Purpose: Plasma N-terminal pro-B-type natriuretic peptide (NT-proBNP) and cardiac troponin T levels show a transient increase after marathon running. The aim of this study was to investigate whether running duration influences the patterns of changes in cardiac biomarkers. Methods: Twenty participants with fast and slow finishing times were included in the study. Blood samples were taken before the marathon race, immediately after, and 24 hours after the race. Samples were analyzed for NT-proBNP and cardiac troponin T concentration. Furthermore, a complete blood cell count was performed. Results: After the marathon race, the fast and slow runners showed similar changes of NT-proBNP and cardiac troponin T (ie, a transient increase). Curve estimation regression analysis showed a curvilinear relationship (quadratic model) between running times and NT-proBNP increments immediately after the race, with less of an increase in the very fast and the very slow runners (r 2 = .359, P = .023). NT-proBNP increments immediately after the race were correlated to the decline 24 hours after the marathon (r = −.612, P = .004). Conclusions: This study indicates that NT-proBNP release immediately after marathon running varies in a curvilinear fashion with running time. It is speculated that low NT-proBNP release is associated with training adaptation in most elite runners and the relatively low cardiac stress in the slowest (but experienced) runners. The combination of less adaptation and relatively large cardiac wall and metabolic stress may explain the highest NT-proBNP values in runners with average running times. In addition, NT-proBNP decrements 24 hours after the race depend primarily on the values reached after the marathon and not on running time.
Natthapon Traiperm, Rungchai Chaunchaiyakul, Martin Burtscher, and Hannes Gatterer
Lachlan P. James, Haresh Suppiah, Michael R. McGuigan, and David L. Carey
Purpose: Dozens of variables can be derived from the countermovement jump (CMJ). However, this does not guarantee an increase in useful information because many of the variables are highly correlated. Furthermore, practitioners should seek to find the simplest solution to performance testing and reporting challenges. The purpose of this investigation was to show how to apply dimensionality reduction to CMJ data with a view to offer practitioners solutions to aid applications in high-performance settings. Methods: The data were collected from 3 cohorts using 3 different devices. Dimensionality reduction was undertaken on the extracted variables by way of principal component analysis and maximum likelihood factor analysis. Results: Over 90% of the variance in each CMJ data set could be explained in 3 or 4 principal components. Similarly, 2 to 3 factors could successfully explain the CMJ. Conclusions: The application of dimensional reduction through principal component analysis and factor analysis allowed for the identification of key variables that strongly contributed to distinct aspects of jump performance. Practitioners and scientists can consider the information derived from these procedures in several ways to streamline the transfer of CMJ test information.
Gennaro Boccia, Marco Cardinale, and Paolo Riccardo Brustio
Purpose: This study investigated (1) the transition rate of elite world-class throwers, (2) the age of peak performance in either elite junior and/or elite senior athletes, and (3) if relative age effect (RAE) influences the chance of being considered elite in junior and/or senior category. Methods: The career performance trajectories of 5108 throwers (49.9% females) were extracted from the World Athletics database. The authors identified throwers who had reached the elite level (operationally defined as the World all-time top 50 ranked for each age category) in either junior and/or senior category and calculated the junior-to-senior transition rate. The age of peak performance and the RAE were also investigated. Results: The transition rate at 16 and 18 years of age was 6% and 12% in males and 16% and 24% in females, respectively. Furthermore, elite senior throwers reached their personal best later in life than elite junior throwers. The athletes of both genders considered elite in the junior category showed a large RAE. Interestingly, male athletes who reached the elite level in senior category also showed appreciable RAE. Conclusions: Only a few of the athletes who reach the top 50 in the world at 16 or 18 years of age manage to become elite senior athletes, underlining that success at the beginning of an athletic career does not predict success in the athlete’s senior career. Moreover, data suggest that being relatively older may confer a benefit across the whole career of male throwers.
Gabriele Gallo, Luca Filipas, Michele Tornaghi, Mattia Garbin, Roberto Codella, Nicola Lovecchio, and Daniele Zaccaria
Purpose: To analyze the anthropometric and physiological characteristics of competitive 15- to 16-year-old young male road cyclists and scale them according to a dichotomous category of successful/unsuccessful riders. Methods: A total of 103 15- to 16-year-old male road cyclists competing in the Italian national under 17 category performed a laboratory incremental exercise test during the in-season period. Age, height, body mass, body mass index, peak height velocity, and absolute and relative power output at 2 mmol/L and 4 mmol/L of blood lactate concentration were compared between 2 subgroups, including those scoring at least 1 point (successful, n = 70) and those that did not score points (unsuccessful, n = 61) in the general season ranking. Results: Successful and unsuccessful riders did not differ anthropometrically. Successful riders recorded significantly higher absolute and relative power output at 2 mmol/L and 4 mmol/L of blood lactate concentration compared with unsuccessful riders. Successful riders were also significantly older and had advanced biological maturation compared with their unsuccessful counterparts. Conclusion: Power associated with blood lactate profiles, together with chronological age and peak height velocity, plays an important role in determining race results in under 17 road cycling. Physiological tests could be helpful for coaches to measure these performance predictors.
