| | The influence of gait pattern on signs of knee osteoarthritis in older adults over a 5–11 year follow-up period: A case study analysisReceived 24 May 2006; received in revised form 5 September 2006; accepted 11 September 2006. published online 10 November 2006. Abstract There is evidence that joint load is a factor in the development of osteoarthritis (OA) and, while altered gait profiles have been linked with OA, it is unknown if abnormal gait is a cause or effect of the disease. While the knee's adduction moment has been implicated in the development and progression of knee OA, it is also known that shearing forces are detrimental to the health of cartilage. The purpose of this pilot study was to examine the adduction moment and gait shear forces to determine if they may lead to signs of knee OA in older adults as they age. Knee gait kinetics, standardized radiographs and a questionnaire were collected on 28 older adults (M:13) during an initial visit, and 5 to 11 years later. Radiographic score increased (knees became more osteoarthritic in 15 of 28 subjects) over time. However, gait time–distance measures remained constant in disease free participants. Two returning participants developed symptoms and radiographic evidence of knee OA. The subject with the largest adduction moment developed signs of medial OA while the subject with the smallest adduction moment developed signs of lateral OA. In addition, there was a strong correlation between the magnitudes of the adduction moment and lateral–medial shear force that needs to be investigated further. Results suggest that gait can remain stable over time in older adults. Also, the medial and lateral OA case study findings suggest that the extreme gait profiles seen in these two participants may be important in explaining cartilage breakdown and the development of OA. This longitudinal study would suggest that perhaps it is the abnormal gait pattern that leads to the development of OA, although a much larger study would be needed to confirm this finding. 1. Introduction  Osteoarthritis (OA) has been called a “wear and tear” disease because of the established relationship between joint load and the development of OA. However, even though it is involved, load is not solely responsible for articular cartilage damage. Brandt et al. (1998) [1] described OA as “a metabolically active, dynamic process, including both destruction and repair that may be triggered by a variety of biochemical as well as mechanical insults.” This suggests that many factors, including the joint load and metabolic activity, are involved in OA initiation and progression. Therefore, it is quite possible that OA can be caused or worsened by atypical forces acting across a physiologically normal joint or typical forces acting across a physiologically abnormal joint. In both cases, OA results because the articular cartilage is broken down faster than it is repaired. For reasons including its anatomy, function and evolution [2], the knee is a common site of cartilage destruction and osteoarthritis [3]. It bears very heavy loads, up to six times body weight during routine activities [4], [5], while moving through a large range of motion. Within the knee, signs of OA occur most commonly at the sites of maximal load bearing [6], strengthening the belief that load is involved in OA progression. With every step taken a load is applied to the knee, which is an important consideration since abnormal gait patterns have been implicated in the development of OA [6], [7], [8], [9] . One gait measure commonly linked to the progression and presence of knee OA is the adduction moment [6], [7], [8], [9]. The hypothesis is that a large adduction moment increases the knee's medial compartment load causing cartilage breakdown and, eventually, a varus deformity and medial OA. This is supported by research showing that the magnitude of the adduction moment was a good predictor of the ratio of medial to lateral bone mineral content [6]. Since bone's metabolic response to continued loading is an increased mineral content, the above research suggests that a high adduction moment would preferentially load the medial side of the joint while a low adduction moment profile would load the lateral side. There is also evidence that shear stress is detrimental to cartilage health and may lead to the development of knee OA. Simulator studies have applied shear loads to animal and cadaver cartilage in vitro and found that these forces do damage the cartilage [10], [11], [12], [13]; but the mechanism for the detrimental effect of shear loads is not clear. Some studies have implicated various biochemical pathways as reasons for the cartilage degradation that results from shear stresses [10], [11], [12]. Others suggest that shear stress causes splitting or separation between the subchondral layer of bone and the intact articular cartilage. It is believed that these separations create local stress concentrations and subsequent cartilage degeneration [13], [14]. Few gait studies have examined the shear loads applied to the knee during gait and thus, the cause and effect of shear forces on cartilage as it relates to cartilage breakdown and OA needs to be investigated further. While gait analysis can quantify gait parameters that may help identify those predisposed to developing OA, the critical issue is to discern what constitutes an abnormal gait pattern and to determine its relative risk. One way to uncover abnormal patterns might be to compare those with and without OA. This has been done and differences have been found [15], [16], [17]. However, suggesting that the gait patterns of those with symptomatic OA increases the risk of OA is problematic, since many OA sufferers will have made gait adaptations to decrease their pain and increase walking stability. Making matters even more complicated is the notion that persons with varying degrees of OA symptoms may make different gait compensations [18]. A long-term study that follows individuals over time is needed to assess the risk of OA given particular gait profiles would assist in establishing effective screening measures and the development of preventative interventions. In order to assess the risk of a particular gait profile, this pilot study evaluated changes in gait and OA in a group of previously healthy older adults over a 5–11 year time period in an attempt to identify the influence of gait loads on the progression of radiographic evidence of knee osteoarthritis. 