Early identification of endurance athletes in danger of overtraining syndrome by flow cytometric immunophenotyping of peripheral blood lymphocytes. A database with 170 parameters was calculated from FSC/SSC/CD19/00, CD45RO/4, CD45RO/8, CD3/HLA-DR, CD3/16 two colour assays for a total of 72 normal/overtrained competition cyclists.
The classification of the learning set of normal individuals, and of cyclists developing overtraining syndrome during a three to four months training period.
The determination of lymphocyte CD45RO antigen expression (antigen surface density) provides excellent identification of the imminent overtraining syndrome. The relative frequency of the various lymphocyte populations, in contrast, is non informative.
Elaboration of CLASSIF1 Classifiers:
CLASSIF1 classifiers are typically established from data sets of clinically well characterized patients. Upon reception of a data set, patients #1,5,10,15 ... etc of each classification category remain a-priori inaccessible to the learning process and constitute the embedded unknown test set which serves to test the robustness of classification for unknown samples.
The remaining patient data are assigned to the learning set from which the classifier is learned according to the principles described previously.
Once the classifier is available, its classification capacities can be assessed by classification of the learning set but more importantly by the classification of the unknown test set patients.
A classifier which correctly classifies the learning set as well as the test set of patients is suitable for a test phase of prospective classification in the clinical environment. The correctness of prospective classification is checked for a certain time prior to classifier use in its operational phase in routine practice.