Literature DB >> 8525513

Histopathological concordance of paired renal allograft biopsy cores. Effect on the diagnosis and management of acute rejection.

J M Sorof1, R K Vartanian, J L Olson, S J Tomlanovich, F G Vincenti, W J Amend.   

Abstract

To assess the effect of sampling error on renal allograft biopsies, we determined the concordance of diagnoses between 2 biopsy samples from the same renal allograft and the frequency with which 1 biopsy sample would underdiagnose or lead to the undertreatment of acute rejection. Two core samples from the same allograft biopsy procedure were labeled as core A and core B and presented to both unblinded and blinded pathologists, and each pathologist independently assigned an acute and a chronic rejection grade. A set of clinical data with pertinent prebiopsy information was combined with either the core A or core B histopathological diagnosis and presented to 3 transplant nephrologists who made treatment recommendations for each combination. Two cores were obtained in 79 allograft biopsies. Core pairs differed by > or = 1 grade of acute rejection in 30% and 50% of cases for unblinded and blinded pathologist readings, respectively. Moderate or severe acute rejection would have been missed with a 1 core in 9.5% of cases, increasing to 25.6% if only biopsy pairs containing at least 1 reading of moderate or severe acute rejection are included. Therapy would have failed to be increased with a single core in 7.5% of cases, increasing to 10.5% if only pairs containing at least one recommendation of an increase in therapy are included. The use of 2 cores of renal allograft tissue provides better diagnostic information and thereby leads to appropriate increases in antirejection therapy without increasing the complication rate of the procedure.

Mesh:

Substances:

Year:  1995        PMID: 8525513

Source DB:  PubMed          Journal:  Transplantation        ISSN: 0041-1337            Impact factor:   4.939


  8 in total

1.  Characterization of renal allograft rejection by urinary proteomic analysis.

Authors:  William Clarke; Benjamin C Silverman; Zhen Zhang; Daniel W Chan; Andrew S Klein; Ernesto P Molmenti
Journal:  Ann Surg       Date:  2003-05       Impact factor: 12.969

2.  Discovery and validation of a molecular signature for the noninvasive diagnosis of human renal allograft fibrosis.

Authors:  Dany Anglicheau; Thangamani Muthukumar; Aurélie Hummel; Ruchuang Ding; Vijay K Sharma; Darshana Dadhania; Surya V Seshan; Joseph E Schwartz; Manikkam Suthanthiran
Journal:  Transplantation       Date:  2012-06-15       Impact factor: 4.939

Review 3.  MRI-detectable nanoparticles: the potential role in the diagnosis of and therapy for chronic kidney disease.

Authors:  Jennifer R Charlton; Scott C Beeman; Kevin M Bennett
Journal:  Adv Chronic Kidney Dis       Date:  2013-11       Impact factor: 3.620

4.  Quantitative (99m)Tc DTPA renal transplant scintigraphic parameters: assessment of interobserver agreement and correlation with graft pathologies.

Authors:  Sandeep K Gupta; Guy Lewis; Kerry M Rogers; John Attia; Kirk Rostron; Leanne O'Neill; Annah Skillen; Suresh Viswanathan
Journal:  Am J Nucl Med Mol Imaging       Date:  2014-04-25

5.  Urinary cell transcriptomics and acute rejection in human kidney allografts.

Authors:  Akanksha Verma; Thangamani Muthukumar; Hua Yang; Michelle Lubetzky; Michael F Cassidy; John R Lee; Darshana M Dadhania; Catherine Snopkowski; Divya Shankaranarayanan; Steven P Salvatore; Vijay K Sharma; Jenny Z Xiang; Iwijn De Vlaminck; Surya V Seshan; Franco B Mueller; Karsten Suhre; Olivier Elemento; Manikkam Suthanthiran
Journal:  JCI Insight       Date:  2020-02-27

6.  Identifying biomarkers as diagnostic tools in kidney transplantation.

Authors:  Valeria R Mas; Thomas F Mueller; Kellie J Archer; Daniel G Maluf
Journal:  Expert Rev Mol Diagn       Date:  2011-03       Impact factor: 5.225

Review 7.  Noninvasive diagnosis of acute rejection of renal allografts.

Authors:  Choli Hartono; Thangamani Muthukumar; Manikkam Suthanthiran
Journal:  Curr Opin Organ Transplant       Date:  2010-02       Impact factor: 2.640

8.  Can pre-implantation biopsies predict renal allograft function in pediatric renal transplant recipients?

Authors:  Jameela A Kari; Alison L Ma; Stephanie Dufek; Ismail Mohamed; Nizam Mamode; Neil J Sebire; Stephen D Marks
Journal:  Saudi Med J       Date:  2015-11       Impact factor: 1.484

  8 in total

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