2. Methods 2.2. Clinical and anthropometric measures Selected anthropometrics measured while standing upright and barefoot in double limb support included the distance from the greater trochanter and the tibial plateau to the floor, thigh and calf circumference, as well as knee and ankle width. The leg dimensions were used in regression equations to estimate the thigh and skank's centre of gravity and kinetic properties [19]. The WOMAC® questionnaire assessed OA symptoms during the follow-up visit only as all subjects were self-described asymptomatic at initial testing. The WOMAC® is a validated, self-administered questionnaire that asks subjects to rate the degree of knee pain, stiffness and altered function on a 5-point Likert scale. These three sections were normalized [20] and totaled to give a clinical score for each participant during the follow-up visit only. A participant with no symptoms would score zero while the maximum possible score was 30. The WOMAC® was not collected during initial testing as all subjects were symptom free and believed themselves to be perfectly healthy at that point. 2.3. Radiographic evaluation At each visit participants had a series of standardized radiographs taken. The radiographs used the QUESTOR Precision Radiographic (QPR) procedure and included, for the test leg only, a hip and knee frontal view and knee lateral view [21], [22]. For this procedure the subjects stood on a rotatable platform in a test frame behind two accurately spaced Plexiglas sheets. The Plexiglas sheets in front of the lower limb contained lead beads embedded at precise locations that were imaged along with the limb and, as the configuration of the beads is known, image magnification and distortion were corrected. The participants were positioned so that the lateral view approximates the knee flexion plane and, by rotating the turntable 90° so that the subjects need not move, the frontal view was orthogonal to the lateral view. For this study the radiographs were used to estimate the extent of radiographic OA, to measure frontal plane knee alignment and to locate internal bone landmarks for the gait analysis. 2.4. Radiographic scoring The standardized radiographs, required for the gait analysis system, were also scored using the Scott OA scoring system [23], which is a valid and reliable measure of radiographic knee OA [24]. The radiographic features ranked included joint space narrowing, sclerosis, osteophytes and the spiking of the tibial spines (Eq. (1)); and, for each score, a higher number corresponded to more severe radiographic OA. Initial and follow-up radiographs were both scored, allowing an approximation of the radiographic change during the follow-up period. A normal knee, free of radiographic anomaly, would receive a score of zero while the maximal possible score was 14. Where: - TF scler =
Tibial–femoral sclerosis (scored as 0 or 1), - Med or Lat TF =
Medial or lateral joint space narrowing (score range from 0–3), - PF ost =
Patellofemoral osteophytes (score range from 0–3), - Med TF ost =
Medial tibial–femoral osteophytes (score range from 0–3), - Lat TF ost =
Lateral tibial–femoral osteophytes (score range from 0–3), - TF spine =
Spiking of the tibial spines (scored as 0 or 1).
2.5. Gait analysis All returning participants were tested using the identical 3D gait analysis system used previously. This is necessary to allow comparisons of data across the follow-up period. This system has been described and validated [25], [26], [27] and combines information from standardized radiographs, an optoelectronic motion tracking system (NDI, Waterloo, Ontario, Canada), an embedded force plate (AMTI, Newton, Mass, USA) and several specific anthropometrics measures to estimate the 3D net forces and net moments at the knee. During testing, participants wore their preferred comfortable walking shoes and walked at their naturally chosen pace. Markers were affixed to the lateral aspect of the test leg (the same leg that was tested during their initial visit) at the greater trochanter, the posterior aspect of the lateral femoral condyle, the head of the fibula, and the lateral malleolus. Two additional markers were attached to forward projecting rods strapped securely to the mid thigh and to the upper tibia just below the tubercle. Motion and force data were sampled synchronously at 100 Hz. When the radiographs were taken the participants wore additional lead beads attached to their skin at the locations where motion tracking markers would be placed later. Before any motion testing the participants assumed the same standardized reference position used during the radiographs and this reference position was recorded. Using the calibration information from the radiographs, the location of specific internal bone landmarks with respect to the coordinate systems developed using the surface markers was determined. Using these measures the location of the center of the femoral head, the midpoint of the distal femur, the midpoint of the proximal tibia and the midpoint of the malleoli were determined. Local segment coordinate systems were defined using these virtual markers and the thigh and shank probes. A standard link-segment model that considered the foot to be part of the shank was