{"title":"Construction and validation of nomogram model for chronic postsurgical pain in patients after total knee arthroplasty: A retrospective study.","authors":"Shenghao Zhao, Ying Hu, Ye Li, Jie Tang","doi":"10.12669/pjms.41.3.11525","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Chronic postsurgical pain (CPSP) after total knee arthroplasty (TKA) is the most common postoperative complication in orthopedics. This study aims to explore the risk factors for CPSP after TKA and construct a nomogram model.</p><p><strong>Methods: </strong>This retrospective study included clinical records of 430 patients who received TKA treatment at Wuhan Fourth Hospital between January 2020 to January 2024. Patients were randomly divided into a training cohort (n=301) and a validation cohort (n=129) in a 7:3 ratios. The Least Absolute Shrinkage and Selection Operator (LASSO) algorithm and logistic regression analysis were used to identify the independent risk factors, and a predictive nomogram model was established based on the identified risk factors. The concordance index (C-index), calibration curve, receiver operating characteristic (ROC) curve and decision curve analysis were used to assess the predictive accuracy and clinical application value of the nomogram model.</p><p><strong>Results: </strong>Six risk factors for predicting CPSP were identified, including preoperative anxiety, preoperative depression, preoperative pain, duration of tourniquet use, pain upon discharge, and postoperative C-reactive protein levels. The nomogram model demonstrated sufficient predictive accuracy, with the area under the curve (AUC) values of 0.761 (95% CI: 0.689-0.833) and 0.806 (95% CI: 0.700-0.911) in the training cohort and validation cohort, respectively. The C-index of the training cohort and validation cohort were 0.733 and 0.761, respectively. The calibration curve shows good consistency between the predicted risk of the model and the actual risk of CPSP. Decision curve analysis (DCA) demonstrated the clinical applicability of the model.</p><p><strong>Conclusions: </strong>The nomogram model established in this study for predicting CPSP after TKA has good predictive value and may be used in clinical practice to identify patients at high risk of developing CPSP after TKA.</p>","PeriodicalId":19958,"journal":{"name":"Pakistan Journal of Medical Sciences","volume":"41 3","pages":"780-787"},"PeriodicalIF":1.2000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11911769/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pakistan Journal of Medical Sciences","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.12669/pjms.41.3.11525","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: Chronic postsurgical pain (CPSP) after total knee arthroplasty (TKA) is the most common postoperative complication in orthopedics. This study aims to explore the risk factors for CPSP after TKA and construct a nomogram model.
Methods: This retrospective study included clinical records of 430 patients who received TKA treatment at Wuhan Fourth Hospital between January 2020 to January 2024. Patients were randomly divided into a training cohort (n=301) and a validation cohort (n=129) in a 7:3 ratios. The Least Absolute Shrinkage and Selection Operator (LASSO) algorithm and logistic regression analysis were used to identify the independent risk factors, and a predictive nomogram model was established based on the identified risk factors. The concordance index (C-index), calibration curve, receiver operating characteristic (ROC) curve and decision curve analysis were used to assess the predictive accuracy and clinical application value of the nomogram model.
Results: Six risk factors for predicting CPSP were identified, including preoperative anxiety, preoperative depression, preoperative pain, duration of tourniquet use, pain upon discharge, and postoperative C-reactive protein levels. The nomogram model demonstrated sufficient predictive accuracy, with the area under the curve (AUC) values of 0.761 (95% CI: 0.689-0.833) and 0.806 (95% CI: 0.700-0.911) in the training cohort and validation cohort, respectively. The C-index of the training cohort and validation cohort were 0.733 and 0.761, respectively. The calibration curve shows good consistency between the predicted risk of the model and the actual risk of CPSP. Decision curve analysis (DCA) demonstrated the clinical applicability of the model.
Conclusions: The nomogram model established in this study for predicting CPSP after TKA has good predictive value and may be used in clinical practice to identify patients at high risk of developing CPSP after TKA.
期刊介绍:
It is a peer reviewed medical journal published regularly since 1984. It was previously known as quarterly "SPECIALIST" till December 31st 1999. It publishes original research articles, review articles, current practices, short communications & case reports. It attracts manuscripts not only from within Pakistan but also from over fifty countries from abroad.
Copies of PJMS are sent to all the import medical libraries all over Pakistan and overseas particularly in South East Asia and Asia Pacific besides WHO EMRO Region countries. Eminent members of the medical profession at home and abroad regularly contribute their write-ups, manuscripts in our publications. We pursue an independent editorial policy, which allows an opportunity to the healthcare professionals to express their views without any fear or favour. That is why many opinion makers among the medical and pharmaceutical profession use this publication to communicate their viewpoint.