Maximal lactate steady-state and anaerobic thresholds from different methods in cyclists

A novel treadmill protocol for uphill running assessment: the incline incremental running test (IIRT)

This study aimed to compare the maximal and submaximal aerobic parameters between two incremental running tests, one being horizontal and the other an incline-based test, namely the incline incremental running test (IIRT). Twenty endurance-trained trail runners completed two incremental treadmill tests, until exhaustion. The first test was performed using an incline of 1%, with speed increments. Then, the IIRT was performed with the speed set at 50% of the peak speed obtained during the previous test, and the incline was incremented. Cardiorespiratory measurements and blood lactate concentration ([La]) were assessed. The mean peak workload from the horizontal test was 17.6 ± 1.4 km.h^-1 and peak workload from IIRT was 17.3 ± 1.3% of incline. The VO₂peak and [La]peak were not significantly different between the protocols. However, the HRpeak was significantly lower at IIRT. In conclusion, most of the maximal and submaximal aerobic indices showed no differences between the incremental tests analysed. The exceptions were the HRpeak and HR at the lactate turnpoints, that were lower, and the peak O₂ pulse that was greater for the IIRT. Taken together, these data support the validity of the IIRT as a specific test for the physiological assessment of runners involved with uphill performances.

Lactate Equivalent for Maximal Lactate Steady State Determination in Soccer

Purpose: The association between an overlooked classical Lactate Threshold (LT), named "Minimum Lactate Equivalent" (LE_min), with Maximal Lactate Steady State (MLSS) has been recently described with good MLSS prediction results in endurance-trained runners. This study aimed to determine the applicability of LE_min to predict MLSS in lower aerobic-conditioned individuals compared to well-established blood lactate-related thresholds (BLTs). Method: Fifteen soccer players [velocity at MLSS (MLSS_V) 13.2 ± 1.0 km·h^-1; coefficient of variation (CV) 7.6%] conducted a submaximal discontinuous incremental running test to determine BLTs and 3-6 constant velocity running tests to determine MLSS_V. Results: LE_min did not differ from conventional LTs (p > .05) and was 24% lower than MLSS (p < .001; ES: 3.26). Among LTs, LE_min best predicted MLSS_V (r = 0.83; p < .001; SEE = 0.59 km·h^-1). There was no statistical difference between MLSS and estimated MLSS using LE_min prediction formula (p = .99; ES: 0.001). Mean bias and limits of agreement were 0.00 ± 0.58 km·h^-1 and ±1.13 km·h^-1, respectively. LE_min best predicted MLSS_V (r = 0.92; p < .001; SEE = 0.54 km·h^-1) in the pooled data of soccer players and endurance-trained runners of the previous study (n = 28; MLSS_V range 11.2-16.5 km·h^-1; CV 9.8%). Conclusion: Results support LE_min to be one of the best single predictors of MLSS. This study is the sole study providing specific operational regression equations to estimate the impractical gold standard MLSS_V in soccer players by means of a BLT measured during a submaximal single-session test.

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.

Estimation of the maximal lactate steady state in postmenopausal women

This study aimed to estimate the maximal lactate steady-state velocity (_vMLSS) from non-invasive bloodless variables and/or blood lactate-related thresholds (BL_RTs) measured during an Incremental submaximal Shuttle Test (IST), and to determine whether the addition of a Constant Velocity Test (CVT) could improve the estimation. Seventy-five postmenopausal women conducted an IST to determine several BL_RTs and bloodless variables, and two to seven CVTs to determine _vMLSS. Determined BL_RTs were conventionally used lactate threshold (LT) measured either visually (_vLT_+0.1mM) or mathematically (_vLE_min), and 0.5, 1 and 1.5 mmol·L^-1 above LT, along with fixed BL_RTs. The best single predictor of _vMLSS (7.1 ± 1.0 km·h^-1) was _vLE_min+1.5mM (R² = 0.80, P < 0.001; SEE = 0.46 km·h^-1). The combination of BL_RTs and bloodless variables improved the estimation of _vMLSS (R² = 0.85, P < 0.001; SEE = 0.38 km·h^-1). The addition of a CVT still improved the prediction of _vMLSS up to 89.2%, with lower SEE (0.32 km·h^-1). This study suggests that _vLE_min-related thresholds obtained from a single submaximal IST are accurate estimates of _vMLSS in postmenopausal women, and thus the time-consuming procedure of _vMLSS testing could be avoided. Performing an additional CVT is encouraged because it improves the prediction of _vMLSS.

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.

