Clustering classification of cyclists according to acute fatigue outcomes produced by an ultra-endurance event

  1. José Luis Sánchez-Jiménez 1
  2. Alexis Gandia-Soriano 1
  3. Pedro Pérez-Soriano 1
  4. José Ignacio Priego-Quesada 2
  5. Alberto Encarnación-Martínez 2
  1. 1 Research Group in Sports Biomechanics (GIBD), Department of Physical Education and Sports, University of Valencia, Valencia, Spain
  2. 2 Research Network in Cycling and Woman (REDICYM), St: Avenida Conde de Torrefiel, 22, 46870,Ontinyent, Valencia, Spain.
Zeitschrift:
European Journal of Human Movement

ISSN: 0214-0071,  2386-4095

Datum der Publikation: 2023

Nummer: 50

Seiten: 31-44

Art: Artikel

DOI: 10.21134/EURJHM DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Andere Publikationen in: European Journal of Human Movement

Zusammenfassung

This study aimed to analyze the differences between clusters obtained by the acute fatigue effect followingan ultra-endurance event on the internal and external load of cyclists. 26 volunteersparticipated in the study, divided into the experimental group (N = 18; height: 177 ± 8 cm; body mass: 78.6 ± 10.3 kg) and the control group (N = 8; height: 176 ± 10 cm; body mass: 78.0 ± 15.7 kg). The experimentalgroup completed a 12 h non-stop cycling event. Jump height, lactate, plasma antioxidant capacity, pain perception and fatigue perception were measured before and after the event. Cyclists of the experimental group were classified taking into accounttheir training characteristics(recreational vs. competitive)and conducting non-supervised K-means clustering. The differentiation of cyclists according to training characteristics resulted in a lower distance covered by recreational cycliststhan competitive cyclists (279.4 ± 39.7 km vs. 371.0 ± 71.7 km; ES ≥ 0.8; p < 0.01), although no differences were observed in the othervariables between groups (p > 0.05). The clusteringanalysis resulted intwo clusters.Cluster 2 suffered a greater jump height decrease(-3.3 ± 1.6 vs. 1.2 ± 0.8; ES ≥ 0.8; p < 0.001) and increased pain and fatigue perception (ES ≥ 0.5; p < 0.05) after the race than Cluster 1. In conclusion, counter-movement jumpand fatigue/pain perception can differentiate the fatigue produced by a cycling ultra-endurance event and therefore, thesenon-invasive measurements areuseful in fatigue monitoring and recovery planning

