Development and validation of a nomogram to predict chronic postoperative pain in elderly orthopedic patients

Abstract

At present, there is no nomogram for predicting chronic postoperative pain (CPSP) in elderly orthopedic patients. This study aimed to develop and validate a predictive nomogram of CPSP in elderly orthopedic patients, in order to analyze the risk factors of CPSP in elderly patients undergoing orthopedic surgery and provide support for the clinical prediction of the CPSP in elderly orthopedic patients. A total of 1,227 elderly patients undergoing elective orthopedic surgery were enrolled. The demographic and clinical data of patients were collected from the hospital electronic case system, and CPSP was diagnosed 3 months after surgery by telephone questionnaire based on the standards of the International Association for the Study of Pain (IASP). Patients were divided into two groups according to whether or not they had CPSP, and a predictive nomogram was developed using multivariate logistic regression analysis, followed by internal and external validation. Six variables were selected as independent predictors of CPSP in elderly patients undergoing orthopedic surgery: spouse or not, preoperative pain at surgical site, preoperative pain at non-surgical site, type of surgery, postoperative hospital stay, and acute postoperative pain (APSP) or not (P<0.05). The area under the curve (AUC) of this nomogram was 0.815 [95% confidence interval (CI): 0.783-0.847], showing good calibration and clinical practicability. The predictive nomogram of CPSP in this study has good prediction ability and accuracy, and can play an important auxiliary role in screening high-risk elderly patients with CPSP undergoing orthopedic surgery.