Steady-state [Formula: see text] above MLSS: evidence that critical speed better represents maximal metabolic steady state in well-trained runners

Agreement Between Maximal Lactate Steady State and Critical Power in Different Sports: A Systematic Review and Bayesian's Meta-Regression

ABSTRACT

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.

Changes in running economy and attainable maximal oxygen consumption in response to prolonged running: The impact of training status

During prolonged running at moderate-to-high intensity, running economy (RE) deteriorates and attainable maximal oxygen consumption (VO2max) decreases. Whether these changes appear similarly in trained and untrained runners exercising at the same relative intensity is not clear. We recruited 10 trained runners (TR) and 10 active adults (AA), and compared RE and attainable VO2max before and after 1 h of running at 70% of VO2max. Submaximal VO2 increased more (p = 0.019) in AA (0.20 ± 0.13 L min-1) than in TR (0.07 ± 0.05 L min-1). Attainable VO2max decreased in AA (-0.21 ± 0.15 L min-1, p = 0.002), but remained unchanged in TR (-0.05 ± 0.10 L min-1, p = 0.18). Relative intensity (i.e., VO2/attainable VO2max), increased more (p = 0.001) in AA (8.3 ± 4.4%) than in TR (2.6 ± 1.9%). These results demonstrate that the ability to resist changes in RE and VO2max following prolonged running is superior in trained versus untrained runners, when exercising at the same relative intensity.

Accuracy of respiratory gas variables, substrate, and energy use from 15 CPET systems during simulated and human exercise

PURPOSE

Various systems are available for cardiopulmonary exercise testing (CPET), but their accuracy remains largely unexplored. We evaluate the accuracy of 15 popular CPET systems to assess respiratory variables, substrate use, and energy expenditure during simulated exercise. Cross-comparisons were also performed during human cycling experiments (i.e., verification of simulation findings), and between-session reliability was assessed for a subset of systems.

METHODS

A metabolic simulator was used to simulate breath-by-breath gas exchange, and the values measured by each system (minute ventilation [V̇E], breathing frequency [BF], oxygen uptake [V̇O2 ], carbon dioxide production [V̇CO2 ], respiratory exchange ratio [RER], energy from carbs and fats, and total energy expenditure) were compared to the simulated values to assess the accuracy. The following manufacturers (system) were assessed: COSMED (Quark CPET, K5), Cortex (MetaLyzer 3B, MetaMax 3B), Vyaire (Vyntus CPX, Oxycon Pro), Maastricht Instruments (Omnical), MGC Diagnostics (Ergocard Clinical, Ergocard Pro, Ultima), Ganshorn/Schiller (PowerCube Ergo), Geratherm (Ergostik), VO2master (VO2masterPro), PNOĒ (PNOĒ), and Calibre Biometrics (Calibre).

RESULTS

Absolute percentage errors during the simulations ranged from 1.15%-44.3% for V̇E, 1.05-3.79% for BF, 1.10%-13.3% for V̇O2 , 1.07%-18.3% for V̇CO2 , 0.62%-14.8% for RER, 5.52%-99.0% for Kcal from carbs, 5.13%-133% for Kcal from fats, and 0.59%-12.1% for total energy expenditure. Between-session variation ranged from 0.86%-21.0% for V̇O2 and 1.14%-20.2% for V̇CO2 , respectively.

CONCLUSION

The error of respiratory gas variables, substrate, and energy use differed substantially between systems, with only a few systems demonstrating a consistent acceptable error. We extensively discuss the implications of our findings for clinicians, researchers and other CPET users.

Acute Oxygen Consumption Response to Fast Start High-Intensity Intermittent Exercise

The current investigation compared the acute oxygen consumption (VO2) response of two high-intensity interval exercises (HIIE), fast start (FSHIIE), and steady power (SPHIIE), which matched w prime (W') depletion. Eight cyclists completed an incremental max test and a three-minute all-out test (3MT) to determine maximal oxygen consumption (VO2max), critical power (CP), and W'. HIIE sessions consisted of 3 X 4 min intervals interspersed by 3 min of active recovery, with W' depleted by 60% (W'target) within each working interval. SPHIIE depleted the W'target consistently throughout the 3 min intervals, while FSHIIE depleted the W'target by 50% within the first minute, with the remaining 50% depleted evenly across the remainder of the interval. The paired samples t-test revealed no differences in the percentage of training time spent above 90% of VO2max (PT ≥ 90% VO2max) between SPHIIE and FSHIIE with an average of 25.20% and 26.07%, respectively. Pairwise comparisons indicated a difference between minute 1 peak VO2, minute 2, and minute 3, while no differences were present between minutes 2 and 3. The results suggest that when HIIE formats are matched based on W' expenditure, there are no differences in PT ≥ 90% VO2max or peak VO2 during each interval.

