A Validation Study on eGFR Equations in Chinese Patients With Diabetic or Non-diabetic CKD

It remains controversial to choose the optimal equation to estimate glomerular filtration rate (GFR) in chronic kidney disease (CKD) patients with diabetes. Two hundred and fifteen diabetic CKD patients and 192 non-diabetic CKD patients were enrolled in this study. Iohexol GFR, serum creatinine (SCr...

Full description

Saved in:
Bibliographic Details
Published inFrontiers in endocrinology (Lausanne) Vol. 10; p. 581
Main Authors Xie, Danshu, Shi, Hao, Xie, Jingyuan, Ding, Ying, Zhang, Wen, Ni, Liyan, Wu, Yifan, Lu, Yimin, Chen, Bing, Wang, Hongrui, Ren, Hong, Wang, Weiming, Liu, Na, Chen, Nan
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 26.08.2019
Subjects
Online AccessGet full text

Cover

Loading…
Abstract It remains controversial to choose the optimal equation to estimate glomerular filtration rate (GFR) in chronic kidney disease (CKD) patients with diabetes. Two hundred and fifteen diabetic CKD patients and 192 non-diabetic CKD patients were enrolled in this study. Iohexol GFR, serum creatinine (SCr), and Cystatin C(CysC) were measured simultaneously for each patient. SCr- and CysC-based estimated GFR (eGFR) were calculated through eight equations, including three CKD-EPI equations, Revised Lund-Malmö study equation (RLM), CAPA equation, and three Full Age Spectrum (FAS) equations. Bias, precision, and accuracy were compared among eGFR equations with iohexol-GFR serving as measured GFR (mGFR). Independent predictive factors of accuracy were explored using multivariate logistic regression analysis. In the diabetic group, CKD-EPI showed the best performance among three CKD-EPI equations (interquartile range of 13.88 ml/min/1.73 m and 30% accuracy of 72.56%). Compared to CKD-EPI , the other five equations did not significantly improve the performance of GFR estimates. Mostly, eGFR equations were less accurate in diabetic group than in non-diabetic group. Significant differences were found in different mGFR range ( < 0.001). The multivariate logistic regression analysis identified that BMI, mGFR, and diabetic kidney disease (DKD) status were independent predictors of accuracy of three equations in diabetic group. HbA1c was a predictor of accuracy of CKD-EPI and CKD-EPI in diabetic group. This study showed that eGFR equations were less accurate in the diabetic group than in the non-diabetic group. CKD-EPI had the best performance among CKD-EPI equations in Chinese diabetic CKD patients. The other five equations did not significantly improve the performance of GFR estimates. BMI, mGFR, DKD status, and HbA1c were independent factors associated with accuracy in eGFR equations.
AbstractList Aims: It remains controversial to choose the optimal equation to estimate glomerular filtration rate (GFR) in chronic kidney disease (CKD) patients with diabetes. Materials and Methods: Two hundred and fifteen diabetic CKD patients and 192 non-diabetic CKD patients were enrolled in this study. Iohexol GFR, serum creatinine (SCr), and Cystatin C(CysC) were measured simultaneously for each patient. SCr- and CysC-based estimated GFR (eGFR) were calculated through eight equations, including three CKD-EPI equations, Revised Lund-Malmö study equation (RLM), CAPA equation, and three Full Age Spectrum (FAS) equations. Bias, precision, and accuracy were compared among eGFR equations with iohexol-GFR serving as measured GFR (mGFR). Independent predictive factors of accuracy were explored using multivariate logistic regression analysis. Results: In the diabetic group, CKD-EPI SCr−CysC showed the best performance among three CKD-EPI equations (interquartile range of 13.88 ml/min/1.73 m 2 and 30% accuracy of 72.56%). Compared to CKD-EPI SCr−CysC , the other five equations did not significantly improve the performance of GFR estimates. Mostly, eGFR equations were less accurate in diabetic group than in non-diabetic group. Significant differences were found in different mGFR range ( P < 0.001). The multivariate logistic regression analysis identified that BMI, mGFR, and diabetic kidney disease (DKD) status were independent predictors of accuracy of three equations in diabetic group. HbA1c was a predictor of accuracy of CKD-EPI SCr and CKD-EPI CysC in diabetic group. Conclusions: This study showed that eGFR equations were less accurate in the diabetic group than in the non-diabetic group. CKD-EPI Scr−CysC had the best performance among CKD-EPI equations in Chinese diabetic CKD patients. The other five equations did not significantly improve the performance of GFR estimates. BMI, mGFR, DKD status, and HbA1c were independent factors associated with accuracy in eGFR equations.
