Reliability of maximal lactate-steady-state

INSCYD physiological performance software is valid to determine the maximal lactate steady state in male and female cyclists

Introduction

The maximal lactate steady state (MLSS) is defined as the highest workload that can be maintained without blood lactate accumulation over time. The power output at MLSS (PMLSS) is regularly implemented to define training zones, quantify training progress, or predict race performance. The gold standard methodology for MLSS determination requires two to five trials of constant-load exercise, which limits the practical application in training. The INSCYD software can calculate the PMLSS (PMLSSINSCYD) based on physiological data that can be obtained during a ∼1 h laboratory visit. However, to the best of our knowledge, the validity of the most recent software version has not yet been investigated. This study aimed to assess the validity of the software's calculations on PMLSS in cycling.

Methods

The data for this study were retrieved from two published scientific sources. Thirty-one cyclists (19 males, 12 females) performed a 15 s sprint to estimate the VLamax, a ramp test for the V ˙ O 2 max assessment, and two to five constant-load tests to determine the PMLSS. The INSCYD software was used to calculate the PMLSS based on the V ˙ O 2 max , VLamax, sex, body mass, and body composition.

Results

The PMLSSINSCYD was higher than the PMLSS in the entire sample (mean difference: 4.6 W, p < 0.05, 95% CI 0.8-8.3 W) and in men (mean difference: 6.6 W, p < 0.05, 95% CI 1.3-11.8 W), but not in women (mean difference: 0.8 W, n.s., 95% CI -3.7 to 5.3 W), which was within the typical error of the PMLSS estimations (∼3%). In 12 subjects (nine males, three females), the PMLSSINSCYD differed by 3.1-7.3% compared to the MLSS. The Pearson correlations between the measured PMLSS and the calculated PMLSS (PMLSSINSCYD) were very strong in men (r = 0.974, p < 0.001, 95% CI 0.933-0.99), women (r = 0.984, p < 0.001, 95% CI 0.931-0.996), and for the entire sample (r = 0.992, p < 0.001, 95% CI 0.982-0.996).

Discussion

In conclusion, the PMLSS can be accurately calculated using the INSCYD software, but it still requires advanced testing equipment to collect valid V ˙ O 2 max and VLamax data.

Is Maximal Lactate Accumulation Rate Promising for Improving 5000-m Prediction in Running?

Endurance running performance can be predicted by maximal oxygen uptake (V̇O2max), the fractional utilisation of oxygen uptake (%V̇O2max) and running economy at lactate threshold (REOBLA). This study aims to assess maximal lactate accumulation rate (ċLamax) in terms of improving running performance prediction in trained athletes. Forty-four competitive female and male runners/triathletes performed an incremental step test, a 100-m sprint test and a ramp test to determine their metabolic profile. Stepwise linear regression was used to predict 5000-m time trial performance. Split times were recorded every 200-m to examine the ‘finishing kick’. Females had a slower t5k and a lower V̇O2max, ċLamax, ‘finishing kick’ and REOBLA. Augmenting Joyner’s model by means of ċLamax explained an additional 4.4% of variance in performance. When performing the same analysis exclusively for males, ċLamax was not included. ċLamax significantly correlated with %V̇O2max (r=-0.439, p=0.003) and the ‘finishing kick’ (r=0.389, p=0.010). ċLamax allows for significant (yet minor) improvements in 5000-m performance prediction in a mixed-sex group. This margin of improvement might differ in middle-distance events. Due to the relationship to the ‘finishing kick’, ċLamax might be related to individual pacing strategies, which should be assessed in future research.

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.

Effects of Short-Term Phosphate Loading on Aerobic Capacity under Acute Hypoxia in Cyclists: A Randomized, Placebo-Controlled, Crossover Study

The aim of this study was to evaluate the effects of sodium phosphate (SP) supplementation on aerobic capacity in hypoxia. Twenty-four trained male cyclists received SP (50 mg·kg-1 of FFM/day) or placebo for six days in a randomized, crossover study, with a three-week washout period between supplementation phases. Before and after each supplementation phase, the subjects performed an incremental exercise test to exhaustion in hypoxia (FiO2 = 16%). Additionally, the levels of 2,3-diphosphoglycerate (2,3-DPG), hypoxia-inducible factor 1 alpha (HIF-1α), inorganic phosphate (Pi), calcium (Ca), parathyroid hormone (PTH) and acid-base balance were determined. The results showed that phosphate loading significantly increased the Pi level by 9.0%, whereas 2,3-DPG levels, hemoglobin oxygen affinity, buffering capacity and myocardial efficiency remained unchanged. The aerobic capacity in hypoxia was not improved following SP. Additionally, our data revealed high inter-individual variability in response to SP. Therefore, the participants were grouped as Responders and Non-Responders. In the Responders, a significant increase in aerobic performance in the range of 3-5% was observed. In conclusion, SP supplementation is not an ergogenic aid for aerobic capacity in hypoxia. However, in certain individuals, some benefits can be expected, but mainly in athletes with less training-induced central and/or peripheral adaptation.

