骨科老年住院患者医院感染危险因素分析及预测模型构建

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Abstract Objective To analyze the risk factors of nosocomial infection in orthopedic hospitalized patients and to construct a predictive model. Methods A total of 2114 patients who were admitted to the Department of Orthopedics of Shanghai Sixth People′s Hospital from January 2015 to December 2018 were selected. The patients were divided into the modeling group and the validation group according to the random number table method, with 1057 patients in each group. Chi-square test and unconditional logistic regression were used to analyze the risk factors affecting nosocomial infection, and the predictive model of nosocomial infection in elderly orthopedic patients was established based on the results. Results Among the 1057 patients in the modeling group, 53 cases had nosocomial infection. Logistic regression analysis showed age, hospital stay, operative time, surgical incision type, catheterization, and osteoporosis were risk factors for nosocomial infection in hospitalized orthopedic patients (P < 0.05). The area under the ROC curve of probability value fitting joint prediction in the constructed prediction model was 0.808, and the sensitivity and specificity were 73.3% and 81.2%, respectively. Based on this, a predictive scoring model was established. The area under the ROC curve of the modeling group and the verification group were 0.801 (95%CI: 0.725-0.852) and 0.721 (95%CI: 0.630-0.812), respectively. Conclusion Age, hospital stay, operative time, surgical incision type, catheterization and osteoporosis of orthopedic patients are risk factors for nosocomial infection. The predictive model constructed by this method has good discriminat validity in both the modeling group and the validation group.

Key words： Orthopedics Nosocomial infection Risk factor Logistic regression Predictive model

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ZUO Lili XUE Yiwei. Risk factors analysis and prediction model construction of nosocomial infection in elderly hospitalized orthopedic patients[J]. 中国医药导报, 2020, 17(3): 86-89,97.

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http://www.yiyaodaobao.com.cn/EN/ OR http://www.yiyaodaobao.com.cn/EN/Y2020/V17/I3/86

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