肺栓塞相关危险因子风险列线图及预测模型系数森林图的建立  

Establishment of Risk Nomograms of Risk Factors Related to Pulmonary Embolism and Forest Plots of Prediction Model Coefficient

作　　者：郑艾波 孙楷[1] 沈奕播[1] 廖慧 陈治宇 ZHENG Aibo;SUN Kai;SHEN Yibo;LIAO Hui;CHEN Zhiyu(Zigong Forth People’s Hospital,Zigong,Sichuan,China 643000)

机构地区：[1]四川省自贡市第四人民医院,四川自贡643000

出　　处：《中国药业》2022年第S02期151-154,共4页China Pharmaceuticals

摘　　要：目的建立肺栓塞相关危险因子风险列线图及预测模型系数森林图。方法回顾性分析医院呼吸与危重症医学科2016年1月至2020年12月收治的患者671例,按病情分为肺栓塞组(221例)及非肺栓塞组(450例)。对患者发生肺栓塞的相关因素进行分析,并建立相关危险因子风险列线图及预测模型系数森林图。结果单因素分析显示,肺栓塞患者中活动性恶性肿瘤(38.5%比17.8%)、双下肢不对称水肿(49.8%比14.0%)、AECOPD(33.9%比24.7%)、慢性心力衰竭(41.6%比28.2%)、Ⅰ型呼吸衰竭(43.0%比21.8%)、D-二聚体(63.8%比26.7%)、近1月内骨科手术史(31.7%比19.3%)、慢性全身使用激素(24.4%比17.1%)占比较非肺栓塞组高,且肺栓塞组患者的年龄(61.12±5.96比59.70±5.95)、体质量指数(BMI)(21.70±3.17比19.27±1.61)均显著大于非肺栓塞组(P<0.05)。Logistic回归模型,以构建患者出现肺栓塞的风险预测模型(模型1、模型2、模型3),结果显示模型2的预测效果最佳,具有最佳的AUC值(0.862),灵敏度(0.638)、特异度(0.896),ROC误差0.026,据此可建立肺栓塞相关危险因子风险列线图及预测模型系数森林图。结论年龄,BMI,近1月骨科手术史,双下肢不对称水肿,绝对卧床(卧床>3d),D-二聚体,I型呼吸衰竭,慢性心力衰竭是肺栓塞发生的相关危险因素,所构建的危险因子列线图及预测模型系数森林图能有效预测肺栓塞的发生风险。Objective To establish the risk nomograms of risk factors related to pulmonary embolism and forest plots of prediction model coefficient.Methods A total of 671 patients admitted to the Department of Respiratory and Critical Care Medicine in the hospital from January 2016 to December 2020 were selected and divided into the pulmonary embolism group(221 cases)and the non-pulmonary embolism group(450 cases)according to the state of illness.The related factors of pulmonary embolism were analyzed,and the risk nomogram of the risk nomograms of risk factors and forest plots of prediction model coefficient were established.Results Single factor analysis showed that active malignant tumors(38.5%vs.17.8%),asymmetric edema of both lower limbs(49.8%vs.14.0%),AECOPD(33.9%vs.24.7%),chronic heart failure(41.6%vs.28.2%),Type I respiratory failure(43.0%vs.21.8%),D-dimer(63.8%vs.26.7%),history of orthopaedic surgery in the last month(31.7%vs.19.3%),chronic systemic hormone use(24.4%vs.17.1%)in the pulmonary embolism group were higher than those of the non-pulmonary embolism group.The age[(6112±5.96)vs.(5970±5.95)],body mass index(BMI)[(2170±3.17)vs.(1927±1.61)]of patients in the pulmonary embolism group were significantly larger than those of the non-pulmonary embolism group(P<0.05).Logistic regression model was used to build the risk prediction model of pulmonary embolism(model 1,model 2,model 3).The results showed that model 2 had the best prediction effect and the best AUC value(0.862),sensitivity(0.638),specificity(0.896)with 0.026 of ROC error,according to which the nomograms of risk factors related to pulmonary embolism and forest plots of prediction model coefficient could be established.Conclusion The age,BMI,orthopedic surgery history in recent one month,asymmetric edema of both lower limbs,absolute bed rest(bed rest>3 d),D-dimer,typeⅠrespiratory failure,and chronic heart failure are related risk factors for pulmonary embolism.The established risk nomograms of risk factors related to pulmonary embolism and forest plo

关 键 词：肺栓塞 危险因子 列线图 预测模型系数森林图 

分 类 号：R563[医药卫生—呼吸系统]