Machine perfusion distribution across clinical phenotypes in kidney transplantation: A national cohort study using unsupervised clustering

doi:10.5500/wjt.121821

Advanced Search

BPG is committed to discovery and dissemination of knowledge

Home / Archive / Volume 16, Issue 3

This Article

(8)

(0)

(130)

Peer-Review Report of This Article

CrossCheck and Google Search of This Article

Academic Rules and Norms of This Article

Citation of this article

Corresponding Author of This Article

Research Domain of This Article

Article-Type of This Article

Open-Access Policy of This Article

Times Cited Counts in Google of This Article

Journal Information of This Article

Publication Name

World Journal of Transplantation

ISSN

2220-3230

Publisher of This Article

Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Observational Study

Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.

World J Transplant. Sep 18, 2026; 16(3): 121821
Published online Sep 18, 2026. doi: 10.5500/wjt.121821

Table 8 Cross-Dataset cluster alignment metrics

Full cohort cluster	MP subgroup cluster	Pearson r	Mean absolute SMD difference
1	1	0.843	0.130
2	2	0.895	0.128
3	3	0.902	0.152
4	4	0.865	0.164
5	5	0.895	0.117
6	6	0.867	0.101

SMD: Standardized mean difference; MP: Machine perfusion.

Full Size Table

Citation: Castellanos De Brigard J, Rangganata E, Papalois VE. Machine perfusion distribution across clinical phenotypes in kidney transplantation: A national cohort study using unsupervised clustering. World J Transplant 2026; 16(3): 121821
URL: https://www.wjgnet.com/2220-3230/full/v16/i3/121821.htm
DOI: https://dx.doi.org/10.5500/wjt.121821

Castellanos De Brigard J, Rangganata E, Papalois VE. Machine perfusion distribution across clinical phenotypes in kidney transplantation: A national cohort study using unsupervised clustering. World J Transplant 2026; 16(3): 121821 [DOI: 10.5500/wjt.121821]

All content on this site: Copyright © 1993-2026 Baishideng Publishing Group Inc, its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply.