A dynamic prediction model for prognosis of acute-on-chronic liver failure based on the trend of clinical indicators

Abstract Acute-on-chronic liver failure (ACLF) is a dynamic syndrome, and sequential assessments can reflect its prognosis more accurately. Our aim was to build and validate a new scoring system to predict short-term prognosis using baseline and dynamic data in ACLF. We conducted a retrospective coh...

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Autores principales:	Zhenjun Yu, Yu Zhang, Yingying Cao, Manman Xu, Shaoli You, Yu Chen, Bing Zhu, Ming Kong, Fangjiao Song, Shaojie Xin, Zhongping Duan, Tao Han
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a2ef3f603cc44cecb114d72f2e613fc0
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spelling	oai:doaj.org-article:a2ef3f603cc44cecb114d72f2e613fc02021-12-02T13:56:48ZA dynamic prediction model for prognosis of acute-on-chronic liver failure based on the trend of clinical indicators10.1038/s41598-021-81431-02045-2322https://doaj.org/article/a2ef3f603cc44cecb114d72f2e613fc02021-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-81431-0https://doaj.org/toc/2045-2322Abstract Acute-on-chronic liver failure (ACLF) is a dynamic syndrome, and sequential assessments can reflect its prognosis more accurately. Our aim was to build and validate a new scoring system to predict short-term prognosis using baseline and dynamic data in ACLF. We conducted a retrospective cohort analysis of patients with ACLF from three different hospitals in China. To construct the model, we analyzed a training set of 541 patients from two hospitals. The model’s performance was evaluated in a validation set of 130 patients from another center. In the training set, multivariate Cox regression analysis revealed that age, WGO type, basic etiology, total bilirubin, creatinine, prothrombin activity, and hepatic encephalopathy stage were all independent prognostic factors in ACLF. We designed a dynamic trend score table based on the changing trends of these indicators. Furthermore, a logistic prediction model (DP-ACLF) was constructed by combining the sum of dynamic trend scores and baseline prognostic parameters. All prognostic scores were calculated based on the clinical data of patients at the third day, first week, and second week after admission, respectively, and were correlated with the 90-day prognosis by ROC analysis. Comparative analysis showed that the AUC value for DP-ACLF was higher than for other prognostic scores, including Child–Turcotte–Pugh, MELD, MELD-Na, CLIF-SOFA, CLIF-C ACLF, and COSSH-ACLF. The new scoring model, which combined baseline characteristics and dynamic changes in clinical indicators to predict the course of ACLF, showed a better prognostic ability than current scoring systems. Prospective studies are needed to validate these results.Zhenjun YuYu ZhangYingying CaoManman XuShaoli YouYu ChenBing ZhuMing KongFangjiao SongShaojie XinZhongping DuanTao HanNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Zhenjun Yu Yu Zhang Yingying Cao Manman Xu Shaoli You Yu Chen Bing Zhu Ming Kong Fangjiao Song Shaojie Xin Zhongping Duan Tao Han A dynamic prediction model for prognosis of acute-on-chronic liver failure based on the trend of clinical indicators
description	Abstract Acute-on-chronic liver failure (ACLF) is a dynamic syndrome, and sequential assessments can reflect its prognosis more accurately. Our aim was to build and validate a new scoring system to predict short-term prognosis using baseline and dynamic data in ACLF. We conducted a retrospective cohort analysis of patients with ACLF from three different hospitals in China. To construct the model, we analyzed a training set of 541 patients from two hospitals. The model’s performance was evaluated in a validation set of 130 patients from another center. In the training set, multivariate Cox regression analysis revealed that age, WGO type, basic etiology, total bilirubin, creatinine, prothrombin activity, and hepatic encephalopathy stage were all independent prognostic factors in ACLF. We designed a dynamic trend score table based on the changing trends of these indicators. Furthermore, a logistic prediction model (DP-ACLF) was constructed by combining the sum of dynamic trend scores and baseline prognostic parameters. All prognostic scores were calculated based on the clinical data of patients at the third day, first week, and second week after admission, respectively, and were correlated with the 90-day prognosis by ROC analysis. Comparative analysis showed that the AUC value for DP-ACLF was higher than for other prognostic scores, including Child–Turcotte–Pugh, MELD, MELD-Na, CLIF-SOFA, CLIF-C ACLF, and COSSH-ACLF. The new scoring model, which combined baseline characteristics and dynamic changes in clinical indicators to predict the course of ACLF, showed a better prognostic ability than current scoring systems. Prospective studies are needed to validate these results.
format	article
author	Zhenjun Yu Yu Zhang Yingying Cao Manman Xu Shaoli You Yu Chen Bing Zhu Ming Kong Fangjiao Song Shaojie Xin Zhongping Duan Tao Han
author_facet	Zhenjun Yu Yu Zhang Yingying Cao Manman Xu Shaoli You Yu Chen Bing Zhu Ming Kong Fangjiao Song Shaojie Xin Zhongping Duan Tao Han
author_sort	Zhenjun Yu
title	A dynamic prediction model for prognosis of acute-on-chronic liver failure based on the trend of clinical indicators
title_short	A dynamic prediction model for prognosis of acute-on-chronic liver failure based on the trend of clinical indicators
title_full	A dynamic prediction model for prognosis of acute-on-chronic liver failure based on the trend of clinical indicators
title_fullStr	A dynamic prediction model for prognosis of acute-on-chronic liver failure based on the trend of clinical indicators
title_full_unstemmed	A dynamic prediction model for prognosis of acute-on-chronic liver failure based on the trend of clinical indicators
title_sort	dynamic prediction model for prognosis of acute-on-chronic liver failure based on the trend of clinical indicators
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/a2ef3f603cc44cecb114d72f2e613fc0
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A dynamic prediction model for prognosis of acute-on-chronic liver failure based on the trend of clinical indicators

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