Literature DB >> 28097633

Meropenem Dosing Based on a Population Pharmacokinetic-Pharmacodynamic Model in Elderly Patients with Infection of the Lower Respiratory Tract.

Qing-Tao Zhou1, Bei He2, Ning Shen1, Ying Liang1, Li-Na Sun1.   

Abstract

BACKGROUND: Meropenem is used for the treatment of severe lower respiratory tract infections (LRTIs) caused by multidrug-resistant Gram-negative bacilli.
OBJECTIVE: We evaluated the clinical benefits of a strategy of meropenem dosing based on a population pharmacokinetics/pharmacodynamics (PK/PD) model in elderly patients with an LRTI.
METHODS: In this prospective single-center open-label randomized controlled trial, 79 elderly patients with an LRTI caused by Gram-negative bacilli were randomized to a study group (SG) or a control group (CG). The latter received meropenem according to a regimen decided by the attending physician. The SG received individualized meropenem therapy with a dosing strategy based on software developed from a meropenem population PK/PD model. The primary endpoint was clinical response to meropenem therapy. Secondary endpoints were the amount of antibiotics used and bacteriologic response.
RESULTS: Klebsiella pneumoniae was the most common pathogen (32.9%), followed by Pseudomonas aeruginosa (30.4%) and Escherichia coli (17.7%). A total of 63 (79.7%) patients achieved clinical success. Prevalence of clinical success was significantly higher in the SG than in the CG (89.7 vs. 70.0%; p = 0.029). The daily dose of meropenem was significantly lower in the SG than in the CG (1.5 vs. 2.0 g; p = 0.017). A total of 52 (65.8%) patients experienced bacteriologic success, the median duration of meropenem therapy was 9 days, and the median total dose of meropenem was 18.0 g. There were no significant differences between the groups in these parameters.
CONCLUSIONS: A strategy for meropenem dosing based on a population PK/PD model can improve clinical response and avoid overtreatment in elderly patients with an LRTI. ClinicalTrials.gov registration number NCT01944319.

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Year:  2017        PMID: 28097633     DOI: 10.1007/s40266-016-0431-9

Source DB:  PubMed          Journal:  Drugs Aging        ISSN: 1170-229X            Impact factor:   3.923


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