The Reliability of 4-Minute and 20-Minute Time Trials and Their Relationships to Functional Threshold Power in Trained Cyclists

The effect of quercetin and citrulline on cycling time trial performance

BACKGROUND

There is growing interest in the use of nutrition and dietary supplements to optimize training and time-trial (TT) performance in cyclists. Separately, quercetin (QCT) and citrulline (CIT) have been used as ergogenic aids to improve oxygen (VO2) kinetics, perceived effort, and cycling TT performance. However, whether the combination of QCT and CIT can provide additive benefits and further enhance cycling performance production is currently unknown.

METHODS

We examined 28-days of QCT + CIT supplementation on TT performance and several performance measures (i.e. mean power, VO2, respiratory exchange ratio (RER), and rate of perceived exertion (RPE)). Forty-eight highly trained cyclists were assigned to one of four supplementation groups: (1) QCT + CIT (QCT: 500 mg, CIT: 3000 g), (2) QCT (500 mg), (3) CIT (3000 mg), or (4) placebo (3500 mg of a zero-calorie flavored crystal light package). Supplements were consumed two times per day for 28 consecutive days. Participants performed a 20-km cycling time-trial race, pre- and post-supplementation to determine the impact of the combined effects of QCT + CIT.

RESULTS

There were no potential benefits of QCT +CIT supplementation on TT performance and several performance measures. However, there was an improvement in VO2 from pre-to-post-supplementation in QCT (p  = 0.05) and CIT (p  = 0.04) groups, but not in the QCT+CIT and PL groups.

CONCLUSIONS

QCT + CIT does not seem beneficial for 20-km TT performance; further exploration with a focus on an increase in cycling duration or QCT+CIT combined with additional polyphenols may amplify any perceived bioactive or metabolic effects on cycling performance. The efficacy of QCT + CIT supplementation to improve cycling performance remains ambiguous.

Cannabis containing THC impairs 20-min cycling time trial performance irrespective of the method of inhalation

Herein, we examine the human exercise response following cannabis inhalation, taking into consideration varied cannabinoid concentrations and different inhalation methods. A semirandomized crossover study design was used, with measures of perceived exertion and physiological responses to submaximal and maximal exercise. Participants (n = 14, 9 males 5 females) completed exercise after 1) smoking Δ-9-tetrahydrocannabinol (THC)-predominant cannabis (S-THC), 2) inhaling aerosol (vaporizing) from THC-predominant cannabis (V-THC), 3) inhaling aerosol from cannabidiol (CBD)-predominant cannabis (V-CBD), or 4) under control conditions. All exercise was performed on a cycle ergometer, with submaximal testing performed at 100 W followed by an evaluation of maximal exercise performance using an all-out 20-min time trial. Metabolism was characterized via the analysis of expired gases while subjective ratings of perceived exertion (RPE) were reported. During submaximal cycling, heart rate was higher during S-THC and V-THC compared with both control and V-CBD (all P < 0.02). During maximal exercise, V̇e was lower in V-THC compared with control, S-THC, and V-CBD (all P < 0.03), as was S-THC compared with control (P < 0.05). Both V̇o2 and RPE were similar between conditions during maximal exercise (both P > 0.1). Mean power output during the 20-min time trial was significantly lower in the S-THC and V-THC conditions compared with both control and V-CBD (all P < 0.04). Cannabis containing THC alters the physiological response to maximal and submaximal exercise, largely independent of the inhalation method. THC-containing cannabis negatively impacts vigorous exercise performance during a sustained 20-min effort, likely due to physiological and psychotropic effects. Inhalation of cannabis devoid of THC and primarily containing CBD has little physiological effect on the exercise response or performance.NEW & NOTEWORTHY Inhalation of cannabis containing THC alters physiological responses to both submaximal and maximal exercise and reduces mean power output during a 20-min time trial, regardless of whether it is inhaled as smoke or aerosol. In contrast, cannabis devoid of THC and predominantly containing CBD has no effect on physiological responses to exercise or performance.

A self-paced 15-minute cycling time trial is a reliable performance measure in recreationally active individuals

Cycling time trial (TT) protocols have been shown to be reliable in trained cyclists, but their reproducibility in lesser-trained individuals is unknown. This study examined the reliability of a self-paced 15-minute cycling TT in recreationally active individuals. Twelve recreationally active males (age 27 ± 3 y; body mass 75.2 ± 8.9 kg; V ˙ O2peak = 51.10 ± 7.53 ml∙kg∙min-1) completed a V ˙ O2peak test and four experimental trials, separated by > 48 h. Experimental trials consisted of 10 min cycling at 60% Wmax, followed by a self-paced 15-min TT. Heart rate and work done were recorded every 5 min during the TT; and coefficient of variation (CV) was calculated. Work done was not different (P = 0.706) between trials (193.2 ± 45.3 kJ; 193.2 ± 43.5 kJ; 192.0 ± 42.3 kJ; 193.9 ± 42.8 kJ). Within participant CV ranged from 0.5-4.9% for the four TTs, with a mean CV of 2.1%. Mean CV decreased from 2.0% (range 0.1-5.0%) for the first two TTs to 1.7% (range 0.2-5.6%) for the second and third TTs, and further decreased to 1.0% (range 0.2-1.8%) for the third and fourth TTs. In conclusion, the use of a short-duration self-paced cycling TT in recreationally active individuals is a reliable performance measure.

