全膝关节置换后慢性疼痛影响因素的回顾性分析

Retrospective analysis of the influencing factors of chronic pain after total knee arthroplasty

背景:膝关节置换后慢性疼痛的影响因素是临床研究热点,而如何实现对膝关节置换后慢性疼痛发生风险的个体化预测,现国内外研究鲜有报道。目的:应用列线图构建并验证膝关节置换后慢性疼痛风险的个体化预测模型,探讨引起膝关节置换后慢性疼痛的影响因素。方法:选取2018年1月至2020年10月于石河子大学第一附属医院行膝关节置换后患者212例,收集患者资料并进行随访,通过Logistics回归分析,甄选出可能引起膝关节置换后慢性疼痛的独立危险因素,构建预测模型。使用C指数、ROC曲线、校准图和决策曲线分析来评估预测模型的鉴别、校准和临床有用性,并使用自举验证评估内部验证。结果与结论:①预测列线图中的预测因子包括睡眠、髋膝踝角、术前疼痛目测类比评分、出院时疼痛目测类比评分、止血带使用时间,构建的预测模型具有良好的识别能力;②ROC曲线显示该模型预测膝关节置换后慢性疼痛影响因素的曲线下面积为0.833,通过R软件计算C指数结果为0.837(95%CI:0.824-0.849);在区间验证中仍可达到0.8104的高C指数值,具有很好的校准性及良好的预测能力;③结论:睡眠、髋膝踝角、术前疼痛目测类比评分、出院时疼痛目测类比评分、止血带使用时间是患者膝关节置换后发生慢性疼痛的独立危险因素,构建预测膝关节置换后慢性疼痛影响因素的列线图模型,具有良好的区分度与准确度,可为临床个体化防治膝关节置换后慢性疼痛提供科学指导。

BACKGROUND:The influencing factors of chronic pain after knee arthroplasty are a hot spot in clinical research.However,there are few reports on how to achieve individualized prediction of the risk of chronic pain after knee arthroplasty at home and abroad.OBJECTIVE:To explore the influencing factors of chronic pain after knee arthroplasty by constructing and validating an individualized prediction model of chronic pain risk after knee arthroplasty using nomogram.METHODS:Totally 212 patients who underwent knee arthroplasty in the First Affiliated Hospital of Shihezi University from January 2018 to October 2020 were enrolled in this study.The data of the patients were collected and followed up.Through Logistics regression analysis,the independent risk factors of chronic pain after knee arthroplasty were selected to construct a predictive model.The C-index,ROC curve,calibration chart and decision curve analysis were used to evaluate the identification,calibration and clinical usefulness of the predictive model.The bootstrap verification was used to evaluate internal verification.RESULTS AND CONCLUSION:(1)Predictors contained in the prediction nomogram included sleep,hip-knee-ankle angle,preoperative pain visual analogue scale score,pain visual analogue scale score at discharge,and time of tourniquet.The constructed model had a good recognition ability.(2)The ROC curve showed that the model predicted the influencing factors of chronic pain after knee arthroplasty.The area under the curve was 0.833,and the C-index calculated by the R software was 0.837(95%CI:0.824-0.849).The high C-index value of 0.8104 could still be reached in the interval verification,with good calibration and good ability to predict.(3)It is concluded that sleep,hip-knee-ankle angle,preoperative pain visual analogue scale score,pain visual analogue scale score at discharge,and time of tourniquet are independent risk factors for chronic pain after knee arthroplasty.A nomogram model is constructed to predict the influencing factors of chronic pain after knee arthroplasty.Good discrimination and accuracy can provide scientific guidance for individualized clinical prevention and treatment of chronic pain after knee arthroplasty.