A 30-Min Rest Protocol Does Not Affect W', Critical Power, and Systemic Response

PURPOSE

This study aimed to assess and compare the systemic response of oxygen uptake kinetics and muscle deoxygenation between a 30-min rest protocol and a multivisit protocol on the parameters of the power-duration relationship (i.e., critical power [CP] and W').

METHODS

Nine endurance-trained triathletes reported to the laboratory on five occasions: a preliminary graded exercise test and a familiarization, a 30-min single-visit protocol (time trials of 10, 5, and 2 min in that order interspersed with 30 min rest), and a multivisit protocol (time trials of 10, 5, and 2 min in randomized order interspersed by >24 h rest). Heart rate (HR) was recorded continuously, respiratory gases were measured breath by breath, and deoxygenation was recorded at 10 Hz using near-infrared spectroscopy (NIRS) during all tests. Blood lactate (BLa-) concentration was measured before all time trials. Maximal HR (HRmax), oxygen uptake (V˙O2) during the first 2 min (V˙O2onset), mean response time, end-exercise V˙O2 (V˙O2peak), V˙O2 amplitude (amplV˙O2), O2 deficit, NIRS τ, amplitude (amplNIRS), and time delay were assessed. To compare the two protocols and to assess the differences in W' and CP, a paired sample t-test was used as well as a two-way ANOVA to assess the differences between trials and/or protocols, including trial-protocol interactions.

RESULTS

No significant differences, and trivial effect sizes, were found for W' and CP between protocols (P = 0.106-0.114, d < 0.01-0.08). Furthermore, no significant differences between protocols were found for all parameters, except for [BLa-]. Significant differences between trials were found for V˙O2ampl, V˙O2onset, NIRS τ, amplNIRS, [BLa-], and HRmax.

CONCLUSION

Results suggest that W' and CP can be determined using the 30-min rest protocol without confounding effects of previous severe exercise compared with the multivisit protocol.

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.

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.

The effects of predictive trials on critical stroke rate and critical swimming speed

BACKGROUND

Critical swimming speed (CSS) and critical stroke rate (CSR) have important practical applications in evaluating endurance capacity and stroke parameters. The CSS and CSR are determined from the linear regression between two or more performance times with the respective predictive distance or "number of stroke cycles," respectively. It is already known that CSS is dependent on the number and duration of the predictive trials chosen, and performance times ranging from 2 to 12 min have been recommended. However, the effects of predictive trials on the CSR have not been reported. It was hypothesized that CSS and CSR determined by different predictive trials lasting 2 to 12 min would elicit similar values. Therefore, the purpose of the present study was to determine the impact of different combinations of predictive trials lasting 2 to 12 min on both CSR and CSS.

METHODS

Thirteen swimmers performed three fixed-distance (200, 400, and 800 m) performances. All possible combinations of CSR and CSS with two (CSR<inf>200-400</inf>/CSS<inf>200-400</inf>, CSR<inf>200-800</inf>/CSS<inf>200-800</inf>, CSR<inf>400-800</inf>/CSS<inf>400-800</inf>) and three (CSR<inf>200-400-800</inf>/CSS<inf>200-400-800</inf>) trials were determined.

RESULTS

No significant differences were found between CSR and CSS determined with different predictive distance tests. In addition, CSR<inf>200-800</inf> and CSS<inf>200-800</inf> showed the lowest coefficient of variation and highest intraclass correlation coefficients with CSR<inf>200-400-800</inf> and CSS<inf>200-400-800</inf>, respectively.

CONCLUSIONS

This study demonstrated that CSR and CSS were not statistically different when determined with different predictive trials located within the recommended durations of 2-12 min. Nevertheless, CSR<inf>200-800</inf> and CSS<inf>200-800</inf> exhibited the best consistency with CSR<inf>200-400-800</inf> and CSS<inf>200-400-800</inf>, respectively.

A model-based estimation of critical torques reduces the experimental effort compared to conventional testing

Purpose

Critical torque (CT) is an important fatigue threshold in exercise physiology and can be used to analyze, predict, or optimize performance. The objective of this work is to reduce the experimental effort when estimating CTs for sustained and intermittent isometric contractions using a model-based approach.

Materials and methods

We employ a phenomenological model of the time course of maximum voluntary isometric contraction (MVIC) torque and compute the highest sustainable torque output by solving an optimization problem. We then show that our results are consistent with the steady states obtained when simulating periodic maximum loading schemes. These simulations correspond to all-out tests, which are used to estimate CTs in practice. Based on these observations, the estimation of CTs can be formulated mathematically as a parameter estimation problem. To minimize the statistical uncertainty of the parameter estimates and consequently of the estimated CTs, we compute optimized testing sessions. This reduces the experimental effort even further.

Results

We estimate CTs of the elbow flexors for sustained isometric contractions to be 28% of baseline MVIC torque and for intermittent isometric contractions consisting of a 3 s contraction followed by 2 s rest to be 41% of baseline MVIC torque. We show that a single optimized testing session is sufficient when using our approach.

Conclusions

Our approach reduces the experimental effort considerably when estimating CTs for sustained and intermittent isometric contractions.

