某三甲教学医院手术病人手术部位感染危险因素及人工网络模型探讨

目的 统计某医院外科病人手术部位感染发生率,找出导致术后感染的相关因素,对外科病人发生术后感染的机率进行科学预测。方法 研究对象选取2012—2015年某三甲教学医院术后病人,发生275例手术部位感染的病人为病例组,另按照1∶1比例选取术后无感染266例病人为对照组,进行病例回顾性调查研究,统计检出致病菌和手术感染部位情况,探讨手术部位感染综合因素,结合术后感染统计分析数据构建人工网络模型。结果 手术部位感染率0.35％。多因素分析结果表明,手术部位感染的独立危险因素分别是手术类型、是否有原发疾病、切口类别、ASA病情分级、病人年龄、手术时长、手术例次(OR=11.043,9.587,2.136,1.818,1.299, 1.293,1.041,P<0.05)。最终确定网络模型运行结果如下,平均误差为0.040%,网络错分率 0.038% ;通过曲线下面积(ROC)大于0.9。结论 部位感染危险因素前三位是手术类型、是否患有原发疾病、切口类别。人工网络模型针对手术部位感染危险度的预测结果较理想,建立与其相关预报信息平台系统,为临床院感管控决策提供指导依据。

Study on the risk factors of surgical site infection and artificial network model in a class a teaching hospital

Objective The incidence rate of surgical site infection of surgical patients in a hospital was calculated, the related factors of postoperative infection were found out, and the probability of postoperative infection of surgical patients was predicted scientifically. Methods Research object selected a top three teaching hospitals in 2012—2015 postoperative patients, 275 cases patients with surgical site infection cases, the other in accordance with the 1∶1 ratio to choose 266 patients as control group, postoperative infection cases retrospective survey study, statistical detection pathogenic bacteria and surgical site infection situation, to probe into comprehensive factors of surgical site infection combined with statistical analysis data to construct artificial network model of postoperative infection. Results The Results showed that surgical site infection rate was 0.35%. The Results of multi-factor analysis showed that the independent risk factors for surgical site infection were the type of operation, the presence of primary disease, the type of incision, the ASA grade, the patient's age, the duration of operation, and the number of cases (OR=11.043, 9.587, 2.136, 1.818, 1.299, 1.293, 1.041, P<0.05). Finally, the operation resultsof the network model are determined as follows: the average error is 0.040% and the network error rate is 0.038%. Area under the curve (ROC) is greater than 0.9. Conclusion The top three risk factors of surgical site infection were surgical type, primary disease and incision type. The prediction Results of the artificial network model for the risk of ssis were satisfactory, and the related prediction information platform system was established to provide guidance for the clinical hospital infection control decision.