| 时间序列模型对细菌耐药率变化趋势预测价值 |
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| 引用本文： | 钱鑫,熊世娟,杨廷秀,胡方芳,谢娟. 时间序列模型对细菌耐药率变化趋势预测价值[J]. 药品评价, 2021, 0(5): 260-264 |
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| 作者姓名： | 钱鑫 熊世娟 杨廷秀 胡方芳 谢娟 |
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| 作者单位： | 贵州省人民医院 |
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| 摘 要： | 目的:探讨时间序列模型对细菌耐药率变化趋势的预测价值.方法:回顾性分析贵州省人民医院2013年1月至2018年12月肺炎克雷伯菌对美罗培南的耐药率,采用自回归移动平均模型(ARMA)对收集的数据进行分析和预测,通过对建立的模型进行拟合优度检验,最终确定最优模型进行耐药趋势的预测.结果:对收集的原始数据进行平稳化检验、差...
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| 关 键 词： | 肺炎克雷伯菌 细菌耐药性 时间序列 |
The Prediction Value of Trends of Antibiotic Resistance by Time Series Model |
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| QIAN Xin,XIONG Shijuan,YANG Tingxiu,HU Fangfang,XIE Juan. The Prediction Value of Trends of Antibiotic Resistance by Time Series Model[J]. Drug Evaluation, 2021, 0(5): 260-264 |
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| Authors: | QIAN Xin XIONG Shijuan YANG Tingxiu HU Fangfang XIE Juan |
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| Affiliation: | (Guizhou Provincial People's Hospital,Guiyang Guizhou 550002,China.) |
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| Abstract: | Objective:To explore the prediction value of trends of antibiotic resistance by time series model.Methods:The resistance rate of klebsiella pneumoniae to meropenem in Guizhou Provincial People's Hospital from January 2013 to December 2018 was retrospectively analyzed.ARMA model was used to analyze the collected data and predict the trend of antibiotic resistance.After fitting data with one or more models,we evaluated the goodness of fit of different models,then the optimal model was finally determined to predict the trend of antibiotic resistance.Results:The collected data was given stationary test,differential,model identification,and IMA(1,1)was the most suitable model,the goodness-of-fit test showed that the predicted values were highly consistent with the actual values,the fitting effect of the model was good.Conclusion:ARMA model can preferably analyze and predict the trend of antibiotic resistance. |
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| Keywords: | Klebsiella pneumoniae Bacterialresistance Time series |
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