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Dynamics of TP, HF-, LF-, and VLF-Waves of the Cardiointervalogram (in Clinostasis Conditions) of an Elite Ski Racer in the Preparatory, Competition, and Transition Periods Depending on the Volume and Intensity of Training Loads

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Abstract

In order to study the mechanisms of adaptation to loads requiring high endurance, a cardiointervalogram (CIG) of a 27-year-old Master of Sports of Russia in cross-country skiing was repeatedly recorded under clinostasis conditions, with estimation of the total power (TP) of the spectrum, as well as the absolute power (ms2) of LF-, HF-, and VLF-waves and the relative power of these waves (as a percentage of TP), i.e., LF%, HF%, and VLF%. They were compared with the volume (Vkm, Vmin) and intensity (Nhr) of training loads. The volume of loads was maximum in the preparatory period (21 km/day) and minimum in the transition period (18 km/day), and their intensity was stable throughout the annual cycle (working pulse, 120–121 bpm). With the change in the volume of loads, the values of the CIG indices also changed. For example, in the preparatory period, the medians of TP, the power of HF-, LF-, and VLF-waves, as well as VLF% increased; in this period, with an increase in the volume of loads (Vkm), the values of VLF% increased. In the competition period, the medians of TP, the power of HF-, LF-, and VLF-waves, and VLF% remained at a high level. In the transition period, the medians of TP, the power of HF-, LF-, and VLF-waves, as well as LF% and VLF%, decreased, whereas the median HF% increased. For the annual cycle, a direct dependence of the median TP on the volume of loads (Vkm) and the median power of VLF-waves on the volume (Vkm) and intensity (Nhr) of the load was revealed. It is assumed that the values of TP, as well as HF-, LF-, and VLF-waves, and VLF% (in clinostasis) reflect the influence of the parasympathetic part of the autonomic nervous system on the heart (VLF% probably reflects the intensity of synthesis of non-neuronal acetylcholine by cardiomyocytes, whereas LF% and HF% values reflect the formation of anxiety in connection with upcoming starts).

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Authors and Affiliations

  1. Vyatka State University, Kirov, Russia

    D. A. Kataev, M. A. Morozova, A. N. Trukhin & S. I. Trukhina

  2. Federation of Cross-Country Skiing of the Republic of Tatarstan, Kazan, Russia

    D. A. Kataev

  3. Kazan State Medical University, Kazan, Russia

    V. I. Tsirkin

  4. Kirov State Medical University, Kirov, Russia

    N. S. Zavalin

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  1. D. A. Kataev
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  4. M. A. Morozova
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Contributions

D.A. Kataev: cardiointervalogram (CIG) recordings in the field, analysis of CIG parameters, writing the article, literature analysis; V.I. Tsirkin: head of scientific work, literature analysis, work on the article; N.S. Zavalin: consultation on the use of methods of mathematical statistics; M.A. Morozova: organization of the purchase of the VNS-Micro autonomic tester, due to which the study and consultation on its use were carried out; S.I. Trukhina and A.N. Trukhin: scientific editing and design of the article and the necessary documentation.

Corresponding authors

Correspondence to D. A. Kataev, V. I. Tsirkin or S. I. Trukhina.

Ethics declarations

Ethics approval. All studies were carried out in accordance with the principles of biomedical ethics formulated in the Declaration of Helsinki of 1964 and its subsequent updates and approved by the local bioethical committee of Vyatka State University (Kirov), protocol no. 1 dated January 17, 2020.

Informed consent. Each participant in the study provided a signed voluntary written informed consent after explanation of the potential risks and benefits, as well as the nature of the upcoming study.

Conflict of interest. The authors declare the absence of obvious and potential conflicts of interest related to the publication of this article.

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Translated by M. Batrukova

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Kataev, D.A., Tsirkin, V.I., Zavalin, N.S. et al. Dynamics of TP, HF-, LF-, and VLF-Waves of the Cardiointervalogram (in Clinostasis Conditions) of an Elite Ski Racer in the Preparatory, Competition, and Transition Periods Depending on the Volume and Intensity of Training Loads. Hum Physiol 49, 525–537 (2023). https://doi.org/10.1134/S0362119723700408

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