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Identifying Modifiable Predictors of Long‐Term Survival in Liver Transplant Recipients With Diabetes Mellitus Using Machine Learning
Diabetes mellitus (DM) significantly impacts long‐term survival after liver transplantation (LT). We identified survival factors for LT recipients who had DM to inform preventive care using machine‐learning analysis. We analyzed risk factors for mortality in patients from across the United States us...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8248095/ https://www.ncbi.nlm.nih.gov/pubmed/33113221 http://dx.doi.org/10.1002/lt.25930 |
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author | Yasodhara, Angeline Dong, Victor Azhie, Amirhossein Goldenberg, Anna Bhat, Mamatha |
author_facet | Yasodhara, Angeline Dong, Victor Azhie, Amirhossein Goldenberg, Anna Bhat, Mamatha |
author_sort | Yasodhara, Angeline |
collection | PubMed |
description | Diabetes mellitus (DM) significantly impacts long‐term survival after liver transplantation (LT). We identified survival factors for LT recipients who had DM to inform preventive care using machine‐learning analysis. We analyzed risk factors for mortality in patients from across the United States using the Scientific Registry of Transplant Recipients (SRTR). Patients had undergone LT from 1987 to 2019, with a follow‐up of 6.47 years (standard deviation [SD] 5.95). Findings were validated on a cohort from the University Health Network (UHN) from 1989 to 2014 (follow‐up 8.15 years [SD 5.67]). Analysis was conducted with Cox proportional hazards and gradient boosting survival. The training set included 84.67% SRTR data (n = 15,289 patients), and the test set included 15.33% SRTR patients (n = 2769) and data from UHN patients (n = 1290). We included 18,058 adults (12,108 [67.05%] men, average age 54.21 years [SD 9.98]) from the SRTR who had undergone LT and had complete data for investigated features. A total of 4634 patients had preexisting DM, and 3158 had post‐LT DM. The UHN data consisted of 1290 LT recipients (910 [70.5%] men, average age 54.0 years [SD 10.4]). Increased serum creatinine and hypertension significantly impacted mortality with preexisting DM 1.36 (95% confidence interval [CI], 1.21‐1.54) and 1.20 (95% CI, 1.06‐1.35) times, respectively. Sirolimus use increased mortality 1.36 times (95% CI, 1.18‐1.58) in nondiabetics and 1.33 times (95% CI, 1.09‐1.63) in patients with preexisting DM. A similar effect was found in post‐LT DM, although it was not statistically significant (1.38 times; 95% CI, 1.07‐1.77; P = 0.07). Survival predictors generally achieved a 0.60 to 0.70 area under the receiver operating characteristic for 5‐year mortality. LT recipients who have DM have a higher mortality risk than those without DM. Hypertension, decreased renal function, and sirolimus for maintenance immunosuppression compound this mortality risk. These predisposing factors must be intensively treated and modified to optimize long‐term survival after transplant. |
format | Online Article Text |
id | pubmed-8248095 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82480952021-07-02 Identifying Modifiable Predictors of Long‐Term Survival in Liver Transplant Recipients With Diabetes Mellitus Using Machine Learning Yasodhara, Angeline Dong, Victor Azhie, Amirhossein Goldenberg, Anna Bhat, Mamatha Liver Transpl Original Articles Diabetes mellitus (DM) significantly impacts long‐term survival after liver transplantation (LT). We identified survival factors for LT recipients who had DM to inform preventive care using machine‐learning analysis. We analyzed risk factors for mortality in patients from across the United States using the Scientific Registry of Transplant Recipients (SRTR). Patients had undergone LT from 1987 to 2019, with a follow‐up of 6.47 years (standard deviation [SD] 5.95). Findings were validated on a cohort from the University Health Network (UHN) from 1989 to 2014 (follow‐up 8.15 years [SD 5.67]). Analysis was conducted with Cox proportional hazards and gradient boosting survival. The training set included 84.67% SRTR data (n = 15,289 patients), and the test set included 15.33% SRTR patients (n = 2769) and data from UHN patients (n = 1290). We included 18,058 adults (12,108 [67.05%] men, average age 54.21 years [SD 9.98]) from the SRTR who had undergone LT and had complete data for investigated features. A total of 4634 patients had preexisting DM, and 3158 had post‐LT DM. The UHN data consisted of 1290 LT recipients (910 [70.5%] men, average age 54.0 years [SD 10.4]). Increased serum creatinine and hypertension significantly impacted mortality with preexisting DM 1.36 (95% confidence interval [CI], 1.21‐1.54) and 1.20 (95% CI, 1.06‐1.35) times, respectively. Sirolimus use increased mortality 1.36 times (95% CI, 1.18‐1.58) in nondiabetics and 1.33 times (95% CI, 1.09‐1.63) in patients with preexisting DM. A similar effect was found in post‐LT DM, although it was not statistically significant (1.38 times; 95% CI, 1.07‐1.77; P = 0.07). Survival predictors generally achieved a 0.60 to 0.70 area under the receiver operating characteristic for 5‐year mortality. LT recipients who have DM have a higher mortality risk than those without DM. Hypertension, decreased renal function, and sirolimus for maintenance immunosuppression compound this mortality risk. These predisposing factors must be intensively treated and modified to optimize long‐term survival after transplant. John Wiley and Sons Inc. 2021-02-02 2021-04 /pmc/articles/PMC8248095/ /pubmed/33113221 http://dx.doi.org/10.1002/lt.25930 Text en Copyright © 2020 The Authors. Liver Transplantation published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Original Articles Yasodhara, Angeline Dong, Victor Azhie, Amirhossein Goldenberg, Anna Bhat, Mamatha Identifying Modifiable Predictors of Long‐Term Survival in Liver Transplant Recipients With Diabetes Mellitus Using Machine Learning |
title | Identifying Modifiable Predictors of Long‐Term Survival in Liver Transplant Recipients With Diabetes Mellitus Using Machine Learning |
title_full | Identifying Modifiable Predictors of Long‐Term Survival in Liver Transplant Recipients With Diabetes Mellitus Using Machine Learning |
title_fullStr | Identifying Modifiable Predictors of Long‐Term Survival in Liver Transplant Recipients With Diabetes Mellitus Using Machine Learning |
title_full_unstemmed | Identifying Modifiable Predictors of Long‐Term Survival in Liver Transplant Recipients With Diabetes Mellitus Using Machine Learning |
title_short | Identifying Modifiable Predictors of Long‐Term Survival in Liver Transplant Recipients With Diabetes Mellitus Using Machine Learning |
title_sort | identifying modifiable predictors of long‐term survival in liver transplant recipients with diabetes mellitus using machine learning |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8248095/ https://www.ncbi.nlm.nih.gov/pubmed/33113221 http://dx.doi.org/10.1002/lt.25930 |
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