Relating clinical measures of pain with experimentally assessed pain mechanisms in patients with knee osteoarthritis.

Background Peripheral and central sensitisation is prominent in knee osteoarthritis (KOA) and could be important for the reduced efficacy in some cases after as well surgery as pharmacological interventions. Although sensitisation is important in KOA it is not known to what degree it contributes to the overall clinical pain problem. The aim was therefore to investigate how much a combination of quantitative pain measures assessing various pain mechanisms (local and spreading hyperalgesia, temporal and spatial summation, descending inhibition) could predict peak pain intensity in patients with KOA. Methods While resting in a comfortable recumbent position the pressure pain thresholds (PPT) in the peripatellar region (eight locations) and at the tibialis anterior muscle (TA) were assessed by handheld pressure algometry, computer-controlled pressure algometry and cuff-algometry in the affected leg of 17 KOA patients without pain or sensory dysfunctions in other regions than the knee. Cuff-algometry was used to detect spatial pain summation of the lower leg. Temporal pain summation was assessed by repeated pressure stimulation on the TA muscle. The conditioning pain modulation (CPM) was evaluated by conditioning tonic arm pain and by PPT from the peripatellar region. The participants rated their peak pain intensity in the previous 24 h using on a 10 cm visual analogue scale. Results A multiple-regression model based on TA pressure pain sensitivity (spreading sensitisation) and temporal pain summation on the lower leg accounted for 55% of the variance in peak pain intensity experienced by the patients (P=0.001). Significant correlations (P< 0.05) were found between PPTs assessed by handheld pressure algometry in the peripatellar region and at TA (R = 0.94), PPTs assessed by computer-controlled pressure algometry and handheld pressure algometry in the peripatellar region (R = 0.71), PPTs assessed by computer-controlled pressure algometry in the peripatellar region and handheld pressure algometry at TA (R = 0.71) and temporal summation at the knee and at TA (R = 0.73). Conclusion Based on the multiple regression model 55% variance of the perceived maximal pain intensity in painful KOA could be explained by the quantitative experimental pain measures reflecting central pain mechanisms (spreading sensitisation, temporal summation). The lack of other correlations between the methods used in assessing pain mechanisms in this study highlights the importance of applying different tests and different pain modalities when assessing the sensitised pain system as different methods add complementary information. Implications Clinical pain intensity can be explained by influences of different central pain mechanisms in KOA. This has implications for pain management in KOA where treatment addressing central pain components may be more important than previously acknowledged.