Keller Sebastian, Fischer Jonas, Ji Sanghyeon, Zwingmann Lukas, Wahl Patrick
Institute of Exercise Training and Sport Informatics, Section Exercise Physiology German Sport University Cologne, Cologne, Germany.
German Research Centre of Elite Sport, German Sport University Cologne, Cologne, Germany.
Int J Sports Med. 2025 Apr 27. doi: 10.1055/a-2550-4988.
This study investigated (1) the agreement of modeled lactate threshold 2 using peak oxygen uptake, cost of locomotion, and fractional utilization of peak oxygen uptake at lactate threshold 2 with the maximal lactate steady state in running and cycling; (2) the impact of different cost of locomotion determination methods on the accuracy of the model and (3) the contributions of peak oxygen uptake, cost of locomotion, and fractional utilization of peak oxygen uptake at lactate threshold 2 to the work rate at maximal lactate steady state. Thirty-four endurance-trained athletes (27.7±6.9 y, 56.2±5.5 ml∙kg∙min) completed an incremental step test on a treadmill or a cycling ergometer. Peak oxygen uptake, cost of locomotion at lactate threshold 1, at 80% of peak oxygen uptake, and at lactate threshold 2, and fractional utilization of peak oxygen uptake at lactate threshold 2 were assessed. Two to five 30-minute constant work rate tests were performed for maximal lactate steady state determination. Moderate to good agreement was found between modeled work rate corresponding to lactate threshold 2 and the maximal lactate steady state for running and cycling (intraclass correlation coefficient≥0.698) with the smallest mean difference (±limits of agreement) for cost of locomotion determined at lactate threshold 2 with -2.0±5.2 and -0.9±6.0%, respectively. Overall, 83 and 79% of the variance in the maximal lactate steady state was explained by peak oxygen uptake, cost of locomotion determined at lactate threshold 2, and fractional utilization of peak oxygen uptake at lactate threshold 2, respectively. Peak oxygen uptake and cost of locomotion determined at lactate threshold 2 contributed the most to the regression in running (54 and 40%) and cycling (74 and 51%), while fractional utilization of peak oxygen uptake at lactate threshold 2 had the smallest contribution (4 and 5%). Based on the high accuracy of the model with the major contribution of peak oxygen uptake and cost of locomotion determined at lactate threshold 2, the work rate corresponding to the maximal lactate steady state could be improved focusing on these two variables during training.
（1）使用峰值摄氧量、运动成本以及在乳酸阈2时峰值摄氧量的分数利用率所建立的乳酸阈2模型与跑步和骑行中最大乳酸稳态之间的一致性；（2）不同运动成本测定方法对模型准确性的影响；以及（3）峰值摄氧量、运动成本和在乳酸阈2时峰值摄氧量的分数利用率对最大乳酸稳态下工作率的贡献。34名耐力训练运动员（年龄27.7±6.9岁，峰值摄氧量56.2±5.5 ml∙kg∙min）在跑步机或自行车测功仪上完成了递增式台阶测试。评估了峰值摄氧量、乳酸阈1时、峰值摄氧量的80%时以及乳酸阈2时的运动成本，以及乳酸阈2时峰值摄氧量的分数利用率。进行了两到五次30分钟的恒定工作率测试以确定最大乳酸稳态。在跑步和骑行中，与乳酸阈2对应的模型工作率和最大乳酸稳态之间发现了中度到良好的一致性（组内相关系数≥0.698），其中在乳酸阈2时测定的运动成本的平均差异最小（±一致性界限），分别为-2.0±5.2%和-0.9±6.0%。总体而言，最大乳酸稳态中83%和79%的方差分别由峰值摄氧量、在乳酸阈2时测定的运动成本以及在乳酸阈2时峰值摄氧量的分数利用率所解释。在跑步（54%和40%）和骑行（74%和51%）中，峰值摄氧量和在乳酸阈2时测定的运动成本对回归的贡献最大，而在乳酸阈2时峰值摄氧量的分数利用率的贡献最小（4%和5%）。基于该模型的高精度以及峰值摄氧量和在乳酸阈2时测定的运动成本的主要贡献，在训练期间关注这两个变量可以提高与最大乳酸稳态对应的工作率。
