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《广州医药》编辑部
目的 探讨自回归求和时间序列模型(ARIMA)在耐碳青霉烯类肺炎克雷伯菌(CRKP)医院感染预测中的应用,为CRKP感染的科学防控提供策略。方法 选取贾汪区人民医院住院患者2018年1月—2024年12月共7年每月CRKP医院感染率,应用SPSS 19.0建立ARIMA模型,利用该模型对2024年1—12月每月CRKP医院感染数据进行验证,以评价模型的预测性能。结果 用2018—2024年住院患者每月CRKP医院感染率建模、拟合,建立最优模型ARIMA(1,1,1),模型拟合值与实际值较吻合,模型对CRKP医院感染率实际值与预测值吻合度较高,平均相对误差为5.40%。结论 用ARIMA模型可有效拟合、预测CRKP医院感染情况,为CRKP防控提供科学指导。
Objective To explore the value of auto regressive integrated moving average(ARIMA)model in predicting theinfection rate of carbapenem-resistant Klebsiella pneumoniae(CRKP).Methods The monthly incidence of nosocomial infection of CRKP in Jiawang District People’s Hospital from 2018 to 2024 was selected,and the ARIMA model was established by19.0 SPSS to analyze the fitting and prediction value of the model.Results The ARIMA was established based on the monthly CRKP infection rate from January 2018 to December 2024.The fitted value of the ARIMA(1,1,1)model was in good agreement with the actual value.The incidence of CRKP infection were in good agreement with the predicted value.The average relative errors were 5.40%.Conclusions The ARIMA model can effectively fit and predict the CRKP infection rate,providing scientific guidance for the prevention and control of CRKP infection.