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用于计算万古霉素曲线下面积的贝叶斯推导方程与一阶分析方程的比较。

Comparison of Bayesian-derived and first-order analytic equations for calculation of vancomycin area under the curve.

作者信息

Olney Katie B, Wallace Katie L, Mynatt Ryan P, Burgess David S, Grieves Kaitlyn, Willett Austin, Mani Johann, Flannery Alexander H

机构信息

Department of Pharmacy Services, University of Kentucky HealthCare, Lexington, Kentucky, USA.

Department of Pharmacy Practice and Science, University of Kentucky College of Pharmacy, Lexington, Kentucky, USA.

出版信息

Pharmacotherapy. 2022 Apr;42(4):284-291. doi: 10.1002/phar.2670. Epub 2022 Feb 17.

Abstract

INTRODUCTION

Consensus guidelines recommend targeting a vancomycin area under the curve to minimum inhibitory concentration (AUC :MIC) ratio of 400-600 to improve therapeutic success and reduce nephrotoxicity. Although guidelines specify either Bayesian software or first-order equations may be used to estimate AUC , there are currently no large studies directly comparing these methods.

OBJECTIVE

To compare calculated vancomycin AUC using first-order equations with two-drug concentrations at steady state to Bayesian two- and one-concentration estimations.

METHODS

This was a single-center, retrospective cohort study of 978 adult hospitalized patients receiving intravenous vancomycin between 2017 and 2019. Patients were included if they received at least 72 h of vancomycin and had two-serum drug concentrations obtained. AUC was calculated using first-order analytic (linear), Bayesian two-concentration, and Bayesian one-concentration methods for each patient. The InsightRx™ software platform was used to calculate Bayesian AUC . Pearson's correlation and clinical agreement (based on AUC  classified as subtherapeutic, therapeutic, or supratherapeutic) were used to assess agreement between methods. Bland-Altman plots were used to assess mean difference (MD) and 95% limits of agreement (LOA).

RESULTS

Excellent agreement was observed between linear and Bayesian two-concentration methods (r = 0.963, clinical agreement = 87.4%) and Bayesian two-concentration and one-concentration methods (r = 0.931, clinical agreement = 88.5%); however, a degree of variability was noted with 95% LOA -99 to 76 (MD = -11.5 mgh/L) and -92 to 113 (MD = -10.4 mgh/L), for the respective comparisons. The agreement between linear and Bayesian one-concentration approaches was less than prior comparisons (r = 0.823, clinical agreement = 76.8%) and demonstrated the greatest amount of variability with 95% LOA -197 to 153 (MD = -21.9 mg*h/L).

CONCLUSIONS

Linear and Bayesian two-concentration methods demonstrated high-level agreement with acceptable variability and may be considered comparable to estimate vancomycin AUC . As linear and Bayesian one-concentration methods demonstrated significant variability and suboptimal agreement, concerns exist surrounding the interchangeability of these methods in clinical practice, particularly at higher extremes of AUC .

摘要

引言

共识指南建议将万古霉素曲线下面积与最低抑菌浓度(AUC:MIC)之比的目标设定为400 - 600,以提高治疗成功率并降低肾毒性。尽管指南规定可使用贝叶斯软件或一阶方程来估算AUC,但目前尚无直接比较这些方法的大型研究。

目的

比较使用一阶方程根据稳态下两种药物浓度计算的万古霉素AUC与贝叶斯双浓度和单浓度估算值。

方法

这是一项单中心回顾性队列研究,研究对象为2017年至2019年间978例接受静脉注射万古霉素的成年住院患者。若患者接受万古霉素治疗至少72小时且获得了两次血清药物浓度,则纳入研究。使用一阶分析(线性)、贝叶斯双浓度和贝叶斯单浓度方法计算AUC。使用InsightRx™软件平台计算贝叶斯AUC。采用Pearson相关性和临床一致性(基于将AUC分类为治疗不足、治疗有效或治疗过度)来评估方法之间的一致性。使用Bland - Altman图评估平均差异(MD)和95%一致性界限(LOA)。

结果

线性方法与贝叶斯双浓度方法之间观察到高度一致性(r = 0.963,临床一致性 = 87.4%),贝叶斯双浓度方法与单浓度方法之间也观察到高度一致性(r = 0.931,临床一致性 = 88.5%);然而,在各自的比较中,95% LOA分别为 - 99至76(MD = - 11.5mgh/L)和 - 92至113(MD = - 10.4mgh/L),存在一定程度的变异性。线性方法与贝叶斯单浓度方法之间的一致性低于先前的比较(r = 0.823,临床一致性 = 76.8%),并且在95% LOA为 - 197至153(MD = - 21.9mg*h/L)时表现出最大程度的变异性。

结论

线性方法和贝叶斯双浓度方法显示出高度一致性且变异性可接受,在估算万古霉素AUC方面可认为具有可比性。由于线性方法和贝叶斯单浓度方法表现出显著的变异性和次优的一致性,因此在临床实践中对这些方法的互换性存在担忧,尤其是在AUC较高的极端情况下。

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