摘要
目的构建预测全身麻醉术后患者出现视物模糊的人工神经网络模型,以期为临床预防措施提供参考。方法对2023年3月至7月在本院接受全身麻醉的患者997例进行回顾性分析。收集患者的基本信息,包括年龄、性别、BMI、ASA分级、高血压病史、糖尿病病史、手术时间、手术体位、手术室室温、是否使用戊乙奎醚、术中是否使用阿托品、血压波动是否剧烈、手术补液量、术中失血量以及术中是否使用气腹等,利用这些数据构建人工网络预测模型。并通过模型评估各因素的重要性,计算模型的特异度、灵敏度和准确度,并绘制ROC曲线,计算AUC值。结果以可能的危险因素为输入层,全身麻醉后是否出现视力模糊为输出层,构建人工神经网络模型,预测模型结构为27-9-2。模型在训练集的特异度、灵敏度和准确度分别为91.7%、65.7%和87.8%;在测试集的特异度、灵敏度和准确度分别为92.2%、74.4%和89.5%,AUC值为0.889。模型预测显示,使用戊乙奎醚(0.193)、手术体位(0.155)、手术时间(0.120)和年龄(0.116)是导致全身麻醉后视力模糊的重要因素(标准化重要性>50%)。结论人工神经网络模型可以有效预测全身麻醉术后视力模糊的发生,为临床医师选择安全合理的预防治疗方案提供科学依据。
Objective To construct an artificial neural network model to predict postoperative blurred vision in patients undergoing general anesthesia,aiming to provide a reference for clinical preventive measures.Methods A retrospective analysis was conducted on 997 patients who underwent general anesthesia at our hospital from March 2023 to July 2023.Basic information of the patients was collected,including age,gender,body mass index(BMI),American society of anesthesiologists(ASA)classification,history of hypertension,history of diabetes,duration of surgery,surgical position,operating room temperature,use of enflurane,use of atropine during surgery,whether blood pressure fluctuated severely,volume of fluid replacement during surgery,intraoperative blood loss,and whether pneumoperitoneum was used during surgery.These data were used to construct an artificial neural network prediction model,and the importance of each factor was assessed through the model.The specificity,sensitivity,and accuracy of the model were calculated,and the receiver operating characteristic(ROC)curve was plotted to calculate the area under the curve(AUC)value.Results An artificial neural network model was constructed with potential risk factors as the input layer and the occurrence of blurred vision after general anesthesia as the output layer,with a model structure of 27-9-2.The specificity,sensitivity,and accuracy of the model in the training set were 91.7%,65.7%,and 87.8%,respectively,while in the test set,they were 92.2%,74.4%,and 89.5%,respectively,with an AUC value of 0.889.The model predicted that the use of enflurane(0.193),surgical position(0.155),duration of surgery(0.120),and age(0.116)are important factors leading to blurred vision after general anesthesia(standardized importance>50%).Conclusion The artificial neural network model can be used effectively to predict the occurrence of blurred vision after general anesthesia,providing a scientific basis for clinical physicians to choose safe and reasonable preventive treatment plans.
出处
《浙江临床医学》
2024年第11期1702-1705,共4页
Zhejiang Clinical Medical Journal
基金
浙江省嘉兴市科技计划项目(备案制)[2023]-SF202314
浙江省平湖市科技计划项目(社发类)[2023]一般-14。
关键词
人工神经网络
视物模糊
戊乙奎醚
Artificial Neural Network
Blurred Vision
Enflurane
