A retrospective study comparing creatinine clearance estimation using different equations on a population-based cohort

Abigail Ferreira; Rui Lapa; Nuno Vale; Abigail Ferreira; Rui Lapa; Nuno Vale

doi:10.3934/mbe.2021287

Mathematical Biosciences and Engineering

2021, Volume 18, Issue 5: 5680-5691. doi: 10.3934/mbe.2021287

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A retrospective study comparing creatinine clearance estimation using different equations on a population-based cohort

1.
OncoPharma Research Group, Center for Health Technology and Services Research (CINTESIS), Rua Dr. Plácido da Costa, Porto 4200-450, Portugal
2.
LAQV/REQUIMTE, Laboratory of Applied Chemistry, Department of Chemical Sciences, Faculty of Pharmacy, University of Porto, Rua de Jorge Viterbo Ferreira, 228, Porto 4050-313, Portugal
3.
Department of Community Medicine, Health Information and Decision (MEDCIDS), Faculty of Medicine, University of Porto, Al. Prof. Hernani Monteiro, Porto 4200-319, Portugal

Received: 21 April 2021 Accepted: 17 June 2021 Published: 23 June 2021

Renal elimination is an important part of drugs' excretion. At the same time, renal function can be impaired as a side effect of medication, particularly during prolonged treatments. Thus, the assessment of patients' renal function is of major consequence, especially in cases where the therapeutic regimen is adjusted taking into consideration renal clearance. Serum creatinine concentration is the most common indicator of renal clearance, since the most accurate indicator, glomerular filtration rate (GFR), is not easily measured. Using equations developed over the last decades, creatinine clearance (CL_Cr) is readily estimated taking into account patients' biological sex, age, body composition, and sometimes race. In this work, differences in estimated CL_Cr between different equations were studied and the influence of some patients' characteristics evaluated. Data collected from 82 inpatients receiving antibiotic therapy was analyzed and CL_Cr was estimated using a total of 12 equations. Patients were stratified according to their sex, age, and body composition to shed some light on the impact of these parameters in the estimations of renal function. More variability between estimation methods was highlighted (a) in patients between 51 and 60 years old, (b) within the normal body mass index group, and (c) in patients with serum creatinine levels below normal criteria. Furthermore, the Cockcroft-Gault equation considering lean body weight produced lower estimated CL_Cr in almost all groups.
- creatinine clearance estimation,
- renal function,
- therapeutic drug monitoring (TDM),
- antibiotics,
- Cockcroft-Gault formula,
- Jelliffe formula,
- Wright formula,
- Corcoran-Salazar formula
Citation: Abigail Ferreira, Rui Lapa, Nuno Vale. A retrospective study comparing creatinine clearance estimation using different equations on a population-based cohort[J]. Mathematical Biosciences and Engineering, 2021, 18(5): 5680-5691. doi: 10.3934/mbe.2021287

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Abstract

Renal elimination is an important part of drugs' excretion. At the same time, renal function can be impaired as a side effect of medication, particularly during prolonged treatments. Thus, the assessment of patients' renal function is of major consequence, especially in cases where the therapeutic regimen is adjusted taking into consideration renal clearance. Serum creatinine concentration is the most common indicator of renal clearance, since the most accurate indicator, glomerular filtration rate (GFR), is not easily measured. Using equations developed over the last decades, creatinine clearance (CL_Cr) is readily estimated taking into account patients' biological sex, age, body composition, and sometimes race. In this work, differences in estimated CL_Cr between different equations were studied and the influence of some patients' characteristics evaluated. Data collected from 82 inpatients receiving antibiotic therapy was analyzed and CL_Cr was estimated using a total of 12 equations. Patients were stratified according to their sex, age, and body composition to shed some light on the impact of these parameters in the estimations of renal function. More variability between estimation methods was highlighted (a) in patients between 51 and 60 years old, (b) within the normal body mass index group, and (c) in patients with serum creatinine levels below normal criteria. Furthermore, the Cockcroft-Gault equation considering lean body weight produced lower estimated CL_Cr in almost all groups.

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