Blood lactate during constant-load exercise at aerobic and anaerobic thresholds

From Incremental Test to Continuous Running at Fixed Lactate Thresholds: Individual Responses on %VO2max, %HRmax, Lactate Accumulation, and RPE

With Norway's successes in middle and long-distance running, lactate-guided threshold training has regained importance in recent years. Therefore, the aim of the present study was to investigate the individual responses on common monitoring parameters based on a lactate-guided conventional training method. In total, 15 trained runners (10 males, 5 females; 18.6 ± 3.3 years; VO2max: 59.3 ± 5.9 mL kg-1 min-1) completed a 40-min continuous running session at a fixed lactate threshold load of 2 mmol L-1. Lactate (La), oxygen uptake (VO2), heart rate (HR), and rating of perceived exertion (RPE) were recorded. The chosen workload led to lactate values of 2.85 ± 0.56 mmol L-1 (range: 1.90-3.80), a percentage of VO2max utilization (%VO2max) of 79.2 ± 2.5% (range: 74.9-83.8), a percentage of HRmax utilization (%HRmax) of 92.2 ± 2.5% (range: 88.1-95.3), and an RPE of 6.1 ± 1.9 (range: 3-10) at the end of the running session. Thereby, the individual responses differed considerably. These results indicate that a conventional continuous training method based on a fixed lactate threshold can lead to different individual responses, potentially resulting in various physiological impacts. Moreover, correlation analyses suggest that athletes with higher lactate threshold performance levels must choose their intensity in continuous training methods more conservatively (lower percentage intensity based on a fixed threshold) to avoid eliciting excessively strong metabolic responses.

Effects of different exercise intensities on prefrontal activity during a dual task

The effects of physical exercise on cognitive tasks have been investigated. However, it is unclear how different exercise intensities affect the neural activity. In this study, we investigated the neural activity in the prefrontal cortex (PFC) by varying the exercise intensity while participants performed a dual task (DT). Twenty healthy young adults performed serial subtraction while driving a cycle ergometer. Exercise intensity was set to one of three levels: low, moderate, or high intensity. We did not find any significant change in PFC activity during DT under either the control (no exercise) or low-intensity conditions. In contrast, we observed a significant increase in PFC activity during DT under moderate- and high-intensity conditions. In addition, we observed complex hemodynamics after DT. PFC activity decreased from baseline after DT under the control condition, while it increased under the low-intensity condition. PFC activity remained higher than the baseline level after DT under the moderate-intensity condition but returned to baseline under the high-intensity condition. The results suggest that moderate-intensity exercise with a cognitive load effectively increases PFC activity, and low-intensity exercise may increase PFC activity when combined with a cognitive load.

Functional Threshold Power Is Not Equivalent to Lactate Parameters in Trained Cyclists

ABSTRACT

Jeffries, O, Simmons, R, Patterson, SD, and Waldron, M. Functional threshold power is not equivalent to lactate parameters in trained cyclists. J Strength Cond Res 35(10): 2790-2794, 2021-Functional threshold power (FTP) is derived from a maximal self-paced 20-minute cycling time trial whereby the average power output is scaled by 95%. However, the physiological basis of the FTP concept is unclear. Therefore, we evaluated the relationship of FTP with a range of laboratory-based blood lactate parameters derived from a submaximal threshold test. Twenty competitive male cyclists completed a maximal 20-minute time trial and an incremental exercise test to establish a range of blood lactate parameters. Functional threshold power (266 ± 42 W) was strongly correlated (r = 0.88, p < 0.001) with the power output associated with a fixed blood lactate concentration 4.0 mmol·L-1 (LT4.0) (268 ± 30 W) and not significantly different (p > 0.05). While mean bias was 2.9 ± 24.6 W, there were large limits of agreement (LOA) between FTP and LT4.0 (-45 to 51 W). All other lactate parameters, lactate threshold (LT) (236 ± 32 W), individual anaerobic threshold (244 ± 33 W), and LT thresholds determined using the Dmax method (221 ± 25 W) and modified Dmax method (238 ± 32 W) were significantly different from FTP (p < 0.05). While FTP strongly correlated with LT4.0, the large LOA refutes any equivalence as a measure with physiological basis. Therefore, we would encourage athletes and coaches to use alternative field-based methods to predict cycling performance.

