| Literature DB >> 29358290 |
Sheng-Hsuan Tseng1, Chuan Poh Lim2, Qi Chen3, Cheng Cai Tang4, Sing Teang Kong5, Paul Chi-Lui Ho6.
Abstract
Bacterial sepsis is a major cause of morbidity and mortality in neonates, especially those involving methicillin-resistant Staphylococcus aureus (MRSA). Guidelines by the Infectious Diseases Society of America recommend the vancomycin 24-h area under the concentration-time curve to MIC ratio (AUC24/MIC) of >400 as the best predictor of successful treatment against MRSA infections when the MIC is ≤1 mg/liter. The relationship between steady-state vancomycin trough concentrations and AUC24 values (mg·h/liter) has not been studied in an Asian neonatal population. We conducted a retrospective chart review in Singapore hospitals and collected patient characteristics and therapeutic drug monitoring data from neonates on vancomycin therapy over a 5-year period. A one-compartment population pharmacokinetic model was built from the collected data, internally validated, and then used to assess the relationship between steady-state trough concentrations and AUC24 A Monte Carlo simulation sensitivity analysis was also conducted. A total of 76 neonates with 429 vancomycin concentrations were included for analysis. Median (interquartile range) was 30 weeks (28 to 36 weeks) for postmenstrual age (PMA) and 1,043 g (811 to 1,919 g) for weight at the initiation of treatment. Vancomycin clearance was predicted by weight, PMA, and serum creatinine. For MRSA isolates with a vancomycin MIC of ≤1, our major finding was that the minimum steady-state trough concentration range predictive of achieving an AUC24/MIC of >400 was 8 to 8.9 mg/liter. Steady-state troughs within 15 to 20 mg/liter are unlikely to be necessary to achieve an AUC24/MIC of >400, whereas troughs within 10 to 14.9 mg/liter may be more appropriate.Entities:
Keywords: AUC; MRSA; Monte Carlo simulation; neonatal intensive care unit; neonatal sepsis; neonates; pharmacokinetics; population pharmacokinetic model; target trough; vancomycin
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Year: 2018 PMID: 29358290 PMCID: PMC5914004 DOI: 10.1128/AAC.01647-17
Source DB: PubMed Journal: Antimicrob Agents Chemother ISSN: 0066-4804 Impact factor: 5.191