Optimization of Beta-lactam Dosing in Critically Ill Patients With Cystatin C (OPTIMIZE-GNI)

The purpose of this study is to evaluate the abilities of Cystatin C (CysC) and CysC-based estimated Glomerular Filtration Rate (eGFR) equations to characterize the pharmacokinetics (PK) profiles of meropenem and cefepime relative to Serum Creatinine (SCR), Serum Creatinine based Equation (SCRE)and iohexol at the population and individual levels in critically ill adult patients with suspected or documented AMR Gram-negative infections. We hypothesize that CysC and CysC-based eGFR equations will characterize the PK profiles of meropenem and cefepime at the population and individual levels with greater accuracy and precision than SCR and SCREs. Iohexol will be administered to patients enrolled in the study and serve as the reference indicator of measured Glomerular Filtration Rate (mGFR), which is the gold standard assessment of kidney function. We hypothesize that the predictive performances of CysC and CysC-based eGFR equations in estimating the PK profiles of meropenem and cefepime at the population and individual levels will be comparable to iohexol. The information obtained in this study will be used to develop PK/pharmacodynamics (PD) optimized meropenem and cefepime dosing schemes based on the renal function biomarker population PK (PopPK) model with the best predictive performance for clinical use in the treatment of critically ill adult patients with suspected or documented AMR Gram-negative infections and varying degrees of renal function. The primary objective of this study is to compare the abilities of renal function biomarkers (CysC, CysC-based eGFR equations, SCR, SCREs) relative to iohexol to characterize the PK profiles of meropenem and cefepime in critically ill adult patients with suspected or documented AMR Gram-negative infections.

The intent of this study is to compare the abilities of Cystatin C (CysC) and CysC-based estimated Glomerular Filtration Rate (eGFR) equations to characterize the pharmacokinetics (PK) profiles of meropenem and cefepime relative to Serum Creatinine (SCR), Serum Creatinine based Equation (SCRE), and iohexol in critically ill patients with suspected or documented AMR Gram-negative infections. We hypothesize that CysC and CysC-based eGFR equations will characterize the PK profiles of meropenem and cefepime at the population and individual levels with greater accuracy and precision than SCR and SCREs. Iohexol will be administered to patients enrolled in the study and serve as the reference indicator of measured Glomerular Filtration Rate (mGFR), which is the gold standard assessment of kidney function. We further hypothesize that the predictive performances of CysC and CysC-based eGFR equations in estimating the PK profiles of meropenem and cefepime at the population and individual levels will be comparable to iohexol. Firstly, population PK (PopPK) modeling will be used to develop meropenem and cefepime PopPK models informed by CysC, CysC-based eGFR equations, SCR, and SCREs (renal function biomarkers), and iohexol. Secondly, model diagnostics will then be used to compare the predictive performances of the renal function biomarkers PopPK models for each antibiotic relative to iohexol PopPK model. Lastly, Monte Carlo simulation (MCS) will be used to design PK/ pharmacodynamics (PD) optimized meropenem and cefepime dosing schemes based on the renal function biomarker PopPK model with the best predictive performance for use in the treatment of critically ill adult patients with suspected or documented AMR Gram-negative infections and varying degrees of renal function. The primary objective of this study is to compare the abilities of renal function biomarkers (CysC, CysC-based eGFR equations, SCR, SCREs) relative to iohexol to characterize the PK profiles of meropenem and cefepime in critically ill adult patients with suspected or documented AMR Gram-negative infections. The secondary objective of this study is to develop PK/PD optimized meropenem and cefepime dosing schemes based on the renal biomarker function PopPK model with the best predictive performance relative to the iohexol PopPK model for critically ill adult patients with suspected or documented AMR Gram-negative infections.