It remains controversial to choose the optimal equation to estimate glomerular filtration rate (GFR) in chronic kidney disease (CKD) patients with diabetes. Two hundred and fifteen diabetic CKD patients and 192 non-diabetic CKD patients were enrolled in this study. Iohexol GFR, serum creatinine (SCr), and Cystatin C(CysC) were measured simultaneously for each patient. SCr- and CysC-based estimated GFR (eGFR) were calculated through eight equations, including three CKD-EPI equations, Revised Lund-Malmö study equation (RLM), CAPA equation, and three Full Age Spectrum (FAS) equations. Bias, precision, and accuracy were compared among eGFR equations with iohexol-GFR serving as measured GFR (mGFR). Independent predictive factors of accuracy were explored using multivariate logistic regression analysis. In the diabetic group, CKD-EPI showed the best performance among three CKD-EPI equations (interquartile range of 13.88 ml/min/1.73 m and 30% accuracy of 72.56%). Compared to CKD-EPI , the other five equations did not significantly improve the performance of GFR estimates. Mostly, eGFR equations were less accurate in diabetic group than in non-diabetic group. Significant differences were found in different mGFR range ( < 0.001). The multivariate logistic regression analysis identified that BMI, mGFR, and diabetic kidney disease (DKD) status were independent predictors of accuracy of three equations in diabetic group. HbA1c was a predictor of accuracy of CKD-EPI and CKD-EPI in diabetic group. This study showed that eGFR equations were less accurate in the diabetic group than in the non-diabetic group. CKD-EPI had the best performance among CKD-EPI equations in Chinese diabetic CKD patients. The other five equations did not significantly improve the performance of GFR estimates. BMI, mGFR, DKD status, and HbA1c were independent factors associated with accuracy in eGFR equations.
Aims: It remains controversial to choose the optimal equation to estimate glomerular filtration rate (GFR) in chronic kidney disease (CKD) patients with diabetes.Materials and Methods: Two hundred and fifteen diabetic CKD patients and 192 non-diabetic CKD patients were enrolled in this study. Iohexol GFR, serum creatinine (SCr), and Cystatin C(CysC) were measured simultaneously for each patient. SCr- and CysC-based estimated GFR (eGFR) were calculated through eight equations, including three CKD-EPI equations, Revised Lund-Malmö study equation (RLM), CAPA equation, and three Full Age Spectrum (FAS) equations. Bias, precision, and accuracy were compared among eGFR equations with iohexol-GFR serving as measured GFR (mGFR). Independent predictive factors of accuracy were explored using multivariate logistic regression analysis.Results: In the diabetic group, CKD-EPISCr−CysC showed the best performance among three CKD-EPI equations (interquartile range of 13.88 ml/min/1.73 m2 and 30% accuracy of 72.56%). Compared to CKD-EPISCr−CysC, the other five equations did not significantly improve the performance of GFR estimates. Mostly, eGFR equations were less accurate in diabetic group than in non-diabetic group. Significant differences were found in different mGFR range (P < 0.001). The multivariate logistic regression analysis identified that BMI, mGFR, and diabetic kidney disease (DKD) status were independent predictors of accuracy of three equations in diabetic group. HbA1c was a predictor of accuracy of CKD-EPISCr and CKD-EPICysC in diabetic group.Conclusions: This study showed that eGFR equations were less accurate in the diabetic group than in the non-diabetic group. CKD-EPIScr−CysC had the best performance among CKD-EPI equations in Chinese diabetic CKD patients. The other five equations did not significantly improve the performance of GFR estimates. BMI, mGFR, DKD status, and HbA1c were independent factors associated with accuracy in eGFR equations.
Author Ding, Ying
Chen, Bing
Xie, Jingyuan
Ren, Hong
Chen, Nan
Liu, Na
Wang, Hongrui
Ni, Liyan
Lu, Yimin
Wang, Weiming
Xie, Danshu
Shi, Hao
Zhang, Wen
Wu, Yifan
AuthorAffiliation 3 University of Lausanne , Lausanne , Switzerland
2 Biomedical and Health Informatics, University of Washington , Seattle, WA , United States
1 Department of Nephrology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai , China
5 Department of Nephrology, Shanghai East Hospital, Tongji University School of Medicine , Shanghai , China
4 Department of Pharmacy, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai , China
AuthorAffiliation_xml – name: 4 Department of Pharmacy, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai , China
