ArticlePublisher preview available
To read the full-text of this research, you can request a copy directly from the authors.
Scand J Med Sci Sports. 2023;33:99–100.
|
99
wileyonlinelibrary.com/journal/sms
Received: 20 June 2022
|
Revised: 12 September 2022
|
Accepted: 13 September 2022
DOI: 10.1111/sms.14259
LETTER TO THE EDITOR
Critical power: Evidence- based robustness
Recently, Gorostiaga et al.1 published an article entitled
“Over 55 years of critical power: Fact or artifact?” with the
objective of “generating an evidence- based debate” regard-
ing the validity of the critical power (CP) as a physiolog-
ical gold- standard parameter. The researchers critically
examined the concept of the CP model under four main
arguments; “(1) the inconsistency in experimentally
demonstrating the classical definition of CP, (2) the wide
range of relative intensities at which CP was identified
to occur, (3) the choice of duration of exercise trials used
to assess CP, and (4) inadequate choice of the hyperbolic
function model, despite the power function model, to de-
scribe the relationship between velocity and time.” These
arguments were originally presented using the best race
time performances of the top 10 male and female Spanish
runners who completed 1.5km to 10km distance races in
the same outdoor competitive season (Year 2019). In this
way, the critical speed values (CS, analogous to CP) were
determined using the race times up to 5km (CS1.5– 5km, 1.5,
3, and 5km) and 10 km (CS1.5– 10km, 1.5, 3, 5, and 10km).
In addition, the researchers added the half- marathon
and marathon performance times of other athletes to the
model. However, we have identified some serious limita-
tions with the data on which their conclusions are based.
Our objectives are to point out important limitations and
misconceptions in the original article by Gorostiaga et al.,1
which distorted the models and conclusions, and highlight
the robustness of the CP model as the lowest intensity
(speed) that represents the severe- intensity domain, when
using a correct and standardized methodology.2 Using the
values (time and distance) provided in the article, we re-
calculated the CS and determined the D′ values (fixed and
limited distance capacity above the CS) through the same
model used (distance– time). CS (CS1.5– 5km, 5.45 ± 0.38 m/s
vs. CS1.5– 10km, 5.19 ± 0.39 m/s; p= 0.02) and D′ (CS1.5– 5km,
140.6 ± 60.1m vs. CS1.5– 10km, 272.2 ± 110.2m; p=0.001) val-
ues were significantly different (paired t- test). In fact, the
influence of duration / distance of predictive trials on the
CP/CS parameters has been previously deomonstrated.3
Interestingly, during modeling we noticed that the av-
erage speed of four athletes (TN, MM, CC, and CV) in the
3km race was lower than their average speed in the 5km
race. This is interesting because the hyperbolic relationship
between speed and time dictates that speed should decrease
with increasing distance up to the CS. Yet, in the best perfor-
mance of these athletes, they ran at a faster average speed
in a race with greater distance. In this case, several factors,
such as “pacing,” may have prevented the complete deple-
tion of the D′ above the CS, thus, confounding the CS1.5- 5km
model prediction. In fact, it was not possible to predict the
3 km running performance for these athletes (i.e., TN, MM,
CC, and CV) using CS1.5– 5km parameters. In the 10- km race,
only two athletes (DP and MJ) ran at average speeds above
CS1.5- 5Km, showing that all other athletes were at intensities
below CS, justifying the running time (average, 31.54 min-
utes). The potential overestimation of D′ may explain why
the actual times (Mean ± SD: 1.5 km, 247.5 ± 22.8, 3 km,
533.2 ± 44.0, 5 km, 893.0 ± 67.4, and 10 km, 1892.3 ± 144.6s)
were statistically (t- test, p=0.05– 0.0002) different from the
predicted times (Mean ± SD: 299.2 ± 59.26, 566,0.9 ± 75.1,
652.3 ± 131, and 2215.7 ± 304.9 s, respectively) when
used CS1.5– 10km model. In this sense, the inclusion of ex-
ecution times at intensities slightly below the CS (10km,
half- marathon, and marathon) introduces errors in the
mathematical modeling, which do not represent real
physiological consequences on performance, possibly by
reaching domains of different intensity. In addition, due to
numerous influences during a competitive sporting season
(e.g., time of day, environmental conditions, training status,
and performance level of competing athletes),4,5 it does not
seem correct and valid to use different sporting events for
CS modeling, particularly paced race times.6
There is evidence that the time trial protocol, similar
to the time to exhaustion protocol, is valid for determin-
ing the CP/CS model, as long as it induces exhaustion to
a maximal of ~15 min, aiming both to deplete D′ and to
attain VO2max.7 Indeed, several key parameters of aerobic
fitness (VO2max/VO2peak, blood lactate response to exer-
cise, running economy, and oxygen uptake kinetics) are
also protocol- dependent, that is, data obtained by different
protocols should not be used interchangeably.
