{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T10:08:11Z","timestamp":1781863691042,"version":"3.54.5"},"reference-count":17,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T00:00:00Z","timestamp":1769817600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T00:00:00Z","timestamp":1769817600000},"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":[[2026,2]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Peri\u2010operative blood transfusion is common during solid\u2010organ transplantation, yet the impact of ABO\u2010incompatible (ABOi) blood exposure on post\u2010transplant immunity and acute rejection (AR) remains uncertain.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We assembled a multicenter cohort of 468 adult kidney, liver and heart recipients (2018\u20132024). Detailed, time\u2010stamped transfusion records were linked to serial immune\u2010phenotyping (30\u2010plex cytokines, flow\u2010cytometric cell subsets) collected from pre\u2010operative baseline to 12 months. The causal effect of ABOi transfusion on biopsy\u2010proven AR was estimated with marginal structural models that incorporated daily inverse\u2010probability\u2010of\u2010treatment weighting and Fine\u2013Gray competing\u2010risk adjustment. We further developed static (XGBoost\u2010Cox) and dynamic attention\u2010LSTM models to predict 30\u2010, 90\u2010 and 365\u2010day AR; model interpretability employed SHAP values and integrated gradients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Fifty\u2010six recipients (12%) received \u2265 1 unit of ABOi blood. After adjustment for baseline characteristics, surgical bleeding, tacrolimus exposure and other time\u2010varying confounders, ABOi transfusion independently increased 1\u2010year AR risk (HR 1.65; 95% CI 1.12\u20132.44). A clear dose\u2010response was observed: transfusion of &gt; 3 incompatible red\u2010cell units doubled AR incidence. ABOi exposure produced an early IL\u20106 surge (80 pg mL\n                      <jats:sup>\u2212<\/jats:sup>\n                      <jats:sup>1<\/jats:sup>\n                      vs 60 pg mL\n                      <jats:sup>\u2212<\/jats:sup>\n                      <jats:sup>1<\/jats:sup>\n                      in controls,\n                      <jats:italic>p<\/jats:italic>\n                      &lt; 0.001) and sustained elevation of CD8\n                      <jats:sup>+<\/jats:sup>\n                      \/Treg ratios. Unsupervised clustering of 10 immune markers identified a hyper\u2010inflammatory phenotype (Cluster A) with a two\u2010fold higher AR hazard, strongly correlated with ABOi load. The dynamic model achieved AUROCs of 0.83, 0.79 and 0.75 for 30\u2010, 90\u2010 and 365\u2010day prediction, respectively, and provided patient\u2010level risk passports 24\u00a0h before clinical rejection.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Peri\u2010operative ABOi transfusion is a modifiable, dose\u2010dependent driver of AR across solid\u2010organ transplants. Early IL\u20106 release and cytotoxic T\u2010cell expansion constitute plausible biological mediators. Minimizing incompatible antigen load and leveraging dynamic risk analytics may improve graft surveillance and inform targeted immunomodulation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/ctr.70469","type":"journal-article","created":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T09:53:06Z","timestamp":1769853186000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Effects of ABO\u2010Incompatible Blood Transfusion on Immune Response and Rejection After Organ Transplantation"],"prefix":"10.1111","volume":"40","author":[{"given":"Peilu","family":"Hu","sequence":"first","affiliation":[{"name":"Department Of Blood Transfusion The First Affiliated Hospital of Soochow University  Suzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8177-5252","authenticated-orcid":false,"given":"Xiaohui","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department Of Blood Transfusion The First Affiliated Hospital of Soochow University  Suzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,1,31]]},"reference":[{"key":"e_1_2_13_2_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1600-6143.2010.03103.x"},{"key":"e_1_2_13_3_1","doi-asserted-by":"publisher","DOI":"10.5500\/wjt.v11.i9.388"},{"key":"e_1_2_13_4_1","doi-asserted-by":"publisher","DOI":"10.5500\/wjt.v10.i7.191"},{"key":"e_1_2_13_5_1","doi-asserted-by":"publisher","DOI":"10.1111\/ajt.16459"},{"key":"e_1_2_13_6_1","doi-asserted-by":"publisher","DOI":"10.1111\/ajt.17206"},{"key":"e_1_2_13_7_1","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2021.778359"},{"key":"e_1_2_13_8_1","doi-asserted-by":"publisher","DOI":"10.1111\/ajt.15290"},{"issue":"5","key":"e_1_2_13_9_1","first-page":"1120","article-title":"Machine Learning for Kidney Allograft Rejection: A Systematic Review","volume":"9","author":"Haas M.","journal-title":"Kidney International Reports"},{"issue":"4","key":"e_1_2_13_10_1","article-title":"Red Blood Cell Transfusion for People Undergoing Hip Fracture Surgery","volume":"2015","author":"Brunskill S. J.","year":"2015","journal-title":"Cochrane Database of Systematic Reviews (Online)"},{"issue":"18","key":"e_1_2_13_11_1","first-page":"4129","article-title":"Peri\u2010Transplant Transfusion and Graft Loss","volume":"10","author":"Karlin D. A.","year":"2021","journal-title":"Journal of Clinical Medicine"},{"key":"e_1_2_13_12_1","doi-asserted-by":"publisher","DOI":"10.1097\/TP.0000000000001452"},{"issue":"3","key":"e_1_2_13_13_1","first-page":"1112","article-title":"Leveraging Marginal Structural Models in Clinical Research","volume":"32","year":"2017","journal-title":"Nephrology Dialysis Transplantation"},{"issue":"5","key":"e_1_2_13_14_1","first-page":"1123","article-title":"Machine\u2010Learning Prediction of Acute Rejection in the Tacrolimus Era","volume":"106","author":"Dvirnik N.","year":"2022","journal-title":"Transplantation"},{"key":"e_1_2_13_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40472-021-00331-4"},{"issue":"7","key":"e_1_2_13_16_1","article-title":"RBC Characteristics and Kidney Transplant Outcomes","volume":"6","author":"Heidenhain C.","year":"2023","journal-title":"JAMA Network Open"},{"key":"e_1_2_13_17_1","article-title":"Promise of Machine Learning in Solid\u2010Organ Transplantation","volume":"9","author":"Khatri P.","year":"2022","journal-title":"Frontiers in Medicine"},{"issue":"8","key":"e_1_2_13_18_1","first-page":"1890","article-title":"Artificial\u2010Intelligence Model for Tacrolimus\u2010Era Rejection","volume":"106","author":"Afzal M.","year":"2022","journal-title":"Transplantation"}],"container-title":["Clinical Transplantation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/ctr.70469","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1111\/ctr.70469","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/ctr.70469","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T23:21:59Z","timestamp":1773012119000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/ctr.70469"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,31]]},"references-count":17,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,2]]}},"alternative-id":["10.1111\/ctr.70469"],"URL":"https:\/\/doi.org\/10.1111\/ctr.70469","archive":["Portico"],"relation":{},"ISSN":["0902-0063","1399-0012"],"issn-type":[{"value":"0902-0063","type":"print"},{"value":"1399-0012","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,31]]},"assertion":[{"value":"2025-05-28","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-01-16","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-01-31","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70469"}}