– name: 5 Department of Nephrology, Shanghai East Hospital, Tongji University School of Medicine , Shanghai , China
– name: 1 Department of Nephrology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai , China
– name: 2 Biomedical and Health Informatics, University of Washington , Seattle, WA , United States
– name: 3 University of Lausanne , Lausanne , Switzerland
Author_xml – sequence: 1
  givenname: Danshu
  surname: Xie
  fullname: Xie, Danshu
  organization: Department of Nephrology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
– sequence: 2
  givenname: Hao
  surname: Shi
  fullname: Shi, Hao
  organization: Department of Nephrology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
– sequence: 3
  givenname: Jingyuan
  surname: Xie
  fullname: Xie, Jingyuan
  organization: Department of Nephrology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
– sequence: 4
  givenname: Ying
  surname: Ding
  fullname: Ding, Ying
  organization: Department of Nephrology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
– sequence: 5
  givenname: Wen
  surname: Zhang
  fullname: Zhang, Wen
  organization: Department of Nephrology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
– sequence: 6
  givenname: Liyan
  surname: Ni
  fullname: Ni, Liyan
  organization: Department of Nephrology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
– sequence: 7
  givenname: Yifan
  surname: Wu
  fullname: Wu, Yifan
  organization: Biomedical and Health Informatics, University of Washington, Seattle, WA, United States
– sequence: 8
  givenname: Yimin
  surname: Lu
  fullname: Lu, Yimin
  organization: University of Lausanne, Lausanne, Switzerland
– sequence: 9
  givenname: Bing
  surname: Chen
  fullname: Chen, Bing
  organization: Department of Pharmacy, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
– sequence: 10
  givenname: Hongrui
  surname: Wang
  fullname: Wang, Hongrui
  organization: Department of Nephrology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
– sequence: 11
  givenname: Hong
  surname: Ren
  fullname: Ren, Hong
  organization: Department of Nephrology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
– sequence: 12
  givenname: Weiming
  surname: Wang
  fullname: Wang, Weiming
  organization: Department of Nephrology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
– sequence: 13
  givenname: Na
  surname: Liu
  fullname: Liu, Na
  organization: Department of Nephrology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
– sequence: 14
  givenname: Nan
  surname: Chen
  fullname: Chen, Nan
  organization: Department of Nephrology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
BackLink https://www.ncbi.nlm.nih.gov/pubmed/31507533$$D View this record in MEDLINE/PubMed
BookMark eNpVkUlPHDEQha2IKBDCPafIx1x68NrdvkRCwxIESqKsUi6Wl2rGqMcGuzsS_z5mBhD44qrnqs9Vem_RTkwREHpPyYLzXh0OEH1aMELVghDZ01doj7ataBhXbOdZvIsOSrkm9Yhaq_o3aJdTSTrJ-R76e4R_mzF4M4UU8Y9p9ne4BnB2-h2f3M4bueAQ8XIVIhTA36oEcSr4T5hW-DgYC1NwOGX8JcXGP-bLi-N36PVgxgIHD_c--nV68nP5ubn8ena-PLpsnGjZ1BjCemPt0FlvYGCKdeAppdIOxkjVSsaYo871raEwDJarupKSQgpKOkYl5fvofMv1yVzrmxzWJt_pZILeCClfaZPrTCNoLmRnWpCkIoR1xEDNFbWWd1J47yrr05Z1M9s1eFc3zWZ8AX35EsNKX6V_uu1oTxmvgI8PgJxuZyiTXofiYBxNhDQXzVjfd9UV0ddSsi11OZWSYXj6hhJ977DeOKzvHdYbh2vLh-fjPTU8-sn_A5rso2I
CitedBy_id crossref_primary_10_1159_000531314
crossref_primary_10_3389_fendo_2021_723720
crossref_primary_10_1038_s41598_022_19185_6
crossref_primary_10_3389_fendo_2022_1003683
crossref_primary_10_1210_clinem_dgaa722
crossref_primary_10_1007_s11255_022_03370_7
crossref_primary_10_1155_2022_2177991
crossref_primary_10_3389_fpubh_2022_952899
crossref_primary_10_1155_2024_9532236
crossref_primary_10_1155_2022_4315361
crossref_primary_10_1371_journal_pone_0264313
crossref_primary_10_3389_fendo_2022_859266
crossref_primary_10_1007_s11255_020_02632_6
Cites_doi 10.1371/journal.pone.0109743
10.1093/ndt/gfw425
10.1053/j.ajkd.2016.07.021
10.2337/dc11-1282
10.1515/cclm-2013-0741
10.1186/s12882-017-0637-z
10.7326/0003-4819-130-6-199903160-00002
10.1007/BF03347201
10.1007/s40620-014-0087-7
10.1373/clinchem.2013.220707
10.1093/ndt/gfy363
10.1111/j.1523-1755.2004.00517.x
10.1373/clinchem.2016.264325
10.1186/s12882-015-0196-0
10.1056/NEJMoa1114248
10.1016/j.clinbiochem.2007.11.012
10.1093/ckj/sfw070
10.1056/NEJMc1602469
10.1001/jama.2017.7596
10.1159/000368545
10.1007/s11255-018-1997-4
10.1053/j.ajkd.2012.07.005
10.1093/ndt/gfv454
10.1016/j.clinbiochem.2013.05.067
10.1038/ki.2008.638
10.7326/0003-4819-150-9-200905050-00006
10.1038/clpt.2009.124
10.1007/s00125-011-2085-9
10.1053/j.ajkd.2008.12.043
10.1016/S0140-6736(10)60674-5
10.1038/ki.2010.536
10.1373/clinchem.2006.077180
10.1093/ndt/gfy086
