Comparative assessment of trough and peak levels and AUC24 for amikacin in nontuberculous mycobacterial infection

IF 3.2 3区 医学 Q2 MEDICAL LABORATORY TECHNOLOGY
Jiyeon Kim , John Hoon Rim , Jaehyeok Jang, Hanmil Jang, Jong-Baeck Lim
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引用次数: 0

Abstract

Background

Amikacin, an aminoglycoside antibiotic, is widely used for the treatment of nontuberculous mycobacterial (NTM) infections. To date, therapeutic drug monitoring (TDM) of amikacin has primarily relied on the measurement of peak and trough levels as indicators rather than the 24-hr area under the concentration–time curve (AUC24).

Methods

NTM patients referred for amikacin TDM from March 2021 to May 2023 were assessed for the AUC24 values based on administered dose. We investigated re-admission rates, all-cause mortality and AFB smear results to evaluate clinical outcome based on the actual AUC24 values. Ototoxicity and nephrotoxicity were also investigated as adverse effects in correlation with TDM parameters.

Results

Among 65 patients, the mean and median values of AUC24 were 234 and 249 mg·hr/L, respectively. In a group of patients with AUC24 values less than 250 mg·hr/L, 42.4 % of patients were re-admitted for pulmonary symptoms. On the contrary, another group with AUC24 values equal to or more than 250 mg·hr/L, had lower re-admission rates (25.0 %). They also showed lower all-cause mortality rates and more improvement on acid-fast bacilli smear results. Moderate to poor correlation between AUC24 values and peak/trough levels were observed. Ototoxicity and nephrotoxicity were revealed to be associated with drug exposure duration rather than AUC24 values.

Conclusion

In this study, we performed comparative assessment of trough/peak level, traditional clinical marker for amikacin TDM, and AUC24 value. Although AUC24 values showed poor to moderate correlation to trough/peak levels, higher AUC24 correlated with favorable clinical outcomes without additional risk of toxicity.

非结核分枝杆菌感染中阿米卡星的谷值和峰值水平以及 AUC24 的比较评估
背景阿米卡星是一种氨基糖苷类抗生素,被广泛用于治疗非结核分枝杆菌(NTM)感染。迄今为止,阿米卡星的治疗药物监测(TDM)主要依靠测量峰值和谷值水平作为指标,而不是 24 小时浓度-时间曲线下面积(AUC24)。方法对 2021 年 3 月至 2023 年 5 月期间转诊进行阿米卡星治疗药物监测(TDM)的非结核分枝杆菌(NTM)患者根据给药剂量评估 AUC24 值。我们根据实际 AUC24 值调查了再入院率、全因死亡率和 AFB 涂片结果,以评估临床结果。我们还调查了耳毒性和肾毒性作为不良反应与 TDM 参数的相关性。结果在 65 例患者中,AUC24 的平均值和中位值分别为 234 mg-hr/L 和 249 mg-hr/L。在 AUC24 值低于 250 mg-hr/L 的一组患者中,42.4% 的患者因肺部症状再次入院。相反,另一组 AUC24 值等于或高于 250 毫克-小时/升的患者再次入院的比例较低(25.0%)。他们的全因死亡率也较低,酸-ast 杆菌涂片结果也有所改善。据观察,AUC24 值与峰值/槽值之间的相关性为中度到低度。结论在这项研究中,我们对阿米卡星 TDM 的传统临床指标谷/峰水平和 AUC24 值进行了比较评估。虽然 AUC24 值与谷值/峰值的相关性较差到中等,但较高的 AUC24 值与良好的临床结果相关,且无额外的毒性风险。
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来源期刊
Clinica Chimica Acta
Clinica Chimica Acta 医学-医学实验技术
CiteScore
10.10
自引率
2.00%
发文量
1268
审稿时长
23 days
期刊介绍: The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells. The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.
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