首页> 外文期刊>Clinical Medicine Insights: Therapeutics >Concordance Among Methods for Empiric Renal Drug Dosing: Meropenem as a Role Model for Clinical Superiority of Cockroft–Gault or Modification of Diet in Renal Disease:
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Concordance Among Methods for Empiric Renal Drug Dosing: Meropenem as a Role Model for Clinical Superiority of Cockroft–Gault or Modification of Diet in Renal Disease:

机译:经验性肾脏药物给药方法之间的一致性:美罗培南作为改善鸡冠心病或改变肾脏疾病饮食的临床优势的榜样:

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Objective:The objectives of this study are, first, to measure concordance between 5 different renal function estimates (methods) in terms of recommended drug doses, and, subsequently, to establish the potential for significant clinical differences between Cockroft–Gault (CG) and Modification of Diet in Renal Disease (MDRD) equations in dosing a specific medication, namely, meropenem.Design and setting:This study used a Monte Carlo simulation, and this is a computer–based study with no actual patient data.Patients:A total of 1200 and 8701 simulated cases to study the concordance for the 5 methods and the potential clinical significance of discordance between CG and MDRD, respectively, were chosen for the study.Methods:Simulated factors were age, sex, height, weight, serum creatinine, ethnicity, and albumin. We estimated the renal function using 5 formulas (ie, 10 combinations) including CG, MDRD, and Chronic Kidney Disease Epidemiology Collaboration (CKD–EPI). Next, the team evaluated concordance for each combination in dosing 22 drugs. Finally, our researchers reviewed and simulated data from the literature to show how CG versus MDRD use can result in clinically significant differences for meropenem.Results:Pairwise combinations yielded statistically significant differences (P ?
机译:目的:本研究的目的是,首先,根据推荐的药物剂量来测量5种不同的肾功能评估(方法)之间的一致性,然后,确定考克罗夫特-高特(CG)和在服用特定药物美罗培南的过程中对肾脏疾病饮食(MDRD)方程的修改。设计与设置:本研究使用了Monte Carlo模拟,这是基于计算机的研究,没有实际的患者数据。选择1200例和8701例模拟病例,研究5种方法的一致性以及CG和MDRD之间不一致的潜在临床意义。方法:模拟因素为年龄,性别,身高,体重,血清肌酐,种族和白蛋白。我们使用CG,MDRD和慢性肾脏病流行病学协作(CKD-EPI)等5种公式(即10种组合)估算了肾功能。接下来,研究小组评估了在服用22种药物时每种组合的一致性。最后,我们的研究人员对文献中的数据进行了回顾和模拟,以显示CG与MDRD的使用如何导致美罗培南的临床显着差异。结果:除CG和MDRD以外,成对组合产生了统计学上的显着差异( P 。0001)。 MDRD(P <<。0.5147)。此外,MDRD和CKD-EPI的一致性最高。平均差异在25%到30%的范围内,最低者在CG和基于白蛋白的估计之间。 CG和MDRD在很大程度上不一致,使用美罗培南等药物可能高达40%,并且可能与重大不良后果相关。结论:我们的模拟中CG和MDRD在统计学上具有可比性。尽管如此,在临床上,它们在推荐的药物剂量方面明显不一致。我们鼓励根据在不同人群中使用的方程式,对根据经验在肾病患者中按剂量给药的单个或一组药物(例如美洛培南和抗生素)的结果进行实用比较。

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