10.2337/dc13-1899
10.1038/kisup.2012.64
10.2215/CJN.11491116
10.3109/00365517209084290
ContentType Journal Article
Copyright Copyright © 2019 Xie, Shi, Xie, Ding, Zhang, Ni, Wu, Lu, Chen, Wang, Ren, Wang, Liu and Chen. 2019 Xie, Shi, Xie, Ding, Zhang, Ni, Wu, Lu, Chen, Wang, Ren, Wang, Liu and Chen
Copyright_xml – notice: Copyright © 2019 Xie, Shi, Xie, Ding, Zhang, Ni, Wu, Lu, Chen, Wang, Ren, Wang, Liu and Chen. 2019 Xie, Shi, Xie, Ding, Zhang, Ni, Wu, Lu, Chen, Wang, Ren, Wang, Liu and Chen
DBID NPM
AAYXX
CITATION
7X8
5PM
DOA
DOI 10.3389/fendo.2019.00581
DatabaseName PubMed
CrossRef
MEDLINE - Academic
PubMed Central (Full Participant titles)
Open Access: DOAJ - Directory of Open Access Journals
DatabaseTitle PubMed
CrossRef
MEDLINE - Academic
DatabaseTitleList
PubMed

Database_xml – sequence: 1
  dbid: DOA
  name: DOAJ Directory of Open Access Journals
  url: https://www.doaj.org/
  sourceTypes: Open Website
– sequence: 2
  dbid: NPM
  name: PubMed
  url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
DeliveryMethod fulltext_linktorsrc
Discipline Medicine
EISSN 1664-2392
EndPage 581
ExternalDocumentID oai_doaj_org_article_3457a6e509294bc0ae57a91bb3754ddc
10_3389_fendo_2019_00581
31507533
Genre Journal Article
GrantInformation_xml – fundername: Science and Technology Commission of Shanghai Municipality
  grantid: 13430720800; 17441902200
– fundername: School of Medicine, Shanghai Jiao Tong University
  grantid: DLY201510
– fundername: Shanghai Municipal Education Commission
  grantid: 20152207
GroupedDBID 53G
5VS
9T4
AAFWJ
AAKDD
ACGFO
ACGFS
ACXDI
ADBBV
ADRAZ
AFPKN
ALMA_UNASSIGNED_HOLDINGS
AOIJS
BAWUL
BCNDV
DIK
EMOBN
GROUPED_DOAJ
GX1
HYE
IAO
IEA
IHR
IHW
IPNFZ
KQ8
M48
M~E
NPM
OK1
PGMZT
RIG
RPM
AAYXX
CITATION
7X8
5PM
ID FETCH-LOGICAL-c462t-a028abbf7bdaef2927ed1115bfaa5965222c1cc86a1effb393929545410721513
IEDL.DBID RPM
ISSN 1664-2392
IngestDate Tue Oct 22 15:13:11 EDT 2024
Tue Sep 17 20:40:34 EDT 2024
Sat Oct 26 01:30:32 EDT 2024
Thu Sep 26 18:16:42 EDT 2024
Sat Sep 28 08:40:57 EDT 2024
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Keywords diabetic kidney disease
chronic kidney disease (CKD)
glomerular filtration rate
CKD-EPI
diabetes
Language English
License This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c462t-a028abbf7bdaef2927ed1115bfaa5965222c1cc86a1effb393929545410721513
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
This article was submitted to Diabetes, a section of the journal Frontiers in Endocrinology
Reviewed by: Pierre Delanaye, University of Liège, Belgium; Robert Ekart, University Clinical Centre Maribor, Slovenia; Sebastjan Bevc, University Clinical Centre Maribor, Slovenia
Edited by: Jan Polák, Charles University, Czechia
OpenAccessLink https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6718123/
PMID 31507533
PQID 2288723948
PQPubID 23479
PageCount 1
ParticipantIDs doaj_primary_oai_doaj_org_article_3457a6e509294bc0ae57a91bb3754ddc
pubmedcentral_primary_oai_pubmedcentral_nih_gov_6718123
proquest_miscellaneous_2288723948
crossref_primary_10_3389_fendo_2019_00581
pubmed_primary_31507533
PublicationCentury 2000
PublicationDate 2019-08-26
PublicationDateYYYYMMDD 2019-08-26
PublicationDate_xml – month: 08
  year: 2019
  text: 2019-08-26
  day: 26
PublicationDecade 2010
PublicationPlace Switzerland
PublicationPlace_xml – name: Switzerland
PublicationTitle Frontiers in endocrinology (Lausanne)
PublicationTitleAlternate Front Endocrinol (Lausanne)
PublicationYear 2019
Publisher Frontiers Media S.A
Publisher_xml – name: Frontiers Media S.A
References Levey (B5) 1999; 130
MacIsaac (B38) 2015; 16
Levey (B25) 2007; 53
(B15) 2012; 60
Pottel (B13) 2017; 32
Foundation (B21) 2002; 39
Nyman (B10) 2014; 52
Chi (B34) 2017; 18
Tsuda (B36) 2016; 41
Stevens (B29) 2009; 86
Silveiro (B23) 2011; 34
Manetti (B28) 2005; 28
Inker (B8) 2012; 367
Du Bois (B19) 1989; 5
Delanaye (B17) 2016; 9
Luis-Lima (B39) 2019; 34
(B9) 2013; 3
Zhang (B2) 2016; 375
Abbink (B6) 2008; 41
Knight (B30) 2004; 65
Stevens (B27) 2009; 75
Wang (B1) 2017; 317
Alicic (B16) 2017; 12
Bargnoux (B33) 2017; 63
van der Velde (B4) 2011; 79
Delanaye (B32) 2014; 27
Tsuda (B37) 2014; 37
Pottel (B12) 2016; 31
Cheuiche (B26) 2013; 46
Vupputuri (B31) 2009; 53
Levey (B7) 2009; 150
Liu (B14) 2016; 68
Brochner-Mortensen (B18) 1972; 30
Nair (B22) 2011; 54
Grubb (B11) 2014; 60
Liu (B24) 2014; 9
Agarwal (B40) 2018
Yong (B35) 2019; 51
Stevens (B20) 2008; 21
Matsushita (B3) 2010; 375
References_xml – volume: 9
  start-page: e109743
  year: 2014
  ident: B24
  article-title: A new modified CKD-EPI equation for Chinese patients with type 2 diabetes
  publication-title: PLoS ONE.
