{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T18:32:06Z","timestamp":1770834726629,"version":"3.50.1"},"reference-count":36,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,3,27]],"date-time":"2023-03-27T00:00:00Z","timestamp":1679875200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Medicines"],"abstract":"<jats:p>Background: Better understanding of the different phenotypes\/subgroups of non-U.S. citizen kidney transplant recipients may help the transplant community to identify strategies that improve outcomes among non-U.S. citizen kidney transplant recipients. This study aimed to cluster non-U.S. citizen kidney transplant recipients using an unsupervised machine learning approach; Methods: We conducted a consensus cluster analysis based on recipient-, donor-, and transplant- related characteristics in non-U.S. citizen kidney transplant recipients in the United States from 2010 to 2019 in the OPTN\/UNOS database using recipient, donor, and transplant-related characteristics. Each cluster\u2019s key characteristics were identified using the standardized mean difference. Post-transplant outcomes were compared among the clusters; Results: Consensus cluster analysis was performed in 11,300 non-U.S. citizen kidney transplant recipients and identified two distinct clusters best representing clinical characteristics. Cluster 1 patients were notable for young age, preemptive kidney transplant or dialysis duration of less than 1 year, working income, private insurance, non-hypertensive donors, and Hispanic living donors with a low number of HLA mismatch. In contrast, cluster 2 patients were characterized by non-ECD deceased donors with KDPI &lt;85%. Consequently, cluster 1 patients had reduced cold ischemia time, lower proportion of machine-perfused kidneys, and lower incidence of delayed graft function after kidney transplant. Cluster 2 had higher 5-year death-censored graft failure (5.2% vs. 9.8%; p &lt; 0.001), patient death (3.4% vs. 11.4%; p &lt; 0.001), but similar one-year acute rejection (4.7% vs. 4.9%; p = 0.63), compared to cluster 1; Conclusions: Machine learning clustering approach successfully identified two clusters among non-U.S. citizen kidney transplant recipients with distinct phenotypes that were associated with different outcomes, including allograft loss and patient survival. These findings underscore the need for individualized care for non-U.S. citizen kidney transplant recipients.<\/jats:p>","DOI":"10.3390\/medicines10040025","type":"journal-article","created":{"date-parts":[[2023,3,28]],"date-time":"2023-03-28T01:41:34Z","timestamp":1679967694000},"page":"25","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Distinct Phenotypes of Non-Citizen Kidney Transplant Recipients in the United States by Machine Learning Consensus Clustering"],"prefix":"10.3390","volume":"10","author":[{"given":"Charat","family":"Thongprayoon","sequence":"first","affiliation":[{"name":"Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pradeep","family":"Vaitla","sequence":"additional","affiliation":[{"name":"Division of Nephrology, University of Mississippi Medical Center, Jackson, MS 39216, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7860-9519","authenticated-orcid":false,"given":"Caroline C.","family":"Jadlowiec","sequence":"additional","affiliation":[{"name":"Division of Transplant Surgery, Mayo Clinic, Phoenix, AZ 85054, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Napat","family":"Leeaphorn","sequence":"additional","affiliation":[{"name":"Renal Transplant Program, University of Missouri-Kansas City School of Medicine\/Saint Luke\u2019s Health System, Kansas City, MO 64108, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shennen A.","family":"Mao","sequence":"additional","affiliation":[{"name":"Division of Transplant Surgery, Mayo Clinic, Jacksonville, FL 32224, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1814-7003","authenticated-orcid":false,"given":"Michael A.","family":"Mao","sequence":"additional","affiliation":[{"name":"Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Jacksonville, FL 32224, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1117-1350","authenticated-orcid":false,"given":"Fahad","family":"Qureshi","sequence":"additional","affiliation":[{"name":"School of Medicine, University of Missouri-Kansas City, Kansas City, MO 64108, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2920-7235","authenticated-orcid":false,"given":"Wisit","family":"Kaewput","sequence":"additional","affiliation":[{"name":"Department of Military and Community Medicine, Phramongkutklao College of Medicine, Bangkok 10400, Thailand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fawad","family":"Qureshi","sequence":"additional","affiliation":[{"name":"Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6103-2338","authenticated-orcid":false,"given":"Supawit","family":"Tangpanithandee","sequence":"additional","affiliation":[{"name":"Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2888-881X","authenticated-orcid":false,"given":"Pajaree","family":"Krisanapan","sequence":"additional","affiliation":[{"name":"Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA"},{"name":"Department of Military and Community Medicine, Phramongkutklao College of Medicine, Bangkok 10400, Thailand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6010-0033","authenticated-orcid":false,"given":"Pattharawin","family":"Pattharanitima","sequence":"additional","affiliation":[{"name":"Division of Nephrology, Department of Internal Medicine, Faculty of Medicine Thammasat University, Pathum Thani 12120, Thailand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Prakrati C.","family":"Acharya","sequence":"additional","affiliation":[{"name":"Division of Nephrology, Texas Tech Health Sciences Center El Paso, El Paso, TX 79905, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0245-2954","authenticated-orcid":false,"given":"Pitchaphon","family":"Nissaisorakarn","sequence":"additional","affiliation":[{"name":"Department of Medicine, Division of Nephrology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matthew","family":"Cooper","sequence":"additional","affiliation":[{"name":"Medstar Georgetown Transplant Institute, Georgetown University School of Medicine, Washington, DC 21042, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9954-9711","authenticated-orcid":false,"given":"Wisit","family":"Cheungpasitporn","sequence":"additional","affiliation":[{"name":"Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,27]]},"reference":[{"key":"ref_1","unstructured":"(2021, October 16). 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