The hepatic venous pressure gradient (HVPG) has long been the definitive method for accurately assessing portal pressure in patients with cirrhosis [1-3] and is the best predictor of decompensation in those with compensated cirrhosis [4]. However, HVPG's invasive nature and limited availability constrain its widespread use. To surmount this challenge, the latest Baveno VII criteria suggest using liver stiffness measurement (LSM) of ≥25 kPa can confirm clinically significant portal hypertension (CSPH), while a LSM of ≤15 kPa combined with a platelet count (PLT) of ≥150×10⁹/L can exclude CSPH. For patients in the intermediate range, the more complex ANTICIPATE model is used: LSM values between 20–25 kPa with PLT <150×10⁹/L or LSM values between 15–20 kPa with PLT <110×10⁹/L, predicting a CSPH risk of 60% or slightly higher [5,6] demonstrating that using non-invasive tests (NITs), specifically LSM combined with PLT, has excellent discriminative value (area under the curve [AUC], 0.85) in patients with Child-Pugh A compensated cirrhosis.

A study by Song et al. [7] evaluated the usefulness of the Baveno VII criteria, which use LSM to non-invasively diagnose CSPH, in predicting decompensation risk in patients with compensated advanced chronic liver disease (cACLD). In a retrospective cohort study of 1966 patients, categorized into four groups based on the Baveno VII consensus, the risk of decompensation was assessed. Over a median follow-up of 3.06 years, 178 patients developed decompensations. The 3-year cumulative risk of decompensation was highest in patients with CSPH (22%), followed by the grey zone high-risk group (12%), grey zone low-risk group (3.3%), and those without CSPH (1.4%). Compared to the CSPH excluded group, the CSPH included group had a standardized hazard ratio (sHR) of 8.00, the grey zone high-risk group had an sHR of 6.57, and the grey zone low-risk group had an sHR of 2.15, all showing significantly higher risks of decompensation (P<0.01). This study demonstrates that the Baveno VII criteria effectively stratify the risk of decompensation in cACLD patients using non-invasive methods.

According to the Baveno VII consensus, assessing emerging non-invasive methods to diagnose CSPH and determine response to non-selective beta-blockers (NSBB’s) is on the research agenda [5]. To address the grey zone crisis, Liu et al. [8] in a recent issue of Clinical and Molecular Hepatology, aimed to develop and validate a new non-invasive model for predicting CSPH in patients with compensated cirrhosis .Theyalso evaluated the effectiveness of carvedilol in preventing hepatic decompensation in high-risk patients identified by this model [8]. The study involved a systematic review and meta-analysis of six studies with HVPG, forming the derivation cohort, which reported odds ratios (ORs) with confidence intervals (CIs) to identify risk factors for CSPH. LSM and PLT were identified as the key risk factors stratifying CSPH. The model “CSPH risk model” was developed by calculating the β-coefficient for each risk factor based on the pooled ORs and their corresponding 95% CIs. The score for each component was determined by multiplying the value of the component by its β-coefficient. Finally, the CSPH risk was calculated by summing the scores of LSM and PLT. Validated across three cohorts (i.e., international HVPG cohort, international follow-up cohort, and carvedilol-treating cohort: 1,396 patients), the model accurately predicted CSPH with cutoff values of >0 for high-risk and <–0.68 for low-risk, reducing the diagnostic grey zone from 50.3% (Baveno VII criteria) to 22.5%. High-risk CSPH patients treated with carvedilol had significantly lower rates of hepatic decompensation: 4.9% compared to 13.2% in untreated patients before propensity score matching (PSM), and 4.9% compared to 17.3% after PSM. The incidence of ascites was also significantly lower in carvedilol-treated high-risk CSPH patients, at 1.2% before PSM and 2.5% after PSM, compared to 8.7% and 12.3% in untreated patients, respectively. In the HVPG cohort, the ROC of the new CSPH risk model showed an AUC of 0.91 (95% CI 0.86–0.95), which was better compared to 0.80 (95% CI 0.73–0.87) for the ANTICIPATE model and 0.83 (95% CI 0.77–0.89) for the Baveno VII criteria.