Roberto A. González-Fimbres, German Hernández-Cruz, and Andrew A. Flatt
Purpose: To assess heart rate (HR) variability responses to various markers of training load, quantify associations between HR variability and fitness, and compare responses and associations between 1-minute ultrashort and 5-minute criterion measures among a girls’ field hockey team. Methods: A total of 11 players (16.8 [1.1] y) recorded the logarithm of the root mean square of successive differences (LnRMSSD) daily throughout a 4-week training camp. The weekly mean (LnRMSSDM) and coefficient of variation (LnRMSSDCV) were analyzed. The internal training load (ITL) and external training load (ETL) were acquired with session HR and accelerometry, respectively. Speed, agility, repeated sprint ability, and intermittent fitness were assessed precamp and postcamp. Results: Similar increases in the ultrashort and criterion LnRMSSDM were observed in week 3 versus week 1 (P < .05–.06, effect size [ES] = 0.28 to 0.36). The ultrashort and criterion LnRMSSDCV showed small ES reductions in week 2 (ES = −0.40 to −0.50), moderate reductions in week 3 (ES = −0.61 to −0.72), and small reductions in week 4 (ES = −0.42 to −0.51) versus week 1 (P > .05). Strong agreement was observed between the ultrashort and criterion values (intraclass correlation coefficient = .979). The ITL:ETL ratio peaked in week 1 (P < .05 vs weeks 2–4), displaying a weekly pattern similar to LnRMSSDCV, and inversely similar to LnRMSSDM. Changes in the ultrashort and criterion LnRMSSDCV from week 1 to 4 were associated with ITL (P < .01). The ultrashort and criterion LnRMSSDCV in week 4 were associated (P < .05) with postcamp fitness. Conclusions: The ultrashort HR variability parameters paralleled the criterion responses, and the associations with ITL and fitness were similar in magnitude.
Øyvind Sandbakk, Thomas Haugen, and Gertjan Ettema
Purpose: To provide novel insight regarding the influence of exercise modality on training load management by (1) providing a theoretical framework for the impact of physiological and biomechanical mechanisms associated with different exercise modalities on training load management in endurance exercise and (2) comparing effort-matched low-intensity training sessions performed by top-level athletes in endurance sports with similar energy demands. Practical Applications and Conclusions: The ability to perform endurance training with manageable muscular loads and low injury risks in different exercise modalities is influenced both by mechanical factors and by muscular state and coordination, which interrelate in optimizing power production while reducing friction and/or drag. Consequently, the choice of exercise modality in endurance training influences effort beyond commonly used external and internal load measurements and should be considered alongside duration, frequency, and intensity when managing training load. By comparing effort-matched low- to moderate-intensity sessions performed by top-level athletes in endurance sports, this study exemplifies how endurance exercise with varying modalities leads to different tolerable volumes. For example, the weight-bearing exercise and high-impact forces in long-distance running put high loads on muscles and tendons, leading to relatively low training volume tolerance. In speed skating, the flexed knee and hip position required for effective speed skating leads to occlusion of thighs and low volume tolerance. In contrast, the non-weight-bearing, low-contraction exercises in cycling or swimming allow for large volumes in the specific exercise modalities. Overall, these differences have major implications on training load management in sports.
Arnaud Hays, Caroline Nicol, Denis Bertin, Romain Hardouin, and Jeanick Brisswalter
Objectives: To identify relevant physiological, mechanical, and strength indices to improve the evaluation of elite mountain bike riders competing in the current Cross-Country Olympic (XCO) format. Methods: Considering the evolution of the XCO race format over the last decade, the present testing protocol adopted a battery of complementary laboratory cycling tests: a maximal aerobic consumption, a force–velocity test, and a multi-short-sprint test. A group of 33 elite-level XCO riders completed the entire testing protocol and at least 5 international competitions. Results: Very large correlations were found between the XCO performance and maximal aerobic power output (r = .78; P < .05), power at the second ventilation threshold (r = .83; P < .05), maximal pedaling force (r = .77; P < .05), and maximum power in the sixth sprint (r = .87; P < .05) of the multi-short-sprint test. A multiple regression model revealed that the normalized XCO performance was predicted at 89.2% (F 3,29 = 89.507; r = .95; P < .001) by maximum power in the sixth sprint (β = 0.602; P < .001), maximal pedaling rate (β = 0.309; P < .001), and relative maximal aerobic power output (β = 0.329; P < .001). Discussion: Confirming our expectations, the current XCO performance was highly correlated with a series of physiological and mechanical parameters reflecting the high level of acyclic and intermittent solicitation of both aerobic and anaerobic metabolic pathways and the required qualities of maximal force and velocity. Conclusion: The combination of physiological, mechanical, and strength characteristics may thus improve the prediction of elite XCO cyclists’ performance. It seems of interest to evaluate the ability to repeatedly produce brief intensive efforts with short active recovery periods.