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引用本文:承华薇,曾蓉,孙言才.基于基因多态性的术后舒芬太尼个体化镇痛给药剂量预测方程的构建[J].中国现代应用药学,2021,38(14):1745-1749.
CHENG Huawei,ZENG Rong,SUN Yancaia.Establishment of Dose Prediction Equation of Postoperative Sufentanil Analgesia Administration Based on Gene Polymorphism[J].Chin J Mod Appl Pharm(中国现代应用药学),2021,38(14):1745-1749.
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基于基因多态性的术后舒芬太尼个体化镇痛给药剂量预测方程的构建
承华薇1, 曾蓉2, 孙言才1
1.中国科学技术大学附属第一医院, 安徽省肿瘤医院药剂科, 合肥 230031;2.中国科学技术大学附属第一医院, 安徽省肿瘤医院麻醉科, 合肥 230031
摘要:
目的 构建患者术后舒芬太尼镇痛个体化给药剂量的预测方程。方法 对胃癌手术患者细胞色素P4503A4酶(cytochrome P450 enzyme,CYP450)*1G、儿茶酚胺氧位甲基转移酶(catechol-O-methyltransferase,COMT) Val158Met、阿片受体编码基因1(opioid receptor mu-1,OPRM1) A118G和多药耐药性蛋白(ATP-binding cassette sub-family B member-1,ABCB1) C3435T进行基因测序,并结合患者临床基本信息,建立胃癌患者术后舒芬太尼镇痛个体化给药预测方程,并代入肺癌手术患者信息进行验证。结果 胃癌患者术后舒芬太尼镇痛给药剂量y=4.104-0.222×[性别]+0.021×[OPRM1 A118G]+0.249×[ABCB1 C3435T],将肺癌手术患者信息代入得出的预测方程,两者结果差异无统计学意义。结论 构建的患者术后舒芬太尼镇痛个体化给药预测方程有效,可供临床借鉴。
关键词:  舒芬太尼  基因多态性  多元线性回归方程
DOI:10.13748/j.cnki.issn1007-7693.2021.14.015
分类号:R969.4
基金项目:中央高校基本科研业务费专项资金资助项目(WK9110000015)
Establishment of Dose Prediction Equation of Postoperative Sufentanil Analgesia Administration Based on Gene Polymorphism
CHENG Huawei1, ZENG Rong2, SUN Yancaia1
1.The First Affiliated Hospital of University of Science and Technology of China, Anhui Provincial Cancer Hospital, Department of Pharmacy, Hefei 230031, China;2.The First Affiliated Hospital of University of Science and Technology of China, Anhui Provincial Cancer Hospital, Department of Anesthesiology, Hefei 230031, China
Abstract:
OBJECTIVE To establish a predictive equation for the individual administration of sufentanil for postoperative analgesia. METHODS Performed gene sequencing of the CYP4503A4*1G enzymes, COMT Val158Met, OPRM1 A118G, ABCB1 C3435T and combined with patient basic clinical information, established individualized dosage sufentanil analgesia postoperatively in patients with gastric cancer prediction equation, and taken the information of patients with lung cancer surgery for validation. RESULTS The predictive equation of postoperative sufentanil dosage in patients with gastric cancer was y=4.104-0.222×[gender]+0.021×[OPRM1 A118G]+0.249×[ABCB1 C3435T]. The information of patients with lung cancer surgery was substituted into the obtained predictive equation, and the results showed no significant difference with the actual dosage of sufentanil. CONCLUSION The prediction equation of postoperative sufentanil is effective and can be used for clinical reference.
Key words:  sufentanil  gene polymorphism  multiple linear regression equation
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