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Development and validation of a nomogram for predicting acute kidney injury after orthotopic liver transplantation
BACKGROUND: We aim to develop and validate a nomogram model for predicting severe acute kidney injury (AKI) after orthotopic liver transplantation (OLT). METHODS: A total of 576 patients who received OLT in our center were enrolled. They were assigned to the development and validation cohort accordi...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8648040/ https://www.ncbi.nlm.nih.gov/pubmed/34865599 http://dx.doi.org/10.1080/0886022X.2021.2009863 |
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author | Guo, Dandan Wang, Huifang Lai, Xiaoying Li, Junying Xie, Demin Zhen, Li Jiang, Chunhui Li, Min Liu, Xuemei |
author_facet | Guo, Dandan Wang, Huifang Lai, Xiaoying Li, Junying Xie, Demin Zhen, Li Jiang, Chunhui Li, Min Liu, Xuemei |
author_sort | Guo, Dandan |
collection | PubMed |
description | BACKGROUND: We aim to develop and validate a nomogram model for predicting severe acute kidney injury (AKI) after orthotopic liver transplantation (OLT). METHODS: A total of 576 patients who received OLT in our center were enrolled. They were assigned to the development and validation cohort according to the time of inclusion. Univariable and multivariable logistic regression using the forward variable selection routine were applied to find risk factors for post-OLT severe AKI. Based on the results of multivariable analysis, a nomogram was developed and validated. Patients were followed up to assess the long-term mortality and development of chronic kidney disease (CKD). RESULTS: Overall, 35.9% of patients were diagnosed with severe AKI. Multivariable logistic regression analysis revealed that recipients’ BMI (OR 1.10, 95% CI 1.04–1.17, p = 0.012), hypertension (OR 2.32, 95% CI 1.22–4.45, p = 0.010), preoperative serum creatine (sCr) (OR 0.96, 95% CI 0.95–0.97, p < 0.001), and intraoperative fresh frozen plasm (FFP) transfusion (OR for each 1000 ml increase 1.34, 95% CI 1.03–1.75, p = 0.031) were independent risk factors for post-OLT severe AKI. They were all incorporated into the nomogram. The area under the ROC curve (AUC) was 0.73 (p < 0.05) and 0.81 (p < 0.05) in the development and validation cohort. The calibration curve demonstrated the predicted probabilities of severe AKI agreed with the observed probabilities (p > 0.05). Kaplan-Meier survival analysis showed that patients in the high-risk group stratified by the nomogram suffered significantly poorer long-term survival than the low-risk group (HR 1.92, p < 0.01). The cumulative risk of CKD was higher in the severe AKI group than no severe AKI group after competitive risk analysis (HR 1.48, p < 0.05). CONCLUSIONS: With excellent predictive abilities, the nomogram may be a simple and reliable tool to identify patients at high risk for severe AKI and poor long-term prognosis after OLT. |
format | Online Article Text |
id | pubmed-8648040 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-86480402021-12-07 Development and validation of a nomogram for predicting acute kidney injury after orthotopic liver transplantation Guo, Dandan Wang, Huifang Lai, Xiaoying Li, Junying Xie, Demin Zhen, Li Jiang, Chunhui Li, Min Liu, Xuemei Ren Fail Clinical Study BACKGROUND: We aim to develop and validate a nomogram model for predicting severe acute kidney injury (AKI) after orthotopic liver transplantation (OLT). METHODS: A total of 576 patients who received OLT in our center were enrolled. They were assigned to the development and validation cohort according to the time of inclusion. Univariable and multivariable logistic regression using the forward variable selection routine were applied to find risk factors for post-OLT severe AKI. Based on the results of multivariable analysis, a nomogram was developed and validated. Patients were followed up to assess the long-term mortality and development of chronic kidney disease (CKD). RESULTS: Overall, 35.9% of patients were diagnosed with severe AKI. Multivariable logistic regression analysis revealed that recipients’ BMI (OR 1.10, 95% CI 1.04–1.17, p = 0.012), hypertension (OR 2.32, 95% CI 1.22–4.45, p = 0.010), preoperative serum creatine (sCr) (OR 0.96, 95% CI 0.95–0.97, p < 0.001), and intraoperative fresh frozen plasm (FFP) transfusion (OR for each 1000 ml increase 1.34, 95% CI 1.03–1.75, p = 0.031) were independent risk factors for post-OLT severe AKI. They were all incorporated into the nomogram. The area under the ROC curve (AUC) was 0.73 (p < 0.05) and 0.81 (p < 0.05) in the development and validation cohort. The calibration curve demonstrated the predicted probabilities of severe AKI agreed with the observed probabilities (p > 0.05). Kaplan-Meier survival analysis showed that patients in the high-risk group stratified by the nomogram suffered significantly poorer long-term survival than the low-risk group (HR 1.92, p < 0.01). The cumulative risk of CKD was higher in the severe AKI group than no severe AKI group after competitive risk analysis (HR 1.48, p < 0.05). CONCLUSIONS: With excellent predictive abilities, the nomogram may be a simple and reliable tool to identify patients at high risk for severe AKI and poor long-term prognosis after OLT. Taylor & Francis 2021-12-04 /pmc/articles/PMC8648040/ /pubmed/34865599 http://dx.doi.org/10.1080/0886022X.2021.2009863 Text en © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Clinical Study Guo, Dandan Wang, Huifang Lai, Xiaoying Li, Junying Xie, Demin Zhen, Li Jiang, Chunhui Li, Min Liu, Xuemei Development and validation of a nomogram for predicting acute kidney injury after orthotopic liver transplantation |
title | Development and validation of a nomogram for predicting acute kidney injury after orthotopic liver transplantation |
title_full | Development and validation of a nomogram for predicting acute kidney injury after orthotopic liver transplantation |
title_fullStr | Development and validation of a nomogram for predicting acute kidney injury after orthotopic liver transplantation |
title_full_unstemmed | Development and validation of a nomogram for predicting acute kidney injury after orthotopic liver transplantation |
title_short | Development and validation of a nomogram for predicting acute kidney injury after orthotopic liver transplantation |
title_sort | development and validation of a nomogram for predicting acute kidney injury after orthotopic liver transplantation |
topic | Clinical Study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8648040/ https://www.ncbi.nlm.nih.gov/pubmed/34865599 http://dx.doi.org/10.1080/0886022X.2021.2009863 |
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