Evaluation of renal function equations to predict amikacin clearance.

Area of Science:

• Pharmacokinetics
• Nephrology
• Clinical Pharmacy

Background:

• Amikacin dosing requires accurate assessment of renal function for optimal therapeutic outcomes and minimizing toxicity.
• Various equations exist to estimate renal function, but their comparative performance in predicting amikacin elimination is not well-established across diverse patient populations.

Purpose of the Study:

• To evaluate and compare the predictive performance of eight different renal function equations in describing amikacin elimination.
• To identify the most accurate equation for amikacin dose adjustment in hospitalized adult patients.

Main Methods:

• Retrospective analysis of 198 hospitalized adult patients treated with amikacin.
• Calculation of renal function using Cockcroft-Gault (total, adjusted, ideal body weight), MDRD-4, CKD-EPI, rLM, BIS1, and FAS equations.
• Non-linear mixed-effects modeling (NONMEM 7.3) to assess amikacin plasma concentrations and drug elimination.

Main Results:

• All evaluated equations adequately described amikacin elimination data.
• A statistically significant improvement in model fit was observed with the Revised Lund-Malmö (rLM) equation, indicating a better linear relationship between clearance and glomerular filtration rate.
• The rLM equation requires careful evaluation in patients with renal failure for precise amikacin dose adjustments.

Conclusions:

• The Revised Lund-Malmö (rLM) and CKD-EPI equations exhibited superior predictive performance for amikacin drug elimination compared to other evaluated metrics.
• These findings suggest that rLM and CKD-EPI are valuable tools for optimizing amikacin dosing strategies.