Remote Determination of Critical Speed and Critical Power in Recreational Runners

PURPOSE

This study aimed to compare estimations of critical speed (CS) and work completed above CS (D'), and their analogies for running power (critical power [CP] and W'), derived from raw data obtained from habitual training (HAB) and intentional maximal efforts in the form of time trials (TTs) and 3-minute all-out tests (3MTs) in recreational runners. The test-retest reliability of the 3MT was further analyzed.

METHODS

Twenty-three recreational runners (4 female) used a foot pod to record speed, altitude, and power output for 8 consecutive weeks. CS and D', and CP and W', were calculated from the best 3-, 7-, and 12-minute segments recorded in the first 6 weeks of their HAB and in random order in weeks 7 and 8 from 3 TTs (3, 7, and 12 min) and three 3MTs (to assess test-retest reliability).

RESULTS

There was no difference between estimations of CS or CP derived from HAB, TT, and 3MT (3.44 [0.63], 3.42 [0.53], and 3.76 [0.57] m · s-1 and 281 [41], 290 [45], and 305 [54] W, respectively), and strong agreement between HAB and TT for CS (r = .669) and CP (r = .916). Limited agreement existed between estimates of D'/W'. Moderate reliability of D'/W' was demonstrated between the first and second 3MTs, whereas excellent reliability was demonstrated for CS/CP.

CONCLUSION

These data suggest that estimations of CS/CP can be derived remotely, from either HAB, TT, or 3MT, although the lower agreement between D'/W' warrants caution when using these measures interchangeably.

Is Running Power a Useful Metric? Quantifying Training Intensity and Aerobic Fitness Using Stryd Running Power Near the Maximal Lactate Steady State

We sought to determine the utility of Stryd, a commercially available inertial measurement unit, to quantify running intensity and aerobic fitness. Fifteen (eight male, seven female) runners (age = 30.2 [4.3] years; V·O2max = 54.5 [6.5] ml·kg-1·min-1) performed moderate- and heavy-intensity step transitions, an incremental exercise test, and constant-speed running trials to establish the maximal lactate steady state (MLSS). Stryd running power stability, sensitivity, and reliability were evaluated near the MLSS. Stryd running power was also compared to running speed, V·O2, and metabolic power measures to estimate running mechanical efficiency (EFF) and to determine the efficacy of using Stryd to delineate exercise intensities, quantify aerobic fitness, and estimate running economy (RE). Stryd running power was strongly associated with V·O2 (R2 = 0.84; p < 0.001) and running speed at the MLSS (R2 = 0.91; p < 0.001). Stryd running power measures were strongly correlated with RE at the MLSS when combined with metabolic data (R2 = 0.79; p < 0.001) but not in isolation from the metabolic data (R2 = 0.08; p = 0.313). Measures of running EFF near the MLSS were not different across intensities (~21%; p > 0.05). In conclusion, although Stryd could not quantify RE in isolation, it provided a stable, sensitive, and reliable metric that can estimate aerobic fitness, delineate exercise intensities, and approximate the metabolic requirements of running near the MLSS.

Muscle oxygen saturation rates coincide with lactate-based exercise thresholds

INTRODUCTION

Monitoring muscle metabolic activity via blood lactate is a useful tool for understanding the physiological response to a given exercise intensity. Recent indications suggest that skeletal muscle oxygen saturation (SmO2), an index of the balance between local O2 supply and demand, may describe and predict endurance performance outcomes.

PURPOSE

We tested the hypothesis that SmO2 rate is tightly related to blood lactate concentration across exercise intensities, and that deflections in SmO2 rate would coincide with established blood lactate thresholds (i.e., lactate thresholds 1 and 2).

METHODS

Ten elite male soccer players completed an incremental running protocol to exhaustion using 3-min work to 30 s rest intervals. Blood lactate samples were collected during rest and SmO2 was collected continuously via near-infrared spectroscopy from the right and left vastus lateralis, left biceps femoris and the left gastrocnemius.

RESULTS

Muscle O2 saturation rate (%/min) was quantified after the initial 60 s of each 3-min segment. The SmO2 rate was significantly correlated with blood lactate concentrations for all muscle sites; RVL, r = - 0.974; LVL, r = - 0.969; LG, r = - 0.942; LHAM, r = - 0.907. Breakpoints in SmO2 rate were not significantly different from LT1 or LT2 at any muscle sites (P > 0.05). Bland-Altman analysis showed speed threshold estimates via SmO2 rate and lactate are similar at LT2, but slightly greater for SmO2 rate at LT1.

