Acute and short-term response to different loading conditions during resisted sprint training

Acute and Short-Term Response to Different Loading Conditions During Resisted Sprint Training Purpose: To analyze the acute and short-term physical and metabolic responses to resisted sprint training with 5 different loading conditions (0%, 20%, 40%, 60%, and 80% body mass). Methods: Fifteen male participants performed 8 × 20-m sprints with 2-minute rests between sprints with 5 different loading conditions. Subjects performed a battery of tests (creatine kinase and lactate concentrations, countermovement jump, 20-m sprint, and isokinetic knee extension and flexion contractions) at 3 different time points (preexercise [PRE], postexercise [POST], and 24-h postexercise [POST24H]). Results: Results revealed significant increases in blood lactate for all loading conditions; however, as sled loadings increased, higher blood lactate concentrations and increments in sprint times during the training session were observed. Significant increases in creatine kinase concentration were observed from PRE to POST24H for all loading conditions. Concerning physical performance, significant decreases in countermovement-jump height from PRE to POST were found for all loading conditions. In addition, significant decreases in 20-m sprint performance from PRE to POST were observed for 0% (P = .05) and 80% (P = .02). No significant differences with PRE were observed for the physicalperformance variables at POST24H, except for 20% load, which induced a significant decrease in mean power during knee flexion (P = .03). Conclusions: These results suggest that the higher the load used during resisted sprint training, the higher the physicalperformance impairments and metabolic response produced, although all loading conditions led to a complete recovery of sprint performance at POST24H. Keywords: sled towing, running, fatigue, lactate, muscle damage, recovery Introduction One of the most commenly used resisted sprint methods is weighted sled training (consisting of a sled device attached to the athlete by a chest or waist harness). This methodology requires greater demand for horizontal forces evoked by the mass of a weighted sled together with the resulting friction between the sled and the ground surface.1 Some of the mechanisms by which this training method induces improvements in sprint performance are related to an increase in (1) the horizontal force production during each ground contact,2 (2) the stride length in the acceleration phase,3 and (3) the maximal velocity.4 In a recent review, Alcaraz et al5 suggested that resisted sprint training is an effective method for the development of sprint performance, mainly in the early acceleration phase (≤10 m), with little impact in the maximum velocity phase (≥20 m). Energy for muscle contraction during brief maximal exercise (≤10 s) is primarily derived from the breakdown of stored muscle phosphagen, such as adenosine triphosphate and phosphocreatine, and anaerobic glycolysis.6,7 When short sprints are repeated during training sessions, reduction in adenosine triphosphate concentration, loss of adenine nucleotides,8 and increased levels of superoxide radicals and creatine kinase (CK) may occur, eventually evoking muscle damage and impairment in muscle force production.9,10 In addition, from a metabolic point of view, fatigue may be explained as a result of hydrogen ion (H+) accumulation and increase in inorganic phosphate levels.11 In this sense, significant increases in lactate levels after running sprints over distances of 40 and 60 m have been found.12,13 On the other hand, fatigue has been described as any exercise-induced reduction in the maximal voluntary force or power produced by a muscle or a muscle group.14 In this line, loss of running velocity and countermovement jump (CMJ) height are considered as good markers of fatigue during sprint training in unresisted conditions.12,13 Moreover, previous studies have also shown a relationship between blood lactate concentration and CMJ height loss during typical 400 m or repeated sprints sessions.15,16 Studies analyzing exercise-induced muscle damage following repeated unloaded sprints reported increases in CK activity together with impairment on the neuromuscular function.17–19 Despite the widespread use of resisted sprint training, to our knowledge, no previous research has examined the acute effects of this training method on metabolic response, muscle damage, and impairments in athletic performance. Despite the scientific attention received by sled towing, there still exists controversy over the load that should be used to maximize gains in sprint performance.5,20 An external load about 10% to 12.5% of body mass (BM), which induces about 