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

The metabolic boundary separating the heavy-intensity and severe-intensity exercise domains is of scientific and practical interest but there is controversy concerning whether the maximal lactate steady state (MLSS) or critical power (synonymous with critical speed, CS) better represents this boundary. We measured the running speeds at MLSS and CS and investigated their ability to discriminate speeds at which \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2 was stable over time from speeds at which a steady-state \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2 could not be established. Ten well-trained male distance runners completed 9–12 constant-speed treadmill tests, including 3–5 runs of up to 30-min duration for the assessment of MLSS and at least 4 runs performed to the limit of tolerance for assessment of CS. The running speeds at CS and MLSS were significantly different (16.4 ± 1.3 vs. 15.2 ± 0.9 km/h, respectively; P < 0.001). Blood lactate concentration was higher and increased with time at a speed 0.5 km/h higher than MLSS compared to MLSS (P < 0.01); however, pulmonary \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2 did not change significantly between 10 and 30 min at either MLSS or MLSS + 0.5 km/h. In contrast, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2 increased significantly over time and reached \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2\,\,\max }$$\end{document}V˙O2max at end-exercise at a speed ~ 0.4 km/h above CS (P < 0.05) but remained stable at a speed ~ 0.5 km/h below CS. The stability of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2 at a speed exceeding MLSS suggests that MLSS underestimates the maximal metabolic steady state. These results indicate that CS more closely represents the maximal metabolic steady state when the latter is appropriately defined according to the ability to stabilise pulmonary \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2.

Reverse lactate threshold test accurately predicts maximal lactate steady state and 5 km performance in running

This study evaluated the accuracy of the reverse lactate threshold (RLT) and the onset of blood lactate accumulation (OBLA; 4 mmol·L^-1) to determine the running speed at the maximal lactate steady state (MLSS) and 5 km running performance in a field test approach. Study 1: 16 participants performed an RLT test, and 2 or more constant-speed tests, lasting 30 minutes each, to determine running speed at the MLSS. Study 2: 23 participants performed an RLT test and a 5000 m all-out run as an indicator of performance. The RLT test consisted of an initial lactate-priming segment, in which running speed was increased stepwise up to ~5% above the estimated MLSS, followed by a reverse segment in which speed was decreased by 0.1 m·s^-1 every 180 s. RLT was determined using the highest lactate equivalent ([La^-]/running speed) during the reverse segment. OBLA was determined during the priming segment and was set at a value of 4 mmol∙L¹. The mean difference in MLSS was +0.06 ± 0.05 m·s^-1 for RLT, and +0.13 ± 0.23 m·s^-1 for OBLA. OBLA showed a good concordance with the MLSS (ICC = 0.83), whereas RLT revealed excellent concordance with the MLSS with an ICC = 0.98. RLT showed a very high correlation with 5000 m speed (r = 0.97). The RLT exhibited exceptional agreement to MLSS and 5000 m running performance. Due to this high accuracy, especially concerning the small intraindividual differences, the RLT test may be superior to common threshold concepts. Further research is needed to evaluate its sensitivity during the training process.

The Maximal Lactate Steady State Workload Determines Individual Swimming Performance