Functional Threshold Power Field Test Exceeds Laboratory Performance in Junior Road Cyclists

Vinetti, G, Rossi, H, Bruseghini, P, Corti, M, Ferretti, G, Piva, S, Taboni, A, and Fagoni, N. The functional threshold power field test exceeds laboratory performance in junior road cyclists. J Strength Cond Res 37(9): 1815–1820, 2023—The functional threshold power (FTP) field test is appealing for junior cyclists, but it was never investigated in this age category, and even in adults, there are few data on FTP collected in field conditions. Nine male junior road cyclists (16.9 ± 0.8 years) performed laboratory determination of maximal aerobic power (MAP), 4-mM lactate threshold (P4mM), critical power (CP), and the curvature constant (W ′), plus a field determination of FTP as 95% of the average power output during a 20-minute time trial in an uphill road. The level of significance was set at p < 0.05. Outdoor FTP (269 ± 34 W) was significantly higher than CP (236 ± 24 W) and P4mM (233 ± 23 W). The V ˙ O 2 peak of the field FTP test (66.9 ± 4.4 ml·kg−1·min−1) was significantly higher than the V ˙ O 2 peak assessed in the laboratory (62.7 ± 3.7 ml·kg−1·min−1). Functional threshold power was correlated, in descending order, with MAP (r = 0.95), P4mM (r = 0.94), outdoor and indoor V ˙ O 2 peak (r = 0.93 and 0.93, respectively), CP (r = 0.84), and W ′ (r = 0.66). It follows that in junior road cyclists, the FTP field test was feasible and related primarily to aerobic endurance parameters and secondarily, but notably, to W ′. However, the FTP field test significantly exceeded all laboratory performance tests. When translating laboratory results to outdoor uphill conditions, coaches and sport scientists should consider this discrepancy, which may be particularly enhanced in this cycling age category.

Effect of varying recovery intensities on power outputs during severe intensity intervals in trained cyclists during the Covid-19 pandemic

Purpose

The study aimed to investigate the effects of different recovery intensities on the power outputs of repeated severe intensity intervals and the implications for W' reconstitution in trained cyclists.

Methods

Eighteen trained cyclists (FTP 258.0 ± 42.7 W; weekly training 8.6 ± 1.7 h∙week-1) familiar with interval training, use of the Zwift® platform throughout the Covid-19 pandemic, and previously established FTP (95% of mean power output from a 20-min test), performed 5 × 3-min severe intensity efforts interspersed with 2-min recoveries. Recovery intensities were: 50 W (LOW), 50% of functional threshold power (MOD), and self-selected power output (SELF).

Results

Whilst power outputs declined as the session progressed, mean power outputs during the severe intervals across the conditions were not different to each other (LOW 300.1 ± 48.1 W; MOD: 296.9 ± 50.4 W; SELF: 298.8 ± 53.3 W) despite the different recovery conditions. Mean power outputs of the self-selected recovery periods were 121.7 ± 26.2 W. However, intensity varied during the self-selected recovery periods, with values in the last 15 s being greater than the first 15 s (p < 0.001) and decreasing throughout the session (128.7 ± 25.4 W to 113.9 ± 29.3 W).

Conclusion

Reducing recovery intensities below 50% of FTP failed to enhance subsequent severe intensity intervals, suggesting that a lower limit for optimal W' reconstitution had been reached. As self-selected recoveries were seen to adapt to maintain the severe intensity power output as the session progressed, adopting such a strategy might be preferential for interval training sessions.

Durability in Professional Cyclists: A Field Study

PURPOSE

To assess durability in professional cyclists, as well as potential associated indicators.

METHODS

Twelve male professional cyclists participated in the study (age: 26 [5] y, VO2max: 83.0 [3.6] mL·kg-1·min-1). They performed a 20-minute time trial (TT) on 2 different sessions separated by a 48-hour period: (1) with no previous fatigue (TTFresh) and (2) immediately after a long submaximal ride (approximately 4 h, 40 kJ/kg) (TTFatigue). We then assessed the decay (in percentage) in mean power output (PO) from TTFresh to TTFatigue and its association with different laboratory-based endurance indicators (ventilatory threshold, peak PO, and VO2max) determined through a previous maximal incremental cycling test, as well as with training loads during the 4 weeks preceding the TTs.

