Ramos Gabriel Vieira, Titotto Angélica Cristina, da Costa Guilherme Barbosa, Ferraz Guilherme de Camargo, de Lacerda-Neto José Corrêa
Equine Sports Medicine Laboratory, Department of Veterinary Clinics and Surgery, School of Agrarian and Veterinary Sciences, Jaboticabal, Brazil.
Equine Exercise Physiology and Pharmacology Laboratory (LAFEQ), Department of Animal Morphology and Physiology, School of Agrarian and Veterinary Sciences, Jaboticabal, Brazil.
Front Physiol. 2024 Apr 25;15:1324038. doi: 10.3389/fphys.2024.1324038. eCollection 2024.
The maximal lactate steady state (MLSS) is a well-known gold standard method for determining the aerobic capacity of athletic horses. Owing to its high cost and complex execution, there is a search for standardized exercise tests that can predict this value in a single session. One of the methods described for this purpose is the lactate minimum test (LMT), which could be more accurate despite being adequate to predict MLSS. This study aimed to examine the impact of training on the speed corresponding to lactate minimum speed (LMS) and to apply new mathematical methods to evaluate the fitness level of horses based on the curve obtained by the LMT. Ten Arabian horses underwent a 6-week training program based on LMS calculated by second-degree polynomial regression (LMS). In addition, the LMS was also determined by visual inspection (LMS), bi-segmented linear regression (LMS) and spline regression (LMS). From the curve obtained during the LMT, it was possible to calculate angles α, β and ω, as well as the total area under the curve (AUC) before (AUC) and after (AUC) the LMS. The methods for determining the LMS were evaluated by ANOVA, intraclass correlation coefficient (ICC) and effect size (ES) by Cohen's d test. The Pearson correlation coefficient (r) between the proposed LMS determination methods and other mathematical methods was also calculated. Despite showing a good correlation (ICC >0.7), the LMS determination methods differed from each other ( < 0.05), albeit without a significant difference resulting from conditioning. There were reductions in α:β ratio, angle α, and AUC, with the latter indicating lower lactate accumulation in the incremental phase of LMT after conditioning, in addition to an improvement in the animals' aerobic capacity. Considering that the most common methods for determining the LMS are applicable yet with low sensitivity for conditioning assessment, the approaches proposed herein can aid in analyzing the aerobic capacity of horses subjected to LMT. The mathematical models presented in this paper have the potential to be applied in human lactate-guided training program trials with a comparable study basis.
最大乳酸稳态（MLSS）是测定运动马匹有氧能力的一种广为人知的金标准方法。由于其成本高昂且执行复杂，人们正在寻找能够在单次测试中预测该值的标准化运动测试方法。为此目的所描述的方法之一是乳酸最低测试（LMT），尽管它足以预测MLSS，但可能更准确。本研究旨在探讨训练对对应乳酸最低速度（LMS）的速度的影响，并应用新的数学方法，根据LMT获得的曲线评估马匹的体能水平。十匹阿拉伯马接受了为期6周的训练计划，该计划基于通过二次多项式回归计算的LMS（LMS）。此外，还通过目视检查（LMS）、双段线性回归（LMS）和样条回归（LMS）来确定LMS。从LMT期间获得的曲线中，可以计算角度α、β和ω，以及LMS之前（AUC）和之后（AUC）曲线下的总面积。通过方差分析、组内相关系数（ICC）和Cohen's d检验的效应大小（ES）对确定LMS的方法进行评估。还计算了所提出的LMS确定方法与其他数学方法之间的Pearson相关系数（r）。尽管显示出良好的相关性（ICC>0.7），但LMS确定方法彼此不同（<0.05），尽管条件训练没有导致显著差异。α:β比值、角度α和AUC有所降低，后者表明条件训练后LMT增量阶段的乳酸积累减少，同时动物的有氧能力有所提高。考虑到确定LMS的最常用方法是适用的，但对条件训练评估的敏感性较低，本文提出的方法有助于分析接受LMT的马匹的有氧能力。本文提出的数学模型有可能应用于具有可比研究基础的人类乳酸引导训练计划试验。
