Modifications of the Dmax method in comparison to the maximal lactate steady state in young male athletes

Zwingmann, Lukas; Strütt, Sarah; Martin, Agnès; Volmary, Prisca; Bloch, Wilhelm; Wahl, Patrick

doi:10.1080/00913847.2018.1546103

Cited by 15 publications

(26 citation statements)

References 29 publications

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“…In contrast to the presented findings, a recent study carried out by Jamnick et al [ 27 ] and Zwingmann et al [ 28 ] showed that the ModD max method is a good MLSS determinant for cyclists and triathletes. However, their studies involved athletes with a lower sports performance than those examined in our study (MLSS: 264 W and 229 W vs. 298 W), which may have led to the discrepancies in the obtained results.…”

Section: Discussioncontrasting

confidence: 99%

“…Given the above, we suggest that the ModD max method cannot be used to indirectly determine MLSS in elite cyclists. ModD max is likely to be useful in people with lower levels of sports performance [ 26 , 28 ], but this aspect requires further research.…”

Section: Discussionmentioning

confidence: 99%

“…Determination of MLSS requires the performance of a series of constant-intensity tests during multiple laboratory visits, which in practice is burdensome and may disrupt the athletes’ training program. Therefore, attempts are made to determine MLSS indirectly based on AT evaluated during a single GXT until volitional exhaustion [ 22 – 28 ]. However, the results comparing various concepts of AT with MLSS are conflicting [ 22 – 28 ].…”

Section: Introductionmentioning

confidence: 99%

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Comparison of maximal lactate steady state with anaerobic threshold determined by various methods based on graded exercise test with 3-minute stages in elite cyclists

Płoszczyca

Jazic

Piotrowicz

et al. 2020

BMC Sports Sci Med Rehabil

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Background The maximal lactate steady state (MLSS) is defined as the highest workload that can be maintained for a longer period of time without continued blood lactate (LA) accumulation. MLSS is one of the physiological indicators of aerobic performance. However, determination of MLSS requires the performance of a series of constant-intensity tests during multiple laboratory visits. Therefore, attempts are made to determine MLSS indirectly by means of anaerobic threshold (AT) evaluated during a single graded exercise test (GXT) until volitional exhaustion. The aim of our study was to verify whether AT determined by maximal deviation (Dmax), modified maximal deviation (ModDmax), baseline LA concentration + 1 mmol/l (+ 1 mmol/l), individual anaerobic threshold (IAT), onset of blood lactate accumulation (OBLA4mmol/l) and V-slope methods based on GXT with 3-min stages provide valid estimates of MLSS in elite cyclists. Methods Twelve elite male cyclists (71.3 ± 3.6 ml/kg/min) completed GXT (the increase by 40 W every 3 min) to establish the AT (by Dmax, ModDmax, + 1 mmol/l, IAT, OBLA4mmol/l and V-slope methods). Next, a series of 30-min constant-load tests to determine MLSS was performed. Agreement between the MLSS and workload (WR) at AT was evaluated using the Bland–Altman method. Results The analysis revealed a very high (rs > 0.90, p < 0.001) correlation between WRMLSS and WRDmax and WRIAT. The other AT methods were highly (rs > 0.70) correlated with MLSS except for OBLA4mmol/l (rs = 0.67). The Bland-Altman analysis revealed the highest agreement with MLSS for the Dmax, IAT and + 1 mmol/l methods. Mean difference between WRMLSS and WRDmax, WRIAT and WR+1mmol/l was 1.7 ± 3.9 W, 4.3 ± 7.9 W and 6.7 ± 17.2 W, respectively. Furthermore, the WRDmax and WRIAT had the lowest limits of agreement with the WRMLSS. The ModDmax and OBLA4mmol/l methods overestimated MLSS by 31.7 ± 18.5 W and 43.3 ± 17.8 W, respectively. The V-slope method underestimated MLSS by 36.2 ± 10.9 W. Conclusions The AT determined by Dmax and IAT methods based on the cycling GXT with 3-min stages provides a high agreement with the MLSS in elite cyclists. Despite the high correlation with MLSS and low mean difference, the AT determined by + 1 mmol/l method may highly overestimate or underestimate MLSS in individual subjects. The individual MLSS cannot be properly estimated by V-slope, ModDmax and OBLA4mmol/l methods.

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Section: Discussioncontrasting

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Comparison of maximal lactate steady state with anaerobic threshold determined by various methods based on graded exercise test with 3-minute stages in elite cyclists

Płoszczyca

Jazic

Piotrowicz

et al. 2020

BMC Sports Sci Med Rehabil

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“…Calculation of sLT using the D-max method resulted in lower speed compared to sMLSS in both children and adolescent swimmers. This observation is in accordance with recent studies in which D-max method result to lower power output or running speed compared to MLSS in male cyclists and runners [21,35]. The validity of LT F method versus MLSS has been successfully verified in a previous study conducted in adult swimmers [10] and this was confirmed in adolescents, but not children swimmers in the present study.…”

Section: Discussionsupporting

confidence: 93%

“…Consequently, a method that may be used for LT should be in agreement with MLSS but may not be appropriate for all ages, because of different lactate kinetics and maximal lactate values [20]. Lactate kinetics may alter the inflection point of the speed vs. lactate concentration curve, while peak lactate values may alter the slope of regression lines used for LT calculation [21].…”