10% of decrement in unloaded velocity while allowing to maintain the sprint technique, has been typically recommended.2,21–23 However, more recently, it has been suggested that heavier loads (≈80% BM) should be used to improve sprinting acceleration, as they allow athletes to produce greater horizontal force in a forward-oriented body position throughout the sprint.24,25 Morin et al25 tested the use of very heavy sled load (80% BM) in soccer players and observed a substantial, increased horizontal force production compared with nonresisted sprinting. However, only trivial between-group differences were observed for power output and sprint performance. In addition, Haugen et al26 proposed that heavy resisted sprinting is likely more appropriate for sports where the athletes are required to perform brief sprints while moving an external mass (eg, bobsleigh). Most of the studies analyzing the acute effects of using different sled loads have focused on kinematic and kinetic variables such as stride length, stride frequency, flight times, contact times, joint angles, force, rate of force development, and power production.1,2,5,22,27–29 However, to the best of our knowledge, the metabolic and physical response to different loading conditions during resisted sprint training has not been previously analyzed. A better understanding of the physical fitness and metabolic acute and short-term responses to a wide range of loading conditions during resisted sprint training may help to improve the sprint training process and recovery strategies. Therefore, the aim of the present study was to analyze the acute and short-term physical and metabolic responses to resisted sprint training with 5 different loading conditions (0%, 20%, 40%, 60%, and 80% BM). Methods Subjects Fifteen male participants volunteered to this study (age 23.8 [5.3] y, height 1.74 [0.06] m, BM 71.9 [5.9] kg). Subjects were physically active sports science students, and all had experience with strength and sprint training. All participants were injury free and had completed at least 3 training sessions per week in team sports or individual sports such as soccer, futsal, and athletics in the 3 months before testing. Their performance standards ranged from recreational- to regional-level athletes. All participants were fully informed about procedures, potential risks, and benefits of the study, and they all signed written informed consent prior to the tests. The study was conducted in accordance with the Declaration of Helsinki II and was approved by the local ethics committee. Design A randomized, cross-sectional, and counterbalanced experimental design was undertaken to examine the acute and short-term physical and metabolic responses to sprint training with 5 different loading conditions (0%, 20%, 40%, 60%, and 80% BM). Following familiarization with the testing exercises and the resisted sled training, subjects were randomly assigned to perform the same sprint training protocol in 5 different loading conditions during 5 sessions separated by 1 week. The same number of sprints and interset rest duration were used in all the protocols (8 × 20 m, 2-min rest). The sessions only differed on the sled load used. To compare the acute and short-term response by the different loading conditions, subjects performed a battery of tests (CK and lactate concentrations, CMJ, 20-m running sprint, and isokinetic knee extension and flexion contractions) at 3 different time points (preexercise [PRE], postexercise [POST], and 24-hour postexercise [POST24H]). Participants were asked to abstain from any strenuous physical activity for at least 2 days before each trial and during the POST24H. All sessions took place at a neuromuscular research laboratory and on a semicovered running rigid surface, always under the direct supervision of a researcher. All protocols were performed at the same time of the day for each subject and under similar environmental conditions (20°C and 60% humidity, approximately). An initial familiarization session, consisting of performing the testing exercises and several sprints with different sled loads, was carried out 1 week before the first trial, and BM was obtained for calculation of the sled loads. Testing Procedures During the first testing day of each loading condition, resting blood samples (CK and lactate concentrations) were taken before the warm-up. Then, subjects performed a standardized warm-up protocol consisting of 5 minutes of jogging at a selfselected easy pace, 5 minutes of joint mobilization exercises, 10 squats without an external load, 5 CMJ progressive in intensity, 3 maximal CMJ, four 20-m running accelerations at 80%, 85%, 90%, and 95% perceived effort, and one 10-m sprint at 100% effort with 1-minute rest periods between