Risk Assessment for Overtraining Syndrome in Competition Cyclists from Leukocyte Immunophenotypes
1. Introduction: The overtraining syndrome as a consequence of prolonged physical exercise leads to reversible episodes of substantially lowered physical strength in combination with an increased susceptibility to opportunistic infections which may lead to life threatening disease. There are no early indicators of a beginning overtraining syndrome.
2. Goal: Early identification of endurance athletes in danger of overtraining syndrome by flow cytometric immunophenotyping of peripheral blood lymphocytes.
Data Pattern Classification:
A database was calculated from the CD45RO/CD4, CD45RO/CD8,
CD3/HLA-DR, CD3/CD16, CD19/blank two colour
assays in conjunction with simultaneous forward(FSC) and
sideward (SSC) light scatter analysis for a total of 72
normal/overtrained competition cyclists.
- Since no significant changes of the usual % frequency values of the various lymphocyte populations were observed, an exhaustive analysis of the flow cytometric list mode files was performed with 5x34=170 database columns instead of only 5x4=20 database columns on % cell frequency analysis alone.
- Standardized and automated data classification with the CLASSIF1 multiparameter data classification program permitted the > 95% single case recognition of overtrained cyclists. The development of the overtraining syndrome was paralleled by a reversible increase of CD45RO antigen expression on the lymphocyte surface. Monitoring this increase with time may be a means to avoid the occurrence of overtraining syndromes in endurance athletes.
4. Conclusion: The determination of lymphocyte CD45RO antigen expression (antigen surface density) provides the > 95% correct identification of an imminent overtraining syndrome by clinical cytomics. The relative frequency of the various lymphocyte populations, in contrast, is non informative.
L1 Gabriel H, Urhausen A, Valet G, Heidelbach U, Kindermann W. Overtraining and immune system: A prospective longitudinal study in endurance athletes. Med.Sci.Sports Exerc. 30:1151-1157 (1998), (pdf).
L2 Valet G, Valet M, Tschöpe D, Gabriel H, Rothe G, Kellermann W, Kahle H. White cell and thrombocyte disorders: Standardized, self-learning flow cytometric list mode data classification with the CLASSIF1 program system. Ann.NY Acad.Sci. 677:233-251 (1993), (pdf).
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