Predictors of Chronic Postsurgical Pain in Elderly Patients Undergoing Hip Arthroplasty: A Multi-Center Retrospective...

Identifying patients at high risk of developing chronic postsurgical pain (CPSP) is of extreme importance in order to help launch appropriate therapeutic strategies and intensive initiation of pain management.

In this study, we aimed to conduct a multi-center retrospective cohort study to establish a prognostic model and a nomogram to predict the risks of CPSP in elderly patients who underwent hip arthroplasty at 6 months postoperatively.

We collected data from 736 patients aged >65 years who had undergone hip arthroplasty from October 1, 2016 to September, 30, 2018 at multiple tertiary referral centers in Guangzhou, China. All data were randomly stratified into a training set and a testing set at a ratio of 8:2. Data were analyzed via multiple logistic regression analysis with receiver operating characteristic (ROC) curves and areas under the curve. This model was further validated by estimating calibration and discrimination. A nomogram was ultimately developed.

A total of 736 eligible patients were enrolled, 27.20% of whom developed CPSP within 6 months postoperatively. Preoperative pain in the surgical area (OR=2.456, 95% CI:1.814-3.327, P<0.001), preoperative depression state (OR=1.256, 95% CI:1.146-1.378, P<0.001), surgical type (OR=7.138, 95% CI:3.548-14.364, P<0.001), acute postoperative numerical rating scale score (OR=5.537, 95% CI:3.607-8.499, P<0.001) and analgesic type (patient-controlled epidural analgesia: OR=0.129, 95% CI:0.055-0.299, P<0.001; patient-controlled intravenous analgesia: OR=0.033, 95% CI:0.011-0.097, P<0.001) were identified as independent significant factors associated with CPSP. A prognostic model was established and further validated. An ROC curve confirmed the predictive ability of this model with a high sensitivity value of 92.12% (95% CI:86.90-95.74) and specificity value of 91.72% (95% CI:88.77-94.11). A nomogram was developed to simplify the use of the predictive model in clinical practice.

This prognostic model could be of great value in clinical practice, serving as the basis for early personalized analgesic management of elderly patients undergoing hip arthroplasty.