Establishing a predictive nomogram for 21‑day transplant-free survival in drug-induced liver failure

Background The high prevalence of drug-induced liver failure (DILF) have drawn great attention from clinicians.Aim To further delineate the clinical features of DILF and develop an easily applicable nomogram, based on readily-discernable clinical data, to predict transplant-free survival (TFS) at di...

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Main Authors: Mengyu Tao, Zhilong Wen, Juan Liu, Wentao Zhu, Jiwei Fu, Xiaoping Wu
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Annals of Medicine
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Online Access:https://www.tandfonline.com/doi/10.1080/07853890.2024.2425828
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author Mengyu Tao
Zhilong Wen
Juan Liu
Wentao Zhu
Jiwei Fu
Xiaoping Wu
author_facet Mengyu Tao
Zhilong Wen
Juan Liu
Wentao Zhu
Jiwei Fu
Xiaoping Wu
author_sort Mengyu Tao
collection DOAJ
description Background The high prevalence of drug-induced liver failure (DILF) have drawn great attention from clinicians.Aim To further delineate the clinical features of DILF and develop an easily applicable nomogram, based on readily-discernable clinical data, to predict transplant-free survival (TFS) at different time points.Methods 202 DILF patients were enrolled between January 2016 and December 2022, and were followed up from DILF diagnosis to death, liver transplantation, or 91 days afterward, whichever came first. The primary endpoint, though, was 21-day TFS. Clinical data was collected from all patients, and independent risk factors associated with death/liver transplantation was identified using both uni- and multi-variate Cox regression analyses.Results Independent risk factors incorporated into the predictive nomogram are neutrophils (HR = 1.148, 95% CI = 1.048–1.257), prothrombin time (HR = 1.048, 95% CI = 1.017–1.080), albumin (HR = 0.880, 95% CI = 0.823–0.941), acute kidney injury (HR = 2.487, 95% CI = 1.134–5.452), and hepatic encephalopathy (HR = 3.378, 95% CI = 1.744–6.543). The resulting nomogram was highly predictive, with an area under the curve of 0.947 for 21-day TFS.Conclusions Compared to existing models, such as the Model for End-Stage Liver Disease score, the predictive nomogram is more accurate, only requires easily-measurable clinical and laboratory metrics, as well as being able to directly calculate TFS at various time points.
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spelling doaj-art-9cf70a9cd2914f718b05f6924570568d2024-11-27T06:46:33ZengTaylor & Francis GroupAnnals of Medicine0785-38901365-20602024-12-0156110.1080/07853890.2024.2425828Establishing a predictive nomogram for 21‑day transplant-free survival in drug-induced liver failureMengyu Tao0Zhilong Wen1Juan Liu2Wentao Zhu3Jiwei Fu4Xiaoping Wu5Department of Infectious Disease, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, ChinaDepartment of Infectious Disease, The First Affiliated Hospital of Gannan Medical University, GanzhouDepartment of Infectious Disease, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, ChinaDepartment of Infectious Disease, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, ChinaDepartment of Infectious Disease, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, ChinaDepartment of Infectious Disease, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, ChinaBackground The high prevalence of drug-induced liver failure (DILF) have drawn great attention from clinicians.Aim To further delineate the clinical features of DILF and develop an easily applicable nomogram, based on readily-discernable clinical data, to predict transplant-free survival (TFS) at different time points.Methods 202 DILF patients were enrolled between January 2016 and December 2022, and were followed up from DILF diagnosis to death, liver transplantation, or 91 days afterward, whichever came first. The primary endpoint, though, was 21-day TFS. Clinical data was collected from all patients, and independent risk factors associated with death/liver transplantation was identified using both uni- and multi-variate Cox regression analyses.Results Independent risk factors incorporated into the predictive nomogram are neutrophils (HR = 1.148, 95% CI = 1.048–1.257), prothrombin time (HR = 1.048, 95% CI = 1.017–1.080), albumin (HR = 0.880, 95% CI = 0.823–0.941), acute kidney injury (HR = 2.487, 95% CI = 1.134–5.452), and hepatic encephalopathy (HR = 3.378, 95% CI = 1.744–6.543). The resulting nomogram was highly predictive, with an area under the curve of 0.947 for 21-day TFS.Conclusions Compared to existing models, such as the Model for End-Stage Liver Disease score, the predictive nomogram is more accurate, only requires easily-measurable clinical and laboratory metrics, as well as being able to directly calculate TFS at various time points.https://www.tandfonline.com/doi/10.1080/07853890.2024.2425828Drug-induced liver failuretransplant-free survivalpredictive nomogram
spellingShingle Mengyu Tao
Zhilong Wen
Juan Liu
Wentao Zhu
Jiwei Fu
Xiaoping Wu
Establishing a predictive nomogram for 21‑day transplant-free survival in drug-induced liver failure
Annals of Medicine
Drug-induced liver failure
transplant-free survival
predictive nomogram
title Establishing a predictive nomogram for 21‑day transplant-free survival in drug-induced liver failure
title_full Establishing a predictive nomogram for 21‑day transplant-free survival in drug-induced liver failure
title_fullStr Establishing a predictive nomogram for 21‑day transplant-free survival in drug-induced liver failure
title_full_unstemmed Establishing a predictive nomogram for 21‑day transplant-free survival in drug-induced liver failure
title_short Establishing a predictive nomogram for 21‑day transplant-free survival in drug-induced liver failure
title_sort establishing a predictive nomogram for 21 day transplant free survival in drug induced liver failure
topic Drug-induced liver failure
transplant-free survival
predictive nomogram
url https://www.tandfonline.com/doi/10.1080/07853890.2024.2425828
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