Cargando…
Estimating glomerular filtration rate in a population-based study
BACKGROUND: Glomerular filtration rate (GFR)-estimating equations are used to determine the prevalence of chronic kidney disease (CKD) in population-based studies. However, it has been suggested that since the commonly used GFR equations were originally developed from samples of patients with CKD, t...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2010
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2922323/ https://www.ncbi.nlm.nih.gov/pubmed/20730018 |
_version_ | 1782185431722360832 |
---|---|
author | Shankar, Anoop Lee, Kristine E Klein, Barbara EK Muntner, Paul Brazy, Peter C Cruickshanks, Karen J Nieto, F Javier Danforth, Lorraine G Schubert, Carla R Tsai, Michael Y Klein, Ronald |
author_facet | Shankar, Anoop Lee, Kristine E Klein, Barbara EK Muntner, Paul Brazy, Peter C Cruickshanks, Karen J Nieto, F Javier Danforth, Lorraine G Schubert, Carla R Tsai, Michael Y Klein, Ronald |
author_sort | Shankar, Anoop |
collection | PubMed |
description | BACKGROUND: Glomerular filtration rate (GFR)-estimating equations are used to determine the prevalence of chronic kidney disease (CKD) in population-based studies. However, it has been suggested that since the commonly used GFR equations were originally developed from samples of patients with CKD, they underestimate GFR in healthy populations. Few studies have made side-by-side comparisons of the effect of various estimating equations on the prevalence estimates of CKD in a general population sample. PATIENTS AND METHODS: We examined a population-based sample comprising adults from Wisconsin (age, 43–86 years; 56% women). We compared the prevalence of CKD, defined as a GFR of <60 mL/min per 1.73 m(2) estimated from serum creatinine, by applying various commonly used equations including the modification of diet in renal disease (MDRD) equation, Cockcroft–Gault (CG) equation, and the Mayo equation. We compared the performance of these equations against the CKD definition of cystatin C >1.23 mg/L. RESULTS: We found that the prevalence of CKD varied widely among different GFR equations. Although the prevalence of CKD was 17.2% with the MDRD equation and 16.5% with the CG equation, it was only 4.8% with the Mayo equation. Only 24% of those identified to have GFR in the range of 50–59 mL/min per 1.73 m(2) by the MDRD equation had cystatin C levels >1.23 mg/L; their mean cystatin C level was only 1 mg/L (interquartile range, 0.9–1.2 mg/L). This finding was similar for the CG equation. For the Mayo equation, 62.8% of those patients with GFR in the range of 50–59 mL/min per 1.73 m(2) had cystatin C levels >1.23 mg/L; their mean cystatin C level was 1.3 mg/L (interquartile range, 1.2–1.5 mg/L). The MDRD and CG equations showed a false-positive rate of >10%. DISCUSSION: We found that the MDRD and CG equations, the current standard to estimate GFR, appeared to overestimate the prevalence of CKD in a general population sample. |
format | Text |
id | pubmed-2922323 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-29223232010-08-20 Estimating glomerular filtration rate in a population-based study Shankar, Anoop Lee, Kristine E Klein, Barbara EK Muntner, Paul Brazy, Peter C Cruickshanks, Karen J Nieto, F Javier Danforth, Lorraine G Schubert, Carla R Tsai, Michael Y Klein, Ronald Vasc Health Risk Manag Original Research BACKGROUND: Glomerular filtration rate (GFR)-estimating equations are used to determine the prevalence of chronic kidney disease (CKD) in population-based studies. However, it has been suggested that since the commonly used GFR equations were originally developed from samples of patients with CKD, they underestimate GFR in healthy populations. Few studies have made side-by-side comparisons of the effect of various estimating equations on the prevalence estimates of CKD in a general population sample. PATIENTS AND METHODS: We examined a population-based sample comprising adults from Wisconsin (age, 43–86 years; 56% women). We compared the prevalence of CKD, defined as a GFR of <60 mL/min per 1.73 m(2) estimated from serum creatinine, by applying various commonly used equations including the modification of diet in renal disease (MDRD) equation, Cockcroft–Gault (CG) equation, and the Mayo equation. We compared the performance of these equations against the CKD definition of cystatin C >1.23 mg/L. RESULTS: We found that the prevalence of CKD varied widely among different GFR equations. Although the prevalence of CKD was 17.2% with the MDRD equation and 16.5% with the CG equation, it was only 4.8% with the Mayo equation. Only 24% of those identified to have GFR in the range of 50–59 mL/min per 1.73 m(2) by the MDRD equation had cystatin C levels >1.23 mg/L; their mean cystatin C level was only 1 mg/L (interquartile range, 0.9–1.2 mg/L). This finding was similar for the CG equation. For the Mayo equation, 62.8% of those patients with GFR in the range of 50–59 mL/min per 1.73 m(2) had cystatin C levels >1.23 mg/L; their mean cystatin C level was 1.3 mg/L (interquartile range, 1.2–1.5 mg/L). The MDRD and CG equations showed a false-positive rate of >10%. DISCUSSION: We found that the MDRD and CG equations, the current standard to estimate GFR, appeared to overestimate the prevalence of CKD in a general population sample. Dove Medical Press 2010 2010-08-09 /pmc/articles/PMC2922323/ /pubmed/20730018 Text en © 2010 Shankar et al, publisher and licensee Dove Medical Press Ltd. This is an Open Access article which permits unrestricted noncommercial use, provided the original work is properly cited. |
spellingShingle | Original Research Shankar, Anoop Lee, Kristine E Klein, Barbara EK Muntner, Paul Brazy, Peter C Cruickshanks, Karen J Nieto, F Javier Danforth, Lorraine G Schubert, Carla R Tsai, Michael Y Klein, Ronald Estimating glomerular filtration rate in a population-based study |
title | Estimating glomerular filtration rate in a population-based study |
title_full | Estimating glomerular filtration rate in a population-based study |
title_fullStr | Estimating glomerular filtration rate in a population-based study |
title_full_unstemmed | Estimating glomerular filtration rate in a population-based study |
title_short | Estimating glomerular filtration rate in a population-based study |
title_sort | estimating glomerular filtration rate in a population-based study |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2922323/ https://www.ncbi.nlm.nih.gov/pubmed/20730018 |
work_keys_str_mv | AT shankaranoop estimatingglomerularfiltrationrateinapopulationbasedstudy AT leekristinee estimatingglomerularfiltrationrateinapopulationbasedstudy AT kleinbarbaraek estimatingglomerularfiltrationrateinapopulationbasedstudy AT muntnerpaul estimatingglomerularfiltrationrateinapopulationbasedstudy AT brazypeterc estimatingglomerularfiltrationrateinapopulationbasedstudy AT cruickshankskarenj estimatingglomerularfiltrationrateinapopulationbasedstudy AT nietofjavier estimatingglomerularfiltrationrateinapopulationbasedstudy AT danforthlorraineg estimatingglomerularfiltrationrateinapopulationbasedstudy AT schubertcarlar estimatingglomerularfiltrationrateinapopulationbasedstudy AT tsaimichaely estimatingglomerularfiltrationrateinapopulationbasedstudy AT kleinronald estimatingglomerularfiltrationrateinapopulationbasedstudy |