Bibliographische Referenzen

  • Bescós, R., Rodríguez, F. A., Iglesias, X., Knechtle, B., Benítez, A., Marina, M., Padullés, J. M., Vázquez, J., & Torrado, P. (2011). Physiological demands of cyclists during an ultra-endurance relay race: A field study report. Chinese Journal of Physiology, 54(5), 339–346. https://doi.org/10.4077/CJP.2011.AMM065
  • Carins, S., Knicker, A. J., Thompson, M. W., & Sjøgaard, G. (2005). Evaluation of Models Used to Study Neuromuscular Fatigue: Exercise and Sport Sciences Reviews. Exercise and Sport Sciences Reviews, 33(1), 9–16.
  • Claudino, J. G., Cronin, J., Mezêncio, B., McMaster, D. T., McGuigan, M., Tricoli, V., Amadio, A. C., & Serrão, J. C. (2017). The countermovement jump to monitor neuromuscular status: A meta-analysis. Journal of Science and Medicine in Sport, 20(4), 397–402. https://doi.org/10.1016/J.JSAMS.2016.08.011
  • Clermont, C. A., Benson, L. C., Edwards, W. B., Hettinga, B. A., & Ferber, R. (2019). New Considerations for Wearable Technology Data: Changes in Running Biomechanics During a Marathon. Journal of Applied Biomechanics, 35(6), 401–409. https://doi.org/10.1123/JAB.2018-0453
  • Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (Second). Lawrance Eribaum Associates.
  • Dantas, R., Caputo, F., Mendes, K., Sigwalt, A. R., Ghisoni, K., Lock, P. C., Remor, A. P., da Luz, D., Antonacci, L. G., & Latini, A. (2014). Increased platelet oxidative metabolism, blood oxidative stress and neopterin levels after ultra-endurance exercise. Journal of Sports Sciences, 32(1), 22–30. https://doi.org/10.1080/02640414.2013.797098
  • Dawson, D., Fletcher, A., & Hussey, F. (2015). Fatigue and Transportation Report To the Neville Committee. 29(1), 37–46.
  • Gandia, A., Carpes, F. P., Rodríguez, A., & Priego, J. I. (2020). Effect of cycling specialization on effort and physiological responses to uphill and flat cycling at similar intensity. European Journal of Sport Science, 1–7. https://doi.org/10.1080/17461391.2020.1785016
  • Gómez, M. C., Pallardó, F. V., Sastre, J., Viña, J., & Garcia, L. (2003). Allopurinol and Markers of Muscle Damage Among Participants in the Tour de France. JAMA, 289(19), 2503–2504. https://doi.org/10.1001/JAMA.289.19.2503-B
  • Hartigan, J. A. ., & Wong, M. . A. . (1979). Algorithm AS 136: A K-Means Clustering Algorithm Author ( s ): J Published by: Wiley for the Royal Statistical Society Stable URL : http://www.jstor.org/stable/2346830. Journal of the Royal Statistical Society: Series C (Applied Statistics), 28(1), 100–108.
  • Lecina, M., Castellar, C., Pradas, F., & López, I. (2022). 768-km Multi-Stage Ultra-Trail Case Study-Muscle Damage, Biochemical Alterations and Strength Loss on Lower Limbs. International Journal of Environmental Research and Public Health, 19(2). https://doi.org/10.3390/ijerph19020876
  • Lewis, N. A., Simpkin, A. J., Moseley, S., Turner, G., Homer, M., Redgrave, A., Pedlar, C. R., & Burden, R. (2020). Increased Oxidative Stress in Injured and Ill Elite International Olympic Rowers. International Journal of Sports Physiology and Performance, 15(5), 625–631. https://doi.org/10.1123/IJSPP.2019-0425
  • Lewis, N. A., Towey, C., Bruinvels, G., Howatson, G., & Pedlar, C. R. (2016). Effects of exercise on alterations in redox homeostasis in elite male and female endurance athletes using a clinical point-of-care test. Https://Doi.Org/10.1139/Apnm-2016-0208, 41(10), 1026–1032. https://doi.org/10.1139/APNM-2016-0208
  • Maunder, E., Seiler, S., Mildenhall, M. J., Kilding, A. E., & Plews, D. J. (2021). The Importance of ‘Durability’ in the Physiological Profiling of Endurance Athletes. Sports Medicine, 51(8), 1619–1628. https://doi.org/10.1007/S40279-021-01459-0/FIGURES/3
  • Mrakic, S., Gussoni, M., Moretti, S., Pratali, L., Giardini, G., Tacchini, P., Dellanoce, C., Tonacci, A., Mastorci, F., Borghini, A., Montorsi, M., & Vezzoli, A. (2015). Effects of mountain ultra-marathon running on ROS production and oxidative damage by micro-invasive analytic techniques. PLoS ONE, 10(11), 1–19. https://doi.org/10.1371/journal.pone.0141780
  • Mündermann, A., Nigg, B. M., Stefanyshyn, D. J., & Humble, R. N. (2002). Development of a reliable method to assess footwear comfort during running. Gait & Posture, 16(1), 38–45. https://doi.org/10.1016/S0966-6362(01)00197-7
  • Nikolaidis, P. T., Knechtle, B., Vancini, R., Gomes, M., & Sousa, C. (2021). Participation and Performance in the Oldest Ultramarathon-Comrades Marathon 1921-2019. International Journal of Sports Medicine, 42(7), 638–644. https://doi.org/10.1055/a-1303-4255
  • Ørtenblad, N., Westerblad, H., & Nielsen, J. (2013). Muscle glycogen stores and fatigue. The Journal of Physiology, 591(18), 4405–4413. https://doi.org/10.1113/JPHYSIOL.2013.251629
