Goal:
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.
CLASSIF1 Classification:
The classification of the learning set of normal individuals,
and of cyclists developing overtraining syndrome during a
three to four months training period.
Conclusion:
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.