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Prediction model of compensation for contralateral kidney after living-donor donation

BACKGROUND: Compensation of contralateral kidney function after living-donor kidney donation is well known, and many predictive factors have been proposed. However, no prediction model has been proposed. This study was performed to establish a tool with which to estimate the degree of compensation o...

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Autores principales: Okumura, Kenji, Yamanaga, Shigeyoshi, Tanaka, Kosuke, Kinoshita, Kohei, Kaba, Akari, Fujii, Mika, Ogata, Masatomo, Hidaka, Yuji, Toyoda, Mariko, Uekihara, Soichi, Miyata, Akira, Inadome, Akito, Yokomizo, Hiroshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6660650/
https://www.ncbi.nlm.nih.gov/pubmed/31349815
http://dx.doi.org/10.1186/s12882-019-1464-1
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author Okumura, Kenji
Yamanaga, Shigeyoshi
Tanaka, Kosuke
Kinoshita, Kohei
Kaba, Akari
Fujii, Mika
Ogata, Masatomo
Hidaka, Yuji
Toyoda, Mariko
Uekihara, Soichi
Miyata, Akira
Inadome, Akito
Yokomizo, Hiroshi
author_facet Okumura, Kenji
Yamanaga, Shigeyoshi
Tanaka, Kosuke
Kinoshita, Kohei
Kaba, Akari
Fujii, Mika
Ogata, Masatomo
Hidaka, Yuji
Toyoda, Mariko
Uekihara, Soichi
Miyata, Akira
Inadome, Akito
Yokomizo, Hiroshi
author_sort Okumura, Kenji
collection PubMed
description BACKGROUND: Compensation of contralateral kidney function after living-donor kidney donation is well known, and many predictive factors have been proposed. However, no prediction model has been proposed. This study was performed to establish a tool with which to estimate the degree of compensation of the contralateral kidney after living-donor kidney donation. METHODS: We retrospectively analyzed 133 living donors for renal transplantation in our institution. We defined a favorable compensation as a post-donation estimated glomerular filtration rate (eGFR) at 1 year (calculated by the Chronic Kidney Disease Epidemiology Collaboration equation) of > 60% of the pre-donation eGFR. We analyzed the living donors’ clinical characteristics and outcomes. RESULTS: The median (range) donor age was 59 (24–79) years, median (range) body mass index was 22.9 (16.8–32.7) kg/m(2), and median (range) body surface area was 1.6 (1.3–2.0) m(2). All donors were Japanese, and 73% of the donors were biologically related. The median (range) donor pre-donation eGFR was 108.7 (82–144) ml/min/1.73 m(2), and the median (range) post-donation eGFR at 1 year was 86.9 (43–143) ml/min/1.73 m(2). Eighty-six percent of donors had compensatory hypertrophy. In the univariate analysis, age, female sex, history of hypertension, body surface area, and pre-donation eGFR were significantly associated with hypertrophy (p < 0.05). In the multivariate analysis, age, female sex, history of hypertension, and ratio of the remnant kidney volume to body weight were significantly associated with hypertrophy (p < 0.05). Based on these results, we created a compensation prediction score (CPS). The median (range) CPS was 8.7 (1.1–17.4). Receiver operating characteristic analysis showed strong diagnostic accuracy for predicting favorable compensation (area under the curve, 0.958; 95% confidence interval, 0.925–0.991, p < 0.001). The optimal cut-off value of the CPS was 5.0 (sensitivity, 92.0%; specificity, 89.5%). The CPS had a strong positive correlation with the post-donation eGFR (R = 0.797, p < 0.001). CONCLUSION: The CPS might be useful tool with which to predict a favorable compensation of the contralateral kidney and remnant kidney function. If the CPS is low, careful management and follow-up might be necessary. Further investigations are needed to validate these findings in larger populations.
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spelling pubmed-66606502019-08-01 Prediction model of compensation for contralateral kidney after living-donor donation Okumura, Kenji Yamanaga, Shigeyoshi Tanaka, Kosuke Kinoshita, Kohei Kaba, Akari Fujii, Mika Ogata, Masatomo Hidaka, Yuji Toyoda, Mariko Uekihara, Soichi Miyata, Akira Inadome, Akito Yokomizo, Hiroshi BMC Nephrol Research Article BACKGROUND: Compensation of contralateral kidney function after living-donor kidney donation is well known, and many predictive factors have been proposed. However, no prediction model has been proposed. This study was performed to establish a tool with which to estimate the degree of compensation of the contralateral kidney after living-donor kidney donation. METHODS: We retrospectively analyzed 133 living donors for renal transplantation in our institution. We defined a favorable compensation as a post-donation estimated glomerular filtration rate (eGFR) at 1 year (calculated by the Chronic Kidney Disease Epidemiology Collaboration equation) of > 60% of the pre-donation eGFR. We analyzed the living donors’ clinical characteristics and outcomes. RESULTS: The median (range) donor age was 59 (24–79) years, median (range) body mass index was 22.9 (16.8–32.7) kg/m(2), and median (range) body surface area was 1.6 (1.3–2.0) m(2). All donors were Japanese, and 73% of the donors were biologically related. The median (range) donor pre-donation eGFR was 108.7 (82–144) ml/min/1.73 m(2), and the median (range) post-donation eGFR at 1 year was 86.9 (43–143) ml/min/1.73 m(2). Eighty-six percent of donors had compensatory hypertrophy. In the univariate analysis, age, female sex, history of hypertension, body surface area, and pre-donation eGFR were significantly associated with hypertrophy (p < 0.05). In the multivariate analysis, age, female sex, history of hypertension, and ratio of the remnant kidney volume to body weight were significantly associated with hypertrophy (p < 0.05). Based on these results, we created a compensation prediction score (CPS). The median (range) CPS was 8.7 (1.1–17.4). Receiver operating characteristic analysis showed strong diagnostic accuracy for predicting favorable compensation (area under the curve, 0.958; 95% confidence interval, 0.925–0.991, p < 0.001). The optimal cut-off value of the CPS was 5.0 (sensitivity, 92.0%; specificity, 89.5%). The CPS had a strong positive correlation with the post-donation eGFR (R = 0.797, p < 0.001). CONCLUSION: The CPS might be useful tool with which to predict a favorable compensation of the contralateral kidney and remnant kidney function. If the CPS is low, careful management and follow-up might be necessary. Further investigations are needed to validate these findings in larger populations. BioMed Central 2019-07-26 /pmc/articles/PMC6660650/ /pubmed/31349815 http://dx.doi.org/10.1186/s12882-019-1464-1 Text en © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Okumura, Kenji
Yamanaga, Shigeyoshi
Tanaka, Kosuke
Kinoshita, Kohei
Kaba, Akari
Fujii, Mika
Ogata, Masatomo
Hidaka, Yuji
Toyoda, Mariko
Uekihara, Soichi
Miyata, Akira
Inadome, Akito
Yokomizo, Hiroshi
Prediction model of compensation for contralateral kidney after living-donor donation
title Prediction model of compensation for contralateral kidney after living-donor donation
title_full Prediction model of compensation for contralateral kidney after living-donor donation
title_fullStr Prediction model of compensation for contralateral kidney after living-donor donation
title_full_unstemmed Prediction model of compensation for contralateral kidney after living-donor donation
title_short Prediction model of compensation for contralateral kidney after living-donor donation
title_sort prediction model of compensation for contralateral kidney after living-donor donation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6660650/
https://www.ncbi.nlm.nih.gov/pubmed/31349815
http://dx.doi.org/10.1186/s12882-019-1464-1
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