Context: Models for prediction of upper extremity(UE) musculoskeletal injuries among female athletes may be useful for implementation of individualized injury risk reduction strategies. The purpose of this study was to identify the most powerful prediction model for quantifi cation of injury risk among female collegiate volleyball players. Methods: A cohort study design was used to assess the power of various risk screening metrics derived from tests of UE, lower extremity(LE), and core performance for prediction of musculoskeletal injury. Forty-eight collegiate volleyball players from 4 teams representing NCAA Division I, Division, III, and NAIA participated in the study. Pre-participation screening included the Horizontal Trunk Hold (HTH), Y-Balance Anterior Reach (YAR), single-leg vertical jump (SVJ), Closed Kinetic Chain Upper Extremity Stability Test (CKCUEST), Wall Angel Test (WAT), Lateral Scapular Slide Test (LSST), isometric internal rotator (IR) and external rotator (ER) strength, and the 10-item Sport Fitness Index (SFI), which assesses persisting effects of previous injury on function. Throughout the subsequent competitive season, number of sets played and all time-loss musculoskeletal injuries (UE, LE, core) were recorded for each athlete. Exposure-outcome associations were assessed using receiver-operating characteristic analysis, and logistic regression was used to identify the strongest multivariable prediction model. Results: Performance on CKCUEST (.24 hand touches), YAR (.62 cm), SVJ (.57 cm), SFI score (.78), and LSST (.1.15 cm asymmetry) were associated with both injury occurrence and volume of game exposure (number of sets played). A 3-factor model including SFI score (.78), game exposure (.100 sets), and LSST (.1.15 cm asymmetry) predicted the occurrence of time-loss musculoskeletal injury (.2 factors positive: ƒÔ2(3)=19.57; P<.001; OR=16.15). Quantifi cation of previous injury effects (SFI score) was the strongest predictor, particularly among players with low game exposure. Conclusions: Asymmetry in LSST (.1.15 cm) was the only upper extremity screening metric that predicted subsequent musculoskeletal injury. Game exposure is a factor that is often neglected in injury prediction studies, which mediated the association between high-level performance capabilities and injury occurrence. Quantifying persisting effects previous injury appears to be valuable for identifi cation of potentially modifi able risk factors. Additionally, scapular positioning asymmetry may be addressed through therapeutic exercise.
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