RESULTS

While no differences were noted in the average heart rate (177 [7] vs 176 [6] beats·min-1, P = .118), there was a significant decay in PO between TTFresh and TTFatigue (386 [29] W vs 375 [28] W [-2.9%], respectively; P = .007), albeit with signs of interindividual variability (range = -8.5% to 1.1%; coefficient of variation = 105%). No significant associations were found between the PO decay and any of the analyzed indicators (all P > .05).

CONCLUSIONS

Performance is significantly impaired after a certain amount of work completed (approximately 40 kJ·kg-1) in professional cyclists, and the magnitude of this impairment seems to be not related to "traditional" laboratory-based endurance indicators or to markers of training load. These findings might support the need for specifically assessing durability in cyclists and confirming potential determinants of this parameter.

The reproducibility of 20-min time-trial performance on a virtual cycling platform

This study aimed to analyse the reproducibility of mean power output during 20-min cycling time-trials, in a remote home-based setting, using the virtual-reality cycling software, Zwift. Forty-four cyclists (11 women, 33 men; 37 ± 8 years old, 180 ± 8 cm, 80.1 ± 13.2 kg) performed 3 x 20-min time-trials on Zwift, using their own setup. Intra-class correlation coefficient (ICC), coefficient of variation (CV) and typical error (TE) were calculated for the overall sample, split into 4 performance groups based on mean relative power output (25% quartiles) and sex. Mean ICC, TE and CV of mean power output between time-trials were 0.97 [0.95-0.98], 9.36 W [8.02-11.28 W], and 3.7% [3.2-4.5], respectively. Women and men had similar outcomes (ICC: 0.96 [0.89-0.99] vs 0.96 [0.92-0.98]; TE: 8.30 W [6.25-13.10] vs. 9.72 W [8.20-12.23]; CV: 3.8% [2.9-6.1] vs. 3.7% [3.1-4.7], respectively), although cyclists from the first quartile showed a lower CV in comparison to the overall sample (Q1: 2.6% [1.9-4.1] vs. overall: 3.7% [3.2-4.5]). Our results indicate that power output during 20-minute cycling time-trials on Zwift are reproducible and provide sports scientists, coaches and athletes, benchmark values for future interventions in a virtual-reality environment.

Constant power threshold—predicting maximal lactate steady state in recreational cyclists

Introduction

Prolonged time trials proved capable of precisely estimating anaerobic threshold. However, time trial studies in recreational cyclists are missing. The aim of the present study was to evaluate accuracy and viability of constant power threshold, which is the highest power output constantly maintainable over time, for estimating maximal lactate steady state in recreational athletes.

Methods

A total of 25 recreational athletes participated in the study of whom 22 (11 female, 11 male) conducted all constant load time trials required for determining constant power threshold 30 min and 45 min, which is the highest power output constantly maintainable over 30 min and 45 min, respectively. Maximal lactate steady state was assessed subsequently from blood samples taken every 5 min during the time trials.

Results

Constant power threshold over 45 min (175.5 ± 49.6 W) almost matched power output at maximal lactate steady state (176.4 ± 50.5 W), whereas constant power threshold over 30 min (181.4 ± 51.4 W) was marginally higher (P = 0.007, d = 0.74). Interrelations between maximal lactate steady state and constant power threshold 30 min and constant power threshold 45 min were very close (R2 = 0.99, SEE = 8.9 W, Percentage SEE (%SEE) = 5.1%, P < 0.001 and R2 = 0.99, SEE = 10.0 W, %SEE = 5.7%, P < 0.001, respectively).

Conclusions

Determination of constant power threshold is a straining but viable and precise alternative for recreational cyclists to estimate power output at maximal lactate steady state and thus maximal sustainable oxidative metabolic rate.

A critical review of critical power

The elegant concept of a hyperbolic relationship between power, velocity, or torque and time to exhaustion has rightfully captivated the imagination and inspired extensive research for over half a century. Theoretically, the relationship's asymptote along the time axis (critical power, velocity, or torque) indicates the exercise intensity that could be maintained for extended durations, or the "heavy-severe exercise boundary". Much more than a critical mass of the extensive accumulated evidence, however, has persistently shown the determined intensity of critical power and its variants as being too high to maintain for extended periods. The extensive scientific research devoted to the topic has almost exclusively centered around its relationships with various endurance parameters and performances, as well as the identification of procedural problems and how to mitigate them. The prevalent underlying premise has been that the observed discrepancies are mainly due to experimental 'noise' and procedural inconsistencies. Consequently, little or no effort has been directed at other perspectives such as trying to elucidate physiological reasons that possibly underly and account for those discrepancies. This review, therefore, will attempt to offer a new such perspective and point out the discrepancies' likely root causes.