used to calculate the knee forces and moments. The forces and moments were defined using the right hand rule in the tibia local coordinate system: the distal–proximal force was parallel to the tibia's long axis with an orthogonal axis running from the lateral to medial aspect and another running from the posterior to anterior aspect. All forces were positive along the axis while moments were positive using a right hand rotation about the axis. The computed force and moments were the external net forces and net moments not their internal counterparts. For example, a positive flexion moment tends to rotate the tibia backwards (flex the knee) with respect to the femur and could be balanced internally by quadriceps contraction. As with many gait systems that use only external measurements, the net forces and moments are a conservative estimate of the true knee loads. In addition, the use of skin mounted markers and their movement during walking may introduce unwanted variation in these net forces and moments; yet it was imperative to use the same data collection protocol and analysis as was used during initial testing to allow for comparisons between visits. During data collection each participant performed at least 5 separate walking trials. Once the anthropometric measurements and radiographic measurements were determined and entered into the database, the knee moment and force data were computed for each trial. These data were normalized by body weight and time normalized to 100% of the cycle. The 5 individual trials were then averaged to produce a single representative trial for each participant. As an outcome measure, the average magnitude of each resultant curve (3 forces and moments) during the stance phase was calculated as a measure of the load experienced by the knee. Standard time–distance gait parameters were also calculated for each participant. These included gait velocity, step length, cadence, time per cycle, percent of time spent in stance phase and time spent in stance phase. 3. Results After initial examination of the knee radiographs and WOMAC® scores upon subsequent testing, two of our 28 returning participants developed both symptomatic and radiographic evidence of OA. Of these two participants, one had developed signs of medial compartment OA (MOA) while another had signs of lateral compartment OA (LOA) in the intervening years since their initial testing. Because of this finding, the relevant knee loads (adduction moment and lateral–medial (LM) shear force) and clinical information for these two participants were examined more closely in a case study format. Along with other radiographic signs of OA, one had medial joint space narrowing (MOA, Fig. 1) while the other had lateral joint space narrowing (LOA, Fig. 2). Other clinical and gait variables that were collected are also presented as individual scores for the MOA and LOA subject and as means for the NE subjects (n =26) in Table 2. | | |  | | WOMAC | Radiographic OA score | Frontal knee alignment (deg) | Gait velocity (m/s) | |
|---|
| | Visit 2 | Visit 1 | Visit 2 | Visit 1 | Visit 2 | Visit 1 | Visit 2 | |
|---|
| MOA | 9.5 | 0 | 6 | 0 | 6 | 1.14 | 0.75 | | | LOA | 9.0 | 5 | 9 | −11 | −10 | 1.30 | 0.81 | | | Controls | 2.2 | 1.6⁎ | 2.4⁎ | −3.0 | −4.1 | 1.16 | 1.08 | | | (4.1) | (1.7) | (2.2) | (3.4) | (2.8) | (0.18) | (0.25) | | | | |
It was also observed that these two subjects were also extremes for both the adduction moment and LM shear force measured during both initial and follow-up gait testing. Fig. 3 (Fig. 3A=Visit 1, Fig. 3B=Visit 2) shows the gait curves of both subjects along with the curves of the other 26 NE subjects. Note that these individual curves are mostly outside and on opposite sides of the spectrum of NE subject curves for both measures. The results of a correlation analysis for the average stance phase magnitudes of the adduction moment and the lateral–medial shear force for the entire group (n=28) revealed that they were significantly correlated at visit one (r=−0.834, p<0.01) and visit two (r=−0.763, p<0.01). If the MOA and LOA subjects were removed the correlations were weakened but were still significant (visit 1, r=−0.790, p<0.01; visit 2, r=−0.673, p<0.01). Fig. 4 displays plots of these relationships. 4. Discussion Since this study was not planned when the initial data were collected, data describing the participants’ health status at visit one is limited. There were no differences in any of the measured time–distance parameters between visits for the NE group (n=26). Since these temporal factors indicate functional ability [28], [29], [30] the NE group's functional walking ability did not change over the follow-up period. This result seems to conflict with those studies that have found a decrease in walking velocity with increasing age [31], [32]. The difference between our results and those of previous studies is that many compare a healthy population of older adults to a healthy young population, while the current study compared a healthy population of older adults to themselves several years later. While it is true that older adults tend to walk slower than young people, the current results suggest that an older person's walking velocity can remain constant over several years as long as they remain healthy. Conversely, for the medial and lateral OA subjects, walking velocity decreased by 34 and 38% respectively from visit 1 to visit 2 (Table 2). Although the NE group's functional walking ability did not change during the follow-up period, the radiographic health of their knees, as measured by the Scott Score [23], did worsen significantly. Why this radiographic change was not reflected in changes in walking ability is explained by the established discordance between radiographic and clinical symptoms [33], [34], [35]. As people age, they continue to apply loads to their joints