Relationship Between Critical Power and Different Lactate Threshold Markers in Recreational Cyclists

Purpose: To analyze the relationship between critical power (CP) and different lactate threshold (LT2) markers in cyclists.

Methods: Seventeen male recreational cyclists [33 ± 5 years, peak power output (PO) = 4.5 ± 0.7 W/kg] were included in the study. The PO associated with four different fixed (onset of blood lactate accumulation) and individualized (Dmax_exp, Dmax_pol, and LT_Δ1) LT2 markers was determined during a maximal incremental cycling test, and CP was calculated from three trials of 1-, 5-, and 20-min duration. The relationship and agreement between each LT2 marker and CP were then analyzed.

Results: Strong correlations (r = 0.81–0.98 for all markers) and trivial-to-small non-significant differences (Hedges’ g = 0.01–0.17, bias = 1–9 W, and p > 0.05) were found between all LT2 markers and CP with the exception of Dmax_exp, which showed the strongest correlation but was slightly higher than the CP (Hedges’ g = 0.43, bias = 20 W, and p < 0.001). Wide limits of agreement (LoA) were, however, found for all LT2 markers compared with CP (from ±22 W for Dmax_exp to ±52 W for Dmax_pol), and unclear to most likely practically meaningful differences (PO differences between markers >1%, albeit <5%) were found between markers attending to magnitude-based inferences.

Conclusion: LT2 markers show a strong association and overall trivial-to-small differences with CP. Nevertheless, given the wide LoA and the likelihood of potentially meaningful differences between these endurance-related markers, caution should be employed when using them interchangeably.

Physiological differences between a noncontinuous and a continuous endurance training protocol in recreational runners and metabolic demand prediction

This study investigated the physiological difference in recreational runners between a noncontinuous and a continuous endurance training protocol. It also aimed to determine physiological surrogate that could monitor metabolic demand of prolonged running in real‐time. For data collection, a total of 18 active male recreational runners were recruited. Physiological (HR, RR, RER, ṼO₂, BLa), and overall perceptual (RPE_O) responses were recorded against three designed test sessions. Session 1 included ṼO_2submax test to determine critical speed (CS) at anaerobic threshold (AT). Session 2 was the noncontinuous CS test until exhaustion, having 4:1 min work‐to‐rest ratio at CS, whereas session 3 was the continuous CS test till exhaustion. As 1‐min recovery during session 2 may change fatigue behavior, it was hypothesized that it will significantly change the physiological stress and hence endurance outcomes. Results reported average time to exhaustion (TTE) was 37.33(9.8) mins for session 2 and 23.28(9.87) mins for session 3. Participants experienced relatively higher metabolic demand (BLa) 6.78(1.43) mmol.l⁻¹ in session 3 as compared to session 2 (5.52(0.93) mmol.l⁻¹). RER was observed to increase in session 3 and decrease in session 2. Student's paired t‐test only reported a significant difference in TTE, ṼO₂, RER, RPE_O, and BLa at “End” between session 2 and 3. Reported difference in RPE_O and %HR_max at “AT” were 5 (2.2) and 89.8 (2.60)% during session 2 and 6 (2.5) and 89.8 (2.59)% during session 3, respectively. Regression analysis reported strong correlation of %HR_max (adj. R‐square = 0.588) with BLa than RPE_O (adj. R‐square = 0.541). The summary of findings suggests that decreasing RER increased TTE and reduced BLa toward “End” during session 2 which might have helped to have better endurance. The %HR_max was identified to be used as a better noninvasive surrogate of endurance intensity estimator.

Effect of Thiamine Pyrophosphate on Levels of Serum Lactate, Maximum Oxygen Consumption and Heart Rate in Athletes Performing Aerobic Activity

The aim of this study was to determine the effect of thiamine pyrophosphate (TPP) on serum lactate levels, maximum oxygen consumption (Vo2max) and heart rate in male athletes performing aerobic activity. A double-blind, randomized, crossover study was performed in which lactate levels, Vo2max and heart rates in 27 male athletes were compared at rest and after exercise, following administration of placebo (sodium chloride 0.9%) or TPP (1 mg/kg). At rest, serum lactate levels after placebo or TPP were similar; however, after exercise, the levels were lower in the athletes after taking TPP than after placebo. During exercise, Vo2max in athletes on TPP was higher than on placebo. At rest, heart rate after taking placebo or TPP was similar but, after exercise, heart rate was lower after taking TPP than after placebo. It is concluded that TPP caused serum lactate levels and heart rate to be lower than placebo and Vo2max to be higher in athletes performing aerobic physical activity.

