Incidence, risk factors, and effect on allograft survival of glomerulonephritis post-transplantation in a United Kingdom population: cohort study
Author(s)
Type
Journal Article
Abstract
BACKGROUND: Post-transplant glomerulonephritis (PTGN) has been associated with inferior long-term allograft survival, and its incidence varies widely in the literature. METHODS: This is a cohort study of 7,623 patients transplanted between 2005 and 2016 at four major transplant UK centres. The diagnosis of glomerulonephritis (GN) in the allograft was extracted from histology reports aided by the use of text-mining software. The incidence of the four most common GN post-transplantation was calculated, and the risk factors for disease and allograft outcomes were analyzed. RESULTS: In total, 214 patients (2.8%) presented with PTGN. IgA nephropathy (IgAN), focal segmental glomerulosclerosis (FSGS), membranous nephropathy (MN), and membranoproliferative/mesangiocapillary GN (MPGN/MCGN) were the four most common forms of post-transplant GN. Living donation, HLA DR match, mixed race, and other ethnic minority groups were associated with an increased risk of developing a PTGN. Patients with PTGN showed a similar allograft survival to those without in the first 8 years of post-transplantation, but the results suggest that they do less well after that timepoint. IgAN was associated with the best allograft survival and FSGS with the worst allograft survival. CONCLUSIONS: PTGN has an important impact on long-term allograft survival. Significant challenges can be encountered when attempting to analyze large-scale data involving unstructured or complex data points, and the use of computational analysis can assist.
Date Issued
2022-07-17
Date Acceptance
2022-06-17
Citation
Frontiers in Nephrology, 2022, 2, pp.1-11
ISSN
2813-0626
Publisher
Frontiers Media
Start Page
1
End Page
11
Journal / Book Title
Frontiers in Nephrology
Volume
2
Copyright Statement
Copyright © 2022 Aguiar, Bourmpaki, Bunce, Coker, Delaney, de Jongh, Oliveira, Weir, Higgins, Spiridou, Hasan, Smith, Mulla, Glampson, Mercuri, Montero, Hernandez-Fuentes, Roufosse, Simmonds, Clatworthy, McLean, Ploeg, Davies, Várnai, Woods, Lord, Pruthi, Breen and Chowdhury. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/37675026
Subjects
end-stage renal disease
graft failure
kidney transplantation
machine learning
recurrent glomerulonephritis
Publication Status
Published
Coverage Spatial
Switzerland
Article Number
923813
Date Publish Online
2022-07-14