Individual Patterns in Blood-Borne Indicators of Fatigue—Trait or Chance

• Autores: Julian Ross, Tim Meyer, Hugh H.K. Fullagar, Sabrina Skorski, Mark Pfeiffer, Michael Kellmann, Alexander Ferrauti, Anne Hecksteden
• Localización: Journal of strength and conditioning research: the research journal of the NSCA, ISSN 1064-8011, Vol. 31, Nº. 3, 2017, págs. 608-619
• Idioma: inglés
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• Resumen

  • Blood-borne markers of fatigue such as creatine kinase (CK) and urea (U) are widely used to fine-tune training recommendations. However, predictive accuracy is low. A possible explanation for this dissatisfactory characteristic is the propensity of athletes to react to different patterns of fatigue indicators (e.g., predominantly muscular [CK] or metabolic [U]). The aim of the present trial was to explore this hypothesis by using repetitive fatigue-recovery cycles. A total of 22 elite junior swimmers and triathletes (18 ± 3 years) were monitored for 9 weeks throughout 2 training phases (low-intensity, high-volume [LIHV] and high-intensity, low-volume [HILV] phases). Blood samples were collected each Monday (recovered) and Friday (fatigued) morning. From measured values of CK, U, free-testosterone (FT), and cortisol (C) as determined in the rested and fatigued state, respectively, Monday–Friday differences ([DELTA]) were calculated and classified by magnitude before calculation of ratios ([DELTA]CK/[DELTA]U and [DELTA]FT/[DELTA]C). Coefficient of variation (CV) was calculated as group-based estimates of reproducibility. Linear mixed modeling was used to differentiate inter- and intraindividual variability. Consistency of patterns was analyzed by comparing with threshold values (<0.9 or >1.1 for all weeks). Reproducibility was very low for fatigue-induced changes (CV >= 100%) with interindividual variation accounting for 45–60% of overall variability. Case-wise analysis indicated consistent [DELTA]CK/[DELTA]U patterns for 7 individuals in LIHV and 7 in HILV; 5 responded consistently throughout. For [DELTA]FT/[DELTA]C the number of consistent patterns was 2 in LIHV and 3 in HILV. These findings highlight the potential value of an individualized and multivariate approach in the assessment of fatigue.