Relationship Between Running Velocity of 2 Distances and Various Lactate Parameters

Purpose:

The purpose of this study was to determine the relationship between various lactate-threshold (LT) definitions and the average running velocity during a 10-km and a 21.1-km time trial (TT).

Methods:

Thirteen well-trained runners completed an incremental maximal exercise test, a 10-km TT, and a 21.1-km TT on a motorized treadmill. Blood samples were collected through a venous catheter placed in an antecubital vein. Pearson's correlation coefficients were used to determine the relationship between the running velocity at the different LT definitions and the average running velocity during each TT. A dependent t test was used to determine statistical differences for the mean lactate response between the 2 running distances.

Results:

The LTDmax, the point on the regression curve that yielded the maximal perpendicular distance to the straight line formed by the 2 endpoints, was the LT definition with the highest correlation for both 10-km (r = .844) and 21.1-km TTs (r = .783). The velocity at the LTDmax was not, however, the velocity closest to the performance velocity for either distance. The mean running velocity at each LT was significantly different and tended to overestimate the mean TT performance velocities. The mean lactate concentration during the 10-km TT (3.52 ± 1.58 mmol) was significantly higher than during the 21.1-km TT (1.86 ± 0.90 mmol).

Conclusion:

These results indicate that a single LT point cannot be reliably associated with different running distances. Furthermore, these data suggest that a different methodology for estimating the LT that considers individual responses might be required for different running distances.

Prediction of time to exhaustion from blood lactate response during submaximal exercise in competitive cyclists

The aim of this investigation was to develop and validate a new method to predict time to exhaustion (pTE) from blood lactate variables measured during a submaximal non-exhaustive constant workload cycling test in professional cyclists. A multiple regression equation to estimate pTE from blood lactate variables measured within the first 10 min of a submaximal test and TE was determined in 40 competitive cyclists. Predicted TE reliability [individual coefficient of variation (CV)] was calculated in eight amateur cyclists who repeated the proposed test three times. Seasonal variations of pTE were monitored in 12 professional cyclists. Validity of pTE was determined by the known-group difference method in 49 professional cyclists. The prediction equation was: log(n)TE = 4.2067 - 0.8221(log(n) B) - 0.2519(log(n) C), where B is the lactate concentration at the 10th minute of the constant workload test and C is the lactate slope calculated between the 5th and 10th minute (adjusted r (2) =0.83, root mean square error in cross validation=23.1%). Predicted TE CV was 11.7%. The pTE obtained at the beginning of the season and the best and worst tests performed during the competitive season, resulted 162, 224 and 103% higher than the basic period test, respectively (P<0.05). Predicted TE was the only parameter discriminating elite from subelite professional cyclists. In conclusion, this study demonstrates that pTE is a valid and practical alternative to incremental tests and direct measures of endurance capacity requiring exhaustive efforts for the evaluation of competitive cyclists.

Maximal lactate steady state determination with a single incremental test exercise

The aim of this study was to determine whether the power output associated with a maximal lactate steady state (MLSS) (.W(MLSS)) can be assessed using a single incremental cycling test. Eleven recreational sportsmen (age: 22+/-1 years, height: 175+/-6 cm, weight: 71+/-5 kg) volunteered to participate in the study. For each subject the first and second ventilatory thresholds (VT(1) and VT(2), respectively) and the power output corresponding to (respiratory exchange ratio) RER=1.00 were determined during an incremental test to exhaustion. Thereafter, each subject performed several 30-min constant load tests to determine MLSS. The workload used in the first constant test was set to the .W(RER=1.00) determined during the incremental test. .W(VT1) (175+/-24 W) and .W(VT2) (265+/-31 W) were significantly different from .W(MLSS )(220+/-36 W). Whereas, .W(RER=1.00) (224+/-33 W) was similar to .W(MLSS). HR, RER and .VE were significantly different between the 10th and the 30th minutes when exercising at .W(RER=1.00) and at .W(MLSS). In contrast, .VO(2) and .VCO(2) were stable over those 30-min constant tests. Power output at VT(1), RER=1.00 and VT(2) were all correlated to .W(MLSS) but the relationship was stronger between RER=1.00 and MLSS (R (2)=0.95). The present study shows that the power output associated with a RER value equal to 1.00 during an incremental test does not differ from that determined for MLSS. Hence, the MLSS can be estimated with a single exercise test.

