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目的:探索新的药品不良反应信号的提取、验证方法。方法:对收集到的头孢呋辛不良反应数据,使用Excel数据透视表,按时间统计出不同时间段发生的不良反应例次。通过主成分分析对数据进行降维,根据头孢呋辛各不良反应降维后的主成分得分,在第一、二主成分坐标平面上绘制头孢呋辛不良反应分布图,通过此分布图观察药品不良反应发生与药品使用的相关性,发现新的药品不良反应,并以传统药品不良反应监测方法优势比计算进行验证。结果:头孢呋辛的不良反应分布图中,距离“总计”点较近的分别为“皮疹”、“瘙痒”、“恶心”、“心悸”等,提示头孢呋辛的使用与这些不良反应的出现高度相关。其中,“心悸”未在说明书上载明,是头孢呋辛新的不良反应。头孢呋辛发生“心悸”风险相对其他药品优势比为2.005。结论:主成分分析能够直观鉴别出药品不良反应风险信号。
Objective: To explore a new drug adverse reaction signal extraction and verification methods. Methods: The collected adverse reactions of cefuroxime data, the use of Excel PivotTable, according to the time statistics of different time periods of adverse reaction cases. The principal component analysis was used to reduce the dimensionality of the data. According to the principal component scores after the dimensionless reduction of the adverse reactions of cefuroxime, the adverse reaction profile of cefuroxime was drawn on the first and second principal component coordinate planes. Adverse reactions occurred with the use of drugs, and found that new adverse drug reactions, and traditional drugs adverse reaction monitoring method to determine the ratio of advantages. Results: In the adverse reaction profile of cefuroxime, the points closer to “total ” were “rash”, “pruritus”, “nausea”, “palpitations” The use of cefuroxime is highly correlated with the emergence of these adverse reactions. Among them, “heart palpitations ” not stated in the manual, is a new side effect of cefuroxime. Cefuroxime “heart palpitations” risk relative to other drugs advantage ratio of 2.005. Conclusion: Principal component analysis can intuitively identify the adverse drug reaction risk signal.