Three weeks of a home-based "sleep low-train low" intervention improves functional threshold power in trained cyclists: A feasibility study

Background

“Sleep Low-Train Low” is a training-nutrition strategy intended to purposefully reduce muscle glycogen availability around specific exercise sessions, potentially amplifying the training stimulus via augmented cell signalling. The aim of this study was to assess the feasibility of a 3-week home-based “sleep low-train low” programme and its effects on cycling performance in trained athletes.

Methods

Fifty-five trained athletes (Functional Threshold Power [FTP]: 258 ± 52W) completed a home-based cycling training program consisting of evening high-intensity training (6 × 5 min at 105% FTP), followed by low-intensity training (1 hr at 75% FTP) the next morning, three times weekly for three consecutive weeks. Participant’s daily carbohydrate (CHO) intake (6 g·kg^-1·d^-1) was matched but timed differently to manipulate CHO availability around exercise: no CHO consumption post- HIT until post-LIT sessions [Sleep Low (SL), n = 28] or CHO consumption evenly distributed throughout the day [Control (CON), n = 27]. Sessions were monitored remotely via power data uploaded to an online training platform, with performance tests conducted pre-, post-intervention.

Results

LIT exercise intensity reduced by 3% across week 1, 3 and 2% in week 2 (P < 0.01) with elevated RPE in SL vs. CON (P < 0.01). SL enhanced FTP by +5.5% vs. +1.2% in CON (P < 0.01). Comparable increases in 5-min peak power output (PPO) were observed between groups (P < 0.01) with +2.3% and +2.7% in SL and CON, respectively (P = 0.77). SL 1-min PPO was unchanged (+0.8%) whilst CON improved by +3.9% (P = 0.0144).

Conclusion

Despite reduced relative training intensity, our data demonstrate short-term “sleep low-train low” intervention improves FTP compared with typically “normal” CHO availability during exercise. Importantly, training was completed unsupervised at home (during the COVID-19 pandemic), thus demonstrating the feasibility of completing a “sleep low-train low” protocol under non-laboratory conditions.

Functional Threshold Power Estimated from a 20-minute Time-trial Test is Warm-up-dependent

This study investigated the influence of different warm-up protocols on functional threshold power. Twenty-one trained cyclists (˙VO₂max=60.2±6.8 ml·kg^-1·min^-1) performed an incremental test and four 20-min time trials preceded by different warm-up protocols. Two warm-up protocols lasted 45 min, with a 5-min time trial performed either 15 min (Traditional) or 25 min (Reverse) before the 20-min time trial. The other two warm-up protocols lasted 25 min (High Revolutions-per minute) and 10 min (Self-selected), including three fast accelerations and self-selected intensity, respectively. The power outputs achieved during the 20-min time trial preceded by the Traditional and Reverse warm-up protocols were significantly lower than the High Revolutions-per-minute and Self-selected protocols (256±30; 257±30; 270±30; 270±30 W, respectively). Participants chose a conservative pacing strategy at the onset (negative) for the Traditional and Reverse but implemented a fast-start strategy (U-shaped) for the High revolutions-per-minute and Self-selected warm-up protocols. In conclusion, 20-min time-trial performance and pacing are affected by different warm-ups. Consequently, the resultant functional threshold power may be different depending on whether the original protocol with a 5-min time trial is followed or not.

Functional Threshold Power Is Not Equivalent to Lactate Parameters in Trained Cyclists

ABSTRACT

Jeffries, O, Simmons, R, Patterson, SD, and Waldron, M. Functional threshold power is not equivalent to lactate parameters in trained cyclists. J Strength Cond Res 35(10): 2790-2794, 2021-Functional threshold power (FTP) is derived from a maximal self-paced 20-minute cycling time trial whereby the average power output is scaled by 95%. However, the physiological basis of the FTP concept is unclear. Therefore, we evaluated the relationship of FTP with a range of laboratory-based blood lactate parameters derived from a submaximal threshold test. Twenty competitive male cyclists completed a maximal 20-minute time trial and an incremental exercise test to establish a range of blood lactate parameters. Functional threshold power (266 ± 42 W) was strongly correlated (r = 0.88, p < 0.001) with the power output associated with a fixed blood lactate concentration 4.0 mmol·L-1 (LT4.0) (268 ± 30 W) and not significantly different (p > 0.05). While mean bias was 2.9 ± 24.6 W, there were large limits of agreement (LOA) between FTP and LT4.0 (-45 to 51 W). All other lactate parameters, lactate threshold (LT) (236 ± 32 W), individual anaerobic threshold (244 ± 33 W), and LT thresholds determined using the Dmax method (221 ± 25 W) and modified Dmax method (238 ± 32 W) were significantly different from FTP (p < 0.05). While FTP strongly correlated with LT4.0, the large LOA refutes any equivalence as a measure with physiological basis. Therefore, we would encourage athletes and coaches to use alternative field-based methods to predict cycling performance.

