Individualised reference ranges for markers of muscle recovery assessment in soccer

Sabrina Skorski, Werner Pitsch, Vanessa Barth, Max Walter, Mark Pfeiffer, Alexander Ferrauti, Michael Kellmann, Anne Hecksteden, Tim Meyer
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Abstract

Recently an individualisation algorithm has been developed and shown to significantly improve the diagnostic accuracy of creatine kinase (CK) and urea in endurance sports and Badminton. In this study, the applicability and benefit of this algorithm was evaluated using repeated measures data from 161 professional German soccer players monitored during the 2015–2017 seasons. Venous blood samples were collected after a day off (recovered state) and after a minimum of two strenuous training sessions within 48 h (non-recovered state) and analysed for CK and urea. Group-based reference ranges were derived from that same dataset to ensure the best possible reference for comparison. A z-test was conducted to analyse differences in error rates between individualised and group-based classifications. CK values for the individualised approach showed significantly lower error rates in the assessment of muscle recovery compared to both a population-based (p < .001; z-value: −17.01; test-pass error rate: 21 vs. 67%; test-fail: 19 vs. 64%) and a group-based cut-off (p < .001; z-value: −15.29; test-pass error rate: 65%; test-fail: 67%). It could be concluded that the assessment of muscle recovery in soccer using individualised interpretations of blood-borne markers may offer higher diagnostic accuracy than a population-based and a sample-specific group-based approach.

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足球运动中肌肉恢复评估标志物的个性化参考范围。
最近,一种个性化算法被开发出来,并被证明可以显著提高耐力运动和羽毛球中肌酸激酶(CK)和尿素的诊断准确性。在这项研究中,使用2015-2017赛季监测的161名德国职业足球运动员的重复测量数据来评估该算法的适用性和效益。在休息一天后(恢复状态)和48小时内至少两次剧烈训练后采集静脉血样 h(未恢复状态),并分析CK和尿素。基于组的参考范围来自同一数据集,以确保尽可能提供最佳的参考进行比较。进行z检验以分析个性化分类和基于组的分类之间的错误率差异。与基于人群的两种方法相比,个体化方法的CK值在评估肌肉恢复方面的错误率显著较低(p z值:-17.01;测试通过错误率:21%对67%;测试失败:19%对64%)和基于组的截止值(p z值:-15.29;测试合格率:65%;测试失败:67%)。可以得出的结论是,使用血源性标志物的个性化解释来评估足球运动中的肌肉恢复,可能比基于人群和样本特异性群体的方法提供更高的诊断准确性。亮点使用个性化范围通过CK评估肌肉恢复似乎比基于样本特定群体的分析提供了更高的诊断准确性。使用个性化算法似乎是一种很有前途的方法,可以克服由于血液参数的个体间和个体内变异性大而引起的诊断问题,因为它显著提高了CK作为恢复标志物的诊断准确性。由于精英足球的恢复评估最终旨在准确检测球员个体的差异,与特定群体的评估相比,该算法似乎为教练和体育科学家提供了一种更敏感的方法。
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