Osteoarthritis is one of the most prevalent diseases throughout the world. The person who suffered from the injuries such as of lower limb has higher chances of developing knee osteoarthritis. However, its early diagnosis and tracking its development is very difficult. To solve this issue, scientist conducted a cross-sectional study.

The objective of this study was to investigate self-reported knee osteoarthritis outcome scores and biomechanical gait parameters association and whether these outcome scores predict gait abnormalities characteristic of knee osteoarthritis in injured populations. Scientists also evaluated whether outcome scores and biomechanical outcomes linked to osteoarthritis severity via Spearman's correlation coefficient or not.

The study operated among asymptomatic patients with lower-limb injury and medial knee osteoarthritis. The evaluation involved a Spearman rank which helped to evaluate the association between outcome scores, knee injury and hip & knee kinetic/kinematic gait parameters. K-Nearest Neighbour algorithm was also conducted to evaluate which of the evaluated parameters that designed the strongest classifier model.  

 The outcome score differences were visible among groups, with the knee quality of life associated with first & second peak external knee adduction moment. Further, by linking hip and knee kinetics with the quality of life outcome, the most robust classifier formed with the least prediction error. This enabled the classification of injured subjects gait as characteristic of either asymptomatic or knee osteoarthritis subjects. Moreover, when the biomechanical outcomes and correlating outcome scores with osteoarthritis severity, only maximum external hip and knee adduction moment with first peak hip adduction moment shown prominent associations.