Construction and validation of a nomogram prediction model for chronic pain after total knee arthroplasty

The aim of this study was to investigate the main risk factors for chronic pain after total knee arthroplasty (TKA) and to develop a predictive model based on these factors. The study sample consisted of patients who underwent total knee replacement surgery between January 2022 and December 2023 at our institution. Independent predictors of postoperative chronic pain were identified by unifactorial and multifactorial logistic regression analyses, and a predictive nomogram was constructed based on the results of the analyses. To verify the validity of the model, receiver operating characteristic curves were plotted and the area under the curve was calculated, and calibration curves and decision curves were plotted to assess the accuracy and clinical applicability of the model. A total of 604 total knee replacement patients were included in the study, and 114 cases of chronic pain occurred after total knee replacement, with an incidence rate of 18.87%. After univariate and multivariate logistic regression analyses, a total of 5 variables were identified as independent risk factors for chronic pain after TKA, which were female (OR = 1.826, 95% CI = 1.084-3.078), insomnia (OR = 2.351, 95% CI = 1.301-4.250), and anxiety (OR = 2.787, 95% CI = 1.411-5.502), osteoporosis (OR = 4.336, 95% CI = 1.496-12.570), and tourniquet use time >60 minutes (OR = 3.047, 95% CI = 1.324-7.008). The nomogram of chronic pain after TKA constructed in this study has good predictive accuracy and helps physicians to intervene in advance in patients at high risk of chronic pain after TKA.