Baseline self-report 'central mechanisms' trait predicts persistent knee pain in the Knee Pain in the Community (KPIC) cohort. Issue 2 (February 2020)

• Record Type: Journal Article
• Authors: Akin-Akinyosoye, K.; Sarmanova, A.; Fernandes, G.S.; Frowd, N.; Swaithes, L.; Stocks, J.; Valdes, A.; McWilliams, D.F.; Zhang, W.; Doherty, M.; Ferguson, E.; Walsh, D.A.
• Is Part Of: Osteoarthritis and cartilage. Volume 28:Issue 2(2020)
• Page Start: 173
• Page End: 181
• Publication Date: 2020-02
• Subjects: Knee pain -- Central pain mechanisms -- Outcome measures -- Quantitative sensory testing -- Phenotypes; Osteoarthritis -- Periodicals; Cartilage -- Periodicals; Osteoarthritis -- Periodicals; Cartilage -- Periodicals; Arthrose -- Périodiques; Articulations -- Maladies -- Périodiques; 616.7223005
• DOI: 10.1016/j.joca.2019.11.004
• Languages: English
• ISSNs: 1063-4584

Abstract

Summary: Objectives: We investigated whether baseline scores for a self-report trait linked to central mechanisms predict 1 year pain outcomes in the Knee Pain in the Community cohort. METHOD: 1471 participants reported knee pain at baseline and responded to a 1-year follow-up questionnaire, of whom 204 underwent pressure pain detection thresholds (PPTs) and radiographic assessment at baseline. Logistic and linear regression models estimated the relative risks (RRs) and associations ( β ) between self-report traits, PPTs and pain outcomes. Discriminative performance for each predictor was compared using receiver-operator characteristics (ROC) curves. Results: Baseline Central Mechanisms trait scores predicted pain persistence (Relative Risk, RR = 2.10, P = 0.001) and persistent pain severity ( β = 0.47, P < 0.001), even after adjustment for age, sex, BMI, radiographic scores and symptom duration. Baseline joint-line PPTs also associated with pain persistence (RR range = 0.65 to 0.68, P < 0.02), but only in univariate models. Lower baseline medial joint-line PPT was associated with persistent pain severity ( β = −0.29, P = 0.013) in a fully adjusted model. The Central Mechanisms trait model showed good discrimination of pain persistence cases from resolved pain cases (Area Under the Curve, AUC = 0.70). The discrimination power of other predictors (PPTs (AUC range = 0.51 to 0.59), radiographic OA (AUC = 0.62), age, sex and BMI (AUC range = 0.51 to 0.64), improved significantly ( P < 0.05) when the central mechanisms trait was included in each logistic regression model (AUC range = 0.69 to 0.74). Conclusion: A simple summary self-report Central Mechanisms trait score may indicate a contribution of central mechanisms to poor knee pain prognosis.