Evidence map›Paper›PMID 40719905›Full record

ArticleClinical and experimental medicine2025

Relative change rate of liver stiffness measurements predicts the risk of liver decompensation in compensated advanced chronic liver disease.

Yanqiu Li, Zihang Qiao, Jinze Li, Bingbing Zhu, Yu Lu, Ying Feng, Xianbo Wang

Abstract read
In one paragraph

Article in Clinical and experimental medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. ALPS-HCC Score: A Dynamic Liver Stiffness Measurement-Based Machine Learning Model to Predict Risk of Hepatocellular Carcinoma.Liver international : official journal of the International Association for the Study of the Liver · 2026
    Article
  2. Noninvasive Tests for Predicting Decompensation in Compensated Advanced Chronic Liver Disease: A Comprehensive Review.Liver international : official journal of the International Association for the Study of the Liver · 2026
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yanqiu Li *Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China.
Zihang Qiao *Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Jinze LiDepartment of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
Bingbing ZhuCenter of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China.
Yu LuCenter of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China.
Ying FengCenter of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China. fengying@ccmu.edu.cn.
Xianbo WangCenter of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China. wangxb@ccmu.edu.cn.

Funding

Beijing Municipal Natural Science Foundation 7232272Beijing Traditional Chinese Medicine Technology Development Fund Project BJZYZD-2023-12Capital's Funds for Health improvement and Research 2024-1-2173high-level Chinese Medicine Key Discipline Construction Project zyyzdxk-2023005National Natural Science Foundation of China 82474419National Natural Science Foundation of China 82474426
6 · The paper itself

Abstract

Patients with compensated advanced chronic liver disease (cACLD) have a significant risk of decompensation. Therefore, this study aimed to evaluate the predictive value of dynamic liver stiffness measurements (LSM) for decompensation risk, and their performance across different clinically significant portal hypertension (CSPH) risk stratification. This retrospective cohort study included 1409 patients with cACLD. Patients were divided into no CSPH, probable CSPH, and certain CSPH groups. Competing risk regression analysis was used to identify the independent predictors. The receiver operating characteristic curve and time-dependent area under the curve were used to evaluate the predictive performance. During follow-up, liver decompensation incidence increased with CSPH severity (22.2% with no CSPH, 37.5% with probable CSPH, and 64.9% with certain CSPH, p < 0.001). Multivariate regression analysis identified age, basal LSM1, delta LSM/LSM1, delta LSM/delta year, spleen diameter, and international normalized ratio as independent risk factors for liver decompensation. In the no CSPH group, spleen diameter showed the best predictive ability (AUC = 0.710). For probable and certain CSPH groups, delta LSM/LSM1 showed superior predictive performance (AUC: 0.777 and 0.782, respectively). The predictive power of basal LSM1 was relatively limited across all groups (AUC: 0.554-0.639). Subgroup analysis revealed interactions between age, sex, different etiologies, and CSPH subgroups. The relative change rate of LSM outperformed basal LSM1 and annual change rate in predicting liver decompensation risk, particularly in patients with existing portal hypertension. Dynamic assessments and differentiated prediction strategies are essential for optimal patient managements.

Indexed as

Elasticity Imaging TechniquesEnd Stage Liver DiseaseHypertension, PortalLiverLiver CirrhosisAgedChronic DiseaseFemaleHumansIncidenceMaleMiddle AgedMultivariate AnalysisRegression AnalysisRetrospective StudiesRisk AssessmentClinically significant portal hypertensionCompensated advanced chronic liver diseaseDynamic changesLiver decompensationLiver stiffness measurement

Identifiers

PMID40719905
PMCPMC12304040

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.