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Introduction of the Grayscale Median for Ultrasound Tissue Characterization of the Transplanted Kidney

Ultrasound examination is advised for early post-kidney transplant assessment. Grayscale median (GSM) quantification is novel in the kidney transplant field, with no systematic assessment previously reported. In this prospective cohort study, we measured the post-operative GSM in a large cohort of a...

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Autores principales: Sotomayor, Camilo G., Benjamens, Stan, Dijkstra, Hildebrand, Yakar, Derya, Moers, Cyril, Bakker, Stephan J. L., Pol, Robert A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7996582/
https://www.ncbi.nlm.nih.gov/pubmed/33668900
http://dx.doi.org/10.3390/diagnostics11030390
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author Sotomayor, Camilo G.
Benjamens, Stan
Dijkstra, Hildebrand
Yakar, Derya
Moers, Cyril
Bakker, Stephan J. L.
Pol, Robert A.
author_facet Sotomayor, Camilo G.
Benjamens, Stan
Dijkstra, Hildebrand
Yakar, Derya
Moers, Cyril
Bakker, Stephan J. L.
Pol, Robert A.
author_sort Sotomayor, Camilo G.
collection PubMed
description Ultrasound examination is advised for early post-kidney transplant assessment. Grayscale median (GSM) quantification is novel in the kidney transplant field, with no systematic assessment previously reported. In this prospective cohort study, we measured the post-operative GSM in a large cohort of adult kidney transplant recipients (KTR) who consecutively underwent Doppler ultrasound directly after transplantation (within 24 h), compared it with GSM in nontransplanted patients, and investigated its association with baseline and follow-up characteristics. B-mode images were used to calculate the GSM in KTR and compared with GSM data in nontransplanted patients, as simulated from summary statistics of the literature using a Mersenne twister algorithm. The association of GSM with baseline and 1-year follow-up characteristics were studied by means of linear regression analyses. In 282 KTR (54 ± 15 years old, 60% male), the median (IQR) GSM was 55 (45–69), ranging from 22 to 124 (coefficient of variation = 7.4%), without differences by type of donation (p = 0.28). GSM in KTR was significantly higher than in nontransplanted patients (p < 0.001), and associated with systolic blood pressure, history of cardiovascular disease, and donor age (std. β = 0.12, −0.20, and 0.13, respectively; p < 0.05 for all). Higher early post-kidney transplant GSM was not associated with 1-year post-kidney transplant function parameters (e.g., measured and estimated glomerular filtration rate). The data provided in this study could be used as first step for further research on the application of early postoperative ultrasound in KTR.
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spelling pubmed-79965822021-03-27 Introduction of the Grayscale Median for Ultrasound Tissue Characterization of the Transplanted Kidney Sotomayor, Camilo G. Benjamens, Stan Dijkstra, Hildebrand Yakar, Derya Moers, Cyril Bakker, Stephan J. L. Pol, Robert A. Diagnostics (Basel) Article Ultrasound examination is advised for early post-kidney transplant assessment. Grayscale median (GSM) quantification is novel in the kidney transplant field, with no systematic assessment previously reported. In this prospective cohort study, we measured the post-operative GSM in a large cohort of adult kidney transplant recipients (KTR) who consecutively underwent Doppler ultrasound directly after transplantation (within 24 h), compared it with GSM in nontransplanted patients, and investigated its association with baseline and follow-up characteristics. B-mode images were used to calculate the GSM in KTR and compared with GSM data in nontransplanted patients, as simulated from summary statistics of the literature using a Mersenne twister algorithm. The association of GSM with baseline and 1-year follow-up characteristics were studied by means of linear regression analyses. In 282 KTR (54 ± 15 years old, 60% male), the median (IQR) GSM was 55 (45–69), ranging from 22 to 124 (coefficient of variation = 7.4%), without differences by type of donation (p = 0.28). GSM in KTR was significantly higher than in nontransplanted patients (p < 0.001), and associated with systolic blood pressure, history of cardiovascular disease, and donor age (std. β = 0.12, −0.20, and 0.13, respectively; p < 0.05 for all). Higher early post-kidney transplant GSM was not associated with 1-year post-kidney transplant function parameters (e.g., measured and estimated glomerular filtration rate). The data provided in this study could be used as first step for further research on the application of early postoperative ultrasound in KTR. MDPI 2021-02-25 /pmc/articles/PMC7996582/ /pubmed/33668900 http://dx.doi.org/10.3390/diagnostics11030390 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Sotomayor, Camilo G.
Benjamens, Stan
Dijkstra, Hildebrand
Yakar, Derya
Moers, Cyril
Bakker, Stephan J. L.
Pol, Robert A.
Introduction of the Grayscale Median for Ultrasound Tissue Characterization of the Transplanted Kidney
title Introduction of the Grayscale Median for Ultrasound Tissue Characterization of the Transplanted Kidney
title_full Introduction of the Grayscale Median for Ultrasound Tissue Characterization of the Transplanted Kidney
title_fullStr Introduction of the Grayscale Median for Ultrasound Tissue Characterization of the Transplanted Kidney
title_full_unstemmed Introduction of the Grayscale Median for Ultrasound Tissue Characterization of the Transplanted Kidney
title_short Introduction of the Grayscale Median for Ultrasound Tissue Characterization of the Transplanted Kidney
title_sort introduction of the grayscale median for ultrasound tissue characterization of the transplanted kidney
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7996582/
https://www.ncbi.nlm.nih.gov/pubmed/33668900
http://dx.doi.org/10.3390/diagnostics11030390
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