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

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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10455164/
https://www.ncbi.nlm.nih.gov/pubmed/37623523
http://dx.doi.org/10.3390/jpm13081273
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author 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
author_facet 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
author_sort Thongprayoon, Charat
collection PubMed
description 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.
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spelling pubmed-104551642023-08-26 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 J Pers Med Article 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. MDPI 2023-08-19 /pmc/articles/PMC10455164/ /pubmed/37623523 http://dx.doi.org/10.3390/jpm13081273 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
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
Characteristics of Kidney Transplant Recipients with Prolonged Pre-Transplant Dialysis Duration as Identified by Machine Learning Consensus Clustering: Pathway to Personalized Care
title Characteristics of Kidney Transplant Recipients with Prolonged Pre-Transplant Dialysis Duration as Identified by Machine Learning Consensus Clustering: Pathway to Personalized Care
title_full Characteristics of Kidney Transplant Recipients with Prolonged Pre-Transplant Dialysis Duration as Identified by Machine Learning Consensus Clustering: Pathway to Personalized Care
title_fullStr Characteristics of Kidney Transplant Recipients with Prolonged Pre-Transplant Dialysis Duration as Identified by Machine Learning Consensus Clustering: Pathway to Personalized Care
title_full_unstemmed Characteristics of Kidney Transplant Recipients with Prolonged Pre-Transplant Dialysis Duration as Identified by Machine Learning Consensus Clustering: Pathway to Personalized Care
title_short Characteristics of Kidney Transplant Recipients with Prolonged Pre-Transplant Dialysis Duration as Identified by Machine Learning Consensus Clustering: Pathway to Personalized Care
title_sort characteristics of kidney transplant recipients with prolonged pre-transplant dialysis duration as identified by machine learning consensus clustering: pathway to personalized care
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10455164/
https://www.ncbi.nlm.nih.gov/pubmed/37623523
http://dx.doi.org/10.3390/jpm13081273
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