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Establishing a new formula for estimating renal depth in a Chinese adult population

We aimed to establish a new formula for estimating renal depth, based on anthropometric variables, and to compare the estimates with actual data from a group of living kidney donors undergoing computed tomography angiography (CTA). Renal depths in 167 living kidney donors were measured by CTA. Regre...

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Autores principales: Xue, Jianjun, Deng, Huixing, Jia, Xi, Wang, Yuanbo, Lu, Xueni, Ding, Xiaoming, Li, Qiang, Yang, Aimin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5293443/
https://www.ncbi.nlm.nih.gov/pubmed/28151880
http://dx.doi.org/10.1097/MD.0000000000005940
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author Xue, Jianjun
Deng, Huixing
Jia, Xi
Wang, Yuanbo
Lu, Xueni
Ding, Xiaoming
Li, Qiang
Yang, Aimin
author_facet Xue, Jianjun
Deng, Huixing
Jia, Xi
Wang, Yuanbo
Lu, Xueni
Ding, Xiaoming
Li, Qiang
Yang, Aimin
author_sort Xue, Jianjun
collection PubMed
description We aimed to establish a new formula for estimating renal depth, based on anthropometric variables, and to compare the estimates with actual data from a group of living kidney donors undergoing computed tomography angiography (CTA). Renal depths in 167 living kidney donors were measured by CTA. Regression analysis was used to derive the formulae for estimation of renal depth of both kidneys based on patient age, sex, body height, body weight, and body mass index (BMI). The results of the renal depth estimation from the derived formulae were compared with those using existing formulae. Using regression analysis, we derived 2 new formulae as follows; for left kidney, renal depth (cm) = 0.083 × W − 0.058 × H + 11.541 (male) or 10.89 (female), for right kidney, renal depth (cm) = 13.498 × W/H + 2.141 (male) or 1.816 (female), in which W represents the weight (kg) and H represents the height (cm). The correlation coefficients between our left or right renal depth estimates and those obtained from other formulae in another 271 kidney donors were 0.864 (left) or 0.893 (right) by the Tønnesen, 0.937 (left) or 0.97 (right) by the Taylor, 0.937 (left) or 0.97 (right) by the Itoh, 0.927 (left) or 0.951 (right) by the Li-qian, and 0.937 (left) or 0.97 (right) by the Inoue formula. Our formula may be more precise than the Tønnesen formula in estimating the renal depth. Estimating formulae based on CT findings might be useful in clinical practice.
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spelling pubmed-52934432017-02-10 Establishing a new formula for estimating renal depth in a Chinese adult population Xue, Jianjun Deng, Huixing Jia, Xi Wang, Yuanbo Lu, Xueni Ding, Xiaoming Li, Qiang Yang, Aimin Medicine (Baltimore) 6800 We aimed to establish a new formula for estimating renal depth, based on anthropometric variables, and to compare the estimates with actual data from a group of living kidney donors undergoing computed tomography angiography (CTA). Renal depths in 167 living kidney donors were measured by CTA. Regression analysis was used to derive the formulae for estimation of renal depth of both kidneys based on patient age, sex, body height, body weight, and body mass index (BMI). The results of the renal depth estimation from the derived formulae were compared with those using existing formulae. Using regression analysis, we derived 2 new formulae as follows; for left kidney, renal depth (cm) = 0.083 × W − 0.058 × H + 11.541 (male) or 10.89 (female), for right kidney, renal depth (cm) = 13.498 × W/H + 2.141 (male) or 1.816 (female), in which W represents the weight (kg) and H represents the height (cm). The correlation coefficients between our left or right renal depth estimates and those obtained from other formulae in another 271 kidney donors were 0.864 (left) or 0.893 (right) by the Tønnesen, 0.937 (left) or 0.97 (right) by the Taylor, 0.937 (left) or 0.97 (right) by the Itoh, 0.927 (left) or 0.951 (right) by the Li-qian, and 0.937 (left) or 0.97 (right) by the Inoue formula. Our formula may be more precise than the Tønnesen formula in estimating the renal depth. Estimating formulae based on CT findings might be useful in clinical practice. Wolters Kluwer Health 2017-02-03 /pmc/articles/PMC5293443/ /pubmed/28151880 http://dx.doi.org/10.1097/MD.0000000000005940 Text en Copyright © 2017 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nd/4.0 This is an open access article distributed under the Creative Commons Attribution-NoDerivatives License 4.0, which allows for redistribution, commercial and non-commercial, as long as it is passed along unchanged and in whole, with credit to the author. http://creativecommons.org/licenses/by-nd/4.0
spellingShingle 6800
Xue, Jianjun
Deng, Huixing
Jia, Xi
Wang, Yuanbo
Lu, Xueni
Ding, Xiaoming
Li, Qiang
Yang, Aimin
Establishing a new formula for estimating renal depth in a Chinese adult population
title Establishing a new formula for estimating renal depth in a Chinese adult population
title_full Establishing a new formula for estimating renal depth in a Chinese adult population
title_fullStr Establishing a new formula for estimating renal depth in a Chinese adult population
title_full_unstemmed Establishing a new formula for estimating renal depth in a Chinese adult population
title_short Establishing a new formula for estimating renal depth in a Chinese adult population
title_sort establishing a new formula for estimating renal depth in a chinese adult population
topic 6800
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5293443/
https://www.ncbi.nlm.nih.gov/pubmed/28151880
http://dx.doi.org/10.1097/MD.0000000000005940
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