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THE JOURNAL OF SPORTS MEDICINE AND PHYSICAL FITNESS
Rivista di Medicina, Traumatologia e Psicologia dello Sport
Indexed/Abstracted in: Chemical Abstracts, CINAHL, Current Contents/Clinical Medicine, EMBASE, PubMed/MEDLINE, Science Citation Index Expanded (SciSearch), Scopus
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(Biochemistry, Immunology, Kinanthropometry, Neurology, Neurophysiology, Ophtalmology, Pharmacology, Phlebology, etc.)
The Journal of Sports Medicine and Physical Fitness 2011 March;51(1):153-9
Performance and blood monitoring in sports: the artificial intelligence evoking target testing in antidoping (AR.I.E.T.T.A.) project
Manfredini F. 1,3, Malagoni A. M. 3, Litmanen H. 1, Zhukovskaja L. 1, Jeannier P. 1, Dal Follo D. 2, Felisatti M. 3, Besseberg A. 1, Geistlinger M. 1, Bayer P. 1, Carrabre J. E. 1 ✉
1 International Biathlon Union, Salzburg, Austria;
2 Biomedical Studies Center applied to Sport, University of Ferrara, Ferrara, Italy;
3 Vascular Diseases Center, University of Ferrara, Ferrara, Italy
AIM: Substances and methods used to increase oxygen blood transport and physical performance can be detected in the blood, but the screening of the athletes to be tested remains a critical issue for the International Federations. This project, AR.I.E.T.T.A., aimed to develop a software capable of analysing athletes’ hematological and performance profiles to detect abnormal patterns.
METHODS: One-hundred eighty athletes belonging to the International Biathlon Union gave written informed consent to have their hematological data, previously collected according to anti-doping rules, used to develop the AR.I.E.T.T.A. software.
RESULTS: Software was developed with the included sections: 1) log-in; 2) data-entry: where data are loaded, stored and grouped; 3) analysis: where data are analysed, validated scores are calculated, and parameters are simultaneously displayed as statistics, tables and graphs, and individual or subpopulation profiles; 4) screening: where an immediate evaluation of the risk score of the present sample and/or the athlete under study is obtained. The sample risk score or AR.I.E.T.T.A. score is calculated by a simple computational system combining different parameters (absolute values and intra-individual variations) considered concurrently. The AR.I.E.T.T.A. score is obtained by the sum of the deviation units derived from each parameter, considering the shift of the present value from the reference values, based on the number of standard deviations.
CONCLUSION: AR.I.E.T.T.A. enables a quick evaluation of blood results assisting surveillance programs and perform timely target testing controls on athletes by the International Federations. Future studies aiming to validate the AR.I.E.T.T.A. score and improve the diagnostic accuracy will improve the system.