Thus, it is important to emphasize that (1) Gorostiaga
et al.1 used severe- intensity race efforts that were per-
formed submaximally in several cases (40% of athletes in
the 3 km race); (2) 80% of the athletes were below the CS in
the 10km race (according to the model with 3 distances);
© 2022 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
... Loss of normal echogenicity and the fibrillar structure were present in more than 90% of the patients. Further, in a recent Delphi study, experts agreed that clinical evaluation and sport-specific tests should be used to support the return to play (RTP) and not imaging [13]. ...
... According to the Doha classification, adductor-related groin pain is defined by a history of pain in the region, adductor tenderness, and pain on resisted adduction testing. This classification has been shown to have excellent interexaminer reliability when the patients presented only one clinical entity but a lower agreement when more than one diagnosis is present [13]. Palpation examination has been found to have a slight to moderate interexaminer reliability while adductor stretch and resisted tests have a moderate-tosubstantial correlation [14]. ...
Article
Full-text available
Adductor-related groin pain is extremely common among athletes, and despite its high prevalence and impact, there is no consensus regarding taxonomy, anatomy, physiopathology, or treatment. We performed a comprehensive literature review and tried to demystify this pathology and its treatment. The Doha agreement classification and its impact are scrutinized as well as the complexity of the proximal adductor longus (AL) insertion and its relationship with the pyramidalis-anterior pubic ligament-AL complex. The stress-shielding and compression theories for the origin of AL tendon pathology are exploited along with how this knowledge translates into injury prevention protocols and surgical techniques. The importance of active rehabilitation protocols and intersegmental control-focused programs is highlighted. The role of an enthesis injection in the treatment algorithm is discussed along with when to perform a tenotomy. The differences between selective and complete tenotomy are highlighted.
Article
Borszcz, FK, de Aguiar, RA, Costa, VP, Denadai, BS, and de Lucas, RD. Agreement between maximal lactate steady state and critical power in different sports: A systematic review and Bayesian's meta-regression. J Strength Cond Res 38(6): e320-e339, 2024-This study aimed to systematically review the literature and perform a meta-regression to determine the level of agreement between maximal lactate steady state (MLSS) and critical power (CP). Considered eligible to include were peer-reviewed and "gray literature" studies in English, Spanish, and Portuguese languages in cyclical exercises. The last search was made on March 24, 2022, on PubMed, ScienceDirect, SciELO, and Google Scholar. The study's quality was evaluated using 4 criteria adapted from the COSMIN tool. The level of agreement was examined by 2 separate meta-regressions modeled under Bayesian's methods, the first for the mean differences and the second for the SD of differences. The searches yielded 455 studies, of which 36 studies were included. Quality scale revealed detailed methods and small samples used and that some studies lacked inclusion/exclusion criteria reporting. For MLSS and CP comparison, likely (i.e., coefficients with high probabilities) covariates that change the mean difference were the MLSS time frame and delta criteria of blood lactate concentration, MLSS number and duration of pauses, CP longest predictive trial duration, CP type of predictive trials, CP model fitting parameters, and exercise modality. Covariates for SD of the differences were the subject's maximal oxygen uptake, CP's longest predictive trial duration, and exercise modality. Traditional MLSS protocol and CP from 2-to 15-minute trials do not reflect equivalent exercise intensity levels; the proximity between MLSS and CP measures can differ depending on test design, and both MLSS and CP have inherent limitations. Therefore, comparisons between them should always consider these aspects.
Article
Full-text available
The power–duration relationship describes the time to exhaustion for exercise at different intensities. It is believed to be a “fundamental bioenergetic property of living systems” that this relationship is hyperbolic. Indeed, the hyperbolic (a.k.a. critical-power) model which formalises this belief is the dominant tool for describing and predicting high-intensity exercise performance, e.g. in cycling, running, rowing or swimming. However, the hyperbolic model is now the focus of a heated debate in the literature because it unrealistically represents efforts that are short (< 2 min) or long (> 15 min). We contribute to this debate by demonstrating that the power–duration relationship is more adequately represented by an alternative, power-law model. In particular, we show that the often-observed good fit of the hyperbolic model between 2 and 15 min should not be taken as proof that the power–duration relationship is hyperbolic. Rather, in this range, a hyperbolic function just happens to approximate a power law fairly well. We also prove mathematical results which suggest that the power-law model is a safer tool for pace selection than the hyperbolic model and that the former more naturally models fatigue than the latter.
