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A non-invasive model based on the virtual portal pressure gradient to predict the first variceal hemorrhage in cirrhotic patients

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Abstract

Background and aims

This study aimed to establish a non-invasive model based on the virtual portal pressure gradient (vPPG) to predict the first variceal hemorrhage (VH) in patients with cirrhosis.

Methods

This single-center study prospectively enrolled cirrhotic patients as the training and validation cohorts during different time periods. The PPG-detection software (PPGS 1.0) was used to perform vPPG calculation, which involves 2 steps including three-dimensional (3D) reconstruction of portal vein tree and subsequent application of computational fluid dynamics. All patients were given standard primary prophylaxis against VH and followed up for 2 years. Data from the training cohort were assessed using univariate and multivariate Cox regression and Kaplan–Meier analyses, by which a nomogram with its dynamic form was developed to estimate the probability of VH.

Results

In the training cohort (n = 128), 37 (28.9%) experienced VH during 2-year follow-up. Four variables including vPPG ≥ 10.5 mmHg (p < 0.001), PLT < 56 × 109/L (p = 0.048), albumin < 32 g/L (p < 0.001) and INR ≥ 1.2 (p = 0.022) were identified as independent risk factors of VH, among which vPPG showed the best diagnostic performance (AUC 0.875). Subsequently, these predictors were incorporated into the nomogram, of which C-indexes were 0.891 and 0.926 for the training and validation cohorts, respectively. Calibration curves demonstrated a great calibration ability of the model. At the threshold probabilities of 0.1–0.6 (1 year) and 0.1–1.0 (2 years), this nomogram could offer more net benefits in decision curve analysis.

Conclusions

The vPPG-based nomogram could be used for risk stratification of the first VH in patients with cirrhosis.

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Funding

This study was supported by grants from National Natural Science Foundation of China (No. 818201008006 to Changqing Yang), Shanghai Municipal Key Specialty Project (No. SHSLCZDZK06801 to Changqing Yang), Clinical research plan of SHDC (No. SHDC2020CR2030B to Changqing Yang), Shanghai Municipal Science and Technology Commission Original Exploration Project (No. 21ZR1481600 to Jing Li) and Western Medicine Guidance Project (No. 17411970600 to Jing Li), and Shanghai Municipal Health Commission Clinical Research Program (No. 201940040 to Weiping Song).

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Author notes

  1. Shuo Zhang, Weiping Song and Bo Yang have contributed equally to this work.

Authors and Affiliations

  1. Department of Gastroenterology and Hepatology, Tongji Hospital, School of Medicine, Tongji University, 389 Xincun Road, Shanghai, 200092, China

    Shuo Zhang, Weiping Song, Bo Yang, Haoyu Jia, Shuai Chen, Jing Li & Changqing Yang

Authors
  1. Shuo Zhang
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  2. Weiping Song
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  3. Bo Yang
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  4. Haoyu Jia
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  5. Shuai Chen
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  6. Jing Li
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  7. Changqing Yang
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Contributions

Conception and design: JL and CY. Acquisition of data: SZ, WS, BY, HJ, SC. Analysis and interpretation of data: SZ, WS and BY. Drafting of the article: SZ. Study supervision: CY and JL.

Corresponding authors

Correspondence to Jing Li or Changqing Yang.

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Conflict of interest

Shuo Zhang, Weiping Song, Bo Yang, Haoyu Jia, Shuai Chen,Jing Li, and Changqing Yang declare no conflict of interest.

Ethical approval

This study is registered with ClinicalTrials.gov, numbers NCT02925975 and NCT0290779, with the protocol approved by the ethics committee of our hospital (KYSB-159, KYSB-352).

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Zhang, S., Song, W., Yang, B. et al. A non-invasive model based on the virtual portal pressure gradient to predict the first variceal hemorrhage in cirrhotic patients. Hepatol Int 16, 926–935 (2022). https://doi.org/10.1007/s12072-022-10344-5

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  • DOI: https://doi.org/10.1007/s12072-022-10344-5

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