肺叶切除术后感染列线图预测模型的建立

Establishment of nomogram prediction model of infection after lobectomy

目的建立切实有效预测患者肺叶切除术后发生感染的列线图模型。方法回顾性分析宁波市第二医院2016年1月-2019年1月收治因各种病因行肺叶切除术患者196例的临床资料,通过单因素及多因素分析得到术后发生感染的影响因素,应用R语言软件包建立列线图预测模型并对该模型进行验证。结果通过对两组患者相关指标分析可知,年龄、吸烟史、糖尿病、美国麻醉医师协会(ASA)分级、手术时间以及病变性质为肺叶切除术后发生感染的影响因素,基于上述影响因素成功建立了列线图模型。验证后发现预测值同实测值基本一致,说明本列线图预测模型具有较好的预测能力,同时采用Bootstrap内部验证法对其进行验证,C-index指数高达0.844(95%CI:0.773~0.915),说明本研究列线图模型具有良好的精准度和区分度。结论本研究成功建立了预测肺叶切除术后感染风险的列线图模型,能够有效地预测患者肺叶切除术后感染的概率,为临床工作提供指导。

OBJECTIVE To establish an effective nomogram model for the prediction of infection after lobectomy.METHODS A retrospective analysis of the clinical data of 196 patients undergoing lobectomy for various causes from Jan.2016 to Jan.2019 in Ningbo Second Hospital was conducted.The influencing factors of postoperative infection were obtained through univariate and multivariate factor analysis.The R language software package was used to establish a nomogram prediction model and verify the model.RESULTS Analysis of relevant indicators of the two groups of patients showed that age,smoking history,diabetes,American Society of Anesthesiologists(ASA)classification,operative time,and lesion properties were the influencing factors of infection after lobectomy.Based on the above influencing factors,a nomogram model was successfully established.After verification,It was found that the predicted values are basically consistent with the measured,which indicated that the nomogram prediction model had good prediction ability.At the same time,it was verified by Bootstrap internal verification method,and the C-index was as high as 0.844(95%CI:0.773-0.915),which showed that nomogram model of this study had good accuracy and discrimination.CONCLUSION This study successfully established a nomogram model for predicting the risk of infection after lobectomy,which can effectively predict the probability of infection after lobectomy and provide guidance for clinical work.