Characteristics of Kidney Transplant Recipients with Prolonged Pre-Transplant Dialysis Duration as Identified by Machine Learning Consensus Clustering: Pathway to Personalized Care

dc.contributor.authorThongprayoon C.
dc.contributor.authorTangpanithandee S.
dc.contributor.authorJadlowiec C.C.
dc.contributor.authorMao S.A.
dc.contributor.authorMao M.A.
dc.contributor.authorVaitla P.
dc.contributor.authorAcharya P.C.
dc.contributor.authorLeeaphorn N.
dc.contributor.authorKaewput W.
dc.contributor.authorPattharanitima P.
dc.contributor.authorSuppadungsuk S.
dc.contributor.authorKrisanapan P.
dc.contributor.authorNissaisorakarn P.
dc.contributor.authorCooper M.
dc.contributor.authorCraici I.M.
dc.contributor.authorCheungpasitporn W.
dc.contributor.otherMahidol University
dc.date.accessioned2023-09-05T18:01:50Z
dc.date.available2023-09-05T18:01:50Z
dc.date.issued2023-08-01
dc.description.abstractLonger pre-transplant dialysis duration is known to be associated with worse post-transplant outcomes. Our study aimed to cluster kidney transplant recipients with prolonged dialysis duration before transplant using an unsupervised machine learning approach to better assess heterogeneity within this cohort. We performed consensus cluster analysis based on recipient-, donor-, and transplant-related characteristics in 5092 kidney transplant recipients who had been on dialysis ≥ 10 years prior to transplant in the OPTN/UNOS database from 2010 to 2019. We characterized each assigned cluster and compared the posttransplant outcomes. Overall, the majority of patients with ≥10 years of dialysis duration were black (52%) or Hispanic (25%), with only a small number (17.6%) being moderately sensitized. Within this cohort, three clinically distinct clusters were identified. Cluster 1 patients were younger, non-diabetic and non-sensitized, had a lower body mass index (BMI) and received a kidney transplant from younger donors. Cluster 2 recipients were older, unsensitized and had a higher BMI; they received kidney transplant from older donors. Cluster 3 recipients were more likely to be female with a higher PRA. Compared to cluster 1, cluster 2 had lower 5-year death-censored graft (HR 1.40; 95% CI 1.16–1.71) and patient survival (HR 2.98; 95% CI 2.43–3.68). Clusters 1 and 3 had comparable death-censored graft and patient survival. Unsupervised machine learning was used to characterize kidney transplant recipients with prolonged pre-transplant dialysis into three clinically distinct clusters with variable but good post-transplant outcomes. Despite a dialysis duration ≥ 10 years, excellent outcomes were observed in most recipients, including those with moderate sensitization. A disproportionate number of minority recipients were observed within this cohort, suggesting multifactorial delays in accessing kidney transplantation.
dc.identifier.citationJournal of Personalized Medicine Vol.13 No.8 (2023)
dc.identifier.doi10.3390/jpm13081273
dc.identifier.eissn20754426
dc.identifier.scopus2-s2.0-85169036338
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/123456789/89383
dc.rights.holderSCOPUS
dc.subjectMedicine
dc.titleCharacteristics of Kidney Transplant Recipients with Prolonged Pre-Transplant Dialysis Duration as Identified by Machine Learning Consensus Clustering: Pathway to Personalized Care
dc.typeArticle
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85169036338&origin=inward
oaire.citation.issue8
oaire.citation.titleJournal of Personalized Medicine
oaire.citation.volume13
oairecerif.author.affiliationThammasat University Hospital
oairecerif.author.affiliationMayo Clinic Scottsdale-Phoenix, Arizona
oairecerif.author.affiliationTexas Tech University Health Sciences Center El Paso
oairecerif.author.affiliationUMKC School of Medicine
oairecerif.author.affiliationFaculty of Medicine Ramathibodi Hospital, Mahidol University
oairecerif.author.affiliationFaculty of Medicine, Thammasat University
oairecerif.author.affiliationMedical College of Wisconsin
oairecerif.author.affiliationPhramongkutklao College of Medicine
oairecerif.author.affiliationMayo Clinic
oairecerif.author.affiliationUniversity of Mississippi Medical Center
oairecerif.author.affiliationHarvard Medical School
oairecerif.author.affiliationMayo Clinic in Jacksonville, Florida

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