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CN 22-1108/R
Volume 41 Issue 6
Jun.  2025
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Article Navigation >  Journal of Clinical Hepatology  > 2025  >  41(6): 1135-1142

Establishment and validation of a risk prediction model for 90-day mortality in patients with acute-on-chronic liver failure based on sarcopenia

DOI: 10.12449/JCH250620
  • 1.

    Beijing Tiantan Hospital，Capital Medical University，Beijing 100070，China

  • 2.

    Fourth Department of Liver Disease Center，Beijing YouAn Hospital，Capital Medical University，Beijing 100069，China

  • 3.

    Beijing Municipal Key Laboratory of Liver Failure and Artificial Liver Treatment Research，Beijing 100069，China

Research funding:

Construction Project of High-level Technology Talents in Public Health (Discipline leader-01-12);

Beijing Hospitals Authority’s Ascent Plan (DFL20221501);

Beijing Nova Program (20220484201);

Beijing Natural Science Foundation (7232081)

More Information
  • Corresponding author: DUAN Zhongping， duan2517@163.com （ORCID： 0000-0002-8455-0426）
  • Received Date: 2024-10-07
  • Accepted Date: 2024-11-19
  • Published Date: 2025-06-25
    Abstract
  •   Objective  To establish and validate a new prediction model for the risk of death in patients with acute-on-chronic liver failure （ACLF） based on sarcopenia and other clinical indicators， and to improve the accuracy of prognostic assessment for ACLF patients.  Methods  A total of 380 patients with ACLF who were admitted to Beijing YouAn Hospital， Capital Medical University， from January 2019 to January 2022 were enrolled， and they were divided into training group with 228 patients and testing group with 152 patients in a ratio of 6∶4 using the stratified random sampling method. For the training group， CT images were used to measure the cross-sectional area of the skeletal muscle at the third lumbar vertebra （L3）， and L3 skeletal muscle index （L3-SMI） was calculated. Sarcopenia was diagnosed based on the previously established L3-SMI reference values for healthy adults in northern China. Univariate and multivariable Cox regression analyses were used to establish a sarcopenia-ACLF model which integrated sarcopenia and clinical risk factors， and a nomogram was developed for presentation. The area under the ROC curve （AUC） was used to assess the predictive performance of the model， the calibration curve was used to assess the degree of calibration， and a decision curve analysis was used to investigate the clinical application value of the model. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. The Kaplan-Meier method was used to plot survival curves， and the Log-rank test was used for comparison between groups. The DeLong test was used for comparison of AUC between different models.  Results  The multivariate Cox regression analysis showed that sarcopenia （hazard ratio ［HR］=1.962， 95% confidence interval ［CI］： 1.185‍ ‍—‍ ‍3.250， P=0.009）， total bilirubin （HR=1.003， 95%CI： 1.002‍ ‍—‍ ‍1.005， P<0.001）， international normalized ratio （HR=1.997， 95%CI： 1.674‍ ‍—‍ ‍2.382， P<0.001）， and lactic acid （HR=1.382， 95%CI： 1.170‍ ‍—‍ ‍1.632， P<0.001） were included in the sarcopenia-ACLF model. In the training cohort， the sarcopenia-ACLF model had a larger AUC than MELD-Na score in predicting 90-day mortality in patients with ACLF （0.80 vs 0.73， Z=1.97， P=0.049）. In the test cohort， the sarcopenia-ACLF model had a significantly larger AUC than MELD score （0.79 vs 0.69， Z=2.70， P=0.007） and MELD-Na score （0.79 vs 0.68， Z=2.92， P=0.004）. The calibration curve showed that the model had good calibration ability， with a relatively good consistency between the predicted risk of mortality and the observed results. The DCA results showed that within a reasonable range of threshold probabilities， the sarcopenia-ACLF model showed a greater net benefit than MELD and MELD-Na scores in both the training cohort and the test cohort.  Conclusion  The sarcopenia-ACLF model developed in this study provides a more accurate tool for predicting the risk of 90-day mortality in ACLF patients， which provides support for clinical decision-making and helps to optimize treatment strategies.

     

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