  doi: 10.1371/journal.pone.0109743
  contributor:
    fullname: Liu
– volume: 32
  start-page: 497
  year: 2017
  ident: B13
  article-title: Estimating glomerular filtration rate for the full age spectrum from serum creatinine and cystatin C
  publication-title: Nephrol Dial Transpl.
  doi: 10.1093/ndt/gfw425
  contributor:
    fullname: Pottel
– volume: 68
  start-page: 892
  year: 2016
  ident: B14
  article-title: Non-GFR determinants of low-molecular-weight serum protein filtration markers in CKD
  publication-title: Am J Kidney Dis.
  doi: 10.1053/j.ajkd.2016.07.021
  contributor:
    fullname: Liu
– volume: 34
  start-page: 2353
  year: 2011
  ident: B23
  article-title: Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation pronouncedly underestimates glomerular filtration rate in type 2 diabetes
  publication-title: Diabetes Care.
  doi: 10.2337/dc11-1282
  contributor:
    fullname: Silveiro
– volume: 52
  start-page: 815
  year: 2014
  ident: B10
  article-title: The revised Lund-Malmo GFR estimating equation outperforms MDRD and CKD-EPI across GFR, age and BMI intervals in a large Swedish population
  publication-title: Clin Chem Lab Med.
  doi: 10.1515/cclm-2013-0741
  contributor:
    fullname: Nyman
– volume: 5
  start-page: 303
  year: 1989
  ident: B19
  article-title: A formula to estimate the approximate surface area if height and weight be known
  publication-title: Nutrition.
  contributor:
    fullname: Du Bois
– volume: 18
  start-page: 226
  year: 2017
  ident: B34
  article-title: CKD-EPI creatinine-cystatin C glomerular filtration rate estimation equation seems more suitable for Chinese patients with chronic kidney disease than other equations
  publication-title: BMC Nephrol.
  doi: 10.1186/s12882-017-0637-z
  contributor:
    fullname: Chi
– volume: 130
  start-page: 461
  year: 1999
  ident: B5
  article-title: A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group
  publication-title: Ann Intern Med.
  doi: 10.7326/0003-4819-130-6-199903160-00002
  contributor:
    fullname: Levey
– volume: 28
  start-page: 346
  year: 2005
  ident: B28
  article-title: Thyroid function differently affects serum cystatin C and creatinine concentrations
  publication-title: J Endocr Investig.
  doi: 10.1007/BF03347201
  contributor:
    fullname: Manetti
– volume: 27
  start-page: 467
  year: 2014
  ident: B32
  article-title: Calibration and precision of serum creatinine and plasma cystatin C measurement: impact on the estimation of glomerular filtration rate
  publication-title: J Nephrol.
  doi: 10.1007/s40620-014-0087-7
  contributor:
    fullname: Delanaye
– volume: 60
  start-page: 974
  year: 2014
  ident: B11
  article-title: Generation of a new cystatin C-based estimating equation for glomerular filtration rate by use of 7 assays standardized to the international calibrator
  publication-title: Clin Chem.
  doi: 10.1373/clinchem.2013.220707
  contributor:
    fullname: Grubb
– year: 2018
  ident: B40
  article-title: Glomerular filtration rate: when to measure and in which patients?
  publication-title: Nephrol Dial Transpl
  doi: 10.1093/ndt/gfy363
  contributor:
    fullname: Agarwal
– volume: 65
  start-page: 1416
  year: 2004
  ident: B30
  article-title: Factors influencing serum cystatin C levels other than renal function and the impact on renal function measurement
  publication-title: Kidney Int.
  doi: 10.1111/j.1523-1755.2004.00517.x
  contributor:
    fullname: Knight
– volume: 63
  start-page: 833
  year: 2017
  ident: B33
  article-title: Multicenter evaluation of cystatin c measurement after assay standardization
  publication-title: Clin Chem.
  doi: 10.1373/clinchem.2016.264325
  contributor:
    fullname: Bargnoux
– volume: 16
  start-page: 198
  year: 2015
  ident: B38
  article-title: The Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) equation does not improve the underestimation of Glomerular Filtration Rate (GFR) in people with diabetes and preserved renal function
  publication-title: BMC Nephrol.
  doi: 10.1186/s12882-015-0196-0
  contributor:
    fullname: MacIsaac
– volume: 367
  start-page: 20
  year: 2012
  ident: B8
  article-title: Estimating glomerular filtration rate from serum creatinine and cystatin C
  publication-title: N Eng J Med.
  doi: 10.1056/NEJMoa1114248
  contributor:
    fullname: Inker
– volume: 41
  start-page: 299
  year: 2008
  ident: B6
  article-title: Beta-trace protein is not superior to cystatin C for the estimation of GFR in patients receiving corticosteroids
  publication-title: Clin Biochem.
