Relative Proximity of Critical Power and Metabolic/Ventilatory Thresholds: Systematic Review and Meta-Analysis.

BACKGROUND: Critical power (CP) has been redefined as the new 'gold standard' that represents the boundary between the heavy- and severe-exercise intensity domains and hence the maximal metabolic steady state (MMSS). However, several other "thresholds", for instance, the maximal lactate steady state [MLSS], ventilatory thresholds [VT1, VT2] and respiratory compensation point [RCP]) have been considered synonymous with CP. OBJECTIVE: This study aimed to systematically review the scientific literature and perform a meta-analysis to determine the degree of correspondence/difference between CP and MLSS, VT1, VT2 and RCP. METHODS: A literature search on 2 databases (Scopus and Web of Science) was conducted on October 2, 2019. After analyzing 356 resultant articles, studies were included if they met the following inclusion criteria: (a) studies were randomized controlled trials, (b) studies included interrelations between CP and VT1, VT2, MLSS, RCP. Articles were excluded if they constituted duplicate articles or did not meet the inclusion criteria. Nine studies met the inclusion criteria and were included in this meta-analysis. This resulted in 104 participants. A random effects weighted meta-analysis with correlation coefficients was used to pool the results. RESULTS: The pooled correlation coefficient of CP and all thresholds analyzed was r = 0.73 (p > 0.00001). The subgroup analysis for each threshold with CP demonstrated significant correlation coefficients of r = 0.80 (95% CI [0.40; 1.21], Z = 3.90, p = 0.0001) for CP & RCP; r = 0.77 (CI 95% = [0.36; 1.18], Z = 3.71, p = 0.0002) for CP & MLSS; r = 0.76 (CI 95% = [0.31; 1.21], Z = 3.32, p = 0.0009) for CP & VT1. However, CP & VT2, r = 0.39 (CI 95% = [- 0.37; 1.15], Z = 1.01, p = 0.31) were not significantly correlated. Despite the significant correlations between CP and VT1, MLSS and RCP these variables and VT2 under- (VT1, 30%; MLSS, 11%) or over-estimated (RCP, 6%; VT2, 21%) CP. CONCLUSION: Regardless of the presence of significant correlations among CP and ventilatory or metabolic thresholds CP differs significantly from each. Thus, logically, if CP represents the best estimate of the heavy-severe exercise intensity transition none of the thresholds considered (i.e., VT1, VT2, MLSS, RCP), at least as determined in the studies analyzed herein, should be considered synonymous with such.

The Relationship between Tactical Positioning and the Race Outcome in 800-M Running at the 2016 Olympic Games and 2017 IAAF World Championship.

The purpose of this analysis was to quantify the probability of achieving a top-3 finishing position during 800-m races at a global championship, based on dispersion of the runners during the first and second laps and the difference in split times between laps. Overall race times, intermediate and finishing positions and 400 m split times were obtained for 43 races over 800 m (21 men's and 22 women's) comprising 334 individual performances, 128 of which resulted in higher positions (top-3) and 206 the remaining positions. Intermediate and final positions along with times, the dispersion of the runners during the intermediate and final splits (SS1 and SS2), as well as differences between the two split times (Dsplits) were calculated. A logistic regression model was created to determine the influence of these factors in achieving a top-3 position. The final position was most strongly associated with SS2, but also with SS1 and Dsplits. The Global Significance Test showed that the model was significant (p < 0.001) with a predictive ability of 91.08% and an area under the curve coefficient of 0.9598. The values of sensitivity and specificity were 96.8% and 82.5%, respectively. The model demonstrated that SS1, SS2 and Dplits explained the finishing position in the 800-m event in global championships.