and, through the years, the joint begins to show signs of OA even though no clinical symptoms are present. This discrepancy was quantified by Lawrence et al. (1996) [34] who found that the prevalence of symptomatic and radiographic OA in elderly people was 9.5% and 33% respectively. Thus, the natural wear and tear on the knees of healthy elderly people over many years does cause them to deteriorate at different rates, even though clinical symptoms may remain absent. Upon visual inspection of the gait data, two participants particularly stood out. One had a large adduction moment and low LM shear force, while the other had a low adduction moment and high LM shear force (Fig. 3). The inversion in the polarity of these gait waveforms between these two participants suggested a relationship among them. Using all returning participants’ stance phase magnitude scores from both visits as well as using the same measures for only the NE subjects, significant correlations were found among the adduction moment and the LM shear force. Removing the MOA and LOA subjects from this correlation weakened this relationship suggesting that if only one population was studied, for example only a medial OA population or only a normal elderly population, this relationship may be masked by the homogenous population. Adding both medial and lateral compartment OA subjects provides a more heterogeneous sample and strengthens this correlation. This suggests some unexplored relationship among these gait profiles that should be investigated further. Also, with recent evidence that OA of the knee's lateral compartment is almost as prevalent as in the medial compartment in some populations [36], adding lateral compartment OA subjects to study populations may provide more evidence relating to the cause of this condition. One explanation for the correlation among these measures is their association to the load distribution between the knee's medial and lateral compartments. The participant with the high adduction moment and low LM shear force had signs of medial OA (MOA — Fig. 1), while the subject with the low adduction moments and the high LM shear force had signs of lateral OA (LOA — Fig. 2). In part, the current results support such an explanation. The adduction moment profile of our MOA participant was larger than the NE group during both visits while the LOA participant's adduction moment during the same visits was lower than the NE group (Fig. 3). Consequently, both subjects have been applying abnormal loads to their knees with every step taken during the follow-up period and, over time, may have contributed to the development of radiographic OA. This is supported by the radiographic scores for the MOA participant that increased from 0 to 6 over the follow-up period and for the LOA participant where it increased from 5 to 9. Although the LOA participant did display some radiographic signs of OA while asymptomatic during the initial visit and the MOA participant did not, both have developed more radiographic signs of OA over the follow-up period and, considering their WOMAC scores, have also developed clinical symptoms as well. A recent cross sectional study examining the gait profiles of symptomatic pre-operative medial (n=15) and lateral (n=15) OAs as compared to a normal reference group (n=15) support this explanation [37]. Although Weidow et al. [37] reported internal moments and the current study reported the external moments, the same inversion in polarity of the adduction moment, as seen in our Fig. 3, was represented in their data. Since these same profiles are seen in our asymptomatic MOA and LOA case study subjects during their initial visit, this is the first longitudinal data that provides evidence that the abnormal gait may in fact precede the disease process. The lateral–medial (LM) shearing force revealed an extremely high laterally directed (large negative LM) force for the MOA participant and a lower than normal (small negative LM) force for the LOA participant at both visits. These findings correspond with Teixeira and Olney (1996) [38] who reported that those with medial OA had reduced LM shear force. While the causes of the strong correlation between the LM force and the adduction moment have yet to be determined, their relationship may be due to the knee's anatomical structure. With a high adduction moment, more load is borne by the tibia through the knee's relatively larger medial compartment. If the bearing surface is not perpendicular to the vertical load vector, as would be the case with a varus deformity, then some portion of the vertical load will be experienced as a shear force component. Therefore, as the adduction moment increases, the vertical compression force and the shear force component increase as well. The relationship between the shear forces created during gait and cartilage breakdown is not fully understood. Many studies have implicated the adduction moment in the breaking down of cartilage and the development of OA [6], [7], [8] but it may very well be the resulting shear forces that are the major cause of cartilage break down as evidence suggests that cyclic shear stress increases the risk of cartilage degradation [10], [11], [12], [13], [14]. This relationship needs to be investigated further. This study examined changes in gait patterns and radiographs for a group of older adults over a 5 to 10 year follow-up period. Those who remained healthy over the follow-up period maintained consistent gait functioning but developed more radiographic signs of OA. This suggests that as long as older people remain without clinical symptoms, they are able to maintain functional gait abilities. 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PII: S0968-0160(06)00148-7 doi:10.1016/j.knee.2006.09.002 © 2006 Elsevier B.V. All rights reserved. | |
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