4.6 Article

Multivariate modelling of subjective and objective monitoring data improve the detection of non-contact injury risk in elite Australian footballers

Journal

JOURNAL OF SCIENCE AND MEDICINE IN SPORT
Volume 20, Issue 12, Pages 1068-1074

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jsams.2017.05.010

Keywords

Injury prevention; Team sports; Load monitoring; Acute:chronic workload ratio

Categories

Funding

  1. International Olympic Committee (IOC)

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Objectives: To assess the association between workload, subjective wellness, musculoskeletal screening measures and non-contact injury risk in elite Australian footballers. Design: Prospective cohort study. Methods: Across 4 seasons in 70 players from one club, cumulative weekly workloads (acute; 1 week, chronic; 2-, 3-, 4-week) and acute:chronic workload ratio's (ACWR: 1-week load/average 4-weekly load) for session-Rating of Perceived Exertion (sRPE) and GPS-derived distance and sprint distance were calculated. Wellness, screening and non-contact injury data were also documented. Univariate and multivariate regression models determined injury incidence rate ratios (IRR) while accounting for interaction/moderating effects. Receiver operating characteristics determined model predictive accuracy (area under curve: AUC). Results: Very low cumulative chronic (2-, 3-, 4-week) workloads were associated with the greatest injury risk (univariate IRR = 1.71-2.16,95% Cl = 1.10-4.52) in the subsequent week. In multivariate analysis, the interaction between a low chronic load and a very high distance (adj-IRR = 2.60, 95% Cl= 1.07-6.34) or low sRPE ACWR (adj-IRR = 2.52,95% Cl = 1.01-6.29) was associated with increased injury risk. Subjectively reporting yes (vs. no) for old lower limb pain and heavy non-football activity in the previous 7 days (multivariate adj-IRR = 2.01-2.25,95% Cl = 1.02-4.95) and playing experience (>9 years) (multivariate adj-IRR =2.05,95% Cl = 1.03-4.06) was also associated with increased injury risk, but screening data were not. Predictive capacity of multivariate models was significantly better than univariate (AUC(multivariate) =0.70, 95% Cl 0.64-0.75; AUC(univariate) range = 0.51-0.60). Conclusions: Chronic load is an important moderating factor in the workload-injury relationship. Low chronic loads coupled with low or very high ACWR are associated with increased injury risk. (C) 2017 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

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