Evidence map›Paper›PMID 34987737›Full record

ArticleInternational journal of organ transplantation medicine2021

Virtual Crossmatching in Kidney Transplantation, Shiraz Experience in Development of a Web-Based Program.

N Jamshidian Tehrani, B Geramizadeh, S A Malekhosseini, S Nikeghbalian, A Bahador, S Gholami, G A Raees Jalali, J Roozbeh, M H Anbardar, N Soleimani and 2 more

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In one paragraph

Article in International journal of organ transplantation medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 41% of its field
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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

12 authors at 2 institutions in 1 country.

N Jamshidian TehraniShiraz Transplant Center, Abu-Ali Sina Hospital, Shiraz University of Medical Sciences, Shiraz, Iran.
B GeramizadehShiraz Transplant Center, Abu-Ali Sina Hospital, Shiraz University of Medical Sciences, Shiraz, Iran.
S A MalekhosseiniShiraz Transplant Center, Abu-Ali Sina Hospital, Shiraz University of Medical Sciences, Shiraz, Iran.
S NikeghbalianShiraz Transplant Center, Abu-Ali Sina Hospital, Shiraz University of Medical Sciences, Shiraz, Iran.
A BahadorShiraz Transplant Center, Abu-Ali Sina Hospital, Shiraz University of Medical Sciences, Shiraz, Iran.
S GholamiShiraz Transplant Center, Abu-Ali Sina Hospital, Shiraz University of Medical Sciences, Shiraz, Iran.
G A Raees JalaliShiraz Transplant Center, Abu-Ali Sina Hospital, Shiraz University of Medical Sciences, Shiraz, Iran.
J RoozbehShiraz Transplant Center, Abu-Ali Sina Hospital, Shiraz University of Medical Sciences, Shiraz, Iran.
M H AnbardarShiraz Transplant Center, Abu-Ali Sina Hospital, Shiraz University of Medical Sciences, Shiraz, Iran.
N SoleimaniShiraz Transplant Center, Abu-Ali Sina Hospital, Shiraz University of Medical Sciences, Shiraz, Iran.
N RasaeiShiraz Transplant Center, Abu-Ali Sina Hospital, Shiraz University of Medical Sciences, Shiraz, Iran.
S MohammadzadehShiraz Transplant Center, Abu-Ali Sina Hospital, Shiraz University of Medical Sciences, Shiraz, Iran.
Shiraz University of Medical Sciences · IRSina Hospital · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundKidney transplantation can increase survival and quality of life in patients with end-stage renal disease. In any allocation system, the crossmatch test plays an essential role in donor-recipient compatibility.

objectiveIn this study, we aim to test the benefits of a web-based program that captures HLA antibody analyses and provides a report to allow fast and accurate virtual crossmatches.

methodsOne hundred potential recipients in the waiting list of renal transplants were selected. The included patients all had a complete HLA antibody profile. Also, 10 potential donors from previous kidney transplants (2020), with available HLA typing results for A, B, and DR locus, were also selected. A comparison was made between 100 recipients against ten potential donors, and virtual crossmatching (VXM) was performed by the web-based program and manually by an experienced immunologist.

resultsThe average time for a manual VXM was 30 minutes per patient, while the virtual cross web-based program took 5 minutes per patient. In 12% of the manual VXM cases, a secondary review of data improved final results. In two manual virtual crossmatches, the VXM results had errors in matching recipient antibodies with the donor HLA typing that could affect the final decision for transplantation.

conclusionIn conclusion, a web-based VXM program that assesses HLA data can accurately perform a VXM with fewer human errors. It is especially true for highly sensitized candidates.

Indexed as

HLAKidney transplantationVirtual crossmatch

Identifiers

PMID34987737
PMCPMC8717962
OpenAlexW4206874200

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.