Baseline self-report ‘central mechanisms’ trait predicts persistent knee pain in the Knee Pain in the Community (KPIC) cohort

Abstract

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 (b) 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 ¼ 2.10, P ¼ 0.001) and persistent pain severity (b ¼ 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 ¼ 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 (b ¼ À0.29, P ¼ 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 ¼ 0.70). The discrimination power of other predictors (PPTs (AUC range ¼ 0.51 to 0.59), radiographic OA (AUC ¼ 0.62), age, sex and BMI (AUC range ¼ 0.51 to 0.64), improved significantly (P < 0.05) when the central mechanisms trait was included in each logistic regression model (AUC range ¼ 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.

The Central Aspects of Pain in the Knee (CAP-Knee) questionnaire; a mixed-methods study of a self-report instrument for assessing central mechanisms in people with knee pain

“…We show that a Central Mechanisms trait, measured by a psychometrically validated CAP-Knee questionnaire was associated both with sensory and affective components of knee pain 8,9 . CAP-Knee items were understood well by people with knee pain, aligned to our mechanistic model of central pain augmentation.…”

“…We showed by factor analytic approaches, that these eight items contributed to a single underlying trait 9 . This 'Central Mechanisms' trait was associated with PPT at a distal site, and with knee pain severity more strongly than was any one of the eight characteristics alone 9 , and was a better predictor of future knee pain than other clinical predictors 8 . Existing questionnaires, including the short-form Central Sensitization Inventory and the Generalized Pain Questionnaire which were originally designed to assess central sensitivity syndromes such as fibromyalgia 14,15 omit important characteristics that have been associated with QST-evidence of central pain mechanisms in people with knee pain.…”

“…CAP-Knee would require further validation before use in conditions other than knee pain. Combination of CAP-Knee with other predictors of poor pain prognosis might best identify people most likely to benefit from interventions which target central pain mechanisms 8 .…”

Central Aspects of Pain in Rheumatoid Arthritis (CAP-RA): protocol for a prospective observational study

“…It has demonstrated good psychometric properties in multiple patient populations, but does not consider traits of neuropathic pain [ 36 ], which we have previously found to be part of the Central Mechanisms Trait in people with knee pain [ 68 ]. The originator painDETECT questionnaire has also been used to imply central pain augmentation in people with RA [ 38 ], although this alone was inferior to the central mechanisms trait in predicting PPT in people with knee pain [ 23 ]. The Allodynia Symptom Checklist is mostly used in people who suffer with headaches and has not been validated in a population with MSK pain [ 69 , 70 ].…”

“…A single page 8 item questionnaire, Central Aspects of Pain in the knee (CAP-knee) was designed and validated as a measurement and classification tool for central pain augmentation in people with knee pain. This self-report tool measures 8 characteristics strongly associated with central pain mechanisms and predicts 1-year pain outcomes in people with knee pain [ 23 ]. The Central Aspects of Pain in RA (CAP-RA) is a minor adaptation of the CAP-knee questionnaire for use in a RA population.…”