Article
Full-text available
This report aims to generate an evidence-based debate of the Critical Power (CP), or its analogous Critical Speed (CS), concept. Race times of top Spanish runners were utilized to calculate CS based on three (1500-m to 5000-m; CS1.5-5km ) and four (1500-m to 10000-m; CS1.5-10km ) distance performances. Male running world records from 1000 to 5000-m (CS1-5km ), 1000 to 10000-m (CS1-10km ), 1000-m to half marathon (CS1km-half marathon ), and 1000-m to marathon (CS1km-marathon ) distance races were also utilized for CS calculations. CS1.5-5km (19.62 km·h-1 ) and CS1.5-10km (18.68 km·h-1 ) were different (P<0.01), but both approached the average race speed of the longest distance chosen in the model, and were remarkably homogeneous among subjects (97±1% and 98±1%, respectively). Similar results were obtained using the world records. CS values progressively declined, until reaching a CS1km-marathon value of 20.77 km·h-1 (10% lower than CS1-5km ). Each CS value approached the average speed of the longest distance chosen in the model (96.4-99.8%). A power function better fitted the speed-time relationship compared to the standardized hyperbolic function. However, the horizontal asymptote of a power function is zero. This better approaches the classical definition of CP: the power output that can be maintained almost indefinitely without exhaustion. Beyond any sophisticated mathematical calculation, CS corresponds to 95-99% of the average speed of the longest distance chosen as an exercise trial. CP could be considered a mathematical artifact rather than an important endurance performance marker. In such a case, the consideration of CP as a physiological "gold-standard" should be re-evaluated.
Article
Full-text available
For high-intensity muscular exercise, the time-to-exhaustion (t) increases as a predictable and hyperbolic function of decreasing power (P) or velocity (V). This relationship is highly conserved across diverse species and different modes of exercise and is well described by two parameters: the 'critical power' (CP or CV), which is the asymptote for power or velocity, and the curvature constant (W') of the relationship such that t = W'/(P-CP). CP represents the highest rate of energy transduction (oxidative ATP production, V? O2) that can be sustained without continuously drawing on the energy store W' (composed in part of anaerobic energy sources and expressed in kilojoules). The limit of tolerance (time t) occurs when W' is depleted. The CP concept constitutes a practical framework in which to explore mechanisms of fatigue and help resolve crucial questions regarding the plasticity of exercise performance and muscular systems physiology. This brief review presents the practical and theoretical foundations for the CP concept, explores rigorous alternative mathematical approaches, and highlights exciting new evidence regarding its mechanistic bases and its broad applicability to human athletic performance.
Article
Full-text available
Introduction The characterization of the hyperbolic power-time (P-tlim) relationship using a two-parameter model implies that exercise tolerance above the asymptote (Critical Power; CP), i.e. within the severe intensity domain, is determined by the curvature (W’) of the relationship. Purposes The purposes of this study were (1) to test whether the amount of work above CP (W>CP) remains constant for varied work rate experiments of high volatility change and (2) to ascertain whether W’ determines exercise tolerance within the severe intensity domain. Methods Following estimation of CP (208 ± 19 W) andW’ (21.4 ± 4.2 kJ), 14 male participants (age: 26 ± 3; peak V_ O2: 3708 ± 389 ml.min-1) performed two experimental trials where the work rate was initially set to exhaust 70% ofW’ in 3 (‘THREE’) or 10 minutes (‘TEN’) before being subsequently dropped to CP plus 10 W. Results W>CP for TEN (104 ± 22%W’) andW’ were not significantly different (P>0.05) but lower than W>CP for THREE (119 ± 17%W’, P<0.05). For both THREE (r = 0.71, P<0.01) and TEN (r = 0.64, P<0.01), a significant bivariate correlation was found betweenW’ and tlim. Conclusion W>CP and tlim can be greater than predicted by the P-tlim relationship when a decrement in the work rate of high-volatility is applied. Exercise tolerance can be enhanced through a change in work rate within the severe intensity domain.W>CP is not constant.