CONCLUSIONS

Muscle O2 saturation rate appears to provide actionable information about maximal metabolic steady state and is consistent with bioenergetic reliance on oxygen and its involvement in the attainment of metabolic steady state.

The fourth dimension: physiological resilience as an independent determinant of endurance exercise performance

Endurance exercise performance is known to be closely associated with the three physiological pillars of maximal O2 uptake (V ̇ O 2 max $\dot{V}_{{\rm O}_{2}{\rm max}}$ ), economy or efficiency during submaximal exercise, and the fractional utilisation ofV ̇ O 2 max $\dot{V}_{{\rm O}_{2}{\rm max}}$ (linked to metabolic/lactate threshold phenomena). However, while 'start line' values of these variables are collectively useful in predicting performance in endurance events such as the marathon, it is not widely appreciated that these variables are not static but are prone to significant deterioration as fatiguing endurance exercise proceeds. For example, the 'critical power' (CP), which is a composite of the highest achievable steady-state oxidative metabolic rate and efficiency (O2 cost per watt), may fall by an average of 10% following 2 h of heavy intensity cycle exercise. Even more striking is that the extent of this deterioration displays appreciable inter-individual variability, with changes in CP ranging from <1% to ∼32%. The mechanistic basis for such differences in fatigue resistance or 'physiological resilience' are not resolved. However, resilience may be important in explaining superlative endurance performance and it has implications for the physiological evaluation of athletes and the design of interventions to enhance performance. This article presents new information concerning the dynamic plasticity of the three 'traditional' physiological variables and argues that physiological resilience should be considered as an additional component, or fourth dimension, in models of endurance exercise performance.

Invited review: The speed-duration relationship across the animal kingdom

The parameters of the hyperbolic speed-duration relationship (the asymptote critical speed, CS, and the curvature constant, D') provide estimates of the maximal steady state speed (CS) and the distance an animal can run, swim, or fly at speeds above CS before it is forced to slow down or stop (D'). The speed-duration relationship has been directly studied in humans, horses, mice and rats. The technical difficulties with treadmill running in dogs and the relatively short greyhound race durations means that, perhaps surprisingly, it has not been assessed in dogs. The endurance capabilities of lizards, crabs and salamanders has also been measured, and the speed-duration relationship can be calculated from these data. These analyses show that 1) raising environmental temperature from 25 °C to 40 °C in lizards can double the CS with no change in D'; 2) that lungless salamanders have an extremely low critical speed due, most likely, to O₂ diffusion limitations associated with cutaneous respiration; and 3) the painted ghost crab possesses the highest endurance parameter ratio (D'/CS) yet recorded (470 s), allowing it to maintain high speeds for extended periods. Although the speed-duration relationship has not been measured in fish, the sustainable swimming speed has been quantified in a range of species and is conceptually similar to the maximal steady state in humans. The high aerobic power of birds and low metabolic cost of transport during flight permits the extreme feats of endurance observed in bird migrations. However, the parameters of the avian speed-duration relationship have not been quantified.

Prescription of High-intensity Aerobic Interval Training Based on Oxygen Uptake Kinetics

Endurance training results in diverse adaptations that lead to increased performance and health benefits. A commonly measured training response is the analysis of oxygen uptake kinetics, representing the demand of a determined load (speed/work) on the cardiovascular, respiratory, and metabolic systems, providing useful information for the prescription of constant load or interval-type aerobic exercise. There is evidence that during high-intensity aerobic exercise some interventions prescribe brief interval times (<1-min), which may lead to a dissociation between the load prescribed and the oxygen uptake demanded, potentially affecting training outcomes. Therefore, this review explored the time to achieve a close association between the speed/work prescribed and the oxygen uptake demanded after the onset of high-intensity aerobic exercise. The evidence assessed revealed that at least 80% of the oxygen uptake amplitude is reached when phase II of oxygen uptake kinetics is completed (1 to 2 minutes after the onset of exercise, depending on the training status). We propose that the minimum work-time during high-intensity aerobic interval training sessions should be at least 1 minute for athletes and 2 minutes for non-athletes. This suggestion could be used by coaches, physical trainers, clinicians and sports or health scientists for the prescription of high-intensity aerobic interval training.

