| 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) 2025. Published by Baishideng Publishing Group Inc. All rights reserved. |
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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 |
Gastroenterology & Hepatology |
| Manuscript Type |
Letter to the Editor |
| Article Title |
Future directions in prognostic modeling for dengue-induced severe hepatitis
|
| Manuscript Source |
Invited Manuscript |
| All Author List |
Chen Wang, Hong Hu, Yun Song, Yu-Gang Wang and Min Shi |
| ORCID |
|
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| The Natural Science Foundation of the Science and Technology Commission of Shanghai Municipality |
No. 23ZR1458300 |
| Key Discipline Project of Shanghai Municipal Health System |
No. 2024ZDXK0004 |
| Doctoral Innovation Talent Base Project for Diagnosis and Treatment of Chronic Liver Diseases |
No. RCJD2021B02 |
| Pujiang Project of Shanghai Magnolia Talent Plan |
No. 24PJD098 |
|
| Corresponding Author |
Min Shi, Professor, Department of Gastroenterology, Shanghai Tongren Hospital, Shanghai Jiao Tong University School of Medicine, No. 1111 Xianxia Road, Changning District, Shanghai 200336, China. sm1790@shtrhospital.com |
| Key Words |
Dengue; Hepatitis; Prognosis; Models; Artificial intelligence |
| Core Tip |
The study by Teerasarntipan et al highlights the utility of the model for end-stage liver disease score as the most accurate predictor for in-hospital mortality in dengue-induced severe hepatitis and validates the Easy Albumin-Bilirubin score as a simpler alternative for resource-limited settings. However, current prognostic models face limitations, including static assessments, reliance on non-specific biomarkers, and applicability constraints in diverse healthcare settings. Future directions emphasize the development of dengue-specific scores incorporating novel biomarkers (e.g., tumor necrosis factor-alpha, interleukin-6), leveraging artificial intelligence (AI) for dynamic risk assessment, and multicenter validation to enhance generalizability. Additionally, insights from this research can inform prognostic models for liver dysfunction caused by other viral infections, such as hepatitis viruses and severe acute respiratory syndrome coronavirus 2. Key strategies include integrating AI-driven models into electronic health records, refining dynamic risk stratification, and standardizing tools across healthcare infrastructures. Addressing these challenges will improve early risk stratification, clinical decision-making, and patient outcomes in viral-induced liver failure. |
| Publish Date |
2025-06-26 07:27 |
| Citation |
<p>Wang C, Hu H, Song Y, Wang YG, Shi M. Future directions in prognostic modeling for dengue-induced severe hepatitis. <i>World J Hepatol</i> 2025; 17(6): 107299</p> |
| URL |
https://www.wjgnet.com/1948-5182/full/v17/i6/107299.htm |
| DOI |
https://dx.doi.org/10.4254/wjh.v17.i6.107299 |
