METHODS: Published population pharmacokinetic models and the Australasian Neonatal Medicines Formulary were used to simulate antimicrobial concentration-time profiles in a virtual neonate population. Laboratory quality assurance data were used to quantify analytical variation in antimicrobial measurement methods used in clinical practice. Guideline-informed dosing recommendations based on drug concentrations were applied to compare the impact of analytical variation and nonanalytical factors on antimicrobial dosing.
RESULTS: Analytical variation caused differences in subsequent guideline-informed dosing recommendations in 9.3-12.1% (amikacin), 16.2-19.0% (tobramycin), 12.2-45.8% (gentamicin), and 9.6-19.5% (vancomycin) of neonates. For vancomycin, inaccuracies in drug administration time (45.6%), use of non-trough concentrations (44.7%), within-subject biological variation (38.2%), and dosing errors (27.5%) were predicted to result in more dosing discrepancies than analytical variation (12.5%). Using current analytical performance specifications, tolerated dosing discrepancies would be up to 14.8% (aminoglycosides) and 23.7% (vancomycin).
CONCLUSIONS: Although analytical variation can influence neonatal antimicrobial dosing recommendations, nonanalytical factors are more influential. These result in substantial variation in subsequent dosing of antimicrobials, risking inadvertent under- or overexposure. Harmonization of measurement methods and improved patient management systems may reduce the impact of analytical and nonanalytical factors on neonatal antimicrobial dosing.
Case presentation: A 29-year-old man presented with pneumonia and melioidosis septicaemia. His condition was complicated with infective endocarditis and septic emboli to the brain. Despite difficulties in reaching a diagnosis, the patient was successfully treated using intravenous gentamicin and ceftazidime and was discharged well.
Discussion: The role of gentamicin in the treatment of the gentamicin-susceptible strain of B. pseudomallei remains unclear.
Materials and methods: Seventy-five enterococci isolates recovered from different clinical sources were re-identified by subculturing on selective medium, Gram staining, biochemical profiling (API 20 Strep), and 16s rRNA sequencing. Antimicrobial susceptibility testing (AST) was performed using Kirby-Bauer disc diffusion, E-test, and broth microdilution methods. PCR amplification was used to detect the presence of aminoglycoside modifying enzyme (AME) genes [aac(6')-Ie-aph(2")-Ia, aph(2")-Ib, aph(2")-Ic, aph(2")-Id, aph(3')-IIIa]. Descriptive data analysis was used to analyze the antibiotic susceptibility profiles and the distribution of HLAR genes.
Results: The majority of the isolates recovered from the clinical samples are E. faecalis (66.7%), with the highest recovery from the pus. The prevalence of HLGR (51%) is higher when compared to HLSR (45-49%). Analysis of the resistance genes showed that bifunctional genes aac(6')-Ie-aph(2")-Ia and aph(3')-IIIa contributed to the HLAR E. faecalis and E. faecium. The other AME genes [aph(2")-Ib, aph(2")-Ic, aph(2")-Id] were not detected in this study.
Conclusion: This study provides the first prevalence data on HLAR and the distribution of the AME genes among E. faecalis and E. faecium isolates from Malaysia. These highlight the need for continued antibiotic surveillance to minimize its emergence and further dissemination.