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中国临床药理学与治疗学 ›› 2017, Vol. 22 ›› Issue (4): 439-442.

• 定量药理学 • 上一篇    下一篇

克林霉素耐药金黄色葡萄球菌检出率与抗菌药物使用的相关性分析

蒋 程1,吕健刚2,李芳琼1,叶佐武1,鲁春芳1,李功华1   

  1. 1 浙江省立同德医院,杭州 310012,浙江;2 浙江科澜信息技术有限公司,杭州 310022,浙江
  • 收稿日期:2016-05-30 修回日期:2016-07-19 出版日期:2017-04-26 发布日期:2017-04-26
  • 通讯作者: 李功华,男,本科,副主任药师,研究方向:医院药学。 Tel:0571-89972239 E-mail:ligonghua88@163.com
  • 作者简介:蒋程,女,博士,主管药师,研究方向:临床药学。 Tel:0571-89972240 E-mail:jiangcheng0818@126.com
  • 基金资助:

    浙江省公益技术应用研究计划项目(2016C33127);浙江省中医药科技计划项目(2015ZQ007);浙江省药学会医院药学专项科研资助项目(2014ZYY10)

Correlation between detection rate of clindamycin-resistant Staphylococcus aureus and utilization of antibacterial drugs

JIANG Cheng 1, LV Jiangang 2, LI Fangqiong 1, YE Zuowu 1, LU Chunfang 1, LI Gonghua 1   

  1. 1 Tongde Hospital of Zhejiang Province, Hangzhou 310012, Zhejiang, China; 2 Zhejiang Keland Information & Technology Co., Ltd., Hangzhou 310022, Zhejiang, China
  • Received:2016-05-30 Revised:2016-07-19 Online:2017-04-26 Published:2017-04-26

摘要:

目的: 建立基于偏最小二乘(PLS)回归算法的克林霉素耐药金黄色葡萄球菌(CRSA)检出率与抗菌药物使用相关性模型,为指导抗菌药物临床的合理使用提供依据。方法: 以不同季度抗菌药物的用药频度(DDDs)为自变量,以同期和非同期CRSA的检出率为因变量,分别建立PLS回归模型,分析CRSA检出率比抗菌药物使用的滞后性。根据各变量的VIP值,筛选对CRSA检出率影响较显著的品种。结果: CRSA的检出率滞后于抗菌药物的使用2个季度,与头孢哌酮/舒巴坦、阿奇霉素、头孢呋辛的DDDs呈显著正相关。结论: PLS回归算法能同时分析CRSA检出率与多种抗菌药物使用的相关性,可为CRSA研究提供新的方法。

关键词: 偏最小二乘回归, 抗菌药物, 用药频度, 克林霉素耐药金黄色葡萄球菌

Abstract:

AIM: To provide information for reasonable clinical application of antibacterial drugs, the partial least squares (PLS) regression models were established for analyzing the correlation between detection rate of clindamycin-resistant Staphylococcus aureus (CRSA) and utilization of antibacterial drugs.  METHODS: The PLS regression models were established with the defined daily doses (DDDs) of antibacterial drugs as independent variables and the detection rates of CRSA with same and different periods as dependent variables. The lag between detection rates of CRSA and utilization of antibacterial drugs were investigated. The antibacterial drugs, which were highly correlated with the detection rate of CRSA, were screened according to the variable importance (VIP) values. RESULTS: The detection rate of CRSA lagged about two quarters behind the utilization of antibacterial drugs, and was significantly positively correlated with the DDDs of cefoperazone/sulbactam, azithromycin and cefuroxime. CONCLUSION: It was effective to employ PLS regression algorithm to simultaneously analyze the correlation between detection rate of CRSA and utilization of multiple antibacterial drugs. This research provided a new scientific tool for the investigation of CRSA.

Key words: partial least squares regression, antibacterial drugs, defined daily doses, clindamycin-resistant Staphylococcus aureus

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