重症监护病房医院感染早期预测模型的建立

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目的:回顾性分析衡水市二级以上医院重症监护病房(ICU)的医院感染患者入住ICU 24 h内的高危因素,建立ICU医院感染早期预测模型。方法:回顾性查阅衡水市二级以上医院2011年1月至2015年12月ICU医院感染患者相关病原学数据和原始病历资料。记录患者一般临床资料,包括患者性别、年龄、转入原因,入住ICU 24 h内血生化、急性生理学与慢性健康状况评分系统Ⅱ(APACHE Ⅱ)和序贯器官衰竭评分(SOFA)、应用血管活性药物、血液净化情况。分析医院感染危险因素,建立早期预测量表,并利用2016年1月至2018年12月医院感染患者的数据对预测模型进行验证。结果:共2 453例患者资料纳入分析,445例患者ICU住院期间发生医院感染,医院感染发生率18%,其中肺炎(包括医院获得性肺炎和呼吸机相关性肺炎)135例(30%),导尿管相关泌尿系感染245例(55%),中心静脉导管相关血流感染65例(15%)。Logistic回归分析发现年龄≥72岁(n OR=2.15,95%n CI:1.23~3.47,n P=0.03)、新发脑卒中(n OR=1.59,95%n CI:1.22~3.31,n P<0.01)、入住ICU 24 h内APACHE Ⅱ评分≥18(n OR=3.64,95%n CI:2.79~5.32,n P=0.02)和SOFA评分≥8(n OR=3.17,95% n CI:1.93~5.66,n P<0.01)是医院感染的独立预测因素。根据上述危险因素建立量表,医院感染早期预测评分范围为0~7分,最佳截断值为4分;导尿管相关泌尿系感染早期预测评分范围为0~7分,最佳截断值为4分;肺炎早期预测评分范围为0~7分,最佳截断值为5分;中心静脉导管相关血流感染早期预测评分范围为0~7分,最佳截断值为6分。利用2016年1月至2018年12月医院感染患者的数据对预测模型进行验证显示该量表预测效果良好。n 结论:年龄≥72岁、新发脑卒中、入住ICU 24 h内APACHE Ⅱ评分≥18分和SOFA评分≥8分能够早期预测ICU医院感染风险,早期发现高危人群。“,”Objective:To analyze the risk factors of intensive care unit (ICU) nosocomial infection in secondary and above hospitals in this region within 24 hours after admission, and establish the early prediction model of ICU nosocomial infection.Methods:The relevant etiological data and original medical records of ICU patients with nosocomial infection from January 2011 to December 2015 were reviewed retrospectively.Records in patients with clinical data, including patient gender, age, reasons for, transfer to ICU blood biochemical, acute physiology and chronic health evaluation system (APACHE Ⅱ) and sequential organ failure score (SOFA), application of vascular active drugs, blood purification within 24 h. Risk factors of nosocomial infection were analyzed, an early prediction scale was established, and data of nosocomial infection patients from January 2016 to December 2018 were used to validate the prediction model.Results:Information included in the analysis of 2453 patients, 445 cases of ICU patients during hospitalization hospital infection, hospital infection rate was 18%, including pneumonia (including hospital-acquired pneumonia and ventilator associated pneumonia) in 135 cases (30%), catheter associated urinary tract infection in 245 cases (55%), central venous catheter-related bloodstream infection in 65 cases (15%). Logistic regression analysis found that age 72 n OR higher (n OR=2.15, 95% n CI: 1.23-3.47, n P=0.03), the new hair stroke (n OR=1.59, 95% n CI: 1.22-3.31, n P<0.01), into the ICU 24 h APACHE Ⅱ score≥18 (n OR=3.64, 95% n CI: 2.79-5.32, n P=0.02) and SOFA score ≥8 (n OR=3.17, 95%n CI: 1.93-5.66, n P<0.01) were independent predictors of nosocomial infection.The scale was established based on the above risk factors, and the early prediction score of nosocomial infection ranged from 0 to 7, with the optimal cut-off value of 4.The early prediction score of urinary catheter-related urinary tract infection ranged from 0 to 7, and the optimal cut-off value was 4.The early prediction score of pneumonia ranged from 0 to 7, and the optimal cut-off value was 5.The early predictive scores for central venous catheter-related bloodstream infection ranged from 0 to 7, with the optimal cutoff value of 6.Data of nosocomial infection patients from January 2016 to December 2018 were used to verify the prediction model, which showed that the prediction effect of the scale was good.n Conclusions:Age ≥72, new stroke, APACHE Ⅱ score ≥18 and SOFA score ≥8 within 24 h in ICU could early predict ICU nosocomial infection and early detect high-risk groups.
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