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New formula for predicting standard liver volume in Chinese adults

AIM: To obtain a reference range of morphological indices and establish a formula to accurately predict standard liver volume (SLV) in Chinese adults. METHODS: Computed tomography (CT)-estimated total liver volume (CTLV) was determined in 369 Chinese adults. Age, sex, body weight, body height, body...

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Autores principales: Feng, Ling-Mei, Wang, Pei-Qin, Yu, Hong, Chen, Ru-Tan, Wang, Jian, Sheng, Xia, Yuan, Zong-Li, Shi, Pei-Mei, Xie, Wei-Fen, Zeng, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5526767/
https://www.ncbi.nlm.nih.gov/pubmed/28785151
http://dx.doi.org/10.3748/wjg.v23.i27.4968
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author Feng, Ling-Mei
Wang, Pei-Qin
Yu, Hong
Chen, Ru-Tan
Wang, Jian
Sheng, Xia
Yuan, Zong-Li
Shi, Pei-Mei
Xie, Wei-Fen
Zeng, Xin
author_facet Feng, Ling-Mei
Wang, Pei-Qin
Yu, Hong
Chen, Ru-Tan
Wang, Jian
Sheng, Xia
Yuan, Zong-Li
Shi, Pei-Mei
Xie, Wei-Fen
Zeng, Xin
author_sort Feng, Ling-Mei
collection PubMed
description AIM: To obtain a reference range of morphological indices and establish a formula to accurately predict standard liver volume (SLV) in Chinese adults. METHODS: Computed tomography (CT)-estimated total liver volume (CTLV) was determined in 369 Chinese adults. Age, sex, body weight, body height, body mass index, and body surface area (BSA) were recorded using CT. Total splenic volume, portal venous diameter (PVD), splenic venous diameter (SVD), and portal venous cross-sectional area (PVCSA) were also measured by CT. Stepwise multiple linear regression analysis was performed to evaluate the impact of each parameter on CTLV and to develop a new SLV formula. The accuracy of the new formula was compared with the existing formulas in a validation group. RESULTS: The average CTLV was 1205.41 ± 257.53 cm(3) (range, 593.80-2250.10 cm(3)). The average of PVD, SVD and PVCSA was 9.34 ± 1.51 mm, 7.40 ± 1.31 mm and 173.22 ± 48.11 mm(2), respectively. The CT-estimated splenic volume of healthy adults varied markedly (range, 46.60-2892.30 cm(3)). Sex, age, body height, body weight, body mass index, and BSA were significantly correlated with CTLV. BSA showed the strongest correlation (r = 0.546, P < 0.001), and was used to establish a new model for calculating SLV: SLV (cm(3)) = 758.259 × BSA (m(2))-124.272 (R(2) = 0.299, P < 0.001). This formula also predicted CTLV more accurately than the existing formulas, but overestimated CTLV in elderly subjects > 70 years of age, and underestimated liver volume when CTLV was > 1800 cm(3). CONCLUSION: Our new BSA-based formula is more accurate than other formulas in estimating SLV in Chinese adults.
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spelling pubmed-55267672017-08-07 New formula for predicting standard liver volume in Chinese adults Feng, Ling-Mei Wang, Pei-Qin Yu, Hong Chen, Ru-Tan Wang, Jian Sheng, Xia Yuan, Zong-Li Shi, Pei-Mei Xie, Wei-Fen Zeng, Xin World J Gastroenterol Prospective Study AIM: To obtain a reference range of morphological indices and establish a formula to accurately predict standard liver volume (SLV) in Chinese adults. METHODS: Computed tomography (CT)-estimated total liver volume (CTLV) was determined in 369 Chinese adults. Age, sex, body weight, body height, body mass index, and body surface area (BSA) were recorded using CT. Total splenic volume, portal venous diameter (PVD), splenic venous diameter (SVD), and portal venous cross-sectional area (PVCSA) were also measured by CT. Stepwise multiple linear regression analysis was performed to evaluate the impact of each parameter on CTLV and to develop a new SLV formula. The accuracy of the new formula was compared with the existing formulas in a validation group. RESULTS: The average CTLV was 1205.41 ± 257.53 cm(3) (range, 593.80-2250.10 cm(3)). The average of PVD, SVD and PVCSA was 9.34 ± 1.51 mm, 7.40 ± 1.31 mm and 173.22 ± 48.11 mm(2), respectively. The CT-estimated splenic volume of healthy adults varied markedly (range, 46.60-2892.30 cm(3)). Sex, age, body height, body weight, body mass index, and BSA were significantly correlated with CTLV. BSA showed the strongest correlation (r = 0.546, P < 0.001), and was used to establish a new model for calculating SLV: SLV (cm(3)) = 758.259 × BSA (m(2))-124.272 (R(2) = 0.299, P < 0.001). This formula also predicted CTLV more accurately than the existing formulas, but overestimated CTLV in elderly subjects > 70 years of age, and underestimated liver volume when CTLV was > 1800 cm(3). CONCLUSION: Our new BSA-based formula is more accurate than other formulas in estimating SLV in Chinese adults. Baishideng Publishing Group Inc 2017-07-21 2017-07-21 /pmc/articles/PMC5526767/ /pubmed/28785151 http://dx.doi.org/10.3748/wjg.v23.i27.4968 Text en ©The Author(s) 2017. Published by Baishideng Publishing Group Inc. All rights reserved. http://creativecommons.org/licenses/by-nc/4.0/ This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial.
spellingShingle Prospective Study
Feng, Ling-Mei
Wang, Pei-Qin
Yu, Hong
Chen, Ru-Tan
Wang, Jian
Sheng, Xia
Yuan, Zong-Li
Shi, Pei-Mei
Xie, Wei-Fen
Zeng, Xin
New formula for predicting standard liver volume in Chinese adults
title New formula for predicting standard liver volume in Chinese adults
title_full New formula for predicting standard liver volume in Chinese adults
title_fullStr New formula for predicting standard liver volume in Chinese adults
title_full_unstemmed New formula for predicting standard liver volume in Chinese adults
title_short New formula for predicting standard liver volume in Chinese adults
title_sort new formula for predicting standard liver volume in chinese adults
topic Prospective Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5526767/
https://www.ncbi.nlm.nih.gov/pubmed/28785151
http://dx.doi.org/10.3748/wjg.v23.i27.4968
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