Influence of a 2-km Swim on the Cycling Power-Duration Relationship in Triathletes

Rothschild, J, Sheard, AC, and Crocker, GH. Influence of a 2-km swim on the cycling power-duration relationship in triathletes. J Strength Cond Res XX(X): 000-000, 2020-Triathletes must cycle after swimming, and so, it is important to understand how cycling performance may be affected by prior swimming. Therefore, the purpose of this study was to determine the effects of a 2-km swim at a self-selected race-pace intensity on the cycling power-duration relationship. Eighteen trained triathletes (12 M, 6 F; 37.1 ± 10.6 years, V[Combining Dot Above]O2max 54.8 ± 10.1 ml·kg·min) performed two 3-minute all-out cycling tests (3MTs) on separate days with one 3 MT immediately after a 2-km swim (swim-bike [SB]) and one without prior swimming (bike-only [BO]). The power-duration relationship was expressed as the total work done (TWD) and subdivided into end-test power (EP) and work done above EP. To assess swimming intensity, heart rate (HR) was continuously monitored during the 2-km swim and blood lactate was assessed on completion of the swim. End-swim lactate was 4.2 ± 1.8 mM, and mean swimming HR was 147 ± 18 b·min. The 2-km swim decreased TWD during the 3MT by 6% (BO: 62.8 ± 12.7 kJ; SB: 58.9 ± 13.4 kJ; p = 0.001) though neither EP (BO: 281 ± 65 W; SB: 269 ± 68 W; p = 0.102) nor work done above EP (BO: 12.1 ± 3.8 kJ; SB: 10.5 ± 4.2 kJ; p = 0.096) differed between trials. In conclusion, TWD while cycling decreases after a 2-km race-pace swim. Results from this study suggest that triathletes should determine racing cycling power following a simulated race-pace swim.

Critical speed and finite distance capacity: norms for athletic and non-athletic groups

PURPOSE

Two parameters in particular span both health and performance; critical speed (CS) and finite distance capacity (D'). The purpose of the present study was to: (1) classify performance norms, (2) distinguish athletic from non-athletic individuals using the 3-min all-out test (3MT) for running, and (3) introduce a deterministic model highlighting the relationship between variables of the 3MT.

METHODS

Athletic (n = 43) and non-athletic (n = 25) individuals participated in the study. All participants completed a treadmill graded exercise test (GXT) with verification bout and a 3MT on an outdoor sprinting track.

RESULTS

Meaningful differences between non-athletic and athletic individuals (denoted by mean difference scores, p value and Cohen's d with 95% confidence intervals) were evident for CS (- 0.74 m s^-1, p < 0.001, d = - 1.41 [1.97, - 0.87]), exponential growth time constant ([Formula: see text]; 2.75 s, p < 0.001, d = - 1.29 [- 1.45, - 0.42]), time to maximal speed ([Formula: see text]; - 2.80 s, p < 0.001, d = - 0.98 [- 1.51, - 0.47]), maximal speed ([Formula: see text]; - 1.36 m s^-1, p < 0.001, d = - 1.56 [- 2.13, - 1.01]), gas exchange threshold (GET; - 5.62 ml kg^-1 min^-1, p < 0.001, d = - 0.97 [- 1.50, - 0.45]), distance covered in the first minute (1st min; - 81.69 m, p < 0.001, d = - 1.91 [- 2.52, - 1.33]), distance covered in the second minute (2nd min; - 52.02 m, p < 0.001, d = - 1.71 [- 2.30, - 1.15]) and maximal distance (- 153.78 m, p < 0.001, d = - 1.27 [- 1.82, - 0.74]). The correlation coefficient between key physiological and performance variables are shown in the form of a deterministic model created from the data derived from the 3MT.

CONCLUSIONS

Coaches and clinicians may benefit from the use of normative data to potentially identify exceptional or irregular occurrences in 3MT performances.

Time to exhaustion during cycling is not well predicted by critical power calculations

Three to 5 cycling tests to exhaustion allow prediction of time to exhaustion (TTE) at power output based on calculation of critical power (CP). We aimed to determine the accuracy of CP predictions of TTE at power outputs habitually endured by cyclists. Fourteen endurance-trained male cyclists underwent 4 randomized cycle-ergometer TTE tests at power outputs eliciting (i) mean Wingate anaerobic test (WAnT_mean), (ii) maximal oxygen consumption, (iii) respiratory compensation threshold (VT₂), and (iv) maximal lactate steady state (MLSS). Tests were conducted in duplicate with coefficient of variation of 5%-9%. Power outputs were 710 ± 63 W for WAnT_mean, 366 ± 26 W for maximal oxygen consumption, 302 ± 31 W for VT₂ and 247 ± 20 W for MLSS. Corresponding TTE were 00:29 ± 00:06, 03:23 ± 00:45, 11:29 ± 05:07, and 76:05 ± 13:53 min:s, respectively. Power output associated with CP was only 2% lower than MLSS (242 ± 19 vs. 247 ± 20 W; P < 0.001). The CP predictions overestimated TTE at WAnT_mean (00:24 ± 00:10 mm:ss) and MLSS (04:41 ± 11:47 min:s), underestimated TTE at VT₂ (-04:18 ± 03:20 mm:ss; P < 0.05), and correctly predicted TTE at maximal oxygen consumption. In summary, CP accurately predicts MLSS power output and TTE at maximal oxygen consumption. However, it should not be used to estimate time to exhaustion in trained cyclists at higher or lower power outputs (e.g., sprints and 40-km time trials). Novelty CP calculation enables to predict TTE at any cycling power output. We tested those predictions against measured TTE in a wide range of cycling power outputs. CP appropriately predicted TTE at maximal oxygen consumption intensity but err at higher and lower cycling power outputs.

