Reliability of peak running speeds obtained from different incremental treadmill protocols

Novel track field test to determine Vpeak, relationship with treadmill test and 10-km running performance in trained endurance runners

Objectives

The aim of this study was to determine the peak running velocity on the track field (V_{peak_TF}) based on the laboratory treadmill test (V_{peak_T}), and relate the V_peak values as well as their correlation with the 10-km running performance in trained endurance runners.

Method

Twenty male trained endurance runners (age: 29.5 ± 5.3 years; V̇O_2max: 67.5±17.6 ml · kg^-1·min^-1) performed three maximum incremental tests to determine the V_peak: one for V_{peak_T} determination and two to obtain V_{peak_TF} on the official track field (400 m), and a 10-km running performance. During the incremental tests, maximum heart rate (HR_max), maximal rating of perceived exertion (RPE_max), and peak lactate concentration (LA_peak) were determined.

Results

The results showed significant difference between the V_{peak_TF} and V_{peak_T} (18.1 ± 1.2 vs. 19.2 ± 1.5 km·h^-1, respectively), as well as the total time of the tests, the distance traveled and the RPE_max determined during the tests. A high correlation was observed between the V_peak values (r = 0.94), and between V_{peak_TF} and V_{peak_T} with 10-km running performance (r = -0.95 vs. r = -0.89, respectively).

Conclusions

The good agreement and association with V_{peak_T} and high correlation with 10-km running performance demonstrate that the novel track field test is efficient for V_{peak_TF} determination.

Reliability of Peak Running Velocity Obtained on the Track Field in Runners of Different Performance Levels

The aim of this study was to verify the reliability of peak running velocity obtained on the track field (V_{peak_TF}) in runners of different performance levels. 39 male endurance runners were divided into two groups: trained runners (TR; n = 22; 10-km time running performance of 35.2 ± 1.7 min), and recreational runners (RR; n = 17; 10-km time running performance of 51.3 ± 4.8 min). They performed three maximal incremental running tests on the official track field (400 m), with an interval of 1 week between trials to determine the reliability of V_{peak_T}. The V_{peak_TF} showed high reliability, presenting an intraclass correlation coefficient and coefficient of variation of 0.97 and 1.28%, and 0.90 and 1.24% for TR and RR, respectively. Both TR and RR showed lowest bias and limits of agreement between test and retest (V_{peak_TF1} and V_{peak_TF2}). In addition, there was no statistical test-retest difference for V_{peak_TF}. In addition, the HR and RPE submaximal values were reliable for both TR and RR. Therefore, the V_{peak_TF} showed high reliability in both TR and RR. These findings reinforce that the protocol for determining V_{peak_TF}, using increments of 1 km h^–1 every 3 min is reliable regardless of the performance level of the runners.

Peak Running Velocity or Critical Speed Under Field Conditions: Which Best Predicts 5-km Running Performance in Recreational Runners?

This study aimed to examine which variable, between the peak running velocity determined on the track field (V_{peak_TF}) and critical speed (CS), is the best predictor of the 5-km running performance in recreational runners. Twenty-five males performed three tests to determine the V_{peak_TF}, CS, and 5-km running performance on the track field, with a minimal interval of 48 h between each test. The V_{peak_TF} protocol started with a velocity of 8 km⋅h^–1, followed by an increase of 1 km⋅h^–1 every 3 min until volitional exhaustion, which was controlled by sound signals, with cones at every 25 m indicating when the participants were required to pass the cone’s position to maintain the required velocity. The participants performed three time trials (TTs) (1: 2,600 m; 2: 1,800 m; and 3: 1,000 m) on the same day, with a 30-min rest period to determine the CS through the combinations of three (CS₁,₂,₃) and two TTs (CS₁,₂, CS₁,₃, and CS₂,₃). The 5-km running performance time was recorded to determine the test duration, and the mean velocity (MV) was calculated. There was a significant difference observed between the V_{peak_TF} and the MV 5-km running performance. However, no differences were found between the CS values and the MV 5-km running performance. A correlation was observed between the V_{peak_TF} (R = −0.90), CS₁,₂,₃ (R = −0.95), CS₁,₃ (R = −0.95), and the 5-km running performance time. Linear regression indicated that the V_{peak_TF} (R² = 0.82), CS₁,₂,₃ (R² = 0.90), and CS₁,₃ (R² = 0.90) significantly predicted the 5-km running performance time. The CS results showed a higher predictive power for the 5-km running performance, slightly better than the V_{peak_TF}. Also, CS₁,₂,₃ and the CS₁,₃ presented the highest predictive power for the 5-km running performance of recreational runners.