Physiological and Fatigue Responses Associated With Male and Mixed-Gender Ultimate Frisbee Game Play

The aims of this study were to describe the physiological and fatigue responses associated with indoor Ultimate Frisbee game play, compare exercise intensities attained to current activity guidelines, and compare responses between male and mixed-gender game formats. A between-subjects (game format) repeated-measures (time points) observational experimental design was used. Subjects competed in male (n = 10; age: 26.3 ± 7.6 years) or mixed-gender (males: n = 4; 28.5 ± 5.7 years; females: n = 6; 28.3 ± 8.1 years) indoor Ultimate Frisbee game play. Games consisted of 10-minute halves, with heart rate (HR), blood lactate concentration ([BLa]), rating of perceived exertion, and 5-m and 20-m sprint times measured. Durations spent in HR-derived intensity zones and sprint decrements were calculated across games. Mixed-gender game play produced significantly (p ≤ 0.05) higher relative HR (94.3 ± 5.1% vs. 89.6 ± 4.8% HRmax) and [BLa] (8.31 ± 2.22 mmol·L vs. 4.68 ± 1.89 mmol·L) than male game play. Significantly (p ≤ 0.05) longer durations were spent at vigorous (male: 60.2 ± 26.1%; mixed-gender: 36.8 ± 34.8%) and near-maximal (male: 31.6 ± 27.6%; mixed-gender: 58.6 ± 37.7%) exercise intensities than moderate (3.9-7.2%), light (0.7-1.0%), and very light (0-0.1%) intensities in both formats. Limited physiological and sprint fatigue was apparent across games. Subjects primarily performed at vigorous and near-maximal intensities during Ultimate Frisbee. The greater physiological demands encountered during mixed-gender game play might be attributed to underlying gender-mediated cardiovascular differences. These findings support the efficacy of Ultimate Frisbee as a prescriptive exercise tool for health benefit.

The effect of two generic aerobic interval training methods on laboratory and field test performance in soccer players

The purpose of this study was to compare the effects of 2 generic aerobic training models, based on peak running velocity in Carminatti's test (PVT-CAR) in U-20 elite soccer players. Seventeen soccer players (age: 17.9 ± 1.0 years; 178.6 ± 5.0 cm; 73.6 ± 6.6 kg; 11.1 ± 1.3%) from a team competing in a national junior league took part in the study. The athletes performed a series of pre- and posttraining tests (incremental test on a treadmill to determine the maximal oxygen uptake [(Equation is included in full-text article.)], velocity at maximal oxygen uptake [(Equation is included in full-text article.)], the lactate threshold [LT], and T-CAR). The interval training models applied were with 180° direction change (T12:12; n = 9) and without direction change (T6:6; n = 8). No significant interaction (time vs. group) was observed for the majority of variables analyzed (p > 0.05), although significant main effects in time were evident regarding peak treadmill velocity (PVTREAD) (F = 56.3, p < 0.0001), (Equation is included in full-text article.)(F = 35.8, p < 0.0001), LT (F = 57.7, p < 0.0001), and PVT-CAR (F = 52.9, p < 0.0001). Moreover, there was no significant change in (Equation is included in full-text article.)between pre and posttraining period (F = 4.26, p = 0.056) in both training groups. Thus, it can be concluded that the prescribed training with and without direction change in the intensity of the PVT-CAR increases the PVTREAD, the (Equation is included in full-text article.), the LT, and the PVT-CAR similarly.

Test-retest reliability of second lactate turnpoint using two different criteria in competitive cyclists

The aim of this study was to determine the relative and absolute reliability of second lactate turnpoint using fixed and individual blood lactate method in competitive cyclists. Twenty-eight male, well-trained cyclists (30.2 ± 10.1 years, 72.0 ± 7.4 kg, 177.3 ± 4.7 cm) were recruited to participate in this study. Cyclists completed two incremental cycling tests to exhaustion over a period of 7 days to determine their peak power output, maximal oxygen uptake, maximal heart rate, maximal blood lactate concentration and two lactate turnpoint criteria. The fixed blood concentration criterion (3.5 mM) and an individual criterion were assessed by a lactate-power curve, considering power output, heart rate and oxygen uptake. The main finding of this study was that both lactate turnpoint criteria showed identical low within-subject variation for power output (2.8% coefficient of variation). High values for test-retest correlations ranging from r = 0.70 to r = 0.94 were found for all variables in both threshold criteria. In conclusion, the individual and fixed method to determine the second lactate turnpoint showed similar high absolute and relative reliability in competitive cyclists.

Maximal power output estimates the MLSS before and after aerobic training

The purpose of this study is to present an equation to predict the maximal lactate steady state (MLSS) through a VO2peak incremental protocol. Twenty-six physically active men were divided in two groups (G1 and G2). They performed one maximal incremental test to determine their VO2peak and maximal power output (Wpeak), and also several constant intensity tests to determine MLSS intensity (MLSSw) on a cycle ergometer. Group G2 underwent six weeks of aerobic training at MLSSw. A regression equation was created using G1 subjects Wpeak and MLSSw to estimate the MLSS intensity (MLSSweq) before and after training for G2 (MLSSweq = 0.866 x Wpeak-41.734). The mean values were not different (150±27W vs 148±27W, before training / 171±26W vs 177±24W, after training) and significant correlations were found between the measured and the estimated MLSSw before (r²=0.49) and after training (r²=0.62) in G2. The proposed equation was effective to estimate the MLSS intensity before and after aerobic training.