them. After the warmup, PRE tests were performed in the following order: CMJ, 20-m sprint (T20m), and isokinetic knee extension and flexion (peak torques and mean power). Then, the training protocol was carried out, and immediately later, POST tests were performed in the same order (Figure 1). Tests were also performed in the same order for the POST24H measures. A detailed description of test temporization at different time-point measures is presented in Figure 1. Metabolic Variables CK Concentration. Plasma CK concentration was assessed at PRE and POST24H tests from 30-μL capillarized whole blood samples collected via fingertip puncture made using a springloaded single-use disposable lancet. The whole blood sample was immediately pipetted to a test strip and analyzed for CK concentration using a colorimetric assay procedure (Reflotron; Boehringer Mannheim, Germany). The reliability and accuracy of Reflotron CK have been previously established with coefficient of variation (CV) of 3.1%.30 Blood Lactate Concentration. About 5 μL of whole blood sample from the fingertip was used for the quantification of lactate concentration, which was measured with a portable lactate analyzer (Lactate Pro 2; ARKRAY, Kyoto, Japan), at the following 3 different time points: before the training protocol (PRE), 1 minute after the fourth sprint during the training protocol (POST4), and 1 minute after the last sprint (the eighth of the training protocol [POST8]). The reliability and accuracy of Lactate Pro 2 analyzer have been previously established with CVs of 7.6%, 3.5%, and 2.7% for a lactate concentration of ~1, 4, and 12 mmol·L−1.31 Physical-Fitness Variables Countermovement Jump. An infrared timing system (Optojump Next; Microgate, Bolzano, Italy) was used for determining jump height. The CMJ was performed with both hands on the waist, while performing a downward movement until about 90° of knee flexion followed by a maximal vertical jump. All participants were instructed to land in an upright position to ensure similar body configuration for takeoff and landing. The participants were required to do 5 trials separated by 30 seconds (the higher and the lower jump values were removed, and mean height of the 3 intermediate jumps was scored) for the PRE and POST24H measurements, and 2 trials separated by 10-second rest for the POST tests measurements, mean height being scored. Test–retest reliability measured by the CV was 2.1%, and the intraclass correlation coefficient (ICC) values were .99 (95% confidence interval [CI], .98−.99). Sprint Testing. Participants performed two T20m, with 3-minute rest between sprints. Sprint times over 0 to 10, 0 to 20, and 10 to 20 m (T10m, T20m, and T1020m) were measured using photocells (Witty, Microgate). The best time of the 2 trials was scored. Runs were performed from static standing; slit-stanced position with the start line located 1 m behind the start photocell on a rigid surface in a semicovered hall. The timing gates had a vertical height of 0.80 m. The test–retest reliability for running sprint variables was T10m (ICC: .95; 95% CI, .86–.98; CV: 1.8%), T20m (ICC: .94; 95% CI, .83–.98; CV: 1.5%), and T1020m (ICC: .94; 95% CI, .82–.98; CV: 2.4%). Isokinetic Test. Isokinetic concentric knee extension and flexion of the dominant leg were performed at an angular velocity of 60° s−1 using an isokinetic dynamometer (Biodex System 4; Biodex Medical Systems, Shirley, NY). Isokinetic data for peak torque and mean power were obtained at a sample rate of 100 Hz using the Biodex System 4 Advantage software. Warm-up consisted of 3 to 4 submaximal contractions of increasing intensity (from 50% to 90%) for each of the isokinetic contractions and then rested for 1 minute between the warm-up and the beginning of the test. Each participant was seated at an angle of 85° and stabilized with straps at the shoulders, waist, and thighs as per manufacturer’s guidelines. Each participant’s seat position was recorded so that it could be replicated during subsequent testing. Participants performed 3 maximal attempts for each of the isokinetic contractions, and all were given verbal encouragement and visual feedback of the torque signal at each repetition. Peak torque value (N·m), obtained from the highest value of all maximum efforts, and mean power output (W) for each muscle action were chosen for further analysis. Training Protocol The training protocol was always the same for the 5 loading conditions (0%, 20%, 40%, 60%, and 80% BM). This training protocol consisted of 8 × 20-m sprint with 2-minute rest between each sprint. Times of each sprint (including partial times T10m, T20m, and T1020m) were recorded, and lactate measurements were taken before the training session, during the training session (1 min after