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 PMID:24744500  

Training load, immune system, upper respiratory symptoms and performance in well-trained cyclists throughout a competitive season.

H G Ferrari | C A Gobatto | F B Manchado-Gobatto
Biology of sport | 2013

This study aimed to evaluate the leukocyte subset counts, serum immunoglobulin A, performance and upper respiratory symptoms (URS), as well as their interrelationships, of well-trained cyclists for a 29-week training season using monitored loads. The season was divided into three phases: preparatory (nine weeks), first competitive phase (nine weeks) and second competitive phase (11 weeks). The sample consisted of eight well-trained cyclists, aged 18 ± 2 years. Immunological parameters and performance were evaluated during weeks 1 (baseline), 10 (early first competitive phase), 19 (early second competitive phase) and 29 (end of the second competitive phase). The training loads (volume x rating of perceived exertion) were monitored daily while the monitoring of URS was performed every 15 days using the WURSS-44 questionnaire. The data were analyzed using a one-way ANOVA and a Pearson correlation test with the significance level set at p ≤ 0.05. No significant differences were found for training load, leukocyte subset counts or serum immunoglobulin A among the three phases. However, serum immunoglobulin A was 50.9% below the control group values. URS were significantly higher during the preparatory period, and there were significant correlations between URS and training load (strain) in the preparatory period (r = 0.72, p = 0.032) and second competitive phase (r = 0.73, p = 0.036). In conclusion, indicators of training load without a significant change throughout the season did not significantly affect immune parameters measured; however, the increase of strain can cause an increase of upper respiratory symptoms throughout the season, but without loss of performance.

Pubmed ID: 24744500

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RRID:SCR_015627

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on June 1,2023. Analytics platform with various sub platforms, each with specific performance capabilities for tasks such as data analysis, data management, data visualization, and data mining procedures.

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