Functional threshold power is not a valid marker of the maximal metabolic steady state

Functional Threshold Power (FTP) has been considered a valid alternative to other performance markers that represent the upper boundary of the heavy intensity domain. However, such a claim has not been empirically examined from a physiological perspective.This study examined the blood lactate and VO₂ response when exercising at and 15 W above the FTP (FTP_+15W). Thirteen cyclists participated in the study. The VO₂ was recorded continuously throughout FTP and FTP_+15W, with blood lactate measured before the test, every 10 minutes and at task failure. Data were subsequently analysed using two-way ANOVA. The time to task failure at FTP and FTP_+15W were 33.7 ± 7.6 and 22.0 ± 5.7 minutes (p < 0.001), respectively. The VO_2peak was not attained when exercising at FTP_+15W (VO_2peak: 3.61 ± 0.81 vs FTP_+15W 3.33 ± 0.68 L·min^-1, p < 0.001). The VO₂ stabilised during both intensities. However, the end test blood lactate corresponding to FTP and FTP_+15W was significantly different (6.7 ± 2.1 mM vs 9.2 ± 2.9 mM; p < 0.05). The VO₂ response corresponding to FTP and FTP_+15W suggests that FTP should not be considered a threshold marker between heavy and severe intensity.

Decoupling of Internal and External Workload During a Marathon: An Analysis of Durability in 82,303 Recreational Runners

Aim

This study characterised the decoupling of internal-to-external workload in marathon running and investigated whether decoupling magnitude and onset could improve predictions of marathon performance.

Methods

The decoupling of internal-to-external workload was calculated in 82,303 marathon runners (13,125 female). Internal workload was determined as a percentage of maximum heart rate, and external workload as speed relative to estimated critical speed (CS). Decoupling magnitude (i.e., decoupling in the 35–40 km segment relative to the 5–10 km segment) was classified as low (< 1.1), moderate (≥ 1.1 but < 1.2) or high (≥ 1.2). Decoupling onset was calculated when decoupling exceeded 1.025.

Results

The overall internal-to-external workload decoupling experienced was 1.16 ± 0.22, first detected 25.2 ± 9.9 km into marathon running. The low decoupling group (34.5% of runners) completed the marathon at a faster relative speed (88 ± 6% CS), had better marathon performance (217.3 ± 33.1 min), and first experienced decoupling later in the marathon (33.4 ± 9.0 km) compared to those in the moderate (32.7% of runners, 86 ± 6% CS, 224.9 ± 31.7 min, and 22.6 ± 7.7 km), and high decoupling groups (32.8% runners, 82 ± 7% CS, 238.5 ± 30.7 min, and 19.1 ± 6.8 km; all p < 0.01). Compared to females, males’ decoupling magnitude was greater (1.17 ± 0.22 vs. 1.12 ± 0.16; p < 0.01) and occurred earlier (25.0 ± 9.8 vs. 26.3 ± 10.6 km; p < 0.01). Marathon performance was associated with the magnitude and onset of decoupling, and when included in marathon performance models utilising CS and the curvature constant, prediction error was reduced from 6.45 to 5.16%.

Conclusion

Durability characteristics, assessed as internal-to-external workload ratio, show considerable inter-individual variability, and both its magnitude and onset are associated with marathon performance.

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.

Power profiling and the power-duration relationship in cycling: a narrative review

Emerging trends in technological innovations, data analysis and practical applications have facilitated the measurement of cycling power output in the field, leading to improvements in training prescription, performance testing and race analysis. This review aimed to critically reflect on power profiling strategies in association with the power-duration relationship in cycling, to provide an updated view for applied researchers and practitioners. The authors elaborate on measuring power output followed by an outline of the methodological approaches to power profiling. Moreover, the deriving a power-duration relationship section presents existing concepts of power-duration models alongside exercise intensity domains. Combining laboratory and field testing discusses how traditional laboratory and field testing can be combined to inform and individualize the power profiling approach. Deriving the parameters of power-duration modelling suggests how these measures can be obtained from laboratory and field testing, including criteria for ensuring a high ecological validity (e.g. rider specialization, race demands). It is recommended that field testing should always be conducted in accordance with pre-established guidelines from the existing literature (e.g. set number of prediction trials, inter-trial recovery, road gradient and data analysis). It is also recommended to avoid single effort prediction trials, such as functional threshold power. Power-duration parameter estimates can be derived from the 2 parameter linear or non-linear critical power model: P(t) = W′/t + CP (W′—work capacity above CP; t—time). Structured field testing should be included to obtain an accurate fingerprint of a cyclist’s power profile.