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基于生物化学血液测试分析的模型来预测运动员的代谢活动

Victoria A Zaborova¹, Evgenii I Balakin², Ksenia A Yurku²

¹Institute of Clinical Medicine, I.M. Sechenov First Moscow State Medical University, 119048, Moscow, Russia.

Sports medicine and health science

|February 24, 2025

概括

一个新的诊断模型使用血液测试预测运动员的新陈代谢过程,改善训练和恢复. 这有助于防止过度训练,并通过识别适应性阶段来提高性能.

科学领域:

运动科学运动科学运动科学
生物化学生化学
运动生理学运动生理学

背景情况:

优化运动表现和防止过度训练取决于有效的训练组织.
运动员对身体压力的适应涉及特定的生化和功能变化.
预测代谢状态有助于定制训练和恢复计划.

研究的目的:

开发一种诊断模型,用于预测运动员的代谢过程.
为了这个预测,利用标准的生化血液分析指标.
加强培训过程的组织,以提高效率.

主要方法:

参与的田径运动员 (n=42).
在一年周期内收集毛细血管血液样本进行生化分析 (3,625项测试).
从线性判别函数中导出方程,以预测合成代谢或合成代谢过程.

主要成果:

开发了一种具有92.1%信息容量的运动代谢过程的预测模型.
该模型的区分函数显示了统计学意义 (p < 0.01).
由神经内分泌系统活动证实,反映了适应性调节机制.

结论:

一个信息化的数学模型可靠地预测运动员的代谢活动阶段.
该模型有助于评估适应,识别弱点和预测绩效.
能够及时调整训练和恢复计划以获得最佳结果.

关键词:

合成代谢 (Anabolism) 是一种进行血液检查.催化作用的催化作用.代谢过程中的代谢.过度训练和运动人口.预测模型是一个预测模型.

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