全膝关节置换术后7 d内非感染性发热的影响因素分析及列线图模型构建  

Analysis in risk factors of non-infectious fever within 7 days after total knee arthroplasty and establishment of a nomogram model

作　　者：宗侠 孙保安 汪宗保 ZONG Xia;SUN Baoan;WANG Zongbao(the First Department of Orthopedics,Huaibei City People′s Hospital of Anhui Province,Huaibei,Anhui,235000;Department of Orthopedics,Anhui Provincial Hospital of Integrated Traditional Chinese and Western Medicine,Hefei,Anhui,230031)

机构地区：[1]安徽省淮北市人民医院骨一科,安徽淮北235000 [2]安徽省中西医结合医院骨科,安徽合肥230031

出　　处：《实用临床医药杂志》2022年第17期67-71,共5页Journal of Clinical Medicine in Practice

基　　金：安徽省卫生健康委科研项目立项项目(AHWJ2021b052)。

摘　　要：目的 探讨全膝关节置换术(TKA)患者术后7 d内非感染性发热(NIF)的影响因素,并构建列线图预测模型进行验证,为临床早期诊断NIF提供简洁的量化工具。方法 采用回顾性队列研究方法,选取行单侧TKA的201例膝骨关节炎患者作为研究对象,根据术后7 d内是否发生NIF将患者分为NIF组57例和无NIF组144例。比较2组患者的临床资料,分别采用LASSO回归模型和多因素Logistic回归分析筛选NIF的影响因素,构建列线图模型并进行内部验证。结果 NIF组术中失血量、术后引流量、输血者、手术时间、抗生素使用时间和住院时间多于或长于无NIF组,差异均有统计学意义(P<0.05)。LASSO回归模型共筛选出4个具有非零特征的变量,即术中失血量、术后引流量、输血和手术时间。多因素Logistic回归分析显示,术中失血量(OR=3.652,95%CI为2.856~3.958,P<0.001)、术后引流量(OR=2.857,95%CI为2.242~3.234,P<0.001)、输血(OR=4.001,95%CI为3.562~4.659,P<0.001)和手术时间(OR=1.859,95%CI为1.326~2.525,P<0.001)均为TKA患者术后7 d内NIF的独立影响因素。应用R软件建立列线图模型,总分120分;受试者工作特征(ROC)曲线显示,列线图模型预测NIF的曲线下面积(AUC)为0.865(95%CI为0.799~0.901),提示该模型的区分度较好;Calibration校正曲线显示,该模型的一致性较好;决策曲线分析(DCA)显示,NIF发生的风险阈值超过8%时,列线图模型的临床价值最大。结论 TKA患者术后7 d内NIF发生率较高,术中失血量、术后引流量、输血和手术时间均为NIF发生的独立影响因素。基于这些影响因素构建的列线图模型可视化效果较好,且预测NIF发生的效能较高。Objective To explore the risk factors of non-infectious fever(NIF) within 7 days after total knee arthroplasty(TKA),and to construct and verify the nomogram predictive model,so as to provide a concise and quantitative tool for clinical early diagnosis of NIF.Methods A total of 201 patients with knee osteoarthritis underwent unilateral TKA were enrolled as study objects by retrospective cohort study.According to whether NIF occurred within 7 days after operation,the patients were divided into NIF group(n=57) and non-NIF group(n=144).The clinical data between the two groups were compared,and the risk factors of NIF were screened by LASSO regression and multivariate Logistic regression.The nomogram model was established and verified internally.Results Compared with the non-NIF group,the intraoperative blood loss,postoperative drainage volume,the number of patients with blood transfusion,operation time,antibiotic use time and hospital stay in the NIF group were significantly more or longer(P<0.05).LASSO regression screened four variables with non-zero characteristics,namely intraoperative blood loss,postoperative drainage volume,blood transfusion and operation time.Multivariate Logistic regression analysis showed that intraoperative blood loss( OR =3.652,95% CI,2.856 to 3.958,P < 0.001),postoperative drainage volume( OR = 2.857,95% CI,2.242 to 3.234,P < 0.001),blood transfusion( OR = 4.001,95% CI,3.562 to 4.659,P <0.001) and operation time( OR = 1.859,95% CI,1.326 to 2.525,P < 0.001) were the independent risk factors to NIF within 7 days after TKA.R software was used to establish the nomogram model,total score was 120.The receiver operating curve( ROC) showed that the area under the curve( AUC) of nomogram for predicting NIF was 0.865( 95% CI,0.799 to 0.901),suggesting that the discrimination of the model was good.Calibration correction curve showed a good consistency of the model.Decision curve analysis( DCA) showed that the clinical value of the model was the greatest when the risk threshold of NIF exceeded 8%.Conc

关 键 词：全膝关节置换术 非感染性发热 膝骨关节炎 列线图模型 

分 类 号：R684.3[医药卫生—骨科学] R47[医药卫生—外科学]