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中国临床研究英文版:2023,36(5):726-729,733
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老年腰椎内固定术后慢性疼痛的风险因素及预测模型建立
(1. 北京市第六医院骨科,北京 100007;2. 北京市第六医院手术室,北京 100007)
Risk factors of chronic pain after lumbar internal fixation on elderly patients and construction of prediction model
摘要
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Received:October 26, 2022   Published Online:May 20, 2023
中文摘要: 目的 探究老年腰椎内固定术后慢性疼痛(CPSP)的风险因素,并构建预测模型。方法 回顾性收集2018年10月至2022年6月于北京市第六医院行后路腰椎内固定术的80例老年患者的临床资料,并进行单因素和多因素logistic回归分析,据此构建风险预测模型,混淆矩阵回代分析对模型的预测效能进行验证。结果 80例患者接受后路腰椎减压融合内固定术后,发生CPSP 27例,发生率为33.75%。手术时间≥3h、术前VAS评分≥6分、术前血管紧张素Ⅱ2型受体(AT2R)浓度≥1000pg/mL为老年腰椎内固定术后发生CPSP的独立危险因素(P<0.05)。根据多因素logistic回归分析中各因素变量回归系数与常数项构建老年腰椎内固定术后CPSP的预测模型,共纳入3项指标,分别为手术时间(X1)、术前VAS评分(X2)和术前AT2R浓度(X3),预测模型为:Prob=1/(e-Y),Y=4.285-1.013X1-1.187X2-1.276X3。ROC曲线分析结果显示,该模型预测老年腰椎内固定术后CPSP的灵敏度、特异度、曲线下面积分别为77.36%、74.07%和0.770(P<0.05);验证结果显示,该模型预测老年腰椎内固定术后CPSP的的总体预测准确率为75.00%(60/80)。结论 手术时间、术前VAS评分和术前AT2R浓度是影响老年腰椎内固定术后CPSP的风险因素,基于以上因素构建的预测模型具有良好预测效能,有利于临床早期识别CPSP的高风险患者。
Abstract:Objective To investigate the risk factors of chronic postsurgical pain(CPSP) after lumbar internal fixation on elderly patients and establish a prediction model for it. Methods A retrospective analysis was performed on the clinical data of 80 elderly patients undergoing posterior lumbar internal fixation in Beijing Sixth Hospital from October 2018 to June 2022. With univariate analysis and multivariate logistic regression analysis, the risk prediction model was constructed, and its predictive performance for CPSP was verified by using feedback analysis of the confusion matrix. Results Out of 80 patients receiving posterior lumbar decompression and internal fixation, 27 patients developed CPSP(33.75%, 27/80). Operation time(≥3h), preoperative VAS score(≥6) and preoperative angiotensin Ⅱ type 2 receptor(AT2R) concentration(≥1000pg/mL) were the independent risk factors of CPSP(P<0.05). According to the regression coefficients and constants of various variables by multivariate logistic regression analysis, the prediction model(Prob=1/(e-Y), Y=4.285-1.013X1-1.187X2-1.276X3) of CPSP was constructed, which included three indicators, namely, the operation time(X1), preoperative VAS score(X2) and preoperative AT2R concentration(X3). ROC curve analysis showed that the sensitivity, specificity and area under the curve(AUC) of the model in predicting CPSP were 77.36%, 74.07% and 0.770, respectively(P<0.05). The overall prediction accuracy of the model for CPSP was 75.00%(60/80) in the elderly after lumbar internal fixation. ConclusionsThe prediction model constructed based on the above-mentioned risk factors has good predictive performance and is conducive to early identification of high-risk elderly patients with CPSP in clinical practice.
文章编号:     中图分类号:R687.3    文献标志码:B
基金项目:北京中医药科技发展资金项目(JJ2018-21)
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