Clearance Confusion: An Exploratory Analysis of Inpatient Dosing Discordances Between Renal Estimating Equations
© The Author(s) 2020. Background: Numerous equations exist for estimating renal clearance for drug dosing, and discordance rates may be as high as 40% in certain populations. However, the populations and types of equations used in these studies may not be generalizable to broader pharmacy practice. Objectives: To determine the dosing discordance rate between Cockcroft-Gault (C-G), Chronic Kidney Disease Epidemiology (CKD-EPI), and Modification of Diet in Renal Disease (MDRD) equations in a community hospital population. Methods: This was a cross-sectional analysis of inpatients who had documented renal function assessment over a 6-month period. Renal estimation was calculated using 5 equations (MDRD, CKD-EPI, and 3 C-G variants). Differences between equations were assessed using mean bias, dosing discordance, and agreement (κ statistic). Patients with acute kidney injury and those requiring renal replacement therapy were excluded. Results: A total of 466 patients were eligible for inclusion. Dosing discordance was evident between C-G variants and both MDRD and CKD-EPI equations in greater than 20% of patients. Agreement was highest between MDRD and CKD-EPI (κ = 0.93) and lowest between MDRD and C-G calculated using ideal body weight (κ = 0.33). The majority of discordant instances led to higher dosing recommendations when using MDRD and CKD-EPI equations compared with C-G variants. Dosing discordance exceeded 18% between the different C-G variants, with the highest discordance (36%) observed between total body weight and ideal body weight variants. Conclusion and Relevance: Dosing discordance between renal estimating equations is widespread. Practitioners and institutions should be aware of these differences when dosing medications and implementing renal dosing policies.
McConachie, Sean M.; Shammout, Laila; and Martirosov, Dmitriy M., "Clearance Confusion: An Exploratory Analysis of Inpatient Dosing Discordances Between Renal Estimating Equations" (2020). Articles. 77.