Effects of a low-carbohydrate diet on body composition and performance in road cycling: a randomized, controlled trial

Introduction

Low-carbohydrate diets are frequently used to improve performance in endurance sports, often with contradictory results. This study aimed to assess whether a low-carbohydrate diet can outperform an isocaloric conventional diet for improving body composition and performance in a sample of twenty-six trained male road cyclists (previous experience in cyclosportive events, 7.6 ± 4.4 years; age, 26.9 ± 4.9 years; weekly training volume, 7.8 ± 2.9 hours; height, 176 ± 7 centimeters; body fat percentage, 9.7 ± 0.8 %; weight, 65.3 ± 2.3 kg). Detraining and pretreatment periods in which nutrition and training were standardized were followed by an eight-week long intervention in which cyclists consumed either a low-carbohydrate diet (15 % of calories from carbohydrates) or a conventional endurance sports diet while maintaining the same training volumes and intensities. Body composition was assessed through electrical impedance, and performance was evaluated through a twenty-minute time trial performed on a smart bike trainer. The results revealed an overall improvement over time in absolute and relative power, body mass, and body fat for both groups, whilst the improvement in absolute power was comparable. The improvements seen in relative power (p = 0.042), body mass (p = 0.006), and body fat (p = 0.01) were significantly higher in the low-carbohydrate group. We concluded that eight weeks of a low-carbohydrate diet significantly reduced body weight and body fat percentage, and improved 20-minute relative power values in a sample of road cyclists when compared to an isocaloric conventional diet.

What is known about the FTP20 test related to cycling? A scoping review

Functional Threshold Power (FTP) in cycling is increasingly used in exercise prescription, particularly with the rise in use of home trainers and virtual exercise platforms. FTP testing does not require biological sampling and is considered a more practical test than others. This scoping review investigated what is known about the 20-minute FTP (FTP²⁰) test. A three-step search strategy was used to identify studies in relevant databases (PubMed, CINAHL, SportDiscus, Google Scholar, Web of Science) and grey literature. Data were extracted and common themes identified which allowed for descriptive analysis and thematic summary. Fifteen studies were included. The primary focus fitted broadly into four themes: reliability, association with other physiological markers, other power-related concepts and performance prediction. The FTP²⁰ test was reported as a reliable test. Studies investigating the relationship of FTP²⁰ with other physiological markers and power-related concepts reported large limits of agreement suggesting parameters cannot be used interchangeably. Some findings indicate that FTP²⁰ may be useful in performance prediction. The majority of studies involved trained male cyclists. Overall, existing literature on the FTP²⁰ test is limited. Further investigation is needed to provide physiological justification for FTP²⁰ and inform use in exercise prescription in a range of populations.

Variability in Submaximal Self-Paced Exercise Bouts of Different Intensity and Duration

PURPOSE

Rating of perceived exertion (RPE) as a training-intensity prescription has been extensively used by athletes and coaches. However, individual variability in the physiological response to exercise prescribed using RPE has not been investigated.

METHODS

Twenty well-trained competitive cyclists (male = 18, female = 2, maximum oxygen consumption =55.07 [11.06] mL·kg-1·min-1) completed 3 exercise trials each consisting of 9 randomized self-paced exercise bouts of either 1, 4, or 8 minutes at RPEs of 9, 13, and 17. Within-athlete variability (WAV) and between-athletes variability (BAV) in power and physiological responses were calculated using the coefficient of variation. Total variability was calculated as the ratio of WAV to BAV.

RESULTS

Increased RPEs were associated with higher power, heart rate, work, volume of expired oxygen (VO2), volume of expired carbon dioxide (VCO2), minute ventilation (VE), deoxyhemoglobin (ΔHHb) (P < .001), and lower tissue saturation index (ΔTSI%) and ΔO2Hb (oxyhaemoglobin; P < .001). At an RPE of 9, shorter durations resulted in lower VO2 (P < .05) and decreased ΔTSI%, and the ΔHHb increased as the duration increased (P < .05). At an RPE of 13, shorter durations resulted in lower VO2, VE, and percentage of maximum oxygen consumption (P < .001), as well as higher power, heart rate, ΔHHb (P < .001), and ΔTSI% (P < .05). At an RPE of 17, power (P < .001) and ΔTSI% (P < .05) increased as duration decreased. As intensity and duration increased, WAV and BAV in power, work, heart rate, VO2, VCO2, and VE decreased, and WAV and BAV in near-infrared spectroscopy increased.

