Model for predicting metabolic activity in athletes based on biochemical blood test analysis

Abstract

Improving the efficiency of athletic performance and reducing the likelihood of overtraining are primarily determined goals that can be achieved by the correct organization of the training process. The nature of adaptation to physical stress is associated with the specificity, focus, and degree of biochemical and functional changes that occur during muscular work. In this study, we aimed to develop a diagnostic model for predicting metabolic processes in athletes based on standard biochemical blood analysis indicators. The study involved athletes from the track and field athletics team (men, n = 42, average age was [22.55 ± 3.68] years). Blood samples were collected in the morning at the beginning and end of the training week during the annual cycle. During the entire period, 3 625 laboratory parameter tests were conducted. Capillary blood sampling in athletes was conducted from the distal phalanx of the finger after overnight fasting, according to standard diagnostic procedures. To determine the predominance of anabolic or catabolic processes, equations were derived from a linear discriminant function. The discriminant function of predicting metabolic processes in athletes has a high information capacity (92.1%), as confirmed by the biochemical results of neuroendocrine system activity, which characterized the body's stage of adaptive regulatory mechanisms in response to stress factors. The classification matrix used to predict the metabolic processes based on the results of the discriminant function calculation demonstrates the statistical significance of the model (p < 0.01). Consequently, an informative mathematical model was developed, which enabled the reliable and timely prediction of the prevalence of one of the metabolic activity phases in the athlete's body. The use of the developed model will also allow us to assess the nature of adaptation to specific muscular work, identify an athlete's weaknesses, forecast the success of their performance, and timely adjust both the training process and the recovery program.

Keywords

Anabolism / Catabolism / Metabolism / Predictive model / Blood test / Overtraining and sports population

Ethical approval statement

All participants were informed of the risks and discomforts associated with the investigation and had signed a written consent to participate. The study was approved by the Board for Ethical Questions in the A. I. Burnazyan State Research Center of the Federal Medical-Biological Agency of Russia (Protocol No 12 from 02.03.2021), according to the principles expressed in the Declaration of Helsinki.

Data statement

The datasets generated during and/or analyzed during the current study are available from Vasiliy I. Pustovoyt ([e-mail]) on reasonable request.

Funding

This work was financed by the Ministry of Science and Higher Education of the Russian Federation within the framework of state support for the creation and development of World-Class Research Centers ‘Digital Biodesign and Personalized Healthcare’ No 75-15-2022-305.

CRediT authorship contribution statement

Victoria A. Zaborova: Software. Evgenii I. Balakin: Methodology, Investigation. Ksenia A. Yurku: Visualization. Olga E. Aprishko: Investigation. Vasiliy I. Pustovoyt: Data curation, Conceptualization.

onflict of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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