LSM changes over time as a significant predictor for hepatic decompensation and liver-related events (LREs) in patients with CLD has been emphasized in study by Semmler et al. [9], which showed that that a 20% increase in LSM is associated with approximately a 50% increased risk of hepatic decompensation (HR 1.58; 95% CI 1.41–1.79; P<0.001) and liver-related death (HR 1.45; 95% CI 1.28–1.68; P<0.001) in patients with cACLD. The LSM dynamics showed high accuracy in predicting hepatic decompensation within the next 12 months, with an AUC of 0.933. Similarly, the study by Gawrieh et al. [10] highlights the bidirectional relationship between LSM changes and LREs in patients with non-alcoholic fatty liver disease (NAFLD). It reports that 29% of participants progressed to LSM ≥10 kPa and 17% to LSM ≥15 kPa, while 44% regressed to LSM <10 kPa and 49% to LSM <15 kPa. Those who progressed to LSM ≥10 kPa experienced a higher cumulative LRE rate (16% vs. 4%; aHR 4.0; 95% CI 1.8–8.9; P<0.01), whereas those who regressed to LSM <10 kPa had a lower LRE rate (7% vs. 32%; aHR 0.25; 95% CI 0.10–0.61; P<0.01). However, in a study by Wong et al. [11] presents a differing viewpoint, suggesting that once the current LSM is known, previous LSM values or their changes over time do not add predictive value for LREs in patients with cACLD. In a study of 480 patients with cACLD over a median follow-up of 68 months, 32% experienced a decrease in LSM to below 10 kPa, and 5.8% experienced LREs. However, neither the prior LSM nor the LSM slope added predictive value to the latest LSM in multivariable Cox regression analysis. There remains some uncertainty about the additional predictive value of LSM changes once the current LSM is known. This suggests that the role of changing LSM in predicting LREs is not yet fully clear and requires further investigation.

The study by Liu et al. [8] had limitations, including a small retrospective cohort treated with carvedilol, lacking detailed data on alcohol consumption, body weight changes, and a limited number of non-alcoholic Steatohepatitis (NASH) patients. The findings, mainly based on viral-related cirrhosis, need validation in non-viral causes. The absence of individual participant data and unaccounted covariates in pooled OR calculations may impact results. Differences in baseline characteristics between carvedilol-treated and untreated patients highlight the need for randomized control trials (RCT)’s. Addressing these limitations in future research will enhance the reliability of LSM dynamics in chronic liver disease management.

This study by Liu et al. [8] highlights NSBB, particularly carvedilol, significantly reduce hepatic decompensation in cirrhosis patients with CSPH when stratified using a new non-invasive model. This model enhances risk stratification and guides NSBB therapy effectively. Pilot data from a retrospective study showed that an algorithm combining spleen stiffness measurement (cut-off >/<40 kPa) with the latest CSPH criteria (LSM ≤15 kPa+PLT ≥150 g/L to exclude CSPH and LSM >25 kPa to confirm CSPH) reduced the diagnostic grey zone from 40–60% to 7–15%. All initial decompensation events occurred within the “rule-in” zone of the model, which incorporated spleen stiffness measurement [12]. These criteria require validation in non-viral cACLD, particularly in obese NASH patients, where LSM accuracy is limited. The impact of cofactors like obesity and diabetes on disease progression and LSM values needs further study. Expanding and validating NITs beyond transient elastography across different etiologies is essential, as is exploring the use of LSM changes alone or with other NITs, like the Fibrosis-4 index, to assess clinically significant improvements. Figure 1 shows the stratification of CSPH risk using LSM and HVPG, comparing the CSPH Risk Model and Baveno VII Criteria. It highlights CD rates over 3 years, showing higher risk at LSM >20 kPa. The figure indicates that carvedilol significantly reduces CD incidence in high-risk patients (e.g., 15.8% to 4.9%, P=0.04). It also displays other NITs used for managing CSPH and assessing NSBB impact.

A study by Karagiannakis et al. [13] assessed spleen stiffness measurement (SSM) via 2D shear-wave elastography in predicting decompensation and mortality in cirrhotic patients. Among 177 patients over 31±18 months, SSM was independently associated with decompensation (HR 1.063; P=0.021; AUROC 0.710) and predicted death/liver transplantation (HR 1.043; P=0.034; AUROC 0.72). The study found SSM to have superior diagnostic accuracy for 1-year outcomes compared to LSM.

Only a few studies have explored the use of NITs alone or with other markers to assess beta-blocker therapy response. Despite uncertainties, the Baveno VII criteria have significantly advanced the role of NITs in managing cACLD, highlighting their crucial importance.