Abstract
Objective
There is growing evidence that knee osteoarthritis (OA), a significant source of chronic pain, is only partly explained by joint pathophysiology, varies significantly between individuals and may be partly driven by changes in periarticular tissues. The objective of this pilot study was to further characterize soft tissue properties that may be important to knee OA pain, and their associations with indicators of pain sensitization.
Methods
Forty‐two older adults (aged 50–85 years) with knee OA pain completed quantitative sensory testing (QST), myotonometry (ie, MyotonPRO) in the rectus femoris and biceps femoris, and clinical measures. Using data reduction techniques and unsupervised machine learning, we identified pain sensitivity profiles. Univariate and multivariate analyses of covariance examined associations between pain sensitivity profiles, muscle properties (stiffness, tone, decrement, relaxation time, and creep) and clinical pain, adjusted for age, sex, and body mass index. Pearson correlations assessed bivariate correlations between QST measures and muscle properties.
Results
Two profiles were identified: (1) high pain sensitivity or inefficient conditioned pain modulation (CPM) and (2) low pain sensitivity or efficient CPM and were significantly associated with muscle properties and clinical pain (
P
Conclusion
Using a brief QST battery, we identified two distinct pain sensitivity profiles that were differentially associated with periarticular tissue properties. Our results align with recent findings demonstrating distinct pain phenotypes in knee OA and that periarticular tissues may be important to understanding pain variability in knee OA.