The concept of maximal lactate steady state: a bridge between biochemistry, physiology and sport science

The maximal lactate steady state (MLSS) is defined as the highest blood lactate concentration (MLSSc) and work load (MLSSw) that can be maintained over time without a continual blood lactate accumulation. A close relationship between endurance sport performance and MLSSw has been reported and the average velocity over a marathon is just below MLSSw. This work rate delineates the low- to high-intensity exercises at which carbohydrates contribute more than 50% of the total energy need and at which the fuel mix switches (crosses over) from predominantly fat to predominantly carbohydrate. The rate of metabolic adenosine triphosphate (ATP) turnover increases as a direct function of metabolic power output and the blood lactate at MLSS represents the highest point in the equilibrium between lactate appearance and disappearance both being equal to the lactate turnover. However, MLSSc has been reported to demonstrate a great variability between individuals (from 2-8 mmol/L) in capillary blood and not to be related to MLSSw. The fate of enhanced lactate clearance in trained individuals has been attributed primarily to oxidation in active muscle and gluconeogenesis in liver. The transport of lactate into and out of the cells is facilitated by monocarboxylate transporters (MCTs) which are transmembrane proteins and which are significantly improved by training. Endurance training increases the expression of MCT1 with intervariable effects on MCT4. The relationship between the concentration of the two MCTs and the performance parameters (i.e. the maximal distance run in 20 minutes) in elite athletes has not yet been reported. However, lactate exchange and removal indirectly estimated with velocity constants of the individual blood lactate recovery has been reported to be related to time to exhaustion at maximal oxygen uptake.

Methods to determine aerobic endurance

Physiological testing of elite athletes requires the correct identification and assessment of sports-specific underlying factors. It is now recognised that performance in long-distance events is determined by maximal oxygen uptake (V(2 max)), energy cost of exercise and the maximal fractional utilisation of V(2 max) in any realised performance or as a corollary a set percentage of V(2 max) that could be endured as long as possible. This later ability is defined as endurance, and more precisely aerobic endurance, since V(2 max) sets the upper limit of aerobic pathway. It should be distinguished from endurance ability or endurance performance, which are synonymous with performance in long-distance events. The present review examines methods available in the literature to assess aerobic endurance. They are numerous and can be classified into two categories, namely direct and indirect methods. Direct methods bring together all indices that allow either a complete or a partial representation of the power-duration relationship, while indirect methods revolve around the determination of the so-called anaerobic threshold (AT). With regard to direct methods, performance in a series of tests provides a more complete and presumably more valid description of the power-duration relationship than performance in a single test, even if both approaches are well correlated with each other. However, the question remains open to determine which systems model should be employed among the several available in the literature, and how to use them in the prescription of training intensities. As for indirect methods, there is quantitative accumulation of data supporting the utilisation of the AT to assess aerobic endurance and to prescribe training intensities. However, it appears that: there is no unique intensity corresponding to the AT, since criteria available in the literature provide inconsistent results; and the non-invasive determination of the AT using ventilatory and heart rate data instead of blood lactate concentration ([La(-)](b)) is not valid. Added to the fact that the AT may not represent the optimal training intensity for elite athletes, it raises doubt on the usefulness of this theory without questioning, however, the usefulness of the whole [La(-)](b)-power curve to assess aerobic endurance and predict performance in long-distance events.

A simple method for individual anaerobic threshold as predictor of max lactate steady state

BACKGROUND

The individual anaerobic threshold (IAT) is defined (18) as the highest metabolic rate where blood lactate (La) concentrations are maintained at a steady-state during prolonged exercise. Stegmann et al.'s (18) method to detect IAT, using La-performance relationship during incremental graded exercise, is based on the assumption that La is in relatively steady state by the end of each 3-min stage of work rate. However, at the end of a 3-min stage, an La steady state (Lass) is not reached (13).