  • Pavlatou, M. G., Papastamataki, M., Apostolakou, F., Papassotiriou, I., & Tentolouris, N. (2009). FORT and FORD: two simple and rapid assays in the evaluation of oxidative stress in patients with type 2 diabetes mellitus. Metabolism, 58(11), 1657–1662. https://doi.org/10.1016/J.METABOL.2009.05.022
  • Priego, J. I., Kerr, Z. Y., Bertucci, W. M., & Carpes, F. P. (2018). The categorization of amateur cyclists as research participants: Findings from an observational study. Journal of Sports Sciences, 36(17), 2018–2024. https://doi.org/10.1080/02640414.2018.1432239
  • Rousseeuw, P. J. (1987). Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20(C), 53–65. https://doi.org/10.1016/0377-0427(87)90125-7
  • Scheer, V. (2019). Participation trends of ultra endurance events. Sports Medicine and Arthroscopy Review, 27(1), 3–7. https://doi.org/10.1097/JSA.0000000000000198
  • Schenk, K., Rauch, S., Procter, E., Grasegger, K., Mrakic-Sposta, S., & Gatterer, H. (2021). Changes in Factors Regulating Serum Sodium Homeostasis During Two Ultra-Endurance Mountain Races of Different Distances: 69km vs. 121km. Frontiers in Physiology, 12(November). https://doi.org/10.3389/fphys.2021.764694
  • Shoak, M., Knechtle, B., Knechtle, P., Rüst, C., Rosemann, T., & Lepers, R. (2013). Participation and performance trends in ultracycling. Open Access Journal of Sports Medicine, 4, 41. https://doi.org/10.2147/OAJSM.S40142
  • Smith, K. A., Kisiolek, J. N., Willingham, B. D., Morrissey, M. C., Leyh, S. M., Saracino, P. G., Baur, D. A., Cook, M. D., & Ormsbee, M. J. (2020). Ultra-endurance triathlon performance and markers of whole-body and gut-specific inflammation. European Journal of Applied Physiology, 120(2), 349–357. https://doi.org/10.1007/S00421-019-04279-3
  • Stelzer, I., Kröpfl, J. M., Fuchs, R., Pekovits, K., Mangge, H., Raggam, R. B., Gruber, H. J., Prüller, F., Hofmann, P., Truschnig-Wilders, M., Obermayer-Pietsch, B., Haushofer, A. C., Kessler, H. H., & Mächler, P. (2015). Ultra-endurance exercise induces stress and inflammation and affects circulating hematopoietic progenitor cell function. Scandinavian Journal of Medicine and Science in Sports, 25(5), e442–e450. https://doi.org/10.1111/SMS.12347
  • Suárez, V. C., Valdivielso, F. N., & Ravé, J. M. G. (2011). Changes in biochemical parameters after a 20-hour ultra-endurance kayak and cycling event. International SportMed Journal, 12(1), 1–6.
  • Tanner, R. K., Fuller, K. L., & Ross, M. L. R. (2010). Evaluation of three portable blood lactate analysers: Lactate Pro, Lactate Scout and Lactate Plus. European Journal of Applied Physiology, 109(3), 551–559. https://doi.org/10.1007/S00421-010-1379-9/FIGURES/5
  • Tomczak, M., & Tomczak, E. (2014). The need to report effect size estimates revisited. An overview of some recommended measures of effect size. Trends in Sport Sciences, 1(21), 19–25.
  • Truppa, L., Guaitolini, M., Garofalo, P., Castagna, C., & Mannini, A. (2020). Assessment of Biomechanical Response to Fatigue through Wearable Sensors in Semi-Professional Football Referees. Sensors (Basel, Switzerland), 21(1), 1–15. https://doi.org/10.3390/S21010066
  • Turner, J. E., Bennett, S. J., Bosch, J. A., Griffiths, H. R., & Aldred, S. (2014). Ultra-endurance exercise: Unanswered questions in redox biology and immunology. Biochemical Society Transactions, 42(4), 989–995. https://doi.org/10.1042/BST20140120
  • van der Zwaard, S., de Ruiter, C. J., Jaspers, R. T., & de Koning, J. J. (2019). Anthropometric Clusters of Competitive Cyclists and Their Sprint and Endurance Performance. Frontiers in Physiology, 10, 1276. https://doi.org/10.3389/FPHYS.2019.01276/BIBTEX
  • Vitti, A., Nikolaidis, P. T., Villiger, E., Onywera, V., & Knechtle, B. (2020). The ‘New York City Marathon’: Participation and performance trends of 1.2M runners during half-century. Research in Sports Medicine (Print), 28(1), 121–137. https://doi.org/10.1080/15438627.2019.1586705
  • Wolff, S., Picco, J. M., Díaz, L., Valenzuela, P. L., Gonzalez, E., Santos, A., Matile, P., Wolff, D., Boraita, A., & Lucia, A. (2022). Exercise-Induced Cardiac Fatigue in Recreational Ultramarathon Runners at Moderate Altitude: Insights From Myocardial Deformation Analysis. Frontiers in Cardiovascular Medicine, 8(January), 1–8. https://doi.org/10.3389/fcvm.2021.744393
  • Wu, P. P. Y., Sterkenburg, N., Everett, K., Chapman, D. W., White, N., & Mengersen, K. (2019). Predicting fatigue using countermovement jump force-time signatures: PCA can distinguish neuromuscular versus metabolic fatigue. PLoS ONE, 14(7), 1–16. https://doi.org/10.1371/journal.pone.0219295
  • Yang, W. H., Park, H., Grau, M., & Heine, O. (2020). Decreased Blood Glucose and Lactate: Is a Useful Indicator of Recovery Ability in Athletes? International Journal of Environmental Research and Public Health, 17(15), 1–16. https://doi.org/10.3390/IJERPH17155470
Fuente de los datos: Dialnet