Institute of Sport and Preventive Medicine, Saarland University, Saarbruecken, Germany.
Institute of Sport Science, Dept. Sociology and Economy of Sports, Saarland University, Saarbruecken, Germany.
Eur J Sport Sci. 2023 Sep;23(9):1829-1837. doi: 10.1080/17461391.2022.2134052. Epub 2022 Nov 11.
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 -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 ( < .001; -value: -17.01; test-pass error rate: 21 vs. 67%; test-fail: 19 vs. 64%) and a group-based cut-off ( < .001; -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.Assessing muscle recovery via CK using individualised ranges seems to offer a higher diagnostic accuracy than a sample-specific group-based analysis.Using an individualised algorithm seems to be a promising approach to overcome diagnostic problems arising from large inter- and intraindividual variability in blood parameters as it significantly improved the diagnostic accuracy of CK as a recovery marker.As recovery assessment in elite soccer ultimately aims at the accurate detection of differences in the individual player this algorithm seems to offer coaches and sport scientists a more sensitive approach compared to group-specific evaluations.
最近开发了一种个体化算法，并已证明其可显著提高肌酸激酶 (CK) 和尿素在耐力运动和羽毛球中的诊断准确性。在这项研究中，使用来自 161 名德国职业足球运动员在 2015-2017 赛季期间监测的重复测量数据评估了该算法的适用性和益处。在休息日（恢复期）和 48 小时内至少两次剧烈训练后（未恢复期）采集静脉血样，并分析 CK 和尿素。从同一数据集得出基于组的参考范围，以确保比较的最佳参考。进行 A-检验分析个体分类和基于组分类之间的错误率差异。与基于人群的分类（<0.001；-值：-17.01；测试通过错误率：21%比 67%；测试失败：19%比 64%）和基于组的截止值（<0.001；-值：-15.29；测试通过错误率：65%；测试失败：67%）相比，个体方法的 CK 值在评估肌肉恢复方面显示出显著更低的错误率。可以得出结论，使用血液标志物的个体化解释评估足球运动员的肌肉恢复可能比基于人群和基于样本的组分类方法具有更高的诊断准确性。使用个体范围评估 CK 来评估肌肉恢复似乎比基于样本的组分析具有更高的诊断准确性。使用个体化算法似乎是克服血液参数个体内和个体间变异性大导致的诊断问题的有前途的方法，因为它显著提高了 CK 作为恢复标志物的诊断准确性。由于精英足球中的恢复评估最终旨在准确检测个体运动员之间的差异，因此与基于组的评估相比，该算法似乎为教练和运动科学家提供了一种更敏感的方法。