On-field prediction vs monitoring of aerobic capacity markers using submaximal lactate and heart rate measures

This study aimed to validate the use of a single blood lactate concentration measurement taken following a 5-minute running bout at 10 km·h^-1 (BLC₁₀ ) and the speed associated with 90% of maximal heart rate (S₉₀ ) to predict and monitor fixed blood lactate concentration (FBLC) thresholds in athletes. Three complementary studies were undertaken. Study I: A cross-sectional study examining the associations of BLC₁₀ and S₉₀ with running speeds at FBLC of 3 (S3mM) and 4 mmol·L^-1 (S4mM) in 100 athletes. Study II: A cross-validation study assessing the predictive capacity of BLC₁₀ and S₉₀ to estimate FBLC thresholds in real practice. Study III: A longitudinal study examining whether training-induced changes in FBLC thresholds could be monitored using BLC₁₀ and S₉₀ in 80 athletes tested before and after an intensified training period. Study I: BLC₁₀ (r=-.87 to -.89) and S₉₀ (r=.73-.79) were very largely (P<.001) related to FBLC thresholds. Study II: Predictive models yielded robust correlations between estimated and measured FBLC thresholds (r=.75-.91; P<.001). The limits of agreements, however, revealed that prediction of FBLC thresholds could be biased up to 9%-15%. Study III: BLC₁₀ was very largely related to training-induced changes in FBLC thresholds (r=-.72 to -.76; P<.001). Increases in S₉₀ were associated with improvements in FBLC thresholds, but decreases in S₉₀ led to unclear changes in FBLC thresholds. This study supports the use of BLC₁₀ as a simple, low-cost, non-fatiguing, and time-efficient functional variable to monitor, but not predict, FBLC thresholds in athletes. The present results also question the use of S₉₀ to detect declines in endurance performance.

Peak velocity and its time limit are as good as the velocity associated with VO 2max for training prescription in runners

This study compared the effects of 4 weeks of training prescribed by peak velocity (V _peak ) or velocity associated with maximum oxygen uptake (vVO _2max ) in moderately trained endurance runners. Study participants were 14 runners (18–35 years) randomized into 2 groups, named group VO ₂ (GVO ₂ ) and group V _peak (GVP). The GVO ₂ had training prescribed by vVO _2max and its time limit (t _lim ), whereas the GVP had training prescribed by V _peak and its t _lim . Four tests were performed on a treadmill: 2 maximum incremental for V _peak and vVO _2max and 2 for their t _lim . Performance (10 km) was evaluated on a 400 m track. Evaluations were repeated after 4 weeks of endurance training. The results showed a significant effect of training on V _peak [GVP (16.7±1.2 – 17.6±1.5 km ^. h ⁻¹ ), GVO ₂ (17.1±1.9–17.7±1.6 km·h ⁻¹ )]; vVO _2max [GVP (16.4±1.4–17.0±1.3 km·h ⁻¹ ), GVO ₂ (17.2±1.7–17.5±1.9 km·h ⁻¹ )]; and 10 km performance [GVP (41.3±2.4–39.9±2.7 min), GVO ₂ (40.1±3.4–39.2±2.9 min)]. The V _peak highly correlated with performance in both pre- and post-training in GVP (–0.97;–0.86) and GVO ₂ (–0.95;–0.94), as well as with vVO _2max in GVP (–0.82;–0.88) and GVO ₂ (–0.99; –0.98). It is concluded that training prescribed by V _peak promoted similar improvements compared to training prescribed by vVO _2max . The use of V _peak is recommended due to its practical application and the low cost of determination.

The influence of the regression model and final speed criteria on the reliability of lactate threshold determined by the Dmax method in endurance-trained runners

Few studies verified the reliability of the lactate threshold determined by Dmax method (LT_Dmax) in runners and it remains unclear the effect of the regression model and the final speed on the reliability of LT_Dmax. This study aimed to examine the test-retest reliability of the speed at LT_Dmax in runners, considering the effects of the regression models (exponential-plus-constant vs third-order polynomial) and final speed criteria (complete vs proportional). Seventeen male, recreational runners performed 2 identical incremental exercise tests, with increments of 1 km·h^-1 each for 3 min on treadmill to determine peak treadmill speed (V_peak) and lactate threshold. Earlobe capillary blood samples were collected during rest between the stages. The V_peak was defined as the speed of the last complete stage (complete final speed criterion) and as the speed of the last complete stage added to the fraction of the incomplete stage (proportional final speed criterion). Lactate threshold was determined from exponential-plus-constant and from third-order polynomial regression models with both complete and proportional final speed criteria and from fixed blood lactate level of 3.5 mmol·L^-1 (LT_3.5mM). The LT_Dmax obtained from the exponential-plus-constant regression model presented higher reliability (coefficient of variation (CV) ≤ 3.7%) than the LT_Dmax calculated from the third-order polynomial regression model (CV ≤ 5.8%) and LT_3.5mM (CV = 5.4%). The proportional final speed criterion is more appropriate when using the exponential-plus-constant regression model, but less appropriate when using the third-order polynomial regression model. In conclusion, exponential-plus-constant using the proportional final speed criterion is preferred over LT_3.5mM and over third-order polynomial regression model to determine a reliable LT_Dmax.