Section: Introductionmentioning

confidence: 99%

Lactate Threshold Evaluation in Swimmers: The Importance of Age and Method

Nikitakis

Toubekis

2021

Int J Sports Med

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The purpose of the study was to define the most appropriate method for the calculation of the speed corresponding to lactate threshold (sLT) in male swimmers. Eight boys and eight adolescents (age: 11.4±0.5 and 15.8±0.8 years) performed 7×200-m swimming front-crawl and after drawing the speed vs. lactate curve, the sLTs were calculated using five methods: i) the intersection of two linear regression lines, ii) visual inspection, iii) D-max, iv) D-max modified, v) intersection of combined linear and exponential regression lines. All methods were compared to the speed corresponding to maximal lactate steady state (sMLSS). Two to four 30-min efforts of continuous swimming at imposed constant pace were used for sMLSS calculation. In both groups, speed of D-max modified was similar to sMLSS (children, 1.061±0.073 vs. sMLSS: 1.071±0.072 m·s−1; p>0.05; effect size: ES=0.15, small; adolescents, 1.318±0.060 vs. sMLSS: 1.284±0.047 m·s−1; p>0.05; ES=0.64, medium). In adolescents, sLT calculated by intersection of two regression lines and by visual inspection presented medium ES (0.22–0.24) and were no different to sMLSS (1.296 ± 0.051, 1.295±0.053 m·s−1, p>0.05). When testing children, D-max modified is the most appropriate method to estimate sMLSS. The intersection of the linear regression lines and visual inspection are suggested for sMLSS determination in adolescents.

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Modeling lactate threshold in young squad athletes: influence of sex, maximal oxygen uptake, and cost of running

Keller

Zwingmann

et al. 2022

Eur J Appl Physiol

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Purpose This study aimed to investigate: 1. The influence of sex and age on the accuracy of the classical model of endurance performance, including maximal oxygen uptake ($$\dot{V}\mathrm{O}_{2}\mathrm{peak}$$ V ˙ O 2 peak ), its fraction (LT2%), and cost of running (CR), for calculating running speed at lactate threshold 2 (vLT2) in young athletes. 2. The impact of different CR determination methods on the accuracy of the model. 3. The contributions of $$\dot{V}\mathrm{O}_{2}\mathrm{peak}$$ V ˙ O 2 peak , LT2%, and CR to vLT2 in different sexes. Methods 45 male and 55 female young squad athletes from different sports (age: 15.4 ± 1.3 years; $$\dot{V}\mathrm{O}_{2}\mathrm{peak}$$ V ˙ O 2 peak : 51.4 ± 6.8 $$\hbox {mL} \cdot \hbox {kg}^{-1} \cdot \hbox {min}^{-1}$$ mL · kg - 1 · min - 1 ) performed an incremental treadmill test to determine $$\dot{V}\mathrm{O}_{2}\mathrm{peak}$$ V ˙ O 2 peak , LT2%, CR, and vLT2. CR was assessed at a fixed running speed (2.8 $$ \hbox {m} \cdot \hbox {s}^{-1} $$ m · s - 1 ), at lactate threshold 1 (LT1), and at 80% of $$\dot{V}\mathrm{O}_{2}\mathrm{peak}$$ V ˙ O 2 peak , respectively. Results Experimentally determined and modeled vLT2 were highly consistent independent of sex and age (ICC $$\ge$$ ≥ 0.959). The accuracy of vLT2 modeling was improved by reducing random variation using individualized CR at 80% $$\dot{V}\mathrm{O}_{2}\mathrm{peak}$$ V ˙ O 2 peak (± 4%) compared to CR at LT1 (± 7%) and at a fixed speed (± 8%). 97% of the total variance of vLT2 was explained by $$\dot{V}\mathrm{O}_{2}\mathrm{peak}$$ V ˙ O 2 peak , LT2%, and CR. While $$\dot{V}\mathrm{O}_{2}\mathrm{peak}$$ V ˙ O 2 peak and CR showed the highest unique (96.5% and 31.9% of total $$R^2$$ R 2 , respectively) and common (– 31.6%) contributions to the regression model, LT2% made the smallest contribution (7.5%). Conclusion Our findings indicate: 1. High accuracy of the classical model of endurance performance in calculating vLT2 in young athletes independent of age and sex. 2. The importance of work rate selection in determining CR to accurately predict vLT2. 3. The largest contribution of $$\dot{V}\mathrm{O}_{2}\mathrm{peak}$$ V ˙ O 2 peak and CR to vLT2, the latter being more important in female athletes than in males, and the least contribution of LT2%.

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Modifications of the Dmax method in comparison to the maximal lactate steady state in young male athletes

Cited by 15 publications

References 29 publications

Comparison of maximal lactate steady state with anaerobic threshold determined by various methods based on graded exercise test with 3-minute stages in elite cyclists

Comparison of maximal lactate steady state with anaerobic threshold determined by various methods based on graded exercise test with 3-minute stages in elite cyclists

Lactate Threshold Evaluation in Swimmers: The Importance of Age and Method

Modeling lactate threshold in young squad athletes: influence of sex, maximal oxygen uptake, and cost of running

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