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...
Saved in:
Published in | Frontiers in endocrinology (Lausanne) Vol. 10; p. 581 |
---|---|
Main Authors | , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
Frontiers Media S.A
26.08.2019
|
Subjects | |
Online Access | Get 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 |