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Discrepant glomerular filtration rate trends from creatinine and cystatin C in patients with chronic kidney disease: results from the KNOW-CKD cohort

BACKGROUND: Serum creatinine (Cr) and cystatin C (CysC) can both be used to estimate glomerular filtration rate (eGFR(Cr) and eGFR(CysC)). However, certain conditions may cause discrepancies between eGFR trends from Cr and CysC, and these remain undetermined in patients with chronic kidney disease (...

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Autores principales: Kang, Eunjeong, Han, Seung Seok, Kim, Jayoun, Park, Sue Kyung, Chung, Wookyung, Oh, Yun Kyu, Chae, Dong-Wan, Kim, Yong-Soo, Ahn, Curie, Oh, Kook-Hwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7364655/
https://www.ncbi.nlm.nih.gov/pubmed/32677901
http://dx.doi.org/10.1186/s12882-020-01932-4
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author Kang, Eunjeong
Han, Seung Seok
Kim, Jayoun
Park, Sue Kyung
Chung, Wookyung
Oh, Yun Kyu
Chae, Dong-Wan
Kim, Yong-Soo
Ahn, Curie
Oh, Kook-Hwan
author_facet Kang, Eunjeong
Han, Seung Seok
Kim, Jayoun
Park, Sue Kyung
Chung, Wookyung
Oh, Yun Kyu
Chae, Dong-Wan
Kim, Yong-Soo
Ahn, Curie
Oh, Kook-Hwan
author_sort Kang, Eunjeong
collection PubMed
description BACKGROUND: Serum creatinine (Cr) and cystatin C (CysC) can both be used to estimate glomerular filtration rate (eGFR(Cr) and eGFR(CysC)). However, certain conditions may cause discrepancies between eGFR trends from Cr and CysC, and these remain undetermined in patients with chronic kidney disease (CKD). METHODS: A total of 1069 patients from the Korean CKD cohort (KNOW-CKD), which enrolls pre-dialytic CKD patients, whose Cr and CysC had been followed for more than 4 years were included in the sample. We performed trajectory analysis using latent class mixed modeling and identified members of the discrepancy group when patient trends between eGFR(Cr) and eGFR(CysC) differed. Multivariate logistic analyses with Firth’s penalized likelihood regression models were performed to identify conditions related to the discrepancy. RESULTS: Trajectory patterns of eGFR(Cr) were classified into three groups: two groups with stable eGFR(Cr) (stable with high eGFR(Cr) and stable with low eGFR(Cr)) and one group with decreasing eGFR(Cr). Trajectory analysis of eGFR(CysC) also showed similar patterns, comprising two groups with stable eGFR(CysC) and one group with decreasing eGFR(CysC). Patients in the discrepancy group (decreasing eGFR(Cr) but stable & low eGFR(CysC); n = 55) were younger and had greater proteinuria values than the agreement group (stable & low eGFR(Cr) and eGFR(CysC); n = 706), differences that remained consistent irrespective of the measurement period (4 or 5 years). CONCLUSIONS: In the present study, we identify conditions related to discrepant trends of eGFR(Cr) and eGFR(CysC). Clinicians should remain aware of such potential discrepancies when tracing both Cr and CysC.
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spelling pubmed-73646552020-07-20 Discrepant glomerular filtration rate trends from creatinine and cystatin C in patients with chronic kidney disease: results from the KNOW-CKD cohort Kang, Eunjeong Han, Seung Seok Kim, Jayoun Park, Sue Kyung Chung, Wookyung Oh, Yun Kyu Chae, Dong-Wan Kim, Yong-Soo Ahn, Curie Oh, Kook-Hwan BMC Nephrol Research Article BACKGROUND: Serum creatinine (Cr) and cystatin C (CysC) can both be used to estimate glomerular filtration rate (eGFR(Cr) and eGFR(CysC)). However, certain conditions may cause discrepancies between eGFR trends from Cr and CysC, and these remain undetermined in patients with chronic kidney disease (CKD). METHODS: A total of 1069 patients from the Korean CKD cohort (KNOW-CKD), which enrolls pre-dialytic CKD patients, whose Cr and CysC had been followed for more than 4 years were included in the sample. We performed trajectory analysis using latent class mixed modeling and identified members of the discrepancy group when patient trends between eGFR(Cr) and eGFR(CysC) differed. Multivariate logistic analyses with Firth’s penalized likelihood regression models were performed to identify conditions related to the discrepancy. RESULTS: Trajectory patterns of eGFR(Cr) were classified into three groups: two groups with stable eGFR(Cr) (stable with high eGFR(Cr) and stable with low eGFR(Cr)) and one group with decreasing eGFR(Cr). Trajectory analysis of eGFR(CysC) also showed similar patterns, comprising two groups with stable eGFR(CysC) and one group with decreasing eGFR(CysC). Patients in the discrepancy group (decreasing eGFR(Cr) but stable & low eGFR(CysC); n = 55) were younger and had greater proteinuria values than the agreement group (stable & low eGFR(Cr) and eGFR(CysC); n = 706), differences that remained consistent irrespective of the measurement period (4 or 5 years). CONCLUSIONS: In the present study, we identify conditions related to discrepant trends of eGFR(Cr) and eGFR(CysC). Clinicians should remain aware of such potential discrepancies when tracing both Cr and CysC. BioMed Central 2020-07-16 /pmc/articles/PMC7364655/ /pubmed/32677901 http://dx.doi.org/10.1186/s12882-020-01932-4 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Kang, Eunjeong
Han, Seung Seok
Kim, Jayoun
Park, Sue Kyung
Chung, Wookyung
Oh, Yun Kyu
Chae, Dong-Wan
Kim, Yong-Soo
Ahn, Curie
Oh, Kook-Hwan
Discrepant glomerular filtration rate trends from creatinine and cystatin C in patients with chronic kidney disease: results from the KNOW-CKD cohort
title Discrepant glomerular filtration rate trends from creatinine and cystatin C in patients with chronic kidney disease: results from the KNOW-CKD cohort
title_full Discrepant glomerular filtration rate trends from creatinine and cystatin C in patients with chronic kidney disease: results from the KNOW-CKD cohort
title_fullStr Discrepant glomerular filtration rate trends from creatinine and cystatin C in patients with chronic kidney disease: results from the KNOW-CKD cohort
title_full_unstemmed Discrepant glomerular filtration rate trends from creatinine and cystatin C in patients with chronic kidney disease: results from the KNOW-CKD cohort
title_short Discrepant glomerular filtration rate trends from creatinine and cystatin C in patients with chronic kidney disease: results from the KNOW-CKD cohort
title_sort discrepant glomerular filtration rate trends from creatinine and cystatin c in patients with chronic kidney disease: results from the know-ckd cohort
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7364655/
https://www.ncbi.nlm.nih.gov/pubmed/32677901
http://dx.doi.org/10.1186/s12882-020-01932-4
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