  doi: 10.1016/j.clinbiochem.2007.11.012
  contributor:
    fullname: Abbink
– volume: 9
  start-page: 682
  year: 2016
  ident: B17
  article-title: Iohexol plasma clearance for measuring glomerular filtration rate in clinical practice and research: a review. Part 1: how to measure glomerular filtration rate with iohexol?
  publication-title: Clin Kidney J.
  doi: 10.1093/ckj/sfw070
  contributor:
    fullname: Delanaye
– volume: 375
  start-page: 905
  year: 2016
  ident: B2
  article-title: Trends in chronic kidney disease in China
  publication-title: N Eng J Med.
  doi: 10.1056/NEJMc1602469
  contributor:
    fullname: Zhang
– volume: 317
  start-page: 2515
  year: 2017
  ident: B1
  article-title: Prevalence and ethnic pattern of diabetes and prediabetes in China in 2013
  publication-title: JAMA.
  doi: 10.1001/jama.2017.7596
  contributor:
    fullname: Wang
– volume: 41
  start-page: 40
  year: 2016
  ident: B36
  article-title: Comparison of the estimated Glomerular Filtration Rate (eGFR) in diabetic patients, non-diabetic patients and living kidney donors
  publication-title: Kidney Blood Pressure Res.
  doi: 10.1159/000368545
  contributor:
    fullname: Tsuda
– volume: 51
  start-page: 139
  year: 2019
  ident: B35
  article-title: A comparison between 2017 FAS and 2012 CKD-EPI equations: a multi-center validation study in Chinese adult population
  publication-title: Int Urol Nephrol.
  doi: 10.1007/s11255-018-1997-4
  contributor:
    fullname: Yong
– volume: 60
  start-page: 850
  year: 2012
  ident: B15
  article-title: KDOQI clinical practice guideline for diabetes and CKD: 2012 Update
  publication-title: Am J Kidney Dis.
  doi: 10.1053/j.ajkd.2012.07.005
– volume: 31
  start-page: 798
  year: 2016
  ident: B12
  article-title: An estimated glomerular filtration rate equation for the full age spectrum
  publication-title: Nephrol Dial Transpl.
  doi: 10.1093/ndt/gfv454
  contributor:
    fullname: Pottel
– volume: 46
  start-page: 1423
  year: 2013
  ident: B26
  article-title: Comparison between IDMS-traceable Jaffe and enzymatic creatinine assays for estimation of glomerular filtration rate by the CKD-EPI equation in healthy and diabetic subjects
  publication-title: Clin Biochem.
  doi: 10.1016/j.clinbiochem.2013.05.067
  contributor:
    fullname: Cheuiche
– volume: 75
  start-page: 652
  year: 2009
  ident: B27
  article-title: Factors other than glomerular filtration rate affect serum cystatin C levels
  publication-title: Kidney Int.
  doi: 10.1038/ki.2008.638
  contributor:
    fullname: Stevens
– volume: 150
  start-page: 604
  year: 2009
  ident: B7
  article-title: A new equation to estimate glomerular filtration rate
  publication-title: Ann Intern Med.
  doi: 10.7326/0003-4819-150-9-200905050-00006
  contributor:
    fullname: Levey
– volume: 86
  start-page: 465
  year: 2009
  ident: B29
  article-title: Use of the MDRD study equation to estimate kidney function for drug dosing
  publication-title: Clin Pharmacol Ther.
  doi: 10.1038/clpt.2009.124
  contributor:
    fullname: Stevens
– volume: 54
  start-page: 1304
  year: 2011
  ident: B22
  article-title: The four-variable modification of diet in renal disease formula underestimates glomerular filtration rate in obese type 2 diabetic individuals with chronic kidney disease
  publication-title: Diabetologia.
  doi: 10.1007/s00125-011-2085-9
  contributor:
    fullname: Nair
– volume: 53
  start-page: 993
  year: 2009
  ident: B31
  article-title: Differential estimation of CKD using creatinine- versus cystatin C-based estimating equations by category of body mass index
  publication-title: Am J Kidney Dis.
  doi: 10.1053/j.ajkd.2008.12.043
  contributor:
    fullname: Vupputuri
– volume: 375
  start-page: 2073
  year: 2010
  ident: B3
  article-title: Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis
  publication-title: Lancet.
  doi: 10.1016/S0140-6736(10)60674-5
  contributor:
    fullname: Matsushita
– volume: 79
  start-page: 1341
  year: 2011
  ident: B4
  article-title: Lower estimated glomerular filtration rate and higher albuminuria are associated with all-cause and cardiovascular mortality. A collaborative meta-analysis of high-risk population cohorts
  publication-title: Kidney Int.
  doi: 10.1038/ki.2010.536
  contributor:
    fullname: van der Velde
– volume: 21
  start-page: 797
  year: 2008
  ident: B20
  article-title: Evaluating the performance of equations for estimating glomerular filtration rate
  publication-title: J Nephrol.
  contributor:
    fullname: Stevens
– volume: 53
  start-page: 766
  year: 2007
  ident: B25
  article-title: Expressing the modification of diet in renal disease study equation for estimating glomerular filtration rate with standardized serum creatinine values
  publication-title: Clin Chem.
