Derivation of a clinical prediction rule for chronic post-surgical pain after total knee arthroplasty considering biopsychosocial factors: A prospective cohort study

Background Biopsychosocial factors are involved in the occurrence of chronic post-surgical pain (CPSP) after total knee arthroplasty (TKA). The purpose of this study was to develop a clinical prediction rule (CPR) that considers biopsychosocial factors to predict which patients are more likely to develop CPSP after TKA. Methods CPSP after TKA was dichotomized into CPSP and non-CPSP groups using the Likert scale and Minimal clinically important difference, and binomial logistic regression analysis was performed. Cut-off values were then calculated using the extracted factors and dichotomized variables. The cut-off values and dichotomized variables were then used to derive a CPR that discriminates between groups with and without CPSP. Results Seventy-one TKA patients were included in the study. Binomial logistic regression analysis revealed that Central Sensitization Inventory (CSI) and Pittsburgh Sleep Quality Index (PSQI) were associated with CPSP. The cut-off values for CSI and PSQI were 26 and 7, respectively. The CPSP scale was created using the cut-off values of CSI and PSQI, with a score of 0 for being below the cut-off values of both CSI and PSQI, 1 for being above the cut-off values of either CSI or PSQI, and 2 for being above the cut-off values of both CSI and PSQI. Furthermore, the area under the curve (AUC) for CPR created by the presence of CPSP and using the CPSP scale was significant (AUC = 0.766; P = 0.001). Conclusion The combination of the two tests, CSI and PSQI, suggested the possibility of predicting CPSP after TKA.