, the VT or LT may also occur at higher absolute exercise work rate in incremental tests comprising shorter stages. These effects may influence the relationship of the variables to endurance performance or potentially influence the sensitivity of these results to endurance training. A difference in maximum work rate with modification of incremental exercise test design may change the validity of using these results for predicting performance, and prescribing or monitoring training. Sports scientists and coaches should consider these factors when conducting incremental exercise testing for the purposes of performance diagnostics.

Validation of a field test to determine the maximal aerobic power in triathletes and endurance cyclists

OBJECTIVE

To validate a field test to assess the maximal and submaximal exercise aerobic adaptation under specific conditions, for endurance modality cyclists and triathletes.

METHODS

30 male and 4 female endurance modality cyclists and triathletes, with heterogeneous performance levels, performed three incremental tests: one in the laboratory and two in the field. Assessment of the validity of the field protocol was carried out by the Student's t test, intraclass correlation coefficient (ICC) and coefficient of variation (CV) of the maximal variables (maximal aerobic speed (MAS), maximal aerobic power (MAP), maximal heart rate (HR(max)), maximal blood lactate concentration ([La(-)](max)) and maximal oxygen uptake (VO(2max))) and submaximal variables (heart rate, HR) measured in each one of the tests. The errors in measurement were calculated. The repeatability of the field tests was assessed by means of the test-retest of the two field tests, and the validity by means of the test-retest of the laboratory test with respect to the mean of the two field tests.

RESULTS

No significant differences were found between the two field tests for any of the variables studied, but differences did exist for some variables between the laboratory tests with respect to the field tests (MAP, [La(-)](max), humidity (H), barometric pressure (Pb) and some characteristics of the protocols). The ICC of all the variables was high and the CV for the MAP was small. Furthermore, the measurement errors were small and therefore, assumable.

CONCLUSIONS

The incremental protocol of the proposed field test turned out to be valid to assess the maximal and submaximal aerobic adaptation.

Clinical Stress Testing in the Pediatric Age Group

This statement is an updated report of the American Heart Association’s previous publications on exercise in children. In this statement, exercise laboratory requirements for environment, equipment, staffing, and procedures are presented. Indications and contraindications to stress testing are discussed, as are types of testing protocols and the use of pharmacological stress protocols. Current stress laboratory practices are reviewed on the basis of a survey of pediatric cardiology training programs.

Prediction of time to exhaustion from blood lactate response during submaximal exercise in competitive cyclists

The aim of this investigation was to develop and validate a new method to predict time to exhaustion (pTE) from blood lactate variables measured during a submaximal non-exhaustive constant workload cycling test in professional cyclists. A multiple regression equation to estimate pTE from blood lactate variables measured within the first 10 min of a submaximal test and TE was determined in 40 competitive cyclists. Predicted TE reliability [individual coefficient of variation (CV)] was calculated in eight amateur cyclists who repeated the proposed test three times. Seasonal variations of pTE were monitored in 12 professional cyclists. Validity of pTE was determined by the known-group difference method in 49 professional cyclists. The prediction equation was: log(n)TE = 4.2067 - 0.8221(log(n) B) - 0.2519(log(n) C), where B is the lactate concentration at the 10th minute of the constant workload test and C is the lactate slope calculated between the 5th and 10th minute (adjusted r (2) =0.83, root mean square error in cross validation=23.1%). Predicted TE CV was 11.7%. The pTE obtained at the beginning of the season and the best and worst tests performed during the competitive season, resulted 162, 224 and 103% higher than the basic period test, respectively (P<0.05). Predicted TE was the only parameter discriminating elite from subelite professional cyclists. In conclusion, this study demonstrates that pTE is a valid and practical alternative to incremental tests and direct measures of endurance capacity requiring exhaustive efforts for the evaluation of competitive cyclists.

Seasonal changes in power of competitive cyclists: Implications for monitoring performance

Sport scientists should consider seasonal trends and individual variability in performance when using tests to track performance changes resulting from training or other medium-term interventions with individuals or in research studies. We report here the seasonal changes and variability in power of 12 male competitive cyclists, who performed laboratory tests of incremental peak and 4-km mean power measured with three ergometers simultaneously in each of five sessions during three phases (base, pre-comp, comp) of a season. Repeated-measures analysis of log-transformed power provided mean percent changes in performance between phases and within-cyclist variability in performance expressed as coefficients of variation between sessions < or = 2 wk apart within a phase and between sessions 8 wk-12 wk apart in different phases. Peak power increased from the base phase to the pre-comp phase on average by 5.3%, and by a further 1.8% from pre-comp to comp phase; corresponding increases in 4-km mean power were 6.1% and 2.2% (90% likely limits all approximately +/-2.6%). The variabilities for peak and 4-km mean powers were 1.2%-1.8% for sessions separated by < or = 2 wk and 2.0%-2.3% for sessions in pre-comp and comp phases, but increased to 3.4%-3.8% for sessions between the base and other phases (likely limits approximately (x/)/(1.6). Individual differences in the improvement in performance after the base phase evidently produced the greater variability between the base and the other phases. Interventions that might produce small but worthwhile changes in performance over a period of weeks-months need to be researched in pre-comp and comp phases, when the variability is small.