the fourth sprint), and at the end of the training session (1 min after the eighth sprint). Fatigue during each training protocol was calculated from sprint times using the following formula: fatigue index = [100 × (total sprint time/ideal sprint time)] − 100, where total sprint time = sum of sprint times from all sprints and ideal sprint time = the number of sprints × fastest sprint time.32 This formula seems to be the most suitable because it considers data from each sprint, provides consistent reliability, and shows good construct and logical validity.33 The mean time of the 8 sprints performed during the training sessions was also calculated (Tmean). Speed loss induced for each loading condition was calculated as the decrement in mean sprint velocity elicited by the sled load with respect to the unloaded condition (measured at PRE). Statistical Analysis Values are reported as mean (SD). Statistical significance was established at P < .05. Test– retest absolute reliability was measured by the standard error of measurement, which was expressed in relative terms through CV. Relative reliability was assessed by the ICC (95% CI) calculated with the 1-way random effects model. The standard error of measurement was calculated as the root mean square of total mean square intrasubject. Homogeneity of variance across groups was verified using the Levene test. The distribution of each variable was examined with the Shapiro–Wilk normality test. A 5 (loading) × 3 (time) repeated-measures analysis of variances was calculated for each parameter. Bonferroni post hoc tests were used when the interaction was significant. Statistical analyses were performed using SPSS for Mac (version 20.0; SPSS Inc, Chicago, IL). Results Fatigue During Training Table 1 shows the description of the results obtained in the training protocol performed for each loading condition. Significant differences were found in Tmean in 10 and 20 m for the 8 sprints performed during the training protocol and speed loss between all loading conditions (P < .001). Fatigue index increased as sled loadings increased (Table 1). Specifically, significant differences were found in fatigue index in 10 m for 60% compared with 0% (P = .02); and for 80% with respect to 0% (P = .0001), 20% (P = .0001), 40% (P = .01), and 60% (P = .01). Additionally, fatigue index in 20 m was higher for 60% compared with 0% (P = .001) and 20% conditions (P = .02), and for 80% compared with the rest of loading conditions (0%: P = .00002; 20%: P = .00001; 40%: P = .01; 60%: P = .03). Physiol Rev. 2008;88(1):287–332. PubMed ID: 18195089 doi:10.1152/physrev.00015.2007 12. Jimenez-Reyes P, Pareja-Blanco F, Cuadrado-Pen˜afiel V, Morcillo J, Párraga J, González-Badillo J. Mechanical, metabolic and perceptual response during sprint training. Int J Sports Med. 2016;37(10):807– 812. PubMed ID: 27286181 doi:10.1055/s-0042-107251 13. Jiménez-Reyes P, Pareja-Blanco F, Cuadrado-Pen˜afiel V, Ortega- Becerra M, Párraga J, González-Badillo JJ. Jump height loss as an indicator of fatigue during sprint training. J Sports Sci. 2019; 37(9):1029–1037. doi:10.1080/02640414.2018.1539445 14. Gandevia SC. Spinal and supraspinal factors in human muscle fatigue. Physiol Rev. 2001;81(4):1725–1789. PubMed ID: 11581501 doi:10. 1152/physrev.2001.81.4.1725 15. Gorostiaga EM, Asiain X, Izquierdo M, et al. Vertical jump performance and blood ammonia and lactate levels during typical training sessions in elite 400-m runners. J Strength Cond Res. 2010;24(4):1138–1149. PubMed ID: 20300013 doi:10.1519/JSC.0b013e3181cf769f 16. Morcillo JA, Jimenez-Reyes P, Cuadrado-Penafiel V, Lozano E, Ortega-Becerra M, Parraga J. Relationships between repeated sprint ability, mechanical parameters, and blood metabolites in professional soccer players. J Strength Cond Res. 2015;29(6):1673–1682. PubMed ID: 25463691 doi:10.1519/JSC.0000000000000782 17. Howatson G, Milak A. Exercise-induced muscle damage following a bout of sport specific repeated sprints. J Strength Cond Res. 2009; 23:2419–2424. PubMed ID: 19826279 doi:10.1519/JSC.0b013e3181bac52e 18. Keane KM, Salicki R, Goodall S, Thomas K, Howatson G. Muscle damage response in female collegiate athletes after repeated sprint activity. J Strength Cond Res. 2015;29(10):2802–2807. PubMed ID: 25853920 doi:10.1519/JSC.0000000000000961 19. Leeder JD, van Someren KA, Gaze D, et al. Recovery and adaptation from repeated intermittent-sprint exercise. Int J Sports Physiol Perform. 