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Associations of Functional Movement Screen Scores and Joint Stability Tests with Non-Contact Lower-Limb Injury Burden
Adam Eckart1, Pragya Sharma-Ghimire1
1Department of Health and Human Performance, Kean University, 1000 Morris Avenue, Union Township, NJ 07083, USA.
Abstract:
Background: The ability of preseason screening to identify athletes at risk for non-contact lower-limb injury remains uncertain. Purpose: To determine whether knee and ankle joint tests, body mass index (BMI), prior lower-limb injury, and Functional Movement Screen (FMS) scores were associated with injury and improved discrimination. Methods: Prospectively collected data from 381 collegiate athletes across 11 sports were retrospectively analyzed. Preseason assessments included BMI, injury history, FMS composite and subtest scores, and knee and ankle special tests summarized regionally. The primary outcome was two or more non-contact lower-limb injuries during the subsequent season; at least one injury was secondary. Hierarchical multivariable logistic regression, sex-stratified and sensitivity analyses, and cross-validated ridge logistic regression were performed. Results: Eighty athletes (21.0%) sustained at least one injury and 41 (10.8%) sustained two or more. Prior injury was associated with ≥2 injuries in Models 1 and 2 (odds ratios = 2.03 and 2.00, respectively) and remained the most consistent correlate across sensitivity analyses. Knee and ankle test findings and FMS composite scores were not consistently associated with injury in primary analyses. Exploratory subgroup associations included female BMI, In-Line Lunge, female Deep Squat, and male ankle instability without prior injury. For the primary outcome, apparent AUC was 0.621-0.649 and cross-validated AUC was 0.535-0.562; adding FMS variables did not improve cross-validated discrimination. Conclusions: Prior injury history was the most consistent risk marker, but the preseason battery showed limited generalizable predictive value. FMS and joint-test measures should not be used alone to predict individual injury risk.

