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Updated: May 27, 2025
An Experimental Paradigm for the Prediction of Post-Operative Pain PPOP
Published on: January 27, 2010
Risk factors and predictive model for acute postoperative pain after hip and knee arthroplasty
Wanling Chen1, Wenjie Chen2, Weiliang Wan2
1The Guangzhou Development District Hospital, Guangzhou, China.
Background:
This study aims to identify key factors influencing acute postoperative pain (APP) following hip and knee arthroplasty, and to develop a predictive model to optimize pain management.
Methods:
The study included 492 patients who underwent hip or knee replacement surgery at our institution from July 2021 to July 2024. Preoperative, intraoperative, and postoperative data were collected. Least Absolute Shrinkage and Selection Operator regression and multivariate logistic regression analyses were utilized to identify factors significantly associated with the occurrence of APP.
Results:
The findings indicated that factors such as body mass index, diabetes, history of long-term use of analgesics, preoperative Visual Analogue Scale scores, Pain Catastrophizing Scale scores, duration of surgery, and intraoperative blood loss were closely linked to the occurrence of APP. Additionally, the preoperative use of prophylactic analgesics, postoperative use of analgesic pumps, and implementation of nerve blocks significantly reduced the risk of APP.
Conclusion:
This study identified several factors closely related to APP after hip and knee arthroplasty and provided a basis for postoperative pain management through the developed predictive model. The research underscores the importance of comprehensive preoperative assessment and the implementation of targeted pain prevention measures. Future studies are recommended to expand the sample size and include multiple centers to enhance the generalizability and practicality of these findings.
