文章摘要
丁兰萍,刘涛,李一辰,袁红宇,王嵘.支架辅助栓塞术后氯吡格雷治疗时血小板高反应性的 风险因素分析[J].药学与临床研究,2022,30(1):71~75
支架辅助栓塞术后氯吡格雷治疗时血小板高反应性的 风险因素分析
Risk Factors of High On-treatment Platelet Reaction after Stent-assisted Coiling Treated with Clopidogrel
投稿时间：2021-07-20  修订日期：2022-02-13
DOI：
中文关键词: 血小板高反应  风险因素  Logistic回归模型
英文关键词: High on-treatment platelet reaction  Risk factors  Logistic regression model
基金项目:江苏省药学会-天晴医院药学基金科研项目（Q202007）； 南京大学医院管理研究所项目课题（NDYG2020032）；江苏省药学会-天晴医院药学基金科研项目（Q202005）
作者单位邮编
丁兰萍 南京医科大学第一附属医院/江苏省人民医院 2100029
刘涛 南京鼓楼医院 
李一辰 南京鼓楼医院 
袁红宇 南京医科大学第一附属医院/江苏省人民医院 
王嵘 南京鼓楼医院 210000
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中文摘要:
      目的：探讨颅内动脉瘤（IAs）患者支架辅助栓塞术（SAC）术后氯吡格雷治疗时血小板高反应性（HTPR）的风险因素，并构建Logistic回归模型，分析该模型对IAs患者SAC术后氯吡格雷治疗时HTPR风险的预测。方法：入组160例SAC术后患者，给予阿司匹林和氯吡格雷抗血小板治疗，连续服用5 d，晨起抽取静脉血，检测血栓弹力图（TEG）。利用单因素和多因素Logistic回归分析HTPR的影响因素，构建预测IAs患者SAC术后氯吡格雷治疗时发生HTPR风险的Logistic回归模型，并绘制ROC曲线，评价其预测效能。结果：160例SAC术后患者氯吡格雷治疗时HTPR发生率为28.75%。多因素Logistic分析结果显示，HTPR的独立风险因素为：糖尿病（OR=6.805，95%CI=2.599~11.630），CYP2C19*2携带（OR=4.567，95%CI=1.795~11.618），血小板计数（OR=3.334，95%CI=1.076~10.330），得到回归方程Logit（P）=-4.283+1.918糖尿病+1.519 CYP2C19*2携带+1.204血小板计数。ROC曲线下面积为0.805（95%CI：0.728~0.882），敏感性为67.40%，特异性为78.90%，阳性预测值为56.36%，阴性预测值为85.71%。结论：糖尿病、CYP2C19*2携带、血小板计数为IAs患者SAC术后氯吡格雷治疗时发生HTPR的独立风险因素，构建的Logistic回归模型对HTPR有较好的预测能力。
英文摘要:
      Objective: To explore the risk factors of high on-treatment platelet reaction (HTPR) after stent-assisted coiling (SAC) for intracranial aneurysms (IAs) patients treated with clopidogrel create a predictive Logistic regression model. Methods: The platelet reactivity was detected by using thrombelastogram (TEG) in 160 patients taking aspirin and clopidogrel for 5 days. The impact factors were assessed by the Logistic regression. Prediction efficiency of the Logistic regression model for HTPR was analyzed by the ROC curve. Results: The incidence of HTPR was 28.75% in this study. Multiple Logistic regression results showed that diabetes (OR=6.805, 95%CI=2.599-11.630), CYP2C19*2 (OR=4.567, 95%CI=1.795-11.618) and platelet count (OR=3.334, 95%CI=1.076-10.330) were independent risk factors. A Logistic regression equation was obtained as Log(P)=-4.283+1.918 diabetes+1.519 CYP2C19*2+1.204 platelet count. The AUC under ROC curve was 0.805 (95%CI: 0.728-0.882, P=0.000); the sensitivity was 67.40%; the specificity was 78.90%; the positive predictive value was 56.36%, and the negative predictive value was 85.71%. Conclusions: Diabetes, CYP2C19*2 and platelet count were independent risk factors of HTPR after SAC for IAs patients treated with clopidogrel. The Logistic regression model showed a good predictive value for HTPR.
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