Associations of Strength and Spatiotemporal Gait Variables With Knee Loading During Gait After Anterior Cruciate Ligament Reconstruction

• Published in: Journal of athletic training Vol. 57; no. 2; pp. 158 - 164
• Main Authors: Lyle, Mark A., Jensen, Jake C., Hunnicutt, Jennifer L., Brown, Jonathan J., Chambliss, Cynthia P., Newsome, Michael A., Xerogeanes, John W., Tsai, Liang-Ching
• Format: Journal Article
• Language: English
• Published: United States National Athletic Trainers Association 01.02.2022
• Subjects: Anterior Cruciate Ligament Injuries - surgery; Anterior Cruciate Ligament Reconstruction; Biomechanical Phenomena; Biomechanics; Body Composition; Body Height; Body Weight; Correlation; Cross-Sectional Studies; Gait; Humans; Kinematics; Knee; Knee Joint - surgery; Ligaments; Motion; Muscle strength; Muscular Strength; Patients; Physical Fitness; Range of motion; Rehabilitation; Scientific Concepts; Statistical Analysis; Surgery; Values; Walking; biomechanics; osteoarthritis; walking; knee function
• ISSN: 1062-6050; 1938-162X; 1938-162X
• DOI: 10.4085/1062-6050-0186.21

Altered knee moments are common during gait in patients after anterior cruciate ligament reconstruction (ACLR). Modifiable factors that influence knee moments and are feasible to record in clinical settings such as strength and spatiotemporal values (eg, step length, step width) have not been identified in persons after ACLR. To identify strength and spatiotemporal gait values that can predict knee moments in persons after ACLR. Cross-sectional study. Laboratory. Twenty-three individuals with ACLR (14.4 ± 17.2 months post-ACLR). Peak knee-flexion and -adduction moments were measured while the participants walked at self-selected speeds. Peak isokinetic knee-extensor strength (60°/s) was recorded on a dynamometer, and spatiotemporal gait values were recorded using a pressure walkway. Pearson coefficients were calculated to examine the association of peak knee moments with strength and gait values. Variables correlated with peak knee-flexion and -adduction moments were entered into a stepwise regression model. Knee-extensor strength and step width were the strongest predictors of knee-flexion moment, accounting for 44% of the variance, whereas stance-phase time and step width were the strongest predictors of knee-adduction moment, explaining 62% of the variance. The identified spatiotemporal variables could be clinically feasible targets for biofeedback to improve gait after ACLR.