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| Main Authors: | , , , , , , , , , , , , , , , , , , , |
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| Format: | Artículo Open Access |
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Wiley
2025
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| Online Access: | https://onlinelibrary.wiley.com/doi/10.1111/apt.70430 |
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Table of Contents:
- Unstable Recompensation: An Intermediate Subtype in Patients With HBV ‐Related Decompensated Cirrhosis Shuai Xia Zhiying He Xiaoning Wu Zhongjie Hu Chunqing Zhang Yanqin Hao Yongfeng Yang Yan Huang Wei Rao Xiaoqian Xu Xinyu Zhao Jialing Zhou Yameng Sun Shuyan Chen Luqi Tang Xiaojuan Ou Xinyan Zhao Jidong Jia Bingqiong Wang Hong You Alimentary Pharmacology & Therapeutics ABSTRACT Background and Aim Recent studies show that patients with hepatitis B virus (HBV)‐related decompensated cirrhosis who achieve recompensation can still experience further decompensation, suggesting that recompensation status can change over time. This study aimed to classify patterns of recompensation and charaterize the clinical differences among these subgroups. Methods Eligible patients with HBV‐related decompensated cirrhosis were enrolled from two cohorts. Clinical characteristics and complications were assessed every 6 months for up to 5 years following their first episode of decompensation. Recompensation was defined according to the Baveno VII criteria and further categorised as stable (no subsequent decompensation) or unstable (recurrent decompensation or recompensation following multiple decompensation episodes). Results A total of 378 patients were included; 294 (77.8%) achieved recompensation, while 84 (22.2%) did not. After a median follow‐up of 5.3 years (IQR 4.4–5.8), recompensated patients were classified into stable recompensation (202/378, 53.4%) and unstable recompensation (92/378, 24.3%). The 5 year rate of hepatocellular carcinoma (HCC) or all‐cause mortality was higher in the unstable group than the stable group (14.7% vs. 10.1%, p = 0.038), yet remained lower than in patients with ongoing decompensation. Liver function improvement was intermediate in the unstable group compared with the stable recompensation and ongoing decompensation. Logistic regression yielded the highest accuracy for predicting recompensation (AUROC = 0.884), while support vector machine algorithms best predicted stable recompensation (AUROC = 0.911). Conclusion Recompensation is not a uniform condition and should be further subclassified. Unstable recompensation is a distinct state with poorer survival than stable recompensation, yet better outcomes than ongoing decompensation. 10.1111/apt.70430 http://creativecommons.org/licenses/by-nc-nd/4.0/