CONCLUSIONS

Self-paced intensity prescriptions of high effort and long duration result in the greatest consistency on both a within- and between-athletes basis.

The Importance of 'Durability' in the Physiological Profiling of Endurance Athletes

Profiling physiological attributes is an important role for applied exercise physiologists working with endurance athletes. These attributes are typically assessed in well-rested athletes. However, as has been demonstrated in the literature and supported by field data presented here, the attributes measured during routine physiological-profiling assessments are not static, but change over time during prolonged exercise. If not accounted for, shifts in these physiological attributes during prolonged exercise have implications for the accuracy of their use in intensity regulation during prolonged training sessions or competitions, quantifying training adaptations, training-load programming and monitoring, and the prediction of exercise performance. In this review, we argue that current models used in the routine physiological profiling of endurance athletes do not account for these shifts. Therefore, applied exercise physiologists working with endurance athletes would benefit from development of physiological-profiling models that account for shifts in physiological-profiling variables during prolonged exercise and quantify the 'durability' of individual athletes, here defined as the time of onset and magnitude of deterioration in physiological-profiling characteristics over time during prolonged exercise. We propose directions for future research and applied practice that may enable better understanding of athlete durability.

Novel evidence on the effect of tramadol on self-paced high-intensity cycling

The use of tramadol is a controversial topic in cycling. In order to provide novel evidence on this issue, we tested 29 participants in a pre-loaded cycling time trial (TT; a 20-min TT preceded by 40-min of constant work-rate at 60% of the VO_2max) after ingesting 100 mg of tramadol (vs placebo and paracetamol (1.5 g)). Participants performed the Psychomotor Vigilance Task (PVT) at rest and a Sustained Attention to Response Task (SART) during the 60 min of exercise. Oscillatory electroencephalography (EEG) activity was measured throughout the exercise. The results showed higher mean power output during the 20-min TT in the tramadol vs. paracetamol condition, but no reliable difference was reported between tramadol and placebo (nor paracetamol vs. placebo). Tramadol resulted in faster responses in the PVT and higher heart rate during exercise. The main effect of substance was reliable in the SART during the 40-min constant workload (no during the 20-min TT), with slower reaction time, but better accuracy for tramadol and paracetamol than for placebo. This study supports the increased behavioural and neural efficiency at rest for tramadol but not the proposed ergogenic or cognitive (harmful) effect of tramadol (vs. placebo) during self-paced high-intensity cycling.

Relationship Between the Critical Power Test and a 20-min Functional Threshold Power Test in Cycling

To investigate the agreement between critical power (CP) and functional threshold power (FTP), 17 trained cyclists and triathletes (mean ± SD: age 31 ± 9 years, body mass 80 ± 10 kg, maximal aerobic power 350 ± 56 W, peak oxygen consumption 51 ± 10 mL⋅min^-1⋅kg^-1) performed a maximal incremental ramp test, a single-visit CP test and a 20-min time trial (TT) test in randomized order on three different days. CP was determined using a time-trial (TT) protocol of three durations (12, 7, and 3 min) interspersed by 30 min passive rest. FTP was calculated as 95% of 20-min mean power achieved during the TT. Differences between means were examined using magnitude-based inferences and a paired-samples t-test. Effect sizes are reported as Cohen's d. Agreement between CP and FTP was assessed using the 95% limits of agreement (LoA) method and Pearson correlation coefficient. There was a 91.7% probability that CP (256 ± 50 W) was higher than FTP (249 ± 44 W). Indeed, CP was significantly higher compared to FTP (P = 0.041) which was associated with a trivial effect size (d = 0.04). The mean bias between CP and FTP was 7 ± 13 W and LoA were -19 to 33 W. Even though strong correlations exist between CP and FTP (r = 0.969; P < 0.001), the chance of meaningful differences in terms of performance (1% smallest worthwhile change), were greater than 90%. With relatively large ranges for LoA between variables, these values generally should not be used interchangeably. Caution should consequently be exercised when choosing between FTP and CP for the purposes of performance analysis.

Estimating Functional Threshold Power in Endurance Running from Shorter Time Trials Using a 6-Axis Inertial Measurement Sensor

Wearable technology has allowed for the real-time assessment of mechanical work employed in several sporting activities. Through novel power metrics, Functional Threshold Power have shown a reliable indicator of training intensities. This study aims to determine the relationship between mean power output (MPO) values obtained during three submaximal running time trials (i.e., 10 min, 20 min, and 30 min) and the functional threshold power (FTP). Twenty-two recreationally trained male endurance runners completed four submaximal running time trials of 10, 20, 30, and 60 min, trying to cover the longest possible distance on a motorized treadmill. Absolute MPO (W), normalized MPO (W/kg) and standard deviation (SD) were calculated for each time trial with a power meter device attached to the shoelaces. All simplified FTP trials analyzed (i.e., FTP10, FTP20, and FTP30) showed a significant association with the calculated FTP (p < 0.001) for both MPO and normalized MPO, whereas stronger correlations were found with longer time trials. Individual correction factors (ICF% = FTP60/FTPn) of ~90% for FTP10, ~94% for FTP20, and ~96% for FTP30 were obtained. The present study procures important practical applications for coaches and athletes as it provides a more accurate estimation of FTP in endurance running through less fatiguing, reproducible tests.

