Optimizing Noninvasive assessMent Of DysmEtabolic Compensated Advanced Liver Disease

Summary

Non-alcoholic fatty liver disease (NAFLD) is responsible for a significant proportion of liver-related deaths and healthcare costs in the United States, accounting for approximately 36% of liver-related deaths and over one billion dollars in annual healthcare expenses. \[PMID: 34863