  doi: 10.1373/clinchem.2006.077180
  contributor:
    fullname: Levey
– volume: 34
  start-page: 287
  year: 2019
  ident: B39
  article-title: Chronic kidney disease staging with cystatin C or creatinine-based formulas: flipping the coin
  publication-title: Nephrology Dial Transpl.
  doi: 10.1093/ndt/gfy086
  contributor:
    fullname: Luis-Lima
– volume: 37
  start-page: 596
  year: 2014
  ident: B37
  article-title: Poor glycemic control is a major factor in the overestimation of glomerular filtration rate in diabetic patients
  publication-title: Diabetes Care.
  doi: 10.2337/dc13-1899
  contributor:
    fullname: Tsuda
– volume: 3
  start-page: 19
  year: 2013
  ident: B9
  article-title: Chapter 1: definition and classification of CKD
  publication-title: Kidney Int Suppl.
  doi: 10.1038/kisup.2012.64
– volume: 12
  start-page: 2032
  year: 2017
  ident: B16
  article-title: Diabetic kidney disease: challenges, progress, and possibilities
  publication-title: Clin J Am Soc Nephrol.
  doi: 10.2215/CJN.11491116
  contributor:
    fullname: Alicic
– volume: 39
  start-page: S1
  year: 2002
  ident: B21
  article-title: K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification
  publication-title: Am J Kidney Dis.
  contributor:
    fullname: Foundation
– volume: 30
  start-page: 271
  year: 1972
  ident: B18
  article-title: A simple method for the determination of glomerular filtration rate
  publication-title: Scand J Clin Lab Investig.
  doi: 10.3109/00365517209084290
  contributor:
    fullname: Brochner-Mortensen
SSID ssj0000401998
Score 2.3184466
Snippet It remains controversial to choose the optimal equation to estimate glomerular filtration rate (GFR) in chronic kidney disease (CKD) patients with diabetes....
Aims: It remains controversial to choose the optimal equation to estimate glomerular filtration rate (GFR) in chronic kidney disease (CKD) patients with...
Aims: It remains controversial to choose the optimal equation to estimate glomerular filtration rate (GFR) in chronic kidney disease (CKD) patients with...
SourceID doaj
pubmedcentral
proquest
crossref
pubmed
SourceType Open Website
Open Access Repository
Aggregation Database
Index Database
StartPage 581
SubjectTerms chronic kidney disease (CKD)
CKD-EPI
diabetes
diabetic kidney disease
Endocrinology
glomerular filtration rate
SummonAdditionalLinks – databaseName: Open Access: DOAJ - Directory of Open Access Journals
  dbid: DOA
  link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1LT9wwELYqDogLoi2PUIqM1AuHiNiJ7eTIa4uodlUhaBEXy0_tXrLtPg78e2biXbSLkHrpLU4ixfomGX-TGX9DyDfha2Ok5LnB7b9VYDG3XEHgWigPzhC8g8fdyP2BvHmobh_F40qrL6wJS_LACbizshLKyADrGm8q6woTYNwwa7F3q_eu875FsxJMdT4YwgYIJFJeEqKw5iyG1uNmP4b6lKJma-tQJ9f_Hsd8Wyq5svb0dsj2gjTS8zTZj-RDaD-Rzf4iLf6ZPJ3TX8CnU3skiqWBzxQOwvfeHb3-m8S8p3TUUuyWHaaB_kxqqlP6ezQb0lQVM3J0PKGDcZv75fjyx9Uueehd31_e5IumCbmrJJ_lBgiDsTYq602IvOEqePBnwkZjRCOBbnHHnKulYSFGWzZIkIBGVQyV0gQr98hGO27DAaElE3UtY-GM4ZWtnC2i4rU1RkFI7YTKyOkSQv0naWNoiCkQbt3BrRFu3cGdkQvE-PU-VLXuToCt9cLW-l-2zsjJ0kIavgJMbZg2jOdTzTk4S-zyXmdkP1ns9VElcl5gtRlRa7Zcm8v6lXY07JS2pUICVB7-j8l_IVsIB_6P5vKIbMwm8_AVCM3MHnfv7guvzvNK
  priority: 102
  providerName: Directory of Open Access Journals
Title A Validation Study on eGFR Equations in Chinese Patients With Diabetic or Non-diabetic CKD
