It appears you don't have support to open PDFs in this web browser. To view this file, Open with your PDF reader
Abstract
Plasma clearance of iohexol is a pivotal metric to quantify glomerular filtration rate (GFR), but the optimal timing and frequency of plasma sampling remain to be assessed. In this study, we evaluated the impact of a Bayesian estimation procedure on iohexol clearance estimates, and we identified an optimal sampling strategy based on data in individuals aged 70+. Assuming a varying number of random effects, we re-estimated previously developed population pharmacokinetic two- and three-compartment models in a model development group comprising 546 patients with iohexol concentration data up to 300 min post injection. Model performance and optimal sampling times were assessed in an evaluation group comprising 104 patients with reduced GFR and concentration data up to 1440 min post injection. Two- and three-compartment models with random effects for all parameters overestimated clearance values (bias 5.07 and 4.40 mL/min, respectively) and underpredicted 24-h concentrations (bias − 14.5 and − 12.0 µg/ml, respectively). Clearance estimates improved distinctly when limiting random effects of the three-compartment model to clearance and central volume of distribution. Two blood samples, one early and one 300 min post injection, were sufficient to estimate iohexol clearance. A simplified three-compartment model is optimal to estimate iohexol clearance in elderly patients with reduced GFR.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details
1 University Hospital Cologne (AöR), Clinical Pharmacology Unit, Department I of Pharmacology, Faculty of Medicine and University Hospital Cologne, Center for Pharmacology, Cologne, Germany (GRID:grid.411097.a) (ISNI:0000 0000 8852 305X)
2 Charité – Universitätsmedizin Berlin, Institute of Public Health, Berlin, Germany (GRID:grid.6363.0) (ISNI:0000 0001 2218 4662)
3 University Hospital Tübingen, Institute for Clinical Epidemiology and Applied Biostatistics, Tübingen, Germany (GRID:grid.411544.1) (ISNI:0000 0001 0196 8249)
4 Charité – Universitätsmedizin Berlin, Department of Nephrology, Berlin, Germany (GRID:grid.6363.0) (ISNI:0000 0001 2218 4662)
5 Vivantes Klinikum Im Friedrichshain, Department of Nephrology, Berlin, Germany (GRID:grid.415085.d)