Zhendong Chen (1), Chunli Chen (1), Max Taubert (1), Michael Mayersohn (2), Uwe Fuhr (1)
(1) University of Cologne, Faculty of Medicine and University Hospital Cologne, Center for Pharmacology, Department I of Pharmacology, Cologne, Germany, (2) College of Pharmacy, University of Arizona, Tucson, Arizona, USA (3) College of Veterinary Medicine, Northeast Agricultural University, Harbin, P.R. China
Introduction: Estimated glomerular filtration rate (GFR) based on serum creatinine is now widely reported by clinical laboratories, and in most circumstances, estimated GFR is sufficient for clinical decision-making [1]. However, commonly used equations are based on steady-state assumptions regarding creatinine formation and elimination and thus are less suitable in patients with unstable renal function [2-4]. A compartmental model based on serum and urine creatinine concentration data from critically ill patients was introduced to estimate creatinine clearance more accurately compared to standard approaches [5]. However, the volume of distribution of creatinine was assumed as 60% of the total body weight in this model. The latter is only a rough approximation and neglects variability, which may result in biased estimates of other kinetic parameters [5]. We report here on the results of one clinical study regarding creatinine pharmacokinetic (PK) profiles with and without ingestion of a cooked meat meal. A significant increase in creatinine plasma concentrations with no clearance change was found after eating boiled beef [6]. The data from this study were used to estimate PK parameters of creatinine using population pharmacokinetic (PPK) analysis, thus helping to refine the creatinine dynamic model and reducing biased estimates of other kinetic parameters.
Objectives: To obtain creatinine PK parameters including: apparent absorption rate constant (Ka); renal clearance (CL); the volume of distribution (Vd); and creatinine generation rate (CGR) based on the PPK approach.
Methods: The PK data for creatinine were captured using the “getdata” software [7], which can digitalize the graphs of the original data from the publication by Mayersohn et al. [6]. Both plasma and urine data during 24-hours following beef or no beef ingestion were analyzed using NONMEM (version 7.4.0, ICON Development Solutions, USA). A one-compartment (1-CMT) creatinine PK model with zero-order creatinine generation rate and first-order clearance was estimated and different error models were evaluated separately, including: additive-only, proportional-only error models, and the combination thereof. Individual bioavailable creatinine “dose” for each subject was estimated using a pre-defined arbitrary population dose which was adjusted by individual post-hoc estimates of apparent bioavailability (F1). The statistical criteria for a parameter to be incorporated into the model were a decrease of >3.84 in the objective function value (OFV) (P = 0.05) of the forward inclusion step and an increase of >6.63 in the OFV (P = 0.01) of the backward elimination step. A decrease in the OFV >3.84 was considered statistically significant.
Results: The PPK model was constructed based on the dataset composed of 133 serial plasma values and 11 urine values. A 1-CMT PK model with linear elimination, first-order absorption, and zero-order creatinine generation provided the most robust fit for creatinine PK profiles. Inter-individual variability (IIV) and residual variability were well described by an exponential model and a proportional error model, respectively.
Finally, the PK parameters including Ka (1.71 1/h), CL (7.57 L/h), Vd (52.8 L), F1 (182%), CGR (67.8 mg/h), and lag time (0.343 h) were estimated from the creatinine model. The IIV of Vd was removed as it did not contribute to model improvement. This may be a result of the low variability of individual weights (65 – 82 kg) in this study since the Vd of creatinine is usually assumed to be a fraction of total body water [8], which is approximately 60% of the total body weight. From this model, the Vd of creatinine was estimated to be 52.8 L (72.3% of the total body weight), which is also close to but slightly higher than the fraction of total body water.
The typical value for creatinine generation rate in healthy volunteers was 67.8 mg/h, which is higher than the value of 42.8 mg/h (1183 mg/day) and 43.8 mg/h in patients reported by Ullah et al. and Daugirdas et al., respectively [5,9]. The values for estimated individual creatinine renal clearance were similar to those that have been reported [6]. However, the adjusted “dose” (based on the equation: F1×180 mg) for each subject was not consistent with the increased creatinine amount excreted in urine after beef ingestion. This does not exclude the possibility that these discrepancies are related to the accuracy of the raw data; also, no demographic information is available in the publication to better define the PPK model.
Conclusion: This study investigated the generation rate and the volume of distribution of creatinine in healthy volunteers using a model-based approach and oral administration of creatinine by boiled meat.
References:
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[2] Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron. 1976, 16(1): 31-41.
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[5] Ullah S, Zoller M, Jaehde U, et al. A Model-Based Approach to Assess Unstable Creatinine Clearance in Critically Ill Patients. Clin Pharmacol Ther. 2021, 110(5): 1240-1249.
[6] Mayersohn M, Conrad KA, Achari R. The influence of a cooked meat meal on creatinine plasma concentration and creatinine clearance. Br J Clin Pharmacol. 1983; 15(2):227-30.
[7] http://getdata-graph-digitizer.com/download.php
[8] Pickering JW, Ralib AM, Endre ZH. Combining creatinine and volume kinetics identifies missed cases of acute kidney injury following cardiac arrest. Crit Care. 2013,17(1): R7.
[9] Daugirdas JT, Depner TA. Creatinine generation from kinetic modeling with or without postdialysis serum creatinine measurement: results from the HEMO study. Nephrol Dial Transplant. 2017, 32(11): 1926-1933.
Reference: PAGE 30 (2022) Abstr 10081 [www.page-meeting.org/?abstract=10081]
Poster: Clinical Applications