心脏外科术后医院感染的调查分析及预测概率模型的初步构建

Survey and analysis on nosocomial infections after cardiac surgery and primary construction of its prediction model

目的分析心脏外科术后医院感染现状,寻找其高危因素,从而初步建立术后医院感染发生的预测概率模型,为患者提供有针对性、预见性的治疗和护理。方法通过回顾性调查的方法,收集536例行心脏外科手术患者的围术期临床资料,进行单因素和多因素分析,确定危险因素,建立Logistic回归预测模型,绘制Logistic回归预测模型概率的受试者工作特征曲线,评价预测模型。结果 536例患者中发生医院院感染54例,感染率为10.07%。应用Logistic回归分析筛选出心脏外科术后医院感染的高危因素有高龄、术前肺功能差、体外循环时间长、心脏重症监护室住院时间长、气管插管时间长。建立Logistic回归预测模型为P=1/[1+exp(15.101-0.210×年龄-0.137×术前MVV%-0.112×体外循环时间-1.180×心脏重症监护室住院时间-3.240×气管插管时间)],受试者工作特征曲线下面积为0.871,总符合率为86.08%。结论心脏外科术后医院感染发生率较高,由多种原因导致,初步构建的心脏外科术后医院感染预测概率模型具有一定可行性。

Objective To analyze the present situation on nosocomial infections after cardiac surgery, find out its high risk factors and construct its prediction model primarily to provide reference for corresponding and predictive treatment and nursing care on patients. Method Collect the perioperative information of 536 patients undergoing cardiac surgery by retro spective investigation. Make single and multiple analysis, find out high risk factors, construct Logistic regression predic tion model and draw the ROC curve. Evaluate the prediction model. Result Of all 536 cases, 54 （10. 07%） occur nosocomi al infections. Logistic regression analysis shows that advanced age, poor preoperative pulmonary function, long cardiopul monary bypass time, long time in cardiac ICU and long intubation time. The Logistic regression prediction model construc ted is P 1/ [1＋exp（15. 101 0. 210×age 0. 137× preoperative MVV% 0. 112Xcardiopulmonary bypass time 1. 180×time in cardiac ICU 3. 240 × intubation time）]. Area under ROC curve is 0. 871. Approximate coincidence rate is 86.08% for postoperative prediction on nosocomial infection. Conclusion There is a high incidence of nosocomial infections after car diac surgery which is caused by many factors. The primary construction of its prediction model on nosocomial infections af ter cardiac surgery is feasible.