The lactate threshold (LT) and the strongly related maximal lactate steady state workload (MLSS_W) are critical for physical endurance capacity and therefore of major interest in numerous sports. However, their relevance to individual swimming performance is not well understood. We used a custom-made visual light pacer for real-time speed modulation during front crawl to determine the LT and MLSS_W in a single-exercise test. When approaching the LT, we found that minute variations in swimming speed had considerable effects on blood lactate concentration ([La^-]). The LT was characterized by a sudden increase in [La^-], while the MLSS_W occurred after a subsequent workload reduction, as indicated by a rapid cessation of blood lactate accumulation. Determination of the MLSS_W by this so-called "individual lactate threshold" (ILT)-test was highly reproducible and valid in a constant speed test. Mean swimming speed in 800 and 1,500 m competition (S-Comp) was 3.4% above MLSS_W level and S-Comp, and the difference between S-Comp and the MLSS_W (Δ S-Comp/MLSS_W) were higher for long-distance swimmers (800-1,500 m) than for short- and middle-distance swimmers (50-400 m). Moreover, Δ S-Comp/MLSS_W varied significantly between subjects and had a strong influence on overall swimming performance. Our results demonstrate that the MLSS_W determines individual swimming performance, reflects endurance capacity in the sub- to supra-threshold range, and is therefore appropriate to adjust training intensity in moderate to severe domains of exercise.

Considerations regarding Maximal Lactate Steady State determination before redefining the gold-standard

We have read with interest the review written by Jones et al. (2019) published in a recent volume‐issue (volume 7, issue 5) of the journal. Criticisms regarding maximal lactate steady state intensity determination are to some extent correct and well‐justified. There are some aspects, however, that should be further clarified and documented before redefining the gold‐standard measure for the evaluation of endurance exercise capacity.

A "Blood Relationship" Between the Overlooked Minimum Lactate Equivalent and Maximal Lactate Steady State in Trained Runners. Back to the Old Days?

Maximal Lactate Steady State (MLSS) and Lactate Threshold (LT) are physiologically-related and fundamental concepts within the sports and exercise sciences. Literature supporting their relationship, however, is scarce. Among the recognized LTs, we were particularly interested in the disused “Minimum Lactate Equivalent” (LE_min), first described in the early 1980s. We hypothesized that velocity at LT, conceptually comprehended as in the old days (LE_min), could predict velocity at MLSS (_VMLSS) more accurate than some other blood lactate-related thresholds (BL_RTs) routinely used nowadays by many sport science practitioners. Thirteen male endurance-trained [_VMLSS 15.0 ± 1.1 km·h⁻¹; maximal oxygen uptake (V.O2max) 67.6 ± 4.1 ml·kg⁻¹·min⁻¹] homogeneous (coefficient of variation: ≈7%) runners conducted 1) a submaximal discontinuous incremental running test to determine several BL_RTs followed by a maximal ramp incremental running test for V.O2max determination, and 2) several (4–5) constant velocity running tests to determine _VMLSS with a precision of 0.20 km·h⁻¹. Determined BL_RTs include LE_min and LE_min-related LE_min plus 1 (LE_min+1mM) and 1.5 mmol·L⁻¹ (LE_min+1.5mM), along with well-established BL_RTs such as conventionally-calculated LT, D_max and fixed blood lactate concentration thresholds. LE_min did not differ from LT (P = 0.71; ES: 0.08) and was 27% lower than MLSS (P < 0.001; ES: 3.54). LE_min+1mM was not different from MLSS (P = 0.47; ES: 0.09). LE_min was the best predictor of _VMLSS (r = 0.91; P < 0.001; SEE = 0.47 km·h⁻¹), followed by LE_min+1mM (r = 0.86; P < 0.001; SEE = 0.58 km·h⁻¹) and LE_min+1.5mM (r = 0.84; P < 0.001; SEE = 0.86 km·h⁻¹). There was no statistical difference between MLSS and estimated MLSS using LE_min prediction formula (P = 0.99; ES: 0.001). Mean bias and limits of agreement were 0.00 ± 0.45 km·h⁻¹ and ±0.89 km·h⁻¹. Additionally, LE_min, LE_min+1mM and LE_min+1.5mM were the best predictors of V.O2max (r = 0.72–0.79; P < 0.001). These results support LE_min, an objective submaximal overlooked and underused BL_RT, to be one of the best single MLSS predictors in endurance trained runners. Our study advocates factors controlling LE_min to be shared, at least partly, with those controlling MLSS.

Manipulating graded exercise test variables affects the validity of the lactate threshold and [Formula: see text]

BACKGROUND

To determine the validity of the lactate threshold (LT) and maximal oxygen uptake ([Formula: see text]) determined during graded exercise test (GXT) of different durations and using different LT calculations. Trained male cyclists (n = 17) completed five GXTs of varying stage length (1, 3, 4, 7 and 10 min) to establish the LT, and a series of 30-min constant power bouts to establish the maximal lactate steady state (MLSS). [Formula: see text] was assessed during each GXT and a subsequent verification exhaustive bout (VEB), and 14 different LTs were calculated from four of the GXTs (3, 4, 7 and 10 min)-yielding a total 56 LTs. Agreement was assessed between the highest [Formula: see text] measured during each GXT ([Formula: see text]) as well as between each LT and MLSS. [Formula: see text] and LT data were analysed using mean difference (MD) and intraclass correlation (ICC).