Article
Full-text available
This study aimed at assessing the sensitivity of both maximal lactate steady state (MLSS) and critical power (CP) in populations of different aerobic training status to ascertain whether CP is as sensitive as MLSS to a change in aerobic fitness. Seven untrained subjects (UT) (maximal oxygen uptake = 37.4 ± 6.5 mL·kg–1·min–1) and 7 endurance cyclists (T) (maximal oxygen uptake = 62.4 ± 5.2 mL·kg–1·min–1) performed an incremental test for maximal oxygen uptake estimation and several constant work rate tests for MLSS and CP determination. MLSS, whether expressed in mL·kg–1·min–1 (T: 51.8 ± 5.7 vs. UT: 29.0 ± 6.1) or % maximal oxygen uptake (T: 83.1 ± 6.8 vs. UT: 77.1 ± 4.5), was significantly higher in the T group. CP expressed in mL·kg–1·min–1 (T: 56.8 ± 5.1 vs. UT: 33.1 ± 6.3) was significantly higher in the T group as well but no difference was found when expressed in % maximal oxygen uptake (T: 91.1 ± 4.8 vs. UT: 88.3 ± 3.6). Whether expressed in absolute or relative values, MLSS is sensitive to aerobic training status and a good measure of aerobic endurance. Conversely, the improvement in CP with years of training is proportional to those of maximal oxygen uptake. Thus, CP might be less sensitive than MLSS for depicting an enhancement in aerobic fitness.
Article
Full-text available
For high-intensity muscular exercise, the time-to-exhaustion (t) increases as a predictable and hyperbolic function of decreasing power (P) or velocity (V ). This relationship is highly conserved across diverse species and different modes of exercise and is well described by two parameters: the "critical power" (CP or CV), which is the asymptote for power or velocity, and the curvature constant (W') of the relationship such that t = W'/(P - CP). CP represents the highest rate of energy transduction (oxidative ATP production, V˙O2) that can be sustained without continuously drawing on the energy store W' (composed in part of anaerobic energy sources and expressed in kilojoules). The limit of tolerance (time t) occurs when W' is depleted. The CP concept constitutes a practical framework in which to explore mechanisms of fatigue and help resolve crucial questions regarding the plasticity of exercise performance and muscular systems physiology. This brief review presents the practical and theoretical foundations for the CP concept, explores rigorous alternative mathematical approaches, and highlights exciting new evidence regarding its mechanistic bases and its broad applicability to human athletic performance.
Article
Full-text available
The linear relationship between work accomplished (W(lim)) and time to exhaustion (t(lim)) can be described by the equation: W(lim) = a + CP x t(lim). Critical power (CP) is the slope of this line and is thought to represent a maximum rate of ATP synthesis without exhaustion, presumably an inherent characteristic of the aerobic energy system. The present investigation determined whether the choice of predictive tests would elicit significant differences in the estimated CP. Ten female physical education students completed, in random order and on consecutive days, five all-out predictive tests at preselected constant-power outputs. Predictive tests were performed on an electrically-braked cycle ergometer and power loadings were individually chosen so as to induce fatigue within approximately 1-10 mins. CP was derived by fitting the linear W(lim)-t(lim) regression and calculated three ways: 1) using the first, third and fifth W(lim)-t(lim) coordinates (I135), 2) using coordinates from the three highest power outputs (I123; mean t(lim) = 68-193 s) and 3) using coordinates from the lowest power outputs (I345; mean t(lim) = 193-485 s). Repeated measures ANOVA revealed that CPI123 (201.0+/-37.9W) > CPI135 (176.1+/-27.6W) > CPI345 (164.0+/-22.8W) (P<0.05). When the three sets of data were used to fit the hyperbolic Power-t(lim) regression, statistically significant differences between each CP were also found (P<0.05). The shorter the predictive trials, the greater the slope of the W(lim)-t(lim) regression; possibly because of the greater influence of 'aerobic inertia' on these trials. This may explain why CP has failed to represent a maximal, sustainable work rate. The present findings suggest that if CP is to represent the highest power output that an individual can maintain "for a very long time without fatigue" then CP should be calculated over a range of predictive tests in which the influence of aerobic inertia is minimised.
