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Blood Biomarkers Variations across the Pre-Season and Interactions with Training Load: A Study in Professional Soccer Players

Clemente, F.M.C. ; González-Fernández, F.T.G.-F. ; Ceylan, H. I. C. ; Silva, R. S. ; Younesi, S. Y. ; Chen, Y.-S.C. ; Badicu, G. B. ; Wolanski, P. W. ; Murawska-Ciałowicz, E. M.-C.

journal of clinical medicine Vol. 10, Nº 23, pp. 5576 - 5576, November, 2021.

ISSN (print): 2077-0383
ISSN (online):

Scimago Journal Ranking: 2,27 (in 2018)

Digital Object Identifier: 10.3390/jcm10235576

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Background: Pre-season training in soccer can induce changes in biological markers in the circulation. However, relationships between chosen hematological and biochemical blood parameters and training load have not been measured. Objective: Analyze the blood measures changes and their relationships with training loads changes after pre-season training. Methodology: Twenty-five professional soccer players were assessed by training load measures (derived from rate of perceived exertion- known as RPE) during the pre-season period. Additionally, blood samples were collected for hematological and biochemical analyses. Results: For hematological parameters, significant increases were found for platelets (PLT) (dif: 6.42; p = 0.006; d = −0.36), while significant decreases were found for absolute neutrophils count (ANC) (dif: −3.98; p = 0.006; d = 0.11), and absolute monocytes count (AMC) (dif: −16.98; p = 0.001; d = 0.78) after the pre-season period. For biochemical parameters, there were significant increases in creatinine (dif: 5.15; p = 0.001; d = −0.46), alkaline phosphatase (ALP) (dif: 12.55; p = 0.001; d = −0.84), C-reactive protein (CRP) (dif: 15.15; p = 0.001; d = −0.67), cortisol (dif: 2.85; p = 0.001; d = −0.28), and testosterone (dif: 5.38; p = 0.001; d = −0.52), whereas there were significant decreases in calcium (dif: −1.31; p = 0.007; d =0.49) and calcium corrected (dif: −2.18; p = 0.015; d = 0.82) after the pre-season period. Moreover, the Hooper Index (dif: 13.22; p = 0.01; d = 0.78), and all derived RPE measures increased after pre-season period. Moderate-to-very large positive and negative correlations (r range: 0.50–0.73) were found between the training load and hematological measures percentage of changes. Moderate-to-large positive and negative correlations (r range: 0.50–0.60) were found between training load and biochemical measures percentage of changes. Conclusions: The results indicated heavy physical loads during the pre-season, leading to a decrease in immune functions. Given the significant relationships between blood and training load measures, monitoring hematological and biochemical measures allow coaches to minimize injury risk, overreaching, and overtraining.