预测肘关节三联征术后恢复的Nomogram图模型建立

目的：通过对肘关节三联征（triad of elbow，TE）的危险因素进行分析，建立个体化预测TE患者术后恢复的Nomogram图预测模型。方法：纳入2012年1月至2018年12月符合标准的TE患者116例，收集临床资料，采用单因素Logistic回归分析筛选独立危险因素，将有统计意义的危险因素纳入多因素Logistic回归模型，采用R软件建立预测TE患者术后恢复的Nomogram图模型，采用C-index验证模型的区分度，Calibration plot验证模型的一致性，采用决策曲线（decision curve analysis，DCA）验证模型的临床净获益率。结果：116例TE患者术后出现症状44例，发生率为37.93%。年龄（OR=1.930，95%CI 1.418~2.764），工作性质（OR=6.153，95%CI 1.466~31.362），吸烟（OR=4.463，95%CI 1.041~2.291），桡骨头Mason分型（OR=1.348，95%CI 2.309~9.348），冠状突Regan-Morrey分型（OR=4.424，95%CI 1.751~2.426）以及术后肘关节制动时间（OR=7.665，95%CI 1.056~5.100）均是影响TE术后恢复的独立危险因素（P<0.05）。Nomogram图的C-index为0.716，Calibration plot显示预测模型一致性良好，DCA曲线显示满意的临床净获益。结论：基于年龄、工作性质、吸烟、桡骨头Mason分型、冠状突Regan-Morrey分型以及术后肘关节制动时间这6项独立危险因素建立的预测TE患者术后恢复的Nomogram图模型，具有良好的区分度和一致性，临床实用价值高，帮助临床医生甄别高风险人群、制定对应干预对策。

Nomograma prediction of the surgical treatment in triad of elbow

Objective: To establish an individualized Nomogram prediction model for predicting the postoperative recovery of patients with triad of elbow(TE) by analyzing risk factors of triad of elbow joint.Methods: From January 2012 to December 2018,116 patients with TE who met the criteria were collected. The independent risk factors were screened by univariate Logistic regression analysis. The statistically significant risk factors were included in the multivariate Logistic regression model. The R software was used to establish the Nomogram diagram model to predict the postoperative recovery of TE patients. C-index was used to verify the discrimination,Calibration plot of the model,and the decision curve (decision curve analysis,DCA) to verify the net clinical benefit rate of the model.Results: Forty-four of the 116 patients with TE developed symptoms after operation,with an incidence of 37.93%. Age (OR=1.930,95% CI 1.418 to 2.764),work(OR=6.153,95%CI 1.466 to 31.362),smoking(OR=4.463,95%CI 1.041 to 2.291),the Mason of radial head(OR=1.348,95%CI 2.309 to 9.348),the Regan-Morrey of coronal process (OR=4.424,95%CI 1.751 to 2.426) and postoperative elbow immobilization time(OR=7.665,95%CI 1.056 to 5.100) were independent risk factors for postoperative recovery of TE(P<0.05). The C-index of Nomogram plot was 0.716. Calibration plot showed that the predictive model was consistent,and the DCA curve showed satisfactory clinical net benefit.Conclusion: The Nomogram for predicting postoperative results of TE patients based on six independent risk factors:age,work,smoking,Mason classification of radial head,Regan-Morrey classification of coronal process and immobilization time of elbow joint after operation,has good distinguishing capacity and consistency. The predictive model could help clinicians to identify high-risk population and establish appropriate intervention strategies.