Medial knee OA effects approximately 4.1 million people in England. Non-surgical strategies to lower knee joint loading is commonly researched in the knee OA literature as a method to alleviate pain and discomfort. Medial knee OA is much more prevalent than lateral knee OA due to the weight bearing line passing medial to the knee causing an external knee adduction moment (KAM). Numerous potential gait retraining strategies have been proposed to reduce either the first and/or the second peak KAM, including: toe-in gait, toe-out gait, lateral trunk lean and medial thrust gait. Gait retraining has been researched with little regard to the biomechanical consequences at the hip and ankle joints. This systematic review aimed to establish whether gait retraining can reduce medial knee loading as assessed by first and second peak KAMs, establish what are the biomechanical effects a reduced KAM has on other lower limb joint biomechanics and outline patient/participant reported outcomes on how easy the gait retraining style was to implement. The protocol for this systematic review was registered with PROSPERO on the 23rd January 2018 (registration ID: CRD42018085738). 13 databases were searched by one author (J.B.B). Additionally, PROSPERO was searched for ongoing or recently completed systematic reviews. Risk of bias was assessed using the Downs and Black quality index. Search: Group one consisted of keywords “walk” OR “gait”. Keywords “knee” OR “adduction moment” built up the second group. Group three consisted “osteoarthriti” OR “arthriti” OR “osteo arthriti”, OR “OA”. Group four included “hip” OR “ankle”. the searched results of each group were combined with conjunction “AND” in all fields. Out of the eight different gait retraining strategies identified, trunk lean reduced first peak KAM the most, which was evaluated in 3 studies, reducing first peak KAM by 20%-65%. There was a lack of collective pelvic, hip and/or ankle joint biomechanical variables reported across all 11 studies. Of eight gait retraining styles identified, the strategy that reduced first peak KAM the most was an increased lateral trunk lean, which was evaluated in 3 different studies. This is the first systematic review that has highlighted that there is limited evidence of the biomechanical consequences of a reduced knee joint load has on the pelvic, hip and/or ankle joints when undertaking gait retraining protocols. Future studies assessing gait retraining strategies should provide biomechanical outputs for other lower limb joints other than the knee joint, as well as providing participant perceptions on the level of difficulty the gait style is to perform.
Whilst home-based exercise rehabilitation plays a key role in determining patient outcomes following orthopaedic intervention (e.g. total knee replacement), it is very challenging for clinicians to objectively monitor patient progress, attribute functional improvement (or lack of) to adherence/non-adherence and ultimately prescribe personalised interventions. This research aimed to identify whether 4 knee rehabilitation exercises could be objectively distinguished from each other using lower body inertial measurement units (IMUs) and principle components analysis (PCA) in the hope to facilitate objective home monitoring of exercise rehabilitation. 5 healthy participants performed 4 repetitions of 4 exercises (knee flexion in sitting, knee extension, single leg step down and sit to stand) whilst wearing lower body IMU sensors (Xsens, Holland; sampling at 60 Hz). Anthropometric measurements and a static calibration were combined to create the biomechanical model, with 3D hip, knee and ankle angles computed using the Euler sequence ZXY. PCA was performed on time normalised (101 points) 3D joint angle data which reduced all joint angle waveforms into new uncorrelated PCs via an orthogonal transformation. Scatterplots of PC1 versus PC2 were used to visually inspect for clustering between the PC values for the 4 exercises. A one-way ANOVA was performed on the first 3 PC values for the 9 variables under analysis. Games-Howell post hoc tests identified variables that were significantly different between exercises. All exercises were clearly distinguishable using the PC scatterplot representing hip flexion-extension waveforms. ANOVA results revealed that PC1 for the knee flexion angle waveform was the only PC value statistically different across all exercises. Findings demonstrate clear potential to objectively distinguish between different knee rehabilitation exercises using IMU sensors and PCA. Flexion-extension angles at the hip and knee appear most suited for accurate separation, which will be further investigated on patient data and additional exercises.
Risk factors for poor outcomes after total knee replacement (TKR) have been identified, but the underlying causes are not fully understood. The aim of this research was to establish the relationship between measurable gait parameters and patients' subjective function, pre and post total knee replacement. 25 subjects underwent gait analysis, before and one year following total knee replacement. Patient reported function was investigated using the Activities of Daily Living Scale of the Knee Outcome Survey (KOS). Gait analysis was performed using infrared cameras and reflective marker clusters. Correlation between motion analysis data and patient reported function was investigate. Whilst multiple gait parameters correlated with KOS score preoperatively, there was no correlation after TKR. Three preoperative measurements correlated with the improvement in score a subject achieved following surgery: These were preoperative rate of extension in swing, total range of flexion from heel strike and time point of maximum stance extension. Our results suggest that whilst preoperatively there is a close relationship between knee biomechanical function and patient reported function, after TKR factors other than biomechanical function determine patient outcomes.
