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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,DMod X)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DMod X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。
Objective To establish an antimicrobial drug monitoring model based on multivariate data analysis (MVA) to provide evidence for the rational use of clinical antimicrobial agents. Methods Data of 81 defined daily doses (DDDs) of 81 antibacterials in inpatients of Tong De Hospital in Zhejiang Province during 2011-2013 were extracted to establish a principal component analysis (PCA) model. Antimicrobials in different quarters were monitored by building a score map and DMod X control chart with variable contribution map to evaluate the quarterly consistency and analyze the causes of the abnormality. Results The consistency of antimicrobial DDDs in the fourth quarter of 2011 and the fourth quarter of 2013 was good. DMod X statistics for the first three quarters of 2011 outweighed the control limits in 2011 primarily due to three special-use antimicrobials (ceftibride, fusidic acid, norvancomycin), eight use-level antibacterials Drugs (cefminin, piperacillin / sulbactam, amoxicillin / sulbactam, furibacil, cefprozil, ceftizoxime, ispamidron, ornidazole) and 4 non-use-limiting antibacterial Drugs (cloxacillin, cephalexin, cefadroxil, cefotaxime) DDDs high. Conclusion This study demonstrates the effectiveness of MVA in the monitoring of antimicrobial agents and provides a new method for the monitoring of clinical antimicrobial agents.