{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T14:24:33Z","timestamp":1782483873114,"version":"3.54.5"},"reference-count":27,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2025,12,26]],"date-time":"2025-12-26T00:00:00Z","timestamp":1766707200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,12,26]],"date-time":"2025-12-26T00:00:00Z","timestamp":1766707200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Internal Medicine Journal"],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The Kidney Failure Risk Equation (KFRE) is a validated tool for assessing the risk of progression to kidney failure requiring renal replacement therapy (RRT). A 2\u2010year KFRE risk threshold of \u226540% may support timely vascular access planning.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>To compare the utility of KFRE with traditional estimated glomerular filtration rate (eGFR) thresholds for guiding vascular access planning in an Australian cohort.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This single\u2010centre observational cohort study retrospectively reviewed 580 adult patients referred to a Kidney Disease Education Clinic (KDEC) between 2016 and 2021. Among these, 211 patients who underwent dialysis access formation were analysed. Patient trajectories, including eGFR and 2\u2010year KFRE scores at referral, access formation and dialysis initiation, were described alongside rates of emergency access.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Of 211 patients with access created, 204 commenced dialysis. A median 2\u2010year KFRE of 46% predicted dialysis within 12 months, supporting its use for access planning. Compared with eGFR &lt; 15 mL\/min\/1.73m\n                      <jats:sup>2<\/jats:sup>\n                      , KFRE thresholds (\u226540% or \u2265\u200950%) better identified those at risk. A 2\u2010year KFRE \u2265 50% offered the best balance of sensitivity (70%) and specificity (68%) for predicting dialysis within 12 months, whereas \u226540% was more accurate for forecasting dialysis at 24 months and guiding early education. Emergency access was required in 31.5% of haemodialysis patients with lower eGFR at referral (11 vs 15 mL\/min\/1.73 m\n                      <jats:sup>2<\/jats:sup>\n                      ), higher 2\u2010year KFRE (87% vs 62%) and more preceding hospitalisations (95.4% vs 38.5%) than others.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>KFRE\u2010based thresholds improve risk\u2010stratified access planning compared with eGFR alone. A KFRE \u2265 40% supports early referral for modality education and vascular access, tailored to patient and institutional needs.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/imj.70281","type":"journal-article","created":{"date-parts":[[2025,12,26]],"date-time":"2025-12-26T11:21:37Z","timestamp":1766748097000},"page":"364-372","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Evaluation of Kidney Failure Risk Equation score for vascular access planning in an Australian cohort"],"prefix":"10.1111","volume":"56","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-2257-826X","authenticated-orcid":false,"given":"Regina","family":"Hong","sequence":"first","affiliation":[{"name":"Department of Renal Medicine St George Hospital  Sydney New South Wales Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6390-9508","authenticated-orcid":false,"given":"Daniel","family":"Hirsch","sequence":"additional","affiliation":[{"name":"Department of Renal Medicine St George Hospital  Sydney New South Wales Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katherine","family":"Li","sequence":"additional","affiliation":[{"name":"Faculty of Medicine &amp; Health University of New South Wales  Sydney New South Wales Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saiyini","family":"Pirabhahar","sequence":"additional","affiliation":[{"name":"Department of Renal Medicine St George Hospital  Sydney New South Wales Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kylie","family":"Turner","sequence":"additional","affiliation":[{"name":"Department of Renal Medicine St George Hospital  Sydney New South Wales Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeffrey Tsun Kit","family":"Ha","sequence":"additional","affiliation":[{"name":"Faculty of Medicine &amp; Health University of New South Wales  Sydney New South Wales Australia"},{"name":"Department of Renal Medicine Wollongong Hospital  Wollongong New South Wales Australia"},{"name":"Renal &amp; Metabolic Division The George Institute for Global Health  Sydney New South Wales Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ivor","family":"Katz","sequence":"additional","affiliation":[{"name":"Department of Renal Medicine St George Hospital  Sydney New South Wales Australia"},{"name":"Faculty of Medicine &amp; Health University of New South Wales  Sydney New South Wales Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,12,26]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2011.451"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.1111\/nep.14160"},{"key":"e_1_2_7_4_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-69715-3"},{"key":"e_1_2_7_5_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12882-019-1643-0"},{"key":"e_1_2_7_6_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2015.18202"},{"key":"e_1_2_7_7_1","first-page":"58","article-title":"Machine learning and chronic kidney disease risk prediction","volume":"24","author":"Wainstein M","year":"2021","journal-title":"Afr J Nephrol"},{"key":"e_1_2_7_8_1","doi-asserted-by":"publisher","DOI":"10.1053\/j.ajkd.2008.07.048"},{"key":"e_1_2_7_9_1","doi-asserted-by":"publisher","DOI":"10.1053\/j.ajkd.2019.12.001"},{"key":"e_1_2_7_10_1","doi-asserted-by":"publisher","DOI":"10.1093\/ndt\/gfx067"},{"key":"e_1_2_7_11_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1000552"},{"key":"e_1_2_7_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.kint.2019.01.017"},{"key":"e_1_2_7_13_1","first-page":"S1","article-title":"KDOQI clinical practice guidelines for chronic kidney disease: evaluation, classification and stratification","volume":"39","author":"NKF","year":"2002","journal-title":"Am J Kidney Dis"},{"key":"e_1_2_7_14_1","doi-asserted-by":"publisher","DOI":"10.7326\/M20-0529"},{"key":"e_1_2_7_15_1","unstructured":"Sumida K. 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