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

Abstract

The lactate anaerobic threshold (AT) determined during an incremental test has been used generally to estimate the maximal lactate steady-state intensity (MLSS int ) in several sports. Furthermore, this index could be useful to predict the time-trial cycling performance and also to prescribe training intensity to enhance aerobic capacity. The aim of this study was to compare three different AT estimations with actual MLSS int in trained cyclists. Fourteen trained cyclists participated in this study. They had previously performed a maximal incremental cycling test (35 W increments each 3 min) in a laboratory followed by three to five visits to measure the MLSS int (30-min tests). Blood lactate concentration ([La]), oxygen uptake (V ˙O2 ), and heart rate (HR) were measured during all tests. Based on the incremental test, we calculated three ATs using different proposed methods: AT 1 -intensity corresponds to fixed [La]; AT 2 -minimum equivalent of the blood lactate-power output relationship plus 1.5 mmol ×L (1 ; AT 3 -power output of the stage antecedent to the second lactate increase of at least 0.5 mmol ×L (1 above the previous values, where the second increase was greater than the first. The MLSS int was determined for each participant as the highest power output that could be maintained with [La] fluctuating less than 1 mmol ×L (1 during the final 20 min of the steady-state tests. ANOVA with repeated measures was used to compare physiological variables in the different methods. The relationship between the MLSS int and the power output of AT 1 , AT 2 , and AT 3 was analysed using Pearson product-moment correlation coefficients. In addition, we calculated the bias and limits of agreement between the three different methods with actual MLSS int . The mean9s values of power output related to MLSS int , AT 1 , AT 2 , and AT 3 were 247933 W, 258939 W, 248935 W, and 230936 W, respectively. The results showed that AT 3 underestimated (P B 0.05) the MLSS int for most of the participants and provided lower mean values compared with AT 1 and AT 2 . Furthermore, AT 2 seems to be more accurate to estimate MLSS int than other methods here verified when we analysed the mean values, correlation coefficient (r 0 0.94), and Bland-Altman limits of agreement (9 9.5%). The AT 1 also provided good prediction values, although it presented with a trend to overestimate MLSS int . Therefore, considering the methods analysed in the current study and the importance of this submaximal aerobic index to flat time-trials and prolonged uphill cycling performance, the AT 2 method could be used with good accuracy by coaches and athletes.

Manipulating graded exercise test variables affects the validity of the lactate threshold and V˙O2peak

“…L -1 was the only LT derived from GXT 3 included in our analysis (bias = -6 ± 35 W). This is consistent with the results of one previous study (bias = 0.5 ± 24 W), which also recruited trained male cyclists and had a similar GXT protocol design [ 56 ]. Consistent with our findings, this study also reported that an OBLA of 3.5 mmol .…”

Estimation of the Maximal Lactate Steady State in Junior Soccer Players

“…3 are narrower or similar to those of other studies predicting MLSS from a 1 600 m time trial (− 0.8 to 0.7 km • h − 1 or ± 6.0 % of the mean) [29], lactate minimum test (− 0.9 to 0.7 km • h − 1 or ± 6.6 % of the mean) [21,32], power output at a fixed blood lactate concentration ( ± 10.3 % of the mean) [15], power output from the minimum equivalent of the blood lactate-power relationship plus 1.5 mmol • L − 1 ( ± 9.5 % of the mean) [15], velocity associated with a respiratory exchange ratio equal to 1.00 (− 1.2 to 1.6 km • h − 1 or ± 9.0 % of the mean) [24] or ventilatory threshold (2.5 to − 1.3 km • h − 1 or ± 12.0 % of the mean) [24], in cyclists MLSS V mean (km . [15], runners [21,24] and physically active men [31,32]. This evidence adds support to the finding that MAV, together with V 80 %HRmax , provide a likely better estimation of the MLSS intensity than other lactate or ventilatory-related thresholds.…”

Estimation of the Maximal Lactate Steady State in Endurance Runners

“…This SEE is very similar to the one previously found in soccer players (0.43 km • h − 1 , 3.5 % of the mean MLSS V ) [27] and compares favorably with other studies predicting MLSS V from the velocity corresponding to a 4 mmol • L − 1 [La − ] and velocity at the maximal constant HR maintainable for 30 min, where SEE values of 0.67 km • h − 1 (5.5 % of the mean MLSS V ) have been reported [37]. The Bland-Altman limits of agreement ( − 1.17 to 1.17 km • h − 1 or ± 7.7 % of mean MLSS V ) of equation 4 are narrower or only slightly higher compared to those of other studies predicting MLSS from a 1600 m time trial ( − 0.8 to 0.7 km • h − 1 or ± 6.0 % of the mean) [31], lactate minimum test ( − 0.9 to 0.7 km • h − 1 or ± 6.6 % of the mean) [22,34], power output at a fixed blood lactate concentration ( ± 10.3 % of the mean) [17], power output from the minimum equivalent of the blood lactate-power relationship plus 1.5 mmol • L − 1 ( ± 9.5 % of the mean) [17], velocity associated with a respiratory exchange ratio equal to 1.00 ( − 1.2 to 1.6 km • h − 1 or ± 9.0 % of the mean) [26] or ventilatory threshold ( − 1.3 to 2.5 km • h − 1 or ± 12.0 % of the mean) [26], in cyclists [17], runners [22,26] and physically active men [33,34]. This evidence lends further support to the finding that MAV, a noninvasive, cheap and objective variable, may provide a similar or better estimation of the MLSS intensity than other more sophisticated, expensive and time consuming lactate or ventilatoryrelated thresholds.…”