{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,2]],"date-time":"2026-11-02T21:51:01Z","timestamp":1793656261723,"version":"4.5.1"},"reference-count":34,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T00:00:00Z","timestamp":1787270400000},"content-version":"vor","delay-in-days":20,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"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":["Clinical Transplantation"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>With increasing use of donation after circulatory death (DCD) donor grafts, the need for accurate risk\u2010stratification tools in liver transplantation has become critical. Machine perfusion has been shown to improve both graft and patient survival. However, existing prediction models were developed in the static cold storage (SCS) era and their accuracy when using machine perfusion remains unknown. Our study aims to study if current scoring systems can predict graft and patient survival for DCD livers preserved using normothermic machine perfusion (NMP).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      This was a retrospective study of patient and graft survival in a two\u2010center U.S. DCD NMP cohort (\n                      <jats:italic>n<\/jats:italic>\n                      = 532) between January 2022 and December 2024. Predicted graft and patient survival rates were obtained from established risk scoring systems, including the United Kingdom DCD risk score (UK\u2010DCD), Early Allograft Dysfunction (EAD) Olthoff score, Liver Graft Assessment Following Transplantation (L\u2010GrAFT\n                      <jats:sub>7<\/jats:sub>\n                      ) score, Donor Risk Index (DRI), Balance of Risk (BAR) score, and Survival Outcomes Following Liver Transplant (SOFT) score. Model discrimination was assessed using receiver operating characteristic (ROC) curves (C\u2010statistics). Survival outcomes across risk strata were estimated and compared using Kaplan\u2010Meier (KM) analysis.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Across scoring systems, predicted survival consistently underestimated actual graft and patient survival in the NMP DCD cohort. The DRI, SOFT, EAD and L\u2010GrAFT\n                      <jats:sub>7<\/jats:sub>\n                      did not demonstrate predictive value. UK\u2010DCD predicted \u226485% and &lt;40% 1\u2010year graft survival for its high\u2010risk and \u201cfutile\u201d groups, whereas observed rates were 93.7% and 86.8%. BAR low\u2010risk predicted &gt;60% 5\u2010year survival but 94.2% was observed; the high\u2010risk group predicted &lt;60% and observed was 53.3%. Despite underestimations and generally poor C\u2010statistics, in KM stratification, high\u2010risk groups still showed statistical differences in the UK\u2010DCD categories (\n                      <jats:italic>p<\/jats:italic>\n                      = 0.007), and in SOFT score groups (\n                      <jats:italic>p<\/jats:italic>\n                      &lt; 0.001). No statistical difference was seen in BAR (\n                      <jats:italic>p<\/jats:italic>\n                      = 0.36), DRI (\n                      <jats:italic>p<\/jats:italic>\n                      = 0.36), EAD (\n                      <jats:italic>p<\/jats:italic>\n                      = 0.12), or L\u2010GrAFT\n                      <jats:sub>7<\/jats:sub>\n                      (\n                      <jats:italic>p<\/jats:italic>\n                      = 0.75).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Existing liver transplant risk scores show limited predictive value for donor\u2010related risk factors in the NMP era, whereas recipient\u2010related factors remain somewhat predictive, despite overestimating risk. Early allograft dysfunction metrics were not reliable predictors of short or long\u2010term outcomes. Future risk models should integrate machine\u2010perfusion parameters and refined donor variables to reflect outcomes more accurately in contemporary DCD liver transplantation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/ctr.70645","type":"journal-article","created":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T09:59:33Z","timestamp":1787306373000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Re\u2010Evaluating Donor\u2013Recipient Risk Scores in the Machine Perfusion Era Using a Large Multicenter Cohort: Do Traditional Predictive Models Still Apply?"],"prefix":"10.1111","volume":"40","author":[{"given":"Mingyi","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Surgery Mayo Clinic Florida  Jacksonville Florida USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michelle","family":"Nguyen","sequence":"additional","affiliation":[{"name":"Department of Surgery Mayo Clinic Arizona  Phoenix Arizona USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shennen","family":"Mao","sequence":"additional","affiliation":[{"name":"Department of Transplant Mayo Clinic Florida  Jacksonville Florida USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryan","family":"Chadha","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology Mayo Clinic Florida  Jacksonville Florida USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"C. Burcin","family":"Taner","sequence":"additional","affiliation":[{"name":"Department of Transplant Mayo Clinic Florida  Jacksonville Florida USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amit K.","family":"Mathur","sequence":"additional","affiliation":[{"name":"Department of Surgery Mayo Clinic Arizona  Phoenix Arizona USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kristopher P.","family":"Croome","sequence":"additional","affiliation":[{"name":"Department of Transplant Mayo Clinic Florida  Jacksonville Florida 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