{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T16:46:42Z","timestamp":1785775602339,"version":"3.56.0"},"reference-count":22,"publisher":"S. Karger AG","issue":"1","license":[{"start":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T00:00:00Z","timestamp":1780963200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T00:00:00Z","timestamp":1780963200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cardiorenal Med"],"abstract":"<jats:p>Introduction: The European Kidney Function Consortium (EKFC) has introduced equations for estimated glomerular filtration rate (eGFR) using serum creatinine (Cr) and cystatin C (Cys). While their diagnostic accuracy is established, their comparative prognostic value for long-term mortality in the general population is not well defined. This study compared the prognostic performance of three EKFC equations \u2013 creatinine-based (EKFC-eGFRcr), Cys-based (EKFC-eGFRcys), and the combined (EKFC-eGFRcrcys) model \u2013 for predicting all-cause and cardiovascular (CV) mortality. Methods: We analyzed a population-based cohort of 4,519 participants from the National Health and Nutrition Examination Survey (NHANES) 1999\u20132002. eGFR was calculated using all three EKFC variations (EKFC-eGFRcr, EKFC-eGFRcys, and EKFC-eGFRcrcys). The primary and secondary endpoints were all-cause and CV mortality, respectively, through December 31, 2019. Predictive improvements were evaluated using integrated discrimination improvement (IDI), net reclassification improvement (NRI), and number needed to measure (NNM). Results: The eGFR value calculated by the EKFC-eGFRcys, EKFC-eGFRcr, and EKFC-eGFRcrcys was 78.92 \u00b1 22.98, 84.45 \u00b1 23.21, and 81.68 \u00b1 22.13 mL\/min\/1.73 m2, respectively. Over a median follow-up of 211 months, all three eGFR models were independent predictors of mortality (all p &lt; 0.001). Restricted cubic spline regression revealed significant non-linear, inverse associations between all eGFR measures and adjusted mortality risks (all p for non-linearity &lt; 0.001). Compared to EKFC-eGFRcr, EKFC-eGFRcys significantly improved risk reclassification for all-cause mortality (categorical NRI = 15.9%; 95% CI: 14.1\u201317.8%; NNM = 7). The combined EKFC-eGFRcrcys also outperformed the Cr-only model (NRI = 8.9%; NNM = 12). However, EKFC-eGFRcys demonstrated modestly better performance than the combined equation (NRI = 7.0%; NNM = 15), suggesting limited incremental value in adding Cr to Cys. The superiority of EKFC-eGFRcys was primarily driven by improved classification of non-events. Conclusion: The EKFC-eGFRcys equation provides superior prognostic value for all-cause and CV mortality compared to both Cr-based and combined EKFC equations. Notably, the combined model offered no prognostic advantage over Cys alone. These findings highlight the clinical importance of Cys-based eGFR for accurate risk stratification in the general population.<\/jats:p>","DOI":"10.1159\/000552852","type":"journal-article","created":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T16:01:00Z","timestamp":1781020860000},"page":"393-408","source":"Crossref","is-referenced-by-count":0,"title":["Comparative Prognostic Assessment of European Kidney Function Consortium Equations for Mortality Prediction: A Population-Based Cohort Study"],"prefix":"10.1159","volume":"16","author":[{"given":"Sitong","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinjing","family":"Shi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Iokfai","family":"Cheang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gengmin","family":"Liang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiang","family":"Qu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziqi","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huaxin","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiyang","family":"Fu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengen","family":"Liao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7889-6359","authenticated-orcid":false,"given":"Xinli","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"127","published-online":{"date-parts":[[2026,6,9]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/s0140-6736(16)32064-5"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(10)60674-5"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/s2214-109x(23)00570-3"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.kint.2023.10.018"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1053\/j.ajkd.2020.09.015"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2023.17002"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1053\/j.ajkd.2015.09.014"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1056\/nejmoa1114248"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.7326\/0003-4819-150-9-200905050-00006"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1053\/j.ajkd.2021.08.003"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2020.34004"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1056\/nejmoa2102953"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.7326\/l21-0248"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1093\/eurjpc\/zwad148"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1056\/nejmoa2203769"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1159\/000542912"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1681\/asn.0000000000000227"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.j2099"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1111\/j.1523-1755.2004.00517.x"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.7326\/0003-4819-158-11-201306040-00007"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1093\/ndt\/gfad219"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.3390\/jcm11247264"}],"container-title":["Cardiorenal Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/karger.com\/article-pdf\/doi\/10.1159\/000552852","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T16:00:55Z","timestamp":1785772855000},"score":1,"resource":{"primary":{"URL":"https:\/\/karger.com\/article\/doi\/10.1159\/000552852"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,9]]},"references-count":22,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,1,1]]}},"URL":"https:\/\/doi.org\/10.1159\/000552852","archive":["Portico"],"relation":{"is-supplemented-by":[{"id-type":"doi","id":"10.6084\/m9.figshare.32603208","asserted-by":"subject"}]},"ISSN":["1664-3828","1664-5502"],"issn-type":[{"value":"1664-3828","type":"print"},{"value":"1664-5502","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,9]]}}}