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Articles Published Processes
3/24/2022 2:13:21 PM | Browse: 375 | Download: 1267
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Received |
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2021-09-27 01:39 |
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Peer-Review Started |
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2021-09-27 01:41 |
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To Make the First Decision |
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Return for Revision |
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2021-12-02 08:55 |
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Revised |
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2021-12-10 16:23 |
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Second Decision |
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2022-02-15 03:19 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2022-02-16 07:19 |
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Articles in Press |
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2022-02-16 07:19 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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2022-02-03 09:48 |
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Typeset the Manuscript |
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2022-03-15 01:11 |
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Publish the Manuscript Online |
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2022-03-24 14:13 |
| ISSN |
1948-5182 (online) |
| Open Access |
This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Noncommercial (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. See: https://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Transplantation |
| Manuscript Type |
Retrospective Cohort Study |
| Article Title |
Risk factors and prediction of acute kidney injury after liver transplantation: Logistic regression and artificial neural network approaches
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Luis Cesar Bredt, Luis Alberto Batista Peres, Michel Risso and Leandro Cavalcanti de Albuquerque Leite Barros |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Luis Cesar Bredt, FRCS (Gen Surg), MD, PhD, Full Professor, Surgeon, Surgical Oncology and Hepatobilary Surgery Department, UNIOESTE, Tancredo Neves Avenue, Cascavel 85819-110, Paraná, Brazil. lcbredt@gmail.com |
| Key Words |
Logistic regression; Liver transplantation; Acute kidney injury; Machine learning; Artificial neural network |
| Core Tip |
This study aimed to identify the risk factors of acute kidney injury (AKI) after deceased-donor liver transplantation and compare the performance of artificial neural network (ANN) with that of logistic regression (LR) analysis to predict this complication. LR analysis revealed the following predictors of AKI: Previous kidney dysfunction, marginal grafts, intra-operative arterial hypotension, massive blood transfusion, and serum lactate. ANN prediction had better performance than LR in this scenario. |
| Publish Date |
2022-03-24 14:13 |
| Citation |
Bredt LC, Peres LAB, Risso M, Barros LCAL. Risk factors and prediction of acute kidney injury after liver transplantation: Logistic regression and artificial neural network approaches. World J Hepatol 2022; 14(3): 570-582 |
| URL |
https://www.wjgnet.com/1948-5182/full/v14/i3/570.htm |
| DOI |
https://dx.doi.org/10.4254/wjh.v14.i3.570 |
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