Injury Predictability of Acute:Chronic Workload Ratios: A Systematic Review and Meta-Analysis

Daniel Maupin, Ben Schram, Rob Marc Orr

Research output: Contribution to conferencePosterResearchpeer-review

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Background: Tracking training load and its relationship to injury risk has recently been gaining popularity in high level sporting environments. One such method of tracking training load is through Acute:Chronic Workload Ratios (ACWRs). While ACWRs are widely used, the quality of this research and volume of evidence supporting the use of this method have yet to be examined. Purpose: The aims of this systematic review were to identify and synthesize key findings of studies that have investigated the ability of ACWRs to predict injury risk. Methods: Pubmed, Embase, CINAHL, and Sports Discuss databases were searched using key search terms, developed through a preliminary review of the literature and using subject matter experts. Duplicates were removed, and articles were screened using inclusion and exclusion criteria established prior to screening. The Downs and Black checklist was used to critically appraise included studies and provide a strength of evidence for this method of injury risk prediction. A Kappa analysis was performed to investigate the level of agreement between raters (DM & BS) with the final score settled by consensus (RO). The scoring system proposed by Kennelly was used to grade the final score. Relevant data were extracted, tabulated, and synthesized. Results: From a total of 4281 identified studies, 16 studies were included for review. These studies ranged in scores from 50% to 64.3% with a mean score of 60.0% demonstrating 'fair' quality. Almost perfect interrater agreement (κ = 0.951) existed between raters. As most of the included studies were cohort studies, the included studies tended to score lower in areas of internal validity, specifically questions 14, 15, 19, 23, 24, 25. These questions were subsequently removed to provide a more valid comparison between studies, resulting in percentage quality scores increasing in range (63.6% to 81.8%), with a mean of 76.4%, demonstrating 'good' methodological quality. There were a high variety of ratios, variables, and reference groups utilized in these studies. Overall, the results tend to suggest that ACWRs are a valid tool to predict injuries in sports. These results appear to follow a parabolic curve, with ACWRs of around 1.00 showing the smallest injury risk and values greater or less than 1.00 increasing injury risk. As ACWRs approach 2.00, this injury risk appears to increase, with ACWRs >2.00 potentially showing the greatest injury risk. Conclusion(s): This systematic review supports the use of ACWR to predict injury risk in sporting populations. Considering the differences between studies, such as the various methods and populations studied, caution should be used when applying these results across all populations. However, this study does provide a general trend to guide clinicians in determining training dose and risk of injury. Implications: Clinicians can use ACWRs to identify those most at risk of injury when participating in sport or other highly physical activities. Clinicians can also use ACWRs to guide their training dose, be it for initial conditioning or return to activity following injury.
Original languageEnglish
Publication statusPublished - May 2019
EventWorld Confederation for Physical Therapy Congress 2019: WCPT 2019 - Geneva, Geneva, Switzerland
Duration: 10 May 201913 May 2019


ConferenceWorld Confederation for Physical Therapy Congress 2019
Abbreviated titleWCPT2019
Internet address


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