测定速度和评估接受乳酸最低测试马匹的调节能力--替代方法

Gabriel V Ramos, Angélica C Titotto, Guilherme Barbosa da Costa, Guilherme de Camargo Ferraz, J. C. Lacerda-Neto
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摘要

众所周知,最大乳酸稳态(MLSS)是测定运动马匹有氧能力的黄金标准方法。由于其成本高、操作复杂,人们一直在寻找能在单次运动中预测该值的标准化运动测试。乳酸最小值测试(LMT)就是为此目的而描述的方法之一,尽管它足以预测 MLSS,但可能更准确。本研究旨在考察训练对乳酸最低速度(LMS)相应速度的影响,并根据 LMT 得出的曲线应用新的数学方法评估马匹的体能水平。十匹阿拉伯马根据二度多项式回归(LMSP)计算出的乳酸最小速度(LMS)接受了为期六周的训练。此外,还通过目测(LMSV)、双分段线性回归(LMSBI)和样条回归(LMSS)确定了 LMS。根据 LMT 得出的曲线,可以计算出角度 α、β 和 ω,以及 LMS 之前(AUCPRELMS)和之后(AUCPOSLMS)的曲线下总面积(AUUCTOTAL)。确定 LMS 的方法通过方差分析、类内相关系数(ICC)和 Cohen's d 检验的效应大小(ES)进行评估。还计算了拟议的 LMS 测定方法与其他数学方法之间的皮尔逊相关系数(r)。尽管显示出良好的相关性(ICC >0.7),但 LMS 测定方法之间存在差异(p < 0.05),尽管没有因调节而产生的显著差异。α:β比值、α角和AUCPOSTLMS都有所下降,后者表明调理后LMT递增阶段的乳酸累积较低,此外动物的有氧能力也有所提高。考虑到确定 LMS 的最常用方法适用于调理评估,但灵敏度较低,本文提出的方法可帮助分析马匹在接受 LMT 后的有氧能力。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盐指导训练计划试验中。
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Determination of speed and assessment of conditioning in horses submitted to a lactate minimum test—alternative approaches
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 (LMSP). In addition, the LMS was also determined by visual inspection (LMSV), bi-segmented linear regression (LMSBI) and spline regression (LMSS). 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 (AUCTOTAL) before (AUCPRELMS) and after (AUCPOSLMS) 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 (p < 0.05), albeit without a significant difference resulting from conditioning. There were reductions in α:β ratio, angle α, and AUCPOSTLMS, 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.
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