Diurnal variation in cycling performance: influence of warm-up

We examined the effects of time of day on a cycling time trial with and without a prolonged warm-up, among cyclists who tended towards being high in "morningness". Eight male cyclists (mean +/- s: age = 24.9 +/- 3.5 years, peak power output = 319 +/- 34 W, chronotype = 39 +/- 6 units) completed a 16.1-km time trial without a substantial warm-up at both 07:30 and 17:30 h. The time trial was also completed at both times of day after a 25-min warm-up at 60% of peak power. Power output, heart rate, intra-aural temperature and category ratings of perceived exertion (CR-10) were measured throughout the time trial. Post-test blood lactate concentration was also recorded. Warm-up generally improved time trial performance at both times of day (95% CI for improvement = 0 to 30 s), but mean cycling time was still significantly slower at 07:30 h than at 17:30 h after the warm-up (95% CI for difference = 33 to 66 s). Intra-aural temperature increased as the time trial progressed (P < 0.0005) and was significantly higher throughout the time trials at 17:30 h (P = 0.001), irrespective of whether the cyclists performed a warm-up or not. Blood lactate concentration after the time trial was lowest at 07:30 h without a warm-up (P = 0.02). No effects of time of day or warm-up were found for CR-10 or heart rate responses during the time trial. These results suggest that 16.1-km cycling performance is worse in the morning than in the afternoon, even with athletes who tend towards 'morningness', and who perform a vigorous 25-min warm-up. Diurnal variation in cycling performance is, therefore, relatively robust to some external and behavioural factors.

A acurácia da determinação do VO2max e do limiar anaeróbio

São raros estudos que tratam da acurácia de parâmetros de trocas gasosas durante o esforço, com a população brasileira. OBJETIVO: Determinar a confiabilidade do consumo máximo de oxigênio (VO2max) e do limiar anaeróbio (LAn), assim como, a objetividade do segundo (LAn) em adultos jovens saudáveis. MÉTODOS: Foram aplicados dois testes de esforço máximo, a partir dos quais dois observadores independentes determinaram o LAn através do método de inspeção visual. Os dados foram tratados por meio da análise de regressão, coeficiente de correlação intraclasse (CCI), ANOVA com dois fatores com teste post hoc de Tukey e teste t pareado para alfa < 0,05. As variações intra-observadores e intra-sujeitos foram determinadas por meio do erro típico (s) e coeficiente de variação (CV). RESULTADOS: Não houve diferença significativa entre os testes para o VO2max e LAn. Não foram observadas diferenças significativas entre testadores para a determinação do LAn. O VO2max apresentou entre os dois testes CCI = 0,97, s = ± 0,14L • min-1 e CV = ± 5,5% e para o LAn o CCI = 0,90, s = ± 0,14L • min¹, e CV = ± 9,2%. A determinação do LAn interobservadores apresentou CCI = 0,95, s = ± 0,10L • min-1 e CV = ± 5,6%. CONCLUSÃO: O VO2max e o LAn foram medidas satisfatoriamente precisas.

Age-related changes in maximal power and maximal heart rate recorded during a ramped test in 114 cyclists age 15-73 years

This study assessed age-related changes in power and heart rate in 114 competitive male cyclists age 15-73 years. Participants completed a maximal Kingcycle ergometer test with maximal ramped minute power (RMPmax, W) recorded as the highest average power during any 60 s and maximal heart rate (HRmax, beats/min) as the highest value during the test. From age 15 to 29 (n = 38) RMPmax increased by 7.2 W/year (r = .53, SE 49 W, p < .05). From age 30 to 73 (n = 78) RMPmax declined by 2.4 W/year (r = - .49, SE 49 W, p < .05). Heart rate decreased across the full age range by 0.66 beats . min( -1 ) . year( -1 ) (r = -.75, SE 9 beats/min, p < .05). Age accounted for only 25% of the variance in RMPmax but 56% in HRmax. RMPmax was shown to peak at age 30, then decline with age, whereas HRmax declined across the full age range.