A survey of mathematical models of human performance using power and energy

The ability to predict the systematic decrease of power during physical exertion gives valuable insights into health, performance, and injury. This review surveys the research of power-based models of fatigue and recovery within the area of human performance. Upon a thorough review of available literature, it is observed that the two-parameter critical power model is most popular due to its simplicity. This two-parameter model is a hyperbolic relationship between power and time with critical power as the power-asymptote and the curvature constant denoted by W′. Critical power (CP) is a theoretical power output that can be sustained indefinitely by an individual, and the curvature constant (W′) represents the amount of work that can be done above CP. Different methods and models have been validated to determine CP and W′, most of which are algebraic manipulations of the two-parameter model. The models yield different CP and W′ estimates for the same data depending on the regression fit and rounding off approximations. These estimates, at the subject level, have an inherent day-to-day variability called intra-individual variability (IIV) associated with them, which is not captured by any of the existing methods. This calls for a need for new methods to arrive at the IIV associated with CP and W′. Furthermore, existing models focus on the expenditure of W′ for efforts above CP and do not model its recovery in the sub-CP domain. Thus, there is a need for methods and models that account for (i) the IIV to measure the effectiveness of individual training prescriptions and (ii) the recovery of W′ to aid human performance optimization.

Changes in the power-duration relationship following prolonged exercise: estimation using conventional and all-out protocols and relationship with muscle glycogen

It is not clear how the parameters of the power-duration relationship [critical power (CP) and W′] are influenced by the performance of prolonged endurance exercise. We used severe-intensity prediction trials (conventional protocol) and the 3-min all-out test (3MT) to measure CP and W′ following 2 h of heavy-intensity cycling exercise and took muscle biopsies to investigate possible relationships to changes in muscle glycogen concentration ([glycogen]). Fourteen participants completed a rested 3MT to establish end-test power (Control-EP) and work done above EP (Control-WEP). Subsequently, on separate days, immediately following 2 h of heavy-intensity exercise, participants completed a 3MT to establish Fatigued-EP and Fatigued-WEP and three severe-intensity prediction trials to the limit of tolerance (Tlim) to establish Fatigued-CP and Fatigued-W′. A muscle biopsy was collected immediately before and after one of the 2-h exercise bouts. Fatigued-CP (256 ± 41 W) and Fatigued-EP (256 ± 52 W), and Fatigued-Wʹ (15.3 ± 5.0 kJ) and Fatigued-WEP (14.6 ± 5.3 kJ), were not different ( P > 0.05) but were ~11% and ~20% lower than Control-EP (287 ± 46 W) and Control-WEP (18.7 ± 4.7 kJ), respectively ( P < 0.05). The change in muscle [glycogen] was not significantly correlated with the changes in either EP ( r = 0.19) or WEP ( r = 0.07). The power-duration relationship is adversely impacted by prolonged endurance exercise. The 3MT provides valid estimates of CP and W′ following 2 h of heavy-intensity exercise, but the changes in these parameters are not primarily determined by changes in muscle [glycogen].

The maximal metabolic steady state: redefining the 'gold standard'

The maximal lactate steady state (MLSS) and the critical power (CP) are two widely used indices of the highest oxidative metabolic rate that can be sustained during continuous exercise and are often considered to be synonymous. However, while perhaps having similarities in principle, methodological differences in the assessment of these parameters typically result in MLSS occurring at a somewhat lower power output or running speed and exercise at CP being sustainable for no more than approximately 20-30 min. This has led to the view that CP overestimates the 'actual' maximal metabolic steady state and that MLSS should be considered the 'gold standard' metric for the evaluation of endurance exercise capacity. In this article we will present evidence consistent with the contrary conclusion: i.e., that (1) as presently defined, MLSS naturally underestimates the actual maximal metabolic steady state; and (2) CP alone represents the boundary between discrete exercise intensity domains within which the dynamic cardiorespiratory and muscle metabolic responses to exercise differ profoundly. While both MLSS and CP may have relevance for athletic training and performance, we urge that the distinction between the two concepts/metrics be better appreciated and that comparisons between MLSS and CP, undertaken in the mistaken belief that they are theoretically synonymous, is discontinued. CP represents the genuine boundary separating exercise in which physiological homeostasis can be maintained from exercise in which it cannot, and should be considered the gold standard when the goal is to determine the maximal metabolic steady state.