URI https://www.ncbi.nlm.nih.gov/pubmed/31507533
https://search.proquest.com/docview/2288723948
https://pubmed.ncbi.nlm.nih.gov/PMC6718123
https://doaj.org/article/3457a6e509294bc0ae57a91bb3754ddc
Volume 10
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Lb9QwELbaHhAXxJvwqIzEhUO6Gye2k2NZuq1AW1WIwoqL5WcbiTpld3vg3zPjJFUXceISxXko1owz_sae-YaQd9zVWgvBco3pv5UvQm6YBMd1Kh0YQ7AODrORF6fi5Lz6tOTLHcLHXJgUtG9NexB_Xh3E9jLFVl5f2ckYJzY5W8yExHmpnOySXRigd1z0ZH7BYwAfot-SBAesmQQfHeb5FUhNyWssDlMiDuJluTUbJdL-fyHNvwMm78xA84fkwQAd6WHfxUdkx8fH5N5i2Bx_Qn4c0m-AqvsiSRQDBH9TOPHH8y_06FdP6b2mbaRYM9uvPT3rOVXX9Hu7uaR9bExrabeip13M3dieff74lJzPj77OTvKhdEJuK8E2uQbYoI0J0jjtA2uY9A6sGjdBa94IAF3MFtbWQhc-BFM2CJMATFUF8qXxonxG9mIX_QtCQVR1LcLUas0qU1kzDZLVRmsJjrXlMiPvRxGq654hQ4FngZJXSfIKJa-S5DPyAWV8-xxyW6cL3epCDRpWZcWlFh6QDGsqY6faQ7spjMFqvc7ZjLwdNaTgX8ANDh19d7NWjIHJxFrvdUae9xq7_dSo8YzILV1u9WX7Dgy_xLc9DLeX__3mK3IfZYBL0Uy8Jnub1Y1_A1hmY_bTGgAcj5fFfhrHfwCDC_WA
link.rule.ids 230,315,730,783,787,867,888,2109,27936,27937,53804,53806
linkProvider National Library of Medicine
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Lb9QwEB6VIgEX3o_wNBIXDtlNnDhOjmXpstDuqkJtqbhYtuPQCJqU3ewBfj0zeVTdigvckjhRHH_2-Jt4_A3AG5GnWicJ9zVt_41dWPiGS3RcA5mjMUTrkNNu5PkimR3Fn07EyRaIYS9MG7RvTTmqfpyNqvK0ja08P7PjIU5sfDCfJJLmpWh8Da7jeA3iS056a4DRZ0AvoluURBcsGxeuymmnX0jilCKl9DARMSERRRvzUSvb_zeueTVk8tIcNL0Dx0Ptu9CT76N1Y0b29xVhx3_-vLtwu2elbKcrvgdbrroPN-b9uvsD-LrDjpGwd_mXGMUe_mJ44D5MP7Pdn51a-IqVFaN03G7l2EEn17piX8rmlHVhN6Vl9ZIt6srPh_PJ3vuHcDTdPZzM_D4rg2_jhDe-RkaijSmkybUreMaly9FgClNoLbIE-Ry3obVpokNXFCbKiIEhT4tDkmITYfQItqu6ck-AIQZpmhSB1ZrHJrYmKCRPjdYSfXYrpAdvB2zUeSe-odBpIUhVC6kiSFULqQfvCLyL-0g2u71QL7-pvnVVFAupE4ckiWexsYF2eJ6FxlAi4Dy3HrweoFc4zGjtRFeuXq8U52iNKY186sHjritcvGroSh7IjU6yUZfNEoS-lfLuoX7630--gpuzw_m-2v-42HsGt6g96I83T57DdrNcuxdImRrzsh0gfwCjqhWb
linkToPdf http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Jb9QwFLagSBUX9iWsRuLCIZPESezkWKYdCmVGI0Sh6sXyFhq1TYaZzAF-Pe9lqWYqTr3FWZTYn_38vfj5e4S8T22mFOfMV7j9N3FR4WsmwHENhQVjCNbB4m7k6YwfHidfTtKTjVRfbdC-0eWourgcVeVZG1u5uDTBECcWzKdjLnBeioOFLYLb5A6M2ZBvOOqtEQa_ATyJbmES3LA8KFxlcbdfhAKVaYYpYmJkQ2kcb81JrXT___jm9bDJjXlocp-cDjXowk_OR-tGj8zfa-KON6riA3KvZ6d0r7vlIbnlqkdkd9qvvz8mp3v0BxD3Lg8TxRjEPxQO3KfJN3rwu1MNX9GyopiW260cnXeyrSv6s2zOaBd-UxpaL-msrnw7lMdH-0_I8eTg-_jQ77Mz-CbhrPEVMBOldSG0Va5gORPOguFMdaFUmnPgdcxExmRcRa4odJwjEwO-lkQoyZZG8VOyU9WVe04o4JBlvAiNUizRidFhIVimlRLgu5tUeOTDgI9cdCIcEpwXhFW2sEqEVbaweuQjAnh1H8pntyfq5S_Zt7CMk1Qo7oAssTzRJlQOynmkNSYEttZ45N0Av4ThhmsoqnL1eiUZA6uM6eQzjzzrusPVq4bu5BGx1VG2vmX7CsDfSnr3cL-48ZNvye58fyK_fp4dvSR3sTnwxzfjr8hOs1y718CcGv2mHSP_AFyiGBs
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+Validation+Study+on+eGFR+Equations+in+Chinese+Patients+With+Diabetic+or+Non-diabetic+CKD&rft.jtitle=Frontiers+in+endocrinology+%28Lausanne%29&rft.au=Xie%2C+Danshu&rft.au=Shi%2C+Hao&rft.au=Xie%2C+Jingyuan&rft.au=Ding%2C+Ying&rft.date=2019-08-26&rft.issn=1664-2392&rft.eissn=1664-2392&rft.volume=10&rft.spage=581&rft.epage=581&rft_id=info:doi/10.3389%2Ffendo.2019.00581&rft.externalDBID=NO_FULL_TEXT
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1664-2392&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1664-2392&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1664-2392&client=summon