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Clinical Phenotypes of Dual Kidney Transplant Recipients in the United States as Identified through Machine Learning Consensus Clustering.
Tangpanithandee, Supawit; Thongprayoon, Charat; Jadlowiec, Caroline C; Mao, Shennen A; Mao, Michael A; Vaitla, Pradeep; Leeaphorn, Napat; Kaewput, Wisit; Pattharanitima, Pattharawin; Krisanapan, Pajaree; Nissaisorakarn, Pitchaphon; Cooper, Matthew; Cheungpasitporn, Wisit.
Afiliación
  • Tangpanithandee S; Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA.
  • Thongprayoon C; Chakri Naruebodindra Medical Institute, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Samut Prakan 10540, Thailand.
  • Jadlowiec CC; Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA.
  • Mao SA; Division of Transplant Surgery, Mayo Clinic, Phoenix, AZ 85054, USA.
  • Mao MA; Division of Transplant Surgery, Mayo Clinic, Jacksonville, FL 32224, USA.
  • Vaitla P; Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Jacksonville, FL 32224, USA.
  • Leeaphorn N; Division of Nephrology, University of Mississippi Medical Center, Jackson, MS 39216, USA.
  • Kaewput W; Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Jacksonville, FL 32224, USA.
  • Pattharanitima P; Department of Military and Community Medicine, Phramongkutklao College of Medicine, Bangkok 10400, Thailand.
  • Krisanapan P; Division of Nephrology, Department of Internal Medicine, Thammasat University, Bangkok 12120, Thailand.
  • Nissaisorakarn P; Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA.
  • Cooper M; Division of Nephrology, Department of Internal Medicine, Thammasat University, Bangkok 12120, Thailand.
  • Cheungpasitporn W; Department of Medicine, Division of Nephrology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
Medicina (Kaunas) ; 58(12)2022 Dec 12.
Article en En | MEDLINE | ID: mdl-36557033
ABSTRACT
Background and

Objectives:

Our study aimed to cluster dual kidney transplant recipients using an unsupervised machine learning approach to characterize donors and recipients better and to compare the survival outcomes across these various clusters. Materials and

Methods:

We performed consensus cluster analysis based on recipient-, donor-, and transplant-related characteristics in 2821 dual kidney transplant recipients from 2010 to 2019 in the OPTN/UNOS database. We determined the important characteristics of each assigned cluster and compared the post-transplant outcomes between clusters.

Results:

Two clinically distinct clusters were identified by consensus cluster analysis. Cluster 1 patients was characterized by younger patients (mean recipient age 49 ± 13 years) who received dual kidney transplant from pediatric (mean donor age 3 ± 8 years) non-expanded criteria deceased donor (100% non-ECD). In contrast, Cluster 2 patients were characterized by older patients (mean recipient age 63 ± 9 years) who received dual kidney transplant from adult (mean donor age 59 ± 11 years) donor with high kidney donor profile index (KDPI) score (59% had KDPI ≥ 85). Cluster 1 had higher patient survival (98.0% vs. 94.6% at 1 year, and 92.1% vs. 76.3% at 5 years), and lower acute rejection (4.2% vs. 6.1% within 1 year), when compared to cluster 2. Death-censored graft survival was comparable between two groups (93.5% vs. 94.9% at 1 year, and 89.2% vs. 84.8% at 5 years).

Conclusions:

In summary, DKT in the United States remains uncommon. Two clusters, based on specific recipient and donor characteristics, were identified through an unsupervised machine learning approach. Despite varying differences in donor and recipient age between the two clusters, death-censored graft survival was excellent and comparable. Broader utilization of DKT from high KDPI kidneys and pediatric en bloc kidneys should be encouraged to better address the ongoing organ shortage.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Trasplante de Riñón Tipo de estudio: Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies País/Región como asunto: America do norte Idioma: En Revista: Medicina (Kaunas) Asunto de la revista: MEDICINA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Trasplante de Riñón Tipo de estudio: Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies País/Región como asunto: America do norte Idioma: En Revista: Medicina (Kaunas) Asunto de la revista: MEDICINA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos
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