| 引用本文: | 蒋程,吕健刚,韩冰,郑造乾,张美玲.抗菌药物使用的多变量监控[J].中国现代应用药学,2015,32(3):370-375. |
| JIANG Cheng,LYU Jiangang,HAN Bing,ZHENG Zaoqian,ZHANG Meiling.Monitoring of Use of Antibiotics Based on Multivariate Data Analysis[J].Chin J Mod Appl Pharm(中国现代应用药学),2015,32(3):370-375. |
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| 摘要: |
| 目的 建立基于多变量数据分析(multivariate data analysis，MVA)的抗菌药物监控模型，为规范临床抗菌药物的合理使用提供依据。方法 提取浙江省立同德医院住院患者2011—2013年共12个季度81种抗菌药物的用药频度(defined daily doses，DDDs)数据，建立主成分分析(principal component analysis，PCA)模型。通过构建得分图和X区块模型距离(distance to model X block，DModX)控制图，结合变量贡献图，对不同季度的抗菌药物进行监控，评价季度一致性，分析导致异常的原因。结果 2011年第4季度和2012年、2013年4个季度抗菌药物DDDs的一致性较好。2011年第1~3季度的DModX统计值超出了控制限，主要原因为3种特殊使用级抗菌药物(头孢噻利、夫西地酸、去甲万古霉素)、8种限制使用级抗菌药物(头孢米诺、哌拉西林/舒巴坦、阿莫西林/舒巴坦、呋苄西林、头孢丙烯、头孢唑肟、异帕米星、奥硝唑)和4种非限制使用级抗菌药物(氯唑西林、头孢氨苄、头孢羟氨苄、头孢噻肟)的DDDs偏高。结论 本研究证明了MVA在抗菌药物监控中的有效性，为临床抗菌药物监控提供新的方法。 |
| 关键词: 多变量数据分析 抗菌药物 用药频度 控制图 |
| DOI： |
| 分类号:R9 |
| 基金项目:浙江省药学会医院药学专项科研资助项目(2014ZYY10) |
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| Monitoring of Use of Antibiotics Based on Multivariate Data Analysis |
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JIANG Cheng1, LYU Jiangang2, HAN Bing1, ZHENG Zaoqian1, ZHANG Meiling1
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1.Department of Pharmacy, Tongde Hospital of Zhejiang Province, Hangzhou 310012, China;2.Kelan Information & Technology Co., Ltd., Hangzhou 310022, China
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| Abstract: |
| OBJECTIVE To provide information for the reasonable clinical application of antibiotics, a monitoring method based on multivariate data analysis (MVA) was developed. METHODS The original defined daily doses (DDDs) of 81 antibiotics in 12 quarters from 2011 to 2013 were used to establish a principal component analysis (PCA) model. The score plot and distance to model X block (DModX) control plot combination with contribution plots were applied to monitor the application of antibiotics in different quarters. The quarter-to-quarter consistency was evaluated and the causes of abnormalities were further diagnosed. RESULTS There was good quarter consistency between the 4th quarter of 2011, 1st-4th quarters of 2012 and 2013. The 1st-3rd quarters of 2011 deviated from the control limit in the DModX control plot, which were caused by the higher DDDs of 3 antibiotics (cefoselis, fusidic acid and norvancomycin), which had special requests in use, 8 antibiotics (cefminox, piperacillin/sulbactam, amoxicillin/sulbactam, furbenicillin, cefprozil, ceftizoxime, isepamicin and ornidazole), which had restrictions in use, and 4 antibiotics (cloxacillin, cefalexin, cefadroxil and cefotaxime), which had no restriction in use. CONCLUSION This study demonstrates that it is effective to employ MVA to monitor the clinical application of antibiotics. This research provides a new scientific tool for the monitoring of antibiotics. |
| Key words: multivariate data analysis antibiotics defined daily doses control plot |