Cycling Performance and Training Load: Effects of Intensity and Duration

PURPOSE

To examine the effect of cycling exercise intensity and duration on subsequent performance and to compare the resulting acute performance decrement (APD) with total work done (TWD) and corresponding training-load (TL) metrics.

METHODS

A total of 14 male cyclists performed a 5-minute time trial (TT) as a baseline and after 4 initial exercise bouts of varying exercise intensity and duration. The initial exercise bouts were performed in a random order and consisted of a 5- and a 20-minute TT and a 20- and a 40-minute submaximal ride. The resulting APD was calculated as the percentage change in 5-minute TT from baseline, and this was compared with the TWD and TL metrics for the corresponding initial exercise bout.

RESULTS

Average power output was different for each of the 4 initial exercise bouts (ηp2=.971; P < .001), and all bouts resulted in an APD. But APD was only different when comparing maximal with submaximal bouts (ηp2=.862; P < .001). The APD contradicted TWD and TL metrics and was not different when comparing 5- and 20-minute maximal TTs or the 20- and 40-minute submaximal bouts. In contrast, TL metrics were different for all training sessions (ηp2=.970; P < .001).

CONCLUSION

An APD is found after initial exercise bouts consisting of 5- and 20-minute TTs and after 20- and 40-minute of submaximal exercise that is not consistent with the corresponding values for TWD or TL. This discrepancy highlights important shortcomings when using TWD and TL to compare exercise bouts of different intensity and duration.

The Application of Critical Power, the Work Capacity above Critical Power (W'), and its Reconstitution: A Narrative Review of Current Evidence and Implications for Cycling Training Prescription

The two-parameter critical power (CP) model is a robust mathematical interpretation of the power–duration relationship, with CP being the rate associated with the maximal aerobic steady state, and W′ the fixed amount of tolerable work above CP available without any recovery. The aim of this narrative review is to describe the CP concept and the methodologies used to assess it, and to summarize the research applying it to intermittent cycle training techniques. CP and W′ are traditionally assessed using a number of constant work rate cycling tests spread over several days. Alternatively, both the 3-min all-out and ramp all-out protocols provide valid measurements of CP and W′ from a single test, thereby enhancing their suitability to athletes and likely reducing errors associated with the assumptions of the CP model. As CP represents the physiological landmark that is the boundary between heavy and severe intensity domains, it presents several advantages over the de facto arbitrarily defined functional threshold power as the basis for cycle training prescription at intensities up to CP. For intensities above CP, precise prescription is not possible based solely on aerobic measures; however, the addition of the W′ parameter does facilitate the prescription of individualized training intensities and durations within the severe intensity domain. Modelling of W′ reconstitution extends this application, although more research is needed to identify the individual parameters that govern W′ reconstitution rates and their kinetics.

Warming Up Before a 20-Minute Endurance Effort: Is It Really Worth It?

PURPOSE

To analyze the effects of different warm-up protocols on endurance-cycling performance from an integrative perspective (by assessing perceptual, neuromuscular, physiological, and metabolic variables).

METHODS

Following a randomized crossover design, 15 male cyclists (35 [9] y; peak oxygen uptake [VO2peak] 66.4 [6.8] mL·kg-1·min-1) performed a 20-minute cycling time trial (TT) preceded by no warm-up, a standard warm-up (10 min at 60% of VO2peak), or a warm-up that was intended to induce potentiation postactivation (PAP warm-up; 5 min at 60% of VO2peak followed by three 10-s all-out sprints). Study outcomes were jumping ability and heart-rate variability (both assessed at baseline and before the TT), TT performance (mean power output), and perceptual (rating of perceived exertion) and physiological (oxygen uptake, muscle oxygenation, heart-rate variability, blood lactate, and thigh skin temperature) responses during and after the TT.

RESULTS

Both standard and PAP warm-up (9.7% [4.7%] and 12.9% [6.5%], respectively, P < .001), but not no warm-up (-0.9% [4.8%], P = .074), increased jumping ability and decreased heart-rate variability (-7.9% [14.2%], P = .027; -20.3% [24.7%], P = .006; and -1.7% [10.5%], P = .366). Participants started the TT (minutes 0-3) at a higher power output and oxygen uptake after PAP warm-up compared with the other 2 protocols (P < .05), but no between-conditions differences were found overall for the remainder of outcomes (P > .05).

