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Article: Which creatinine-based estimated glomerular filtration rate equation best predicts all-cause mortality in Chinese subjects with type 2 diabetes?
Title | Which creatinine-based estimated glomerular filtration rate equation best predicts all-cause mortality in Chinese subjects with type 2 diabetes? |
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Authors | |
Keywords | Chinese eGFR equations Mortality Type 2 diabetes |
Issue Date | 2017 |
Publisher | Elsevier Ireland Ltd. The Journal's web site is located at http://www.elsevier.com/locate/diabres |
Citation | Diabetes Research and Clinical Practice, 2017, v. 126, p. 25-29 How to Cite? |
Abstract | AIM: In Chinese, ethnicity-based and/or diabetes specific modifications of the Modification of Diet in Renal Disease (MDRD) and the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations have been developed for determining estimated glomerular filtrate rate (eGFR). This study aimed to compare the performance of five different creatinine-based eGFR equations in predicting all-cause mortality among Chinese subjects with type 2 diabetes (T2DM). METHODS: A total of 6739 Chinese subjects with T2DM were included. Their eGFR was calculated using the MDRD, CKD-EPI, their respective modified equations for Chinese, and the diabetes specific CKD-EPI Chinese T2DM equations. Multiple Cox regression analysis was used to evaluate the associations of eGFR with all-cause mortality. C-statistics, net reclassification index (NRI) and integrated discrimination index (IDI) were applied to assess the discrimination and reclassification of each eGFR equation in predicting mortality outcome. RESULTS: Over a follow-up of 5.7years, the incidence of all-cause mortality was 12.9% (N=867). The CKD-EPI equation discriminated all-cause mortality better than the MDRD equation (C-statistics: 0.714 vs. 0.689, p<0.0001), and Chinese modification of their respective equations did not improve discrimination. Among the five eGFR equations evaluated, the CKD-EPI Chinese T2DM equation provided the best discrimination in predicting all-cause mortality among Chinese subjects with T2DM, and was the only equation providing a significantly positive NRI and IDI relative to the CKD-EPI equation. CONCLUSIONS: Among Chinese subjects with T2DM, our findings suggested that the CKD-EPI Chinese T2DM equation best predicted all-cause mortality, and relative to the CKD-EPI equation, conferred improved discrimination and reclassification. |
Persistent Identifier | http://hdl.handle.net/10722/240931 |
ISSN | 2023 Impact Factor: 6.1 2023 SCImago Journal Rankings: 1.340 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Lee, CHP | - |
dc.contributor.author | Shih, AZL | - |
dc.contributor.author | Woo, YC | - |
dc.contributor.author | Fong, CHY | - |
dc.contributor.author | Yuen, MMA | - |
dc.contributor.author | Chow, WS | - |
dc.contributor.author | Lam, KSL | - |
dc.date.accessioned | 2017-05-22T09:19:41Z | - |
dc.date.available | 2017-05-22T09:19:41Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Diabetes Research and Clinical Practice, 2017, v. 126, p. 25-29 | - |
dc.identifier.issn | 0168-8227 | - |
dc.identifier.uri | http://hdl.handle.net/10722/240931 | - |
dc.description.abstract | AIM: In Chinese, ethnicity-based and/or diabetes specific modifications of the Modification of Diet in Renal Disease (MDRD) and the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations have been developed for determining estimated glomerular filtrate rate (eGFR). This study aimed to compare the performance of five different creatinine-based eGFR equations in predicting all-cause mortality among Chinese subjects with type 2 diabetes (T2DM). METHODS: A total of 6739 Chinese subjects with T2DM were included. Their eGFR was calculated using the MDRD, CKD-EPI, their respective modified equations for Chinese, and the diabetes specific CKD-EPI Chinese T2DM equations. Multiple Cox regression analysis was used to evaluate the associations of eGFR with all-cause mortality. C-statistics, net reclassification index (NRI) and integrated discrimination index (IDI) were applied to assess the discrimination and reclassification of each eGFR equation in predicting mortality outcome. RESULTS: Over a follow-up of 5.7years, the incidence of all-cause mortality was 12.9% (N=867). The CKD-EPI equation discriminated all-cause mortality better than the MDRD equation (C-statistics: 0.714 vs. 0.689, p<0.0001), and Chinese modification of their respective equations did not improve discrimination. Among the five eGFR equations evaluated, the CKD-EPI Chinese T2DM equation provided the best discrimination in predicting all-cause mortality among Chinese subjects with T2DM, and was the only equation providing a significantly positive NRI and IDI relative to the CKD-EPI equation. CONCLUSIONS: Among Chinese subjects with T2DM, our findings suggested that the CKD-EPI Chinese T2DM equation best predicted all-cause mortality, and relative to the CKD-EPI equation, conferred improved discrimination and reclassification. | - |
dc.language | eng | - |
dc.publisher | Elsevier Ireland Ltd. The Journal's web site is located at http://www.elsevier.com/locate/diabres | - |
dc.relation.ispartof | Diabetes Research and Clinical Practice | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Chinese | - |
dc.subject | eGFR equations | - |
dc.subject | Mortality | - |
dc.subject | Type 2 diabetes | - |
dc.title | Which creatinine-based estimated glomerular filtration rate equation best predicts all-cause mortality in Chinese subjects with type 2 diabetes? | - |
dc.type | Article | - |
dc.identifier.email | Lee, CHP: pchlee@hku.hk | - |
dc.identifier.email | Shih, AZL: ashih@hku.hk | - |
dc.identifier.email | Woo, YC: wooyucho@hku.hk | - |
dc.identifier.email | Fong, CHY: kalofong@hku.hk | - |
dc.identifier.email | Yuen, MMA: mmayuen@hku.hk | - |
dc.identifier.email | Chow, WS: chowws01@hkucc.hku.hk | - |
dc.identifier.email | Lam, KSL: ksllam@hku.hk | - |
dc.identifier.authority | Lee, CHP=rp02043 | - |
dc.identifier.authority | Lam, KSL=rp00343 | - |
dc.description.nature | postprint | - |
dc.identifier.doi | 10.1016/j.diabres.2017.01.010 | - |
dc.identifier.scopus | eid_2-s2.0-85012088508 | - |
dc.identifier.hkuros | 272173 | - |
dc.identifier.volume | 126 | - |
dc.identifier.spage | 25 | - |
dc.identifier.epage | 29 | - |
dc.identifier.isi | WOS:000402467800004 | - |
dc.publisher.place | Ireland | - |
dc.identifier.issnl | 0168-8227 | - |