{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T11:59:46Z","timestamp":1776254386567,"version":"3.50.1"},"reference-count":33,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T00:00:00Z","timestamp":1768348800000},"content-version":"vor","delay-in-days":13,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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":[[2026,1]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Posttransplant opioid dependence has been linked to adverse outcomes in solid organ transplantation, but its impact on pancreas transplantation is underexplored.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This retrospective study analyzed 193 PTA\/PAK recipients from Asan Medical Center (AMC) (2010\u20132022) and externally validated results in 77 recipients from Pusan National University Yangsan Hospital (PNUYH) (2015\u20132022). Posttransplant opioid dependence was defined as \u2265 10 opioid prescriptions between 3 and 12 months posttransplant. Logistic regression and three ML algorithms (CatBoost, XGBoost, and LightGBM) were used to identify risk factors and predict 5\u2010year graft survival.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Posttransplant opioid dependence (OR 2.87,\n                      <jats:italic>p<\/jats:italic>\n                      = 0.005) independently predicted 5\u2010year graft failure, along with pre\u2010transplant retinopathy, bladder drainage, and lower BMI. ML models showed favorable internal AUROC (0.695\u20130.719) and moderate external AUROC (0.649\u20130.671). Opioid dependence consistently ranked among top predictive features across models.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Posttransplant opioid dependence is a significant predictor of graft failure after pancreas transplantation. Incorporating this variable into ML models may enhance risk stratification and candidate selection.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/ctr.70453","type":"journal-article","created":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T15:53:54Z","timestamp":1768406034000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Opioid Use as a Predictor of Pancreas Transplant Outcomes"],"prefix":"10.1111","volume":"40","author":[{"given":"Youngmin","family":"Ko","sequence":"first","affiliation":[{"name":"Division of Kidney and Pancreas Transplantation Department of Surgery Asan Medical Center University of Ulsan College of Medicine  Seoul Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eunbyeol","family":"Cho","sequence":"additional","affiliation":[{"name":"Graduate School of AI, KAIST: Korea Advanced Institute of Science and Technology  Daejeon Republic of 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