CONCLUSIONS

Compared with no warm-up, warming up enhanced jumping performance and sympathetic modulation before the TT, and the inclusion of brief sprints resulted in a higher initial power output during the TT. However, no warm-up benefits were found for overall TT performance or for perceptual or physiological responses during the TT.

Power Assessment in Road Cycling: A Narrative Review

Nowadays, the evaluation of physiological characteristics and training load quantification in road cycling is frequently performed through power meter data analyses, but the scientific evidence behind this tool is scarce and often contradictory. The aim of this paper is to review the literature related to power profiling, functional threshold testing, and performance assessment based on power meter data. A literature search was conducted following preferred reporting items for review statement (PRISMA) on the topic of {“cyclist” OR “cycling” AND “functional threshold” OR “power meter”}. The reviewed evidence provided important insights regarding power meter-based training: (a) functional threshold testing is closely related to laboratory markers of steady state; (b) the 20-min protocol represents the most researched option for functional threshold testing, although shorter durations may be used if verified on an individual basis; (c) power profiling obtained through the recovery of recorded power outputs allows the categorization and assessment of the cyclist’s fitness level; and (d) power meters represent an alternative to laboratory tests for the assessment of the relationship between power output and cadence. This review elucidates the increasing amount of studies related to power profiling, functional threshold testing, and performance assessment based on power meter data, highlighting the opportunity for the expanding knowledge that power meters have brought in the road cycling field.

Probiotic supplementation increases carbohydrate metabolism in trained male cyclists: a randomized, double-blind, placebo-controlled crossover trial

We hypothesized that probiotic supplementation (PRO) increases the absorption and oxidation of orally ingested maltodextrin during 2 h endurance cycling, thereby sparing muscle glycogen for a subsequent time trial (simulating a road race). Measurements were made of lipid and carbohydrate oxidation, plasma metabolites and insulin, gastrointestinal (GI) permeability, and subjective symptoms of discomfort. Seven male cyclists were randomized to PRO (bacterial composition given in methods) or placebo for 4 wk, separated by a 14-day washout period. After each period, cyclists consumed a 10% maltodextrin solution (initial 8 mL/kg bolus and 2 mL/kg every 15 min) while exercising for 2 h at 55% maximal aerobic power output, followed by a 100-kJ time trial. PRO resulted in small increases in peak oxidation rates of the ingested maltodextrin (0.84 ± 0.10 vs. 0.77 ± 0.09 g/min; P = 0.016) and mean total carbohydrate oxidation (2.20 ± 0.25 vs. 1.87 ± 0.39 g/min; P = 0.038), whereas fat oxidation was reduced (0.40 ± 0.11 vs. 0.55 ± 0.10 g/min; P = 0.021). During PRO, small but significant increases were seen in glucose absorption, plasma glucose, and insulin concentration and decreases in nonesterified fatty acid and glycerol. Differences between markers of GI damage and permeability and time-trial performance were not significant (P > 0.05). In contrast to the hypothesis, PRO led to minimal increases in absorption and oxidation of the ingested maltodextrin and small reductions in fat oxidation, whereas having no effect on subsequent time-trial performance.

Is the Functional Threshold Power Interchangeable With the Maximal Lactate Steady State in Trained Cyclists?

PURPOSE

Functional threshold power (FTP), determined as 95% of the average power during a 20-min time trial, is suggested as a practical test for the determination of the maximal lactate steady state (MLSS) in cycling. Therefore, the objective of the present study was to determine the validity of FTP in predicting MLSS.

METHODS

A total of 15 cyclists, 7 classified as trained and 8 as well trained (mean [SD] maximal oxygen uptake 62.3 [6.4] mL·kg-1·min-1, maximal aerobic power 329 [30] W), performed an incremental test to exhaustion, an FTP test, and several constant-load tests to determine the MLSS. The bias ± 95% limits of agreement (LoA), typical error of the estimate (TEE), and Pearson coefficient of correlation (r) were calculated to assess validity.

RESULTS

For the power-output measures, FTP presented a bias ± 95% LoA of 1.4% ± 9.2%, a moderate TEE (4.7%), and nearly perfect correlation (r = .91) with MLSS in all cyclists together. When divided by training level, the bias ± 95% LoA and TEE were higher in the trained group (1.4% ± 11.8% and 6.4%, respectively) than in the well-trained group (1.3% ± 7.4% and 3.0%, respectively). For the heart-rate measurement, FTP presented a bias ± 95% LoA of -1.4% ± 8.2%, TEE of 4.0%, and very large correlation (r = .80) with MLSS.

CONCLUSION

Therefore, trained and well-trained cyclists can use FTP as a noninvasive and practical alternative to estimate MLSS.