Evaluation of a sport-specific field test to determine maximal lactate accumulation rate and sprint performance parameters in running

Quittmann, Oliver J.; Appelhans, Daniel; Abel, Thomas; Strüder, Heiko K.

doi:10.1016/j.jsams.2019.08.013

Cited by 19 publications

(65 citation statements)

References 35 publications

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“…In running, the participants performed a 100-m sprint test on an indoor track, including a standardized warm-up of 15 min as recently published [7]. Throughout the sprints, participants were verbally encouraged by the examiners.…”

Section: Designmentioning

confidence: 99%

“…Throughout the sprints, participants were verbally encouraged by the examiners. The time to cover the 100 meters (t 100 ) was determined using a start pedal and a double infrared photoelectric light barrier [7]. The velocity of the athletes was determined using a laser velocity guard (LDM-300-C-SPORT, 100 Hz, Jenoptik, Jena, Germany), installed as previously published [7].…”

Section: Designmentioning

confidence: 99%

“…A f was individually determined using calibrated pictures in a running-specific posture (▶Fig. 1) [7].…”

Section: Instrumentationmentioning

confidence: 99%

“…Lactate kinetics following all-out exercise tests in cycling and running were interpolated using a modified biexponential time function as described in previous research (Eq. 2) [6,7].…”

Section: Instrumentationmentioning

confidence: 99%

“…where La(t) = interpolated lactate concentration at a certain time [mmol•l - As a representation of phosphocreatine metabolism, t alac was determined as the period when power output decreased by 3.5 % (t pmax-3.5 % ) [6,7,9]. The difference between t test and t pmax-3.5 % can be classified as lactic time interval (t lac ).…”

Section: La T = Lamentioning

confidence: 99%

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Maximal Lactate Accumulation Rate in All-out Exercise Differs between Cycling and Running

et al. 2020

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This study aims to compare maximal lactate accumulation rate (V̇ Lamax) and power output (Pmax) between cycling and running in terms of reliability, differences between, and correlations among modalities. Eighteen competitive triathletes performed a 15-s all-out exercise test in cycling and a 100-m sprint test in running. Each test was performed twice and separated by one week. Exercise tests in cycling were performed on an ergometer whereas sprint tests in running were performed on an indoor track. Differences between trials and exercise modality were analyzed using two-way ANOVA. V̇ Lamax (ICC=0.894, ICC=0.868) and Pmax (ICC=0.907, ICC=0.965) attained ‘good’ to ‘excellent’ reliability in both cycling and running, respectively. V̇ Lamax was higher in running (d=0.709, p=0.016) whereas Pmax was lower in running (d=−0.862, p < 0.001). For V̇ Lamax, limits of agreement between modalities ranged from −0.224 to +0.437 mmol·l-1·s-1. Pmax correlated between modalities (r=0.811, p < 0.001), whereas no correlation was found in V̇ Lamax (r=0.418, p=0.084). V̇ Lamax is highly reliable in both modalities and higher in running compared to cycling. Since V̇ Lamax does not correlate between cycling and running, it should be determined sport-specifically.

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Section: Designmentioning

confidence: 99%

Section: Designmentioning

confidence: 99%

“…A f was individually determined using calibrated pictures in a running-specific posture (▶Fig. 1) [7].…”

Section: Instrumentationmentioning

confidence: 99%

“…Lactate kinetics following all-out exercise tests in cycling and running were interpolated using a modified biexponential time function as described in previous research (Eq. 2) [6,7].…”

Section: Instrumentationmentioning

confidence: 99%

Section: La T = Lamentioning

confidence: 99%

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Maximal Lactate Accumulation Rate in All-out Exercise Differs between Cycling and Running

et al. 2020

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Identifying physiological determinants of 800 m running performance using post-exercise blood lactate kinetics

Watanabe,

Inaba,

van Rassel

et al. 2024

Eur J Appl Physiol

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Purpose The aims of the present study were to investigate blood lactate kinetics following high intensity exercise and identify the physiological determinants of 800 m running performance. Methods Fourteen competitive 800 m runners performed two running tests. First, participants performed a multistage graded exercise test to determine physiological indicators related to endurance performance. Second, participants performed four to six 30-s high intensity running bouts to determine post-exercise blood lactate kinetics. Using a biexponential time function, lactate exchange ability (γ1), lactate removal ability (γ2), and the quantity of lactate accumulated (QLaA) were calculated from individual blood lactate recovery data. Results 800 m running performance was significantly correlated with peak oxygen consumption (r = −0.794), γ1 and γ2 at 800 m race pace (r = −0.604 and −0.845, respectively), and QLaA at maximal running speed (r = −0.657). $${\dot{\text{V}}}$$ V ˙ O2peak and γ2 at 800 m race pace explained 83% of the variance in 800 m running performance. Conclusion Our results indicate that (1) a high capacity to exchange and remove lactate, (2) a high capacity for short-term lactate accumulation and, (3) peak oxygen consumption, are critical elements of 800 m running performance. Accordingly, while lactate has primarily been utilized as a performance indicator for long-distance running, post-exercise lactate kinetics may also prove valuable as a performance determinant in middle-distance running.

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

et al. 2022

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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.

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Evaluation of a sport-specific field test to determine maximal lactate accumulation rate and sprint performance parameters in running

Cited by 19 publications

References 35 publications

Maximal Lactate Accumulation Rate in All-out Exercise Differs between Cycling and Running

Maximal Lactate Accumulation Rate in All-out Exercise Differs between Cycling and Running

Identifying physiological determinants of 800 m running performance using post-exercise blood lactate kinetics

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

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