Your browser doesn't support javascript.
loading
Characteristics of Kidney Transplant Recipients with Prolonged Pre-Transplant Dialysis Duration as Identified by Machine Learning Consensus Clustering: Pathway to Personalized Care.
Thongprayoon, Charat; Tangpanithandee, Supawit; Jadlowiec, Caroline C; Mao, Shennen A; Mao, Michael A; Vaitla, Pradeep; Acharya, Prakrati C; Leeaphorn, Napat; Kaewput, Wisit; Pattharanitima, Pattharawin; Suppadungsuk, Supawadee; Krisanapan, Pajaree; Nissaisorakarn, Pitchaphon; Cooper, Matthew; Craici, Iasmina M; Cheungpasitporn, Wisit.
Afiliación
  • Thongprayoon C; Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA.
  • Tangpanithandee S; Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA.
  • Jadlowiec CC; Chakri Naruebodindra Medical Institute, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Samut Prakan 10540, Thailand.
  • Mao SA; Division of Nephrology, University of Mississippi Medical Center, Jackson, MS 39216, USA.
  • Mao MA; Division of Transplant Surgery, Mayo Clinic, Phoenix, AZ 85054, USA.
  • Vaitla P; Division of Transplant Surgery, Mayo Clinic, Jacksonville, FL 32224, USA.
  • Acharya PC; Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Jacksonville, FL 32224, USA.
  • Leeaphorn N; Division of Nephrology, Texas Tech Health Sciences Center El Paso, El Paso, TX 79905, USA.
  • Kaewput W; Renal Transplant Program, University of Missouri-Kansas City School of Medicine/Saint Luke's Health System, Kansas City, MO 64108, USA.
  • Pattharanitima P; Department of Military and Community Medicine, Phramongkutklao College of Medicine, Bangkok 10400, Thailand.
  • Suppadungsuk S; Division of Nephrology, Department of Internal Medicine, Faculty of Medicine Thammasat University, Pathum Thani 12120, Thailand.
  • Krisanapan P; Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA.
  • Nissaisorakarn P; Chakri Naruebodindra Medical Institute, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Samut Prakan 10540, Thailand.
  • Cooper M; Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA.
  • Craici IM; Division of Nephrology, Department of Internal Medicine, Faculty of Medicine Thammasat University, Pathum Thani 12120, Thailand.
  • Cheungpasitporn W; Division of Nephrology, Department of Internal Medicine, Thammasat University Hospital, Pathum Thani 12120, Thailand.
J Pers Med ; 13(8)2023 Aug 19.
Article en En | MEDLINE | ID: mdl-37623523
Longer 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.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: J Pers Med Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: J Pers Med Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza