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

CONTEXT: 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. OBJECTIVE: To identify strength and spatiotemporal gait values that can predict knee moments in persons after ACLR. DESIGN: Cross-sectional study. SETTING: Laboratory. PATIENTS OR OTHER PARTICIPANTS: Twenty-three individuals with ACLR (14.4 ± 17.2 months post-ACLR). MAIN OUTCOME MEASURE(S): 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. RESULTS: 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. CONCLUSIONS: The identified spatiotemporal variables could be clinically feasible targets for biofeedback to improve gait after ACLR.

Identification of strength and spatiotemporal gait parameters associated with knee loading during gait in persons after anterior cruciate ligament reconstruction.

CONTEXT: Altered knee moments are common during gait in patients following anterior cruciate ligament reconstruction (ACLR). Modifiable factors that influence knee moments and are feasible to record in clinical settings such as strength and spatiotemporal parameters (e.g. step length, step width) have not been identified in persons after ACLR. OBJECTIVE: The objective was to identify strength and spatiotemporal gait parameters that can predict knee moments in persons after ACLR. DESIGN: Cross-Sectional Study Setting: Laboratory Patients: Twenty-three participants with ACLR (14.4 ± 17.2 months post-ACLR) participated. MAIN OUTCOME MEASURES: Peak knee flexion and adduction moments were measured while walking at self-selected speeds. Spatiotemporal gait parameters were recorded with a pressure walkway, and peak isokinetic knee extensor strength (60°/s) was recorded on a dynamometer. Pearson coefficients were used to examine the association of peak knee moments with strength and gait parameters. Variables correlated with peak knee flexion and adduction moments were entered into a stepwise regression model. RESULTS: Step width and knee extensor strength were the strongest predictors of knee flexion moment accounting for 44% of data variance, whereas stance phase time and step width were the strongest predictors of knee adduction moment explaining 62% of data variance. CONCLUSIONS: The spatiotemporal variables that were identified could be clinically feasible targets for biofeedback to improve gait after ACLR.