2014;9(3):489–496. doi:10.1123/ijspp.2012-0316 20. Petrakos G, Morin JB, Egan B. Resisted sled sprint training to improve sprint performance: a systematic review. Sports Med. 2016; 46(3):381–400. PubMed ID: 26553497 doi:10.1007/s40279-015-0422-8 21. Alcaraz PE, Palao JM, Elvira JL. Determining the optimal load for resisted sprint training with sled towing. J Strength Cond Res. 2009;23(2):480–485. PubMed ID: 19197200 doi:10.1519/JSC.0b013e318198f92c 22. Lockie RG, Murphy AJ, Spinks CD. Effects of resisted sled towing on sprint kinematics in field-sport athletes. J Strength Cond Res. 2003;17(4):760–767. PubMed ID: 14636109 23. Spinks CD, Murphy AJ, Spinks WL, Lockie RG. The effects of resisted sprint training on acceleration performance and kinematics in soccer, rugby union, and Australian football players. J Strength Cond Res. 2007;21(1):77–85. PubMed ID: 17313259 doi:10.1519/ 00124278-200702000-00015 24. Cross MR, Brughelli M, Samozino P, Brown SR, Morin JB. Optimal loading for maximizing power during sled-resisted sprinting. Int J Sports Physiol Perform. 2017;12(8):1069–1077. PubMed ID: 28051333 doi:10.1123/ijspp.2016-0362 25. Morin JB, Petrakos G, Jimenez-Reyes P, Brown SR, Samozino P, Cross MR. Very-heavy sled training for improving horizontal force output in soccer players. Int J Sports Physiol Perform. 2017; 12(6):840–844. PubMed ID: 27834560 doi:10.1123/ijspp.2016-0444 26. Haugen TA, Breitschädel F, Seiler S. Sprint mechanical variables in elite athletes: are force-velocity profiles sport specific or individual? PLoS One. 2019;14(7):e0215551. PubMed ID: 31339890 doi:10.1371/journal.pone.0215551 27. Alcaraz PE, Palao JM, Elvira JL, Linthorne NP. Effects of three types of resisted sprint training devices on the kinematics of sprinting at maximum velocity. J Strength Cond Res. 2008;22(3):890–897. PubMed ID: 18438225 doi:10.1519/JSC.0b013e31816611ea 28. Martinez-Valencia MA, Romero-Arenas S, Elvira JL, Gonzalez-Rave JM, Navarro-Valdivielso F, Alcaraz PE. Effects of sled towing on peak force, the rate of force development and sprint performance during the acceleration phase. J Hum Kinet. 2015;46(1):139–148. doi:10.1515/hukin-2015-0042 29. Maulder PS, Bradshaw EJ, Keogh JWL. Kinematic alterations due to different loading schemes in early acceleration sprint performance from starting blocks. J Strength Cond Res. 2008;22(6):1992–2002. PubMed ID: 18978610 doi:10.1519/JSC.0b013e31818746fe 30. Horder M, Jørgensen P, Hafkenscheid JCM, et al. Creatine kinase determination: a European evaluation of the creatine kinase determination in serum, plasma and whole blood with the Reflotron® system. Eur J Clin Chem Biochem. 1991;29:691– 696. 31. Bonaventura JM, Sharpe K, Knight E, Fuller KL, Tanner RK, Gore CJ. Reliability and accuracy of six hand-held blood lactate analysers. J Sport Sci Med. 2015;14(1):203–214. 32. Fitzsimons M, Dawson B, Ware D, Wilkinson A. Cycling and running tests of repeated sprint ability. Aust J Sci Med Sport. 1993; 25:82–87. 33. Glaister M, Howatson G, Pattison JR, McInnes G. The reliability and validity of fatigue measures during multiple-sprint work: an issue revisited. J Strength Cond Res. 2008;22(5):1597–1601. PubMed ID: 18714226 doi:10.1519/JSC.0b013e318181ab80 34. Morin JB, Samozino P, Edouard P, Tomazin K. Effect of fatigue on force production and force application technique during repeated sprints. J Biomech. 2011;44(15):2719–2723. PubMed ID: 21839456 doi:10.1016/j.jbiomech.2011.07.020 35. Whelan N, O’Regan C, Harrison AJ. Resisted sprints do not acutely enhance sprinting performance. J Strength Cond Res. 2014;28(7): 1858–1866. PubMed ID: 24378662 doi:10.1519/JSC.0000000000000357 36. Winwood PW, Posthumus LR, Cronin JB, Keogh JW. The acute potentiating effects of heavy sled pulls on sprint performance. J Strength Cond Res. 2016;30(5):1248–1254. PubMed ID: 26439786 doi:10.1519/JSC.0000000000001227 37. Girard O, Mendez-Villanueva A, Bishop D. Repeated-sprint ability – part I: factors contributing to fatigue. Sports Med. 2011;41:673–694. PubMed ID: 21780851 doi:10.2165/11590550-000000000-00000 38. Bentley I, Sinclair JK, Atkins SJ, Metcalfe J, Edmundson CJ. Effect of velocitybased loading on acceleration kinetics and kinematics during sled towing [published online ahead of print October 05, 2018]. J Strength Cond Res. 39. Morin JB, Gimenez P, Edouard P, et al. Sprint acceleration mechanics: the major role of hamstrings in horizontal force production. Front Physiol. 2015;6:404. PubMed ID: 26733889 doi:10.3389/fphys.2015.00404 Figure 1 — Schematic representation of study design:(A) blood sampling and physicalfitness measurements at 3different time points; (B) structure of tests and sprint-training protocol for each loading condition. Figure 2 — Changes in blood lactate concentration for each loading condition. Intragroup significant differences: **P < .01, ***P < .001 (with respect to PRE); ###P< .01, ††P < .001 (with respect to 0%); #P Figure 3 — Changes in creatine kinase concentration for each loading condition. Intragroup significant differences: *P < .05, **P < .01, ***P < .001 (with respect to PRE).