PURPOSE

The present study was designed to investigate whether the IAT should be determined by attributing La value to the antecedent stage (IATa) or to the same stage of its measurement (IATm), then to verify whether this IAT would be a valid indicator of the max Lass during prolonged exercise.

METHODS

Forty-one athletes (21 male and 20 female), regularly involved in different physical training, performed three exercise tests on treadmill. The first one was a 3-min stage incremental test to detect the IATa and IATm. The other two tests were 30-min prolonged tests at the IATa and IATm workload. Lass were present in IATa intensity (about 4.0 mmol x L(-1)) both in male and female athletes, whereas at IATm intensity a Lass was not present and a premature break-off occurred in some cases.

DISCUSSION

This protocol can be useful for practical use because: 1) the method of choosing the anaerobic threshold is easy to apply; 2) it does not require to reach the maximal effort; and 3) although in some cases the IATa could probably underestimate the workload of max Lass, the IATa can be regarded as guideline to define the intensity of endurance training.

Effect of incremental test protocol on the lactate minimum speed

PURPOSE

The purpose of this study was to investigate the effect of altering the initial running speed (RS) in the incremental portion of the lactate minimum test on the lactate minimum speed (LMS).

METHODS

Eight well-trained endurance runners (mean +/- SD age 29.0 +/- 5.4 yr, body mass 72.0 +/- 5.6 kg, VO2max 63.1 +/- 3.8 mL x kg(-1) min(-1)) completed a standard incremental treadmill test for the assessment of the lactate threshold (LT) and VO2max, and eight lactate minimum tests. Following a period of supramaximal exercise, subjects were allowed 8 min of recovery to allow blood [lactate] to peak. Subjects then undertook eight randomly-assigned incremental treadmill tests from different initial running speeds (3.0, 2.5, 2.0, 1.5, 1.0, and 0.5 km x h(-1) below the predetermined RS-LT, at the RS-LT, and at 1.0 km x h(-1) above the RS-LT) with RS increased by 1.0 km x h(-1) every 5 min until volitional fatigue. Blood samples for the determination of blood [lactate] were taken at the end of each stage and the LMS was determined by fitting a spline function to the data.

RESULTS

No LMS could be determined for the two highest initial RS conditions. For the other conditions, the LMS was significantly affected by the initial RS used in the incremental test and varied from 13.8 +/- 0.7 km x h(-1) with an initial RS of 3.0 km x h(-1) below the RS-LT, to 15.8 +/- 0.8 km x h(-1) with an initial RS of 0.5 km x h(-1) below the RS-LT. The LMS was significantly different from the RS-LT (15.4 +/- 0.8 km x h(-1)) (P < 0.05), except when the incremental test started at 1.0 or 1.5 km x h(-1) below the RS-LT.

CONCLUSIONS

These results suggest that the LMS test is not a valid method for estimation of the LT since it is profoundly influenced by the starting speed selected for the incremental portion of the test.

Use of blood lactate measurements for prediction of exercise performance and for control of training. Recommendations for long-distance running

Time over a distance, i.e. speed, is the reference for performance for all events whose rules are based on locomotion in different mechanical constraints. A certain power output has to be maintained during a distance or over time. The energy requirements and metabolic support for optimal performance are functions of the length of the race and the intensity at which it is completed. However, despite the complexity of the regulation of lactate metabolism, blood lactate measurements can be used by coaches for prediction of exercise performance. The anaerobic threshold, commonly defined as the exercise intensity, speed or fraction of maximal oxygen uptake (VO2max) at a fixed blood lactate level or at a maximal lactate steady-state (MLSS), has been accepted as a measure of the endurance. The blood lactate threshold, expressed as a fraction of the velocity associated with VO2max, depends on the relationship between velocity and oxygen uptake (VO2). The measurement of the post-competition blood lactate in short events (lasting 1 to 2 minutes) has been found to be related to the performance in events (400 to 800m in running). Blood lactate levels can be used to assist with determining training exercise intensity. However, to interpret the training effect on the blood lactate profile, the athlete's nutritional state and exercise protocol have also to be controlled. Moreover, improvement of fractional utilisation of VO2max at the MLSS has to be considered among all discriminating factors of the performance, such as the velocity associated with VO2max.

