Evidence map›Paper›PMID 39350474›Full record

ArticleAnnals of transplantation2024

Prediction of Renal Graft Function 1 Year After Adult Deceased-Donor Kidney Transplantation Using Variables Available Prior to Transplantation.

Ulrich Zwirner, Dennis Kleine-Döpke, Alexander Wagner, Simon Störzer, Felix Gronau, Oliver Beetz, Nicolas Richter, Wilfried Gwinner, Ulf Kulik, Moritz Schmelzle and 1 more

Abstract read
In one paragraph

Article in Annals of transplantation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Ulrich ZwirnerDepartment of General, Visceral and Transplant Surgery, Hannover Medical School, Hannover, Germany.ORCID 0000-0003-2247-7144
Dennis Kleine-DöpkeDepartment of General, Visceral and Transplant Surgery, Hannover Medical School, Hannover, Germany.ORCID 0000-0001-6515-3508
Alexander WagnerDepartment of General, Visceral and Transplant Surgery, Hannover Medical School, Hannover, Germany.
Simon StörzerDepartment of General, Visceral and Transplant Surgery, Hannover Medical School, Hannover, Germany.
Felix GronauDepartment of General, Visceral and Transplant Surgery, Hannover Medical School, Hannover, Germany.
Oliver BeetzDepartment of General, Visceral, Pediatric and Transplant Surgery, Aachen University Hospital, Aachen, Germany.
Nicolas RichterDepartment of General, Visceral and Transplant Surgery, Hannover Medical School, Hannover, Germany.ORCID 0009-0009-8063-0398
Wilfried GwinnerDepartment of Nephrology and Hypertension, Hannover Medical School, Hannover, Germany.ORCID 0000-0003-1703-893X
Ulf KulikDepartment of General, Visceral and Transplant Surgery, Hannover Medical School, Hannover, Germany.ORCID 0000-0002-7709-838X
Moritz SchmelzleDepartment of General, Visceral and Transplant Surgery, Hannover Medical School, Hannover, Germany.
Harald SchremDepartment of General and Visceral Surgery, Klinikum Chemnitz, Chemnitz, Germany.ORCID 0000-0002-5527-7555

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND Kidney transplantation is still the best therapy for patients with end-stage renal disease, but the demand for donor organs persistently surpasses the supply. A prognostic model using pre-transplant data for the prediction of renal graft function would be helpful to optimize organ allocation and avoid futile transplantations. MATERIAL AND METHODS Retrospective data of 2431 patients who underwent kidney transplantation between January 01, 2000, and December 31, 2012 with subsequent ten-year clinical follow-up in our transplant center were analyzed. Of these, 1172 patients met the inclusion criteria. Multivariable regression modelling was used to develop a prognostic model for the prediction of graft function after 1 year utilizing only pre-transplant data. The final model was assessed with the area under the receiver operating characteristic (AUROC) curve. RESULTS Donor age, donor serum creatinine, recipient body mass index, re-transplantations beyond the second kidney transplantation, and cold ischemia time had an independent, significant influence on graded renal graft function 1 year after kidney transplantation. AUROC analysis of the prognostic model was >0.700 for all GFR categories except KDIGO G5, indicating high sensitivity and specificity of prediction. CONCLUSIONS For improvement of renal graft function, organs from older donors or donors with high serum creatinine should not be used in obese recipients and for re-transplantations beyond the second one. Cold ischemia time should be as short as possible.

Indexed as

Kidney TransplantationAdultCold IschemiaCreatinineFemaleGlomerular Filtration RateGraft SurvivalHumansKidney Failure, ChronicMaleMiddle AgedPrognosisRetrospective StudiesTissue DonorsCreatinine

Identifiers

PMID39350474
PMCPMC11453122

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.