The combination of high acute training load, recent history of a leg injury, and a substantial reduction in the adductor squeeze test score was associated with a massive increase in injury risk (HR 22).
Cohort (n=55)
No
Do multiple risk factors (training load, injury history, screening, wellness) increase the risk of soft-tissue non-contact lower limb injuries in elite Australian footballers?
In elite team sport athletes, combining multiple risk factors such as high acute training load, recent injury history, and reduced musculoskeletal screening scores identifies extremely high risks for soft-tissue non-contact injuries.
Hazard Ratio: 22 (95% CI 9.7–52)
Aim: Relationships between athlete monitoring-derived variables and injury risk have been investigated predominantly in isolation. The aim of this study was to evaluate the individual and combined effects of multiple factors on the risk of soft-tissue non-contact injuries in elite team sport athletes. Methods: Fifty-five elite Australian footballers were prospectively monitored over two consecutive seasons. Internal and external training load was quantified using the session rating of perceived exertion and GPS/accelerometry respectively. Cumulative load and acute-to-chronic workload ratios were derived using rolling averages and exponentially weighted moving averages. History of injuries in the current and previous seasons was recorded along with professional experience, weekly musculoskeletal screening, and subjective wellness scores for individual athletes. Individual and combined effects of these variables on injury risk were evaluated with generalized linear mixed models. Results: High cumulative loads and acute-to-chronic workload ratios were associated with increased risk of injuries. The effects for measures derived using exponentially weighted moving averages were greater than those for rolling averages. History of a recent injury, long-term experience at professional level, and substantial reductions in a selection of musculoskeletal screening and subjective wellness scores were associated with increased risk. The effects of high cumulative loads were underestimated by ~20% before adjusting for previous injuries, whereas the effects of high acute-to-chronic workload ratios were overestimated by 10-15%. Injury-prone players, identified via player identity in the mixed model, were at > 5 times higher risk of injuries compared to robust players (hazard ratio 5.4, 90% confidence limits 3.6–12) despite adjusting for training load and previous injuries. Combinations of multiple risk factors were associated with extremely large increases in risk; for example, a hazard ratio of 22 (9.7–52) was observed for the combination of high acute load, recent history of a leg injury, and a substantial reduction in the adductor squeeze test score. Conclusion: On the basis of our findings with an elite team of Australian footballers, the information from athlete monitoring practices in team sports should be interpreted collectively and used as a part of the injury prevention decision-making process along with consideration of individual differences in risk.
Esmaeili et al. (Fri,) conducted a cohort in Soft tissue non-contact injuries (n=55). Combination of high acute training load, recent leg injury, and reduced adductor squeeze test score vs. Low acute load, no recent leg injury, and normal adductor squeeze test score was evaluated on Risk of lower limb soft-tissue non-contact injuries (HR 22, 95% CI 9.7-52). The combination of high acute training load, recent history of a leg injury, and a substantial reduction in the adductor squeeze test score was associated with a massive increase in injury risk (HR 22).