Article
Whether the transition in fatigue processes between "low-intensity" and "high-intensity" contractions occurs gradually, as the torque requirements are increased, or whether this transition occurs more suddenly at some identifiable "threshold", is not known. We hypothesized that the critical torque (CT; the asymptote of the torque-duration relationship) would demarcate distinct profiles of central and peripheral fatigue during intermittent isometric quadriceps contractions (3-s contraction, 2-s rest). Nine healthy men performed seven experimental trials to task failure or for up to 60 min, with maximal voluntary contractions (MVCs) performed at the end of each minute. The first five trials were performed to determine CT [~35-55% MVC, denoted severe 1 (S1) to severe 5 (S5) in ascending order], while the remaining two trials were performed 10 and 20% below the CT (denoted CT-10% and CT-20%). Dynamometer torque and the electromyogram of the right vastus lateralis were sampled continuously. Peripheral and central fatigue was determined from the fall in potentiated doublet torque and voluntary activation, respectively. Above CT, contractions progressed to task failure in ~3-18 min, at which point the MVC did not differ from the target torque (S1 target, 88.7 ± 4.3 N·m vs. MVC, 89.3 ± 8.8 N·m, P = 0.94). The potentiated doublet fell significantly in all trials, and voluntary activation was reduced in trials S1-S3, but not trials S4 and S5. Below CT, contractions could be sustained for 60 min on 17 of 18 occasions. Both central and peripheral fatigue developed, but there was a substantial reserve in MVC torque at the end of the task. The rate of global and peripheral fatigue development was four to five times greater during S1 than during CT-10% (change in MVC/change in time S1 vs. CT-10%: -7.2 ± 1.4 vs. -1.5 ± 0.4 N·m·min(-1)). These results demonstrate that CT represents a critical threshold for neuromuscular fatigue development.
Article
Chronobiology is the science concerned with investigations of time-dependent changes in physiological variables. Circadian rhythms refer to variations that recur every 24 hours. Many physiological circadian rhythms at rest are endogenously controlled, and persist when an individual is isolated from environmental fluctuations. Unlike physiological variables, human performance cannot be monitored continuously in order to describe circadian rhythmicity. Experimental studies of the effect of circadian rhythms on performance need to be carefully designed in order to control for serial fatigue effects and to minimise disturbances in sleep. The detection of rhythmicity in performance variables is also highly influenced by the degree of test-retest repeatability of the measuring equipment. The majority of components of sports performance, e.g. flexibility, muscle strength, short term high power output, vary with time of day in a sinusoidal manner and peak in the early evening close to the daily maximum in body temperature. Psychological tests of short term memory, heart rate-based tests of physical fitness, and prolonged submaximal exercise performance carried out in hot conditions show peak times in the morning. Heart rate-based tests of work capacity appear to peak in the morning because the heart rate responses to exercise are minimal at this time of day. Post-lunch declines are evident with performance variables such as muscle strength, especially if measured frequently enough and sequentially within a 24-hour period to cause fatigue in individuals. More research work is needed to ascertain whether performance in tasks demanding fine motor control varies with time of day. Metabolic and respiratory rhythms are flattened when exercise becomes strenuous whilst the body temperature rhythm persists during maximal exercise. Higher work-rates are selected spontaneously in the early evening. At present, it is not known whether time of day influences the responses of a set training regimen (one in which the training stimulus does not vary with time of day) for endurance, strength, or the learning of motor skills. The normal circadian rhythms can be desynchronised following a flight across several time zones or a transfer to nocturnal work shifts. Although athletes show all the symptoms of ‘jet lag’ (increased fatigue, disturbed sleep and circadian rhythms), more research work is needed to identify the effects of transmeridian travel on the actual performances of elite sports competitors. Such investigations would need to be chronobiological, i.e. monitor performance at several dmes on several post-flight days, and take into account direction of travel, time of day of competition and the various performance components involved in a particular sport. Shiftwork interferes with participation in competitive sport, although there may be greater opportunities for shiftworkers to train in the hours of daylight for individual sports such as cycling and swimming. Studies should be conducted to ascertain whether shiftwork-mediated rhythm disturbances affect sports performance. Individual differences in performance rhythms are small but significant. Circadian rhythms are larger in amplitude in physically fit individuals than sedentary individuals. Athletes over 50 years of age tend to be higher in ‘momingness’, habitually scheduling relatively more training in the morning and selecting relatively higher work-rates during exercise compared with young athletes. These differences should be recognised by practitioners concerned with organising the habitual regimens of athletes.
Effect of aerobic training status on both maximal lactate steady state and critical power
  • CC Greco
  • RAC Caritá
  • J Dekerle
  • BS Denadai
Greco CC, Caritá RAC, Dekerle J, Denadai BS. Effect of aerobic training status on both maximal lactate steady state and critical power. Appl Physiol Nutr Metab. 2012;37(4):736-743.