Surgeon preimplantation macroscopic graft appraisal improves risk stratification of deceased kidney donors: a prospective study.


Journal

Minerva urology and nephrology
ISSN: 2724-6442
Titre abrégé: Minerva Urol Nephrol
Pays: Italy
ID NLM: 101777299

Informations de publication

Date de publication:
Oct 2022
Historique:
pubmed: 24 4 2021
medline: 23 9 2022
entrez: 23 4 2021
Statut: ppublish

Résumé

Preimplantation scores assist with correct kidney graft allocation, but macroscopic graft features have never been evaluated in this scenario. We designed a graft appraisal questionnaire, assessed its reproducibility by comparing the senior and junior surgeon responses and evaluated which features can predict transplant outcomes in 202 patients transplanted from 144 donors at a tertiary center. We created new prediction models in combination with validated preimplantation scores. The primary outcome was graft loss or eGFR<30 mL/min/1.73 m Interrater correlation was very good for adherent perinephric fat (kappa=0.91) and acceptable for cortical surface roughness (kappa=0.51) and cortical color (kappa=0.47). Adherent perirenal fat (Odds ratio=4.77; 95% CI: 2.10-10.85) and surface roughness (OR=2.11, 95% CI: 1.25-3.58) were independent predictors of the primary outcome, improving the kidney donor risk index efficacy model (AUC 0.71 vs. 0.82, P≤0.001), while cortical color and adherent fat improved the Irish risk model for delayed graft function (AUC 0.76 vs. 0.82, P=0.03). We created nomograms to visually assess the risk of both endpoints. Kidney graft macroscopic appraisal is reproducible between surgeons and can improve the accuracy of clinical preimplantational prediction scores.

Sections du résumé

BACKGROUND BACKGROUND
Preimplantation scores assist with correct kidney graft allocation, but macroscopic graft features have never been evaluated in this scenario.
METHODS METHODS
We designed a graft appraisal questionnaire, assessed its reproducibility by comparing the senior and junior surgeon responses and evaluated which features can predict transplant outcomes in 202 patients transplanted from 144 donors at a tertiary center. We created new prediction models in combination with validated preimplantation scores. The primary outcome was graft loss or eGFR<30 mL/min/1.73 m
RESULTS RESULTS
Interrater correlation was very good for adherent perinephric fat (kappa=0.91) and acceptable for cortical surface roughness (kappa=0.51) and cortical color (kappa=0.47). Adherent perirenal fat (Odds ratio=4.77; 95% CI: 2.10-10.85) and surface roughness (OR=2.11, 95% CI: 1.25-3.58) were independent predictors of the primary outcome, improving the kidney donor risk index efficacy model (AUC 0.71 vs. 0.82, P≤0.001), while cortical color and adherent fat improved the Irish risk model for delayed graft function (AUC 0.76 vs. 0.82, P=0.03). We created nomograms to visually assess the risk of both endpoints.
CONCLUSIONS CONCLUSIONS
Kidney graft macroscopic appraisal is reproducible between surgeons and can improve the accuracy of clinical preimplantational prediction scores.

Identifiants

pubmed: 33887895
pii: S2724-6051.21.04345-7
doi: 10.23736/S2724-6051.21.04345-7
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

615-624

Commentaires et corrections

Type : CommentIn

Auteurs

Enric Miret Alomar (E)

Department of Urology and Kidney Transplantation, Vall d'Hebrón Hospital, Autonomous University of Barcelona, Barcelona, Spain - enricmiret@gmail.com.

Francesc Moreso (F)

Department of Nephrology and Kidney Transplantation, Vall d'Hebrón Hospital, Autonomous University of Barcelona, Barcelona, Spain.

Nestor Toapanta (N)

Department of Nephrology and Kidney Transplantation, Vall d'Hebrón Hospital, Autonomous University of Barcelona, Barcelona, Spain.

David Lorente (D)

Department of Urology and Kidney Transplantation, Vall d'Hebrón Hospital, Autonomous University of Barcelona, Barcelona, Spain.

Marina Triquell (M)

Department of Urology and Kidney Transplantation, Vall d'Hebrón Hospital, Autonomous University of Barcelona, Barcelona, Spain.

Teresa Pont (T)

Transplant Coordination, Vall d'Hebrón Hospital, Autonomous University of Barcelona, Barcelona, Spain.

Santiago Pérez-Hoyos (S)

Unit of Statistics and Bioinformatics, Vall d'Hebrón Hospital, Autonomous University of Barcelona, Barcelona, Spain.

Daniel Serón (D)

Department of Nephrology and Kidney Transplantation, Vall d'Hebrón Hospital, Autonomous University of Barcelona, Barcelona, Spain.

Juan Morote (J)

Department of Urology and Kidney Transplantation, Vall d'Hebrón Hospital, Autonomous University of Barcelona, Barcelona, Spain.

Enrique Trilla (E)

Department of Urology and Kidney Transplantation, Vall d'Hebrón Hospital, Autonomous University of Barcelona, Barcelona, Spain.

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Classifications MeSH