基于随机森林算法的术中输血预测模型的建立与评价  

Establishment and evaluation of intraoperative blood transfusion prediction model based on random forest algorithm

作　　者：冯丽梅[1] 张婷[1] FANG Limei;ZHAGN Ting(Department of Blood Transfusion,First Medical Center of the Chinese People′s Liberation Army General Hospital,Beijing 100853,China)

机构地区：[1]解放军总医院第一医学中心输血医学科,北京100853

出　　处：《中国输血杂志》2022年第7期715-719,共5页Chinese Journal of Blood Transfusion

基　　金：解放军总医院临床科研扶持基金(2015FC-TSYS-1037)。

摘　　要：目的建立预测术中输血风险影响因素的随机森林算法预测模型,评价其临床预测性能。方法收集解放军总医院第一医学中心2014年1月~2017年12月手术患者48176例,根据术中是否输血分为输血组(n=5035)和未输血组(n=43141),比较分析2组年龄、性别、体重、血常规与凝血检测指标、手术等级、手术次数与麻醉方式,以及术前输血史等指标;将所有病例按7∶3随机分为训练集(n=33723)与测试集(n=14453),利用计算机编程语言(Python V 3.9.0)中sklearn功能包引入随机森林算法,将2组差异因素纳入随机森林算法以构建模型,使用受试者操作曲线(ROC)做模型评价。结果1)输血组与未输血组性别、年龄、血常规、凝血功能、手术等级、术前输血史等指标间差异均具有明显差别(P<0.05);2)除血型分布外,训练集与测试集病例其他指标间差异不大(P>0.05);3)建立的术中用血模型中血常规、凝血功能、全身麻醉等指标影响较大,累积重要度>0.90;4)ROC分析显示该随机森林模型在训练集与测试集预测时ROC曲线下面积达0.91和0.82,具有良好的预测能力。结论基于随机森林法的术中用血预测模型能较好地预测术中用血及输血风险因素。Objective To predict the risk factors of intraoperative blood transfusion by establishing a random forest algorithm prediction model,and to evaluate its prediction performance in clinical.Methods A total of 48176 patients who underwent surgery from January 2014 to December 2017 in the First Medical Center of the Chinese People′s Liberation Army General Hospital were collected and divided into a blood transfusion group(n=5035)and a non-transfusion group(n=43141)according to whether blood was transfused or not during the operation,and the age,gender,weight,blood routine,coagulation test indicators,surgical grade,number of operations and anesthesia methods,and preoperative blood transfusion history between the two groups were compared and analyzed.All cases were randomly divided into training set(n=33723)and the test set(n=14453),using the sklearn function package in the computer programming language(Python V 3.9.0)to introduce the random forest algorithm,with 2 groups of different factors incorporated into the random forest algorithm to build the model,and the model was evaluated using the operating curve(ROC).Results 1)There were statistically significant differences between the blood transfusion group and the non-transfusion group in terms of gender,age,blood routine,coagulation function,surgical grade,and preoperative blood transfusion history(P0.05);3)In the established intraoperative blood model,the blood routine,coagulation function and general anesthesia had a great influence,with the cumulative importance>"0.90";4)The ROC analysis showed that the area under the ROC curve of the random forest model was 0.91 and 0.82 in the training set and the test set,which demonstrated a good predictive ability.Conclusion The intraoperative blood,using prediction model based on random forest method,can predict intraoperative blood use and blood transfusion risk factors.

关 键 词：术中输血 输血预测模型 输血风险因素 随机森林算法 机器学习 

分 类 号：R457.1[医药卫生—治疗学] TP181[医药卫生—临床医学]