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Methods
Two groups of 20 females each, between the ages of 18 and 45 yr, were recruited for this study. All participants in the ACL group must have had a unilateral ACL reconstruction, completed rehabilitation, and returned to playing sports. Only females were recruited because previous research has shown sex differences in gait within healthy cohorts and in other tasks postoperatively such as jumping. Subjects were not excluded based on a bone patellar bone graft, hamstring graft, allograft, meniscal repair, or partial meniscectomy at the time of ACL reconstruction. Eligible subjects were involved in sports at the time of injury and reported that they had returned to competitive sports and jogging at least two times a week on the Tegner activity scale. The control group had to be free from any injuries within the past 6 months; individuals with a previous ACL reconstruction, meniscectomy, or other knee surgery were excluded. The control group was matched to the ACL subjects by age, height, weight, and activity level. In addition, all participants had to be heel-toe runners. The study was approved by the internal review board, and before enrollment, all participants gave their written consent for the study.
All participants completed an instrumented gait analysis. First, retroreflective markers were placed on the skin at the L4-5 junction, bilateral iliac crests, anterior superior illiac spines, greater trochanters, medial and lateral femoral condyles, tibial plateaus, malleoli, as well as the first and fifth metatarsal heads. Rigid shells with clusters of four markers were placed bilaterally on the thigh and shank. Additional tracking markers were placed on the posterior aspect of the shoes. All subjects wore New Balance WR662 running sneakers (New Balance, Brighton, MA). A standing calibration was then collected, followed by a hip motion trial to establish the hip joint center. The participant was then asked to walk at a self-selected pace for a 5-min warm-up to familiarize herself with the instrumented treadmill (Bertec Corp, Columbus, OH). After the warm-up, the subject walked at 1.5 m·s and then ran at 2.8 m·s, during which the marker trajectories and force data were recorded. The marker trajectories were recorded at 200 Hz with a 15-camera motion analysis system (Motion Analysis Corp., Santa Rosa, CA). Force data were collected at 1200 Hz, and heel strike and toe off were determined when the vertical ground reaction force was greater or less than 30 N.
Data were then postprocessed with Visual 3D software (C-motion, Germantown, MD) to filter the data, identify the functional hip joint center, and calculate joint angles and joint moments. Marker trajectory data were filtered at 8 Hz, and force data were filtered at 35 Hz using a fourth-order Butterworth low-pass filter. Custom LabView code (National Instruments, Austin, TX) was used to extract the sagittal plane joint angles, moments, loading rates, and initial impact forces. The average loading rate was determined between 20% and 80% of the period between foot strike and the initial impact peak in running or at 15% of stance in walking (Fig. 1). The period for calculating the average loading rate and the initial impact forces was chosen to be consistent with other previously published reports. Forces were expressed as BW and loading rates were expressed as BWs. Joint angles were determined using an x–y–z Cardan angle sequence, referencing the distal segment to the proximal. Joint moments were calculated from the proximal end of the distal segment and were normalized to body mass and height. The injured limb in the ACL-reconstructed subject was compared to the same limb in the matched control participant. Means and SD were then calculated for each group. Because of the differences in walking and running gait, we stratified the analysis based on gait condition, and differences between groups were determined using an independent two-sample t-test. To determine between-limb differences, the value of the injured limb was subtracted from the noninjured limb; this was repeated in the same limb order for the matched control subject. Means and differences between groups were then determined as described above. Statistical analysis was performed with SPSS Version 18.0 (IBM SPSS, Chicago, IL). Differences were considered significant if P < 0.05; trends were operationally defined as P values between 0.05 and 0.10. Lastly, each participant's kinematic and kinetic data series were time normalized and averaged across the five trials and then across each group to generate ensemble average graphs. Because of this, discrete data points taken from individual trials may not be reflected in the time-normalized and averaged graphs.
(Enlarge Image)
Figure 1.
Vertical ground reaction force (BW) and knee joint moments (N·m·kg·m) for the ACL group (large dashes) and the control group (small dashes) during (A) walking and (B) running. A vertical line was superimposed on the time point approximating the initial impact peak during running and 15% of stance in walking. The region over which loading rates were measured occurred sooner in running than walking. This also corresponded to the period when individuals transitioned from a small flexor to an extensor moment. Knee extensor moment is positive. The transition was delayed in the ACL cohort during running and this explains the small knee flexor moment observed at initial impact peak. Lastly, the brackets indicate the region over which the average loading rate was determined.
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