RESULTS

The [Formula: see text] value from GXT1 was 61.0 ± 5.3 mL.kg-1.min-1 and the peak power 420 ± 55 W (mean ± SD). The power at the MLSS was 264 ± 39 W. [Formula: see text] from GXT3, 4, 7, 10 underestimated [Formula: see text] by ~1-5 mL.kg-1.min-1. Many of the traditional LT methods were not valid and a newly developed Modified Dmax method derived from GXT4 provided the most valid estimate of the MLSS (MD = 1.1 W; ICC = 0.96).

CONCLUSION

The data highlight how GXT protocol design and data analysis influence the determination of both [Formula: see text] and LT. It is also apparent that [Formula: see text] and LT cannot be determined in a single GXT, even with the inclusion of a VEB.

Reliability of time-to-exhaustion and selected psycho-physiological variables during constant-load cycling at the maximal lactate steady-state

The maximal lactate steady-state (MLSS) is frequently assessed for prescribing endurance exercise intensity. Knowledge of the intra-individual variability of the MLSS is important for practical application. To date, little is known about the reliability of time-to-exhaustion and physiological responses to exercise at MLSS. Twenty-one healthy men (age, 25.2 (SD 3.3) years; height, 1.83 (0.06) m; body mass, 78.9 (8.9) kg; maximal oxygen uptake, 57.1 (10.7) mL·min^-1·kg^-1) performed 1 incremental exercise test, and 2 constant-load tests to determine MLSS intensity. Subsequently, 2 open-end constant-load tests (MLSS 1 and 2) at MLSS intensity (3.0 (0.7) W·kg^-1, 76% (10%) maximal oxygen uptake) were carried out. During the tests, blood lactate concentrations, heart rate, ratings of perceived exertion (RPE), variables of gas exchange, and core body temperature were determined. Time-to-exhaustion was 50.8 (14.0) and 48.2 (16.7) min in MLSS 1 and 2 (mean change: -2.6 (95% confidence interval: -7.8, 2.6)), respectively. The coefficient of variation (CV) was high for time-to-exhaustion (24.6%) and for mean (4.8 (1.2) mmol·L^-1) and end (5.4 (1.7) mmol·L^-1) blood lactate concentrations (15.7% and 19.3%). The CV of mean exercise values for all other parameters ranged from 1.4% (core temperature) to 8.3% (ventilation). At termination, the CVs ranged from 0.8% (RPE) to 11.8% (breathing frequency). The low reliability of time-to-exhaustion and blood lactate concentration at MLSS indicates that the precise individual intensity prescription may be challenging. Moreover, the obtained data may serve as reference to allow for the separation of intervention effects from random variation in our sample.

The midpoint between ventilatory thresholds approaches maximal lactate steady state intensity in amateur cyclists

The aim was to determine whether the midpoint between ventilatory thresholds (MPVT) corresponds to maximal lactate steady state (MLSS). Twelve amateur cyclists (21.0 ± 2.6 years old; 72.2 ± 9.0 kg; 179.8 ± 7.5 cm) performed an incremental test (25 W·min^-1) until exhaustion and several constant load tests of 30 minutes to determine MLSS, on different occasions. Using MLSS determination as the reference method, the agreement with five other parameters (MPVT; first and second ventilatory thresholds: VT1 and VT2; respiratory exchange ratio equal to 1: RER = 1.00; and Maximum) was analysed by the Bland-Altman method. The difference between workload at MLSS and VT1, VT2, RER=1.00 and Maximum was 31.1 ± 20.0, -86.0 ± 18.3, -63.6 ± 26.3 and -192.3 ± 48.6 W, respectively. MLSS was underestimated from VT1 and overestimated from VT2, RER = 1.00 and Maximum. The smallest difference (-27.5 ± 15.1 W) between workload at MLSS and MPVT was in better agreement than other analysed parameters of intensity in cycling. The main finding is that MPVT approached the workload at MLSS in amateur cyclists, and can be used to estimate maximal steady state.