Hughes Tom, Riley Richard D, Callaghan Michael J, Sergeant Jamie C
Manchester United Football Club, AON Training Complex, Birch Road, Off Isherwood Road, Carrington, Manchester, M31 4BH, UK.
Centre for Epidemiology Versus Arthritis, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK.
Sports Med Open. 2020 May 27;6(1):22. doi: 10.1186/s40798-020-00249-8.
In elite football (soccer), periodic health examination (PHE) could provide prognostic factors to predict injury risk.
To develop and internally validate a prognostic model to predict individualised indirect (non-contact) muscle injury (IMI) risk during a season in elite footballers, only using PHE-derived candidate prognostic factors.
Routinely collected preseason PHE and injury data were used from 152 players over 5 seasons (1st July 2013 to 19th May 2018). Ten candidate prognostic factors (12 parameters) were included in model development. Multiple imputation was used to handle missing values. The outcome was any time-loss, index indirect muscle injury (I-IMI) affecting the lower extremity. A full logistic regression model was fitted, and a parsimonious model developed using backward-selection to remove factors that exceeded a threshold that was equivalent to Akaike's Information Criterion (alpha 0.157). Predictive performance was assessed through calibration, discrimination and decision-curve analysis, averaged across all imputed datasets. The model was internally validated using bootstrapping and adjusted for overfitting.
During 317 participant-seasons, 138 I-IMIs were recorded. The parsimonious model included only age and frequency of previous IMIs; apparent calibration was perfect, but discrimination was modest (C-index = 0.641, 95% confidence interval (CI) = 0.580 to 0.703), with clinical utility evident between risk thresholds of 37-71%. After validation and overfitting adjustment, performance deteriorated (C-index = 0.589 (95% CI = 0.528 to 0.651); calibration-in-the-large = - 0.009 (95% CI = - 0.239 to 0.239); calibration slope = 0.718 (95% CI = 0.275 to 1.161)).
The selected PHE data were insufficient prognostic factors from which to develop a useful model for predicting IMI risk in elite footballers. Further research should prioritise identifying novel prognostic factors to improve future risk prediction models in this field.
NCT03782389.
在精英足球(英式足球)领域,定期健康检查(PHE)可为预测受伤风险提供预后因素。
开发并在内部验证一个预后模型,以仅使用源自定期健康检查的候选预后因素来预测精英足球运动员在一个赛季中个体化间接(非接触性)肌肉损伤(IMI)的风险。
使用了152名球员在5个赛季(2013年7月1日至2018年5月19日)常规收集的季前定期健康检查和损伤数据。模型开发纳入了10个候选预后因素(12个参数)。采用多重填补法处理缺失值。结局为任何导致失能的、影响下肢的索引间接肌肉损伤(I - IMI)。拟合了一个完整的逻辑回归模型,并使用向后选择法开发了一个简约模型,以去除超过相当于赤池信息准则阈值(α = 0.157)的因素。通过校准、区分度和决策曲线分析评估预测性能,并在所有填补数据集中求平均值。该模型通过自举法进行内部验证,并针对过度拟合进行了调整。
在317个参与者赛季中,记录了138例I - IMI。简约模型仅包括年龄和既往IMI的发生频率;表观校准良好,但区分度一般(C指数 = 0.641,95%置信区间(CI) = 0.580至0.703),在37% - 71%的风险阈值之间临床效用明显。经过验证和过度拟合调整后,性能有所下降(C指数 = 0.589(95% CI = 0.528至0.651);总体校准 = - 0.009(95% CI = - 0.239至0.239);校准斜率 = 0.718(95% CI = 0.275至1.161))。
所选的定期健康检查数据作为预后因素,不足以开发出一个用于预测精英足球运动员IMI风险的有用模型。进一步的研究应优先确定新的预后因素,以改进该领域未来的风险预测模型。
NCT03782389。