A method for determining the maximal steady state of blood lactate concentration from two levels of submaximal exercise

The aim of this study was to estimate the characteristic exercise intensity (WCL) which produces the maximal steady state of blood lactate concentration (MLSS) from submaximal intensities of 20 min carried out on the same day and separated by 40 min. Ten fit male adults [maximal oxygen uptake (VO2max) 62 (SD 7) ml.min-1.kg-1] exercised for two 30-min periods on a cycle ergometer at 67% (test 1.1) and 82% of VO2max (test 1.2) separated by 40 min. They exercised 4 days later for 30 min at 82% of VO2max without prior exercise (test 2). Blood lactate was collected for determination of lactic acid concentration every 5 min and heart rate and O2 uptake (VO2) were measured every 30 s. There were no significant differences at the 5th, 10th, 15th, 20th, 25th, or 30th min between VO2, lactacidaemia, and heart rate during tests 1.2 and 2. Moreover, we compared the exercise intensities (WCL) which produced the MLSS obtained during tests 1.1 and 1.2 or during tests 1.1 and 2 calculated from differential values of lactic acid blood concentration ([la-]b) between the 30th and the 5th min or between the 20th and the 5th min. There was no significant difference between the different values of WCL [68 (SD 9), 71 (SD 7, 73 (SD 6), 71 (SD 11)% of VO2max] (ANOVA test, P < 0.05). Four subjects ran for 60 min at their WCL determined from periods performed on the same day (test 1.1 and 1.2) and the difference between the [la-]b at 5 min and at 20 min (delta ([la-]b)) was computed.(ABSTRACT TRUNCATED AT 250 WORDS)

Fingertip and venous blood lactate concentration in response to graded treadmill exercise

Fingertip and venous blood lactate concentrations were determined pre-exercise and after 4-min bouts of treadmill running at 2.69, 3.13, 3.58 and 4.03 m s-1 in 14 normal healthy volunteers. A 1-min rest period intervened each exercise period, and was used for the simultaneous sampling of fingertip and venous blood. Compared to pre-exercise, fingertip and venous blood lactate (BLa) concentrations increased significantly (P < 0.05) in a progressive pattern with increasing exercise intensity. Fingertip BLa concentrations were significantly higher (P < 0.05) than venous blood prior to exercise and in response to all four running speeds. Treadmill speed, heart rate and oxygen consumption were significantly lower (P < 0.05) at a BLa concentration of 4 mM when estimated from fingertip blood as compared with venous blood. These results indicate that differences between fingertip and venous blood exist during treadmill exercise and should be considered when lactate determination is employed as a criterion to evaluate and predict performance and when used as a training guide to standardize exercise intensity.

Arterial and venous measurement in resting forearm of metabolic indicators during rest and leg exercise

We compared the levels of various metabolic indicators in arterial and venous forearm blood during maximal treadmill leg exercise, and the subsequent 9 min in nine volunteers aged 31-56 years. At maximal exercise plasma lactate was 13.2 +/- 3.1 mmol l-1 arterially, while venous was 41% lower, but increased more than arterial after exercise. There was a linear relationship between arterial and venous samples during and after exercise, but not at baseline. Plasma pyruvate increased on the arterial side from 49 +/- 8 to 172 +/- 30 mumol l-1 at maximal exercise, maximal venous was 21% lower. Free fatty acids were not different at rest, but decreased during exercise by 52 and 38% on the arterial and venous side. There was no relationship between arterial and venous levels. Changes in these three variables occurred significantly earlier on the arterial side. Arterial cyclic AMP rose from 97.3 +/- 28.4 to 262.7 +/- 67.5 nmol l-1 from rest to exercise, and was linearly inversely related to the decrease in free fatty acids. The mean venous pH was lower than arterial at rest, but was the same as arterial at maximal exercise and after. Thus, venous plasma lactate and pyruvate, but not free fatty acids, are linearly related to arterial measurements during maximal exercise, while pH is identical. Non-working muscle modifies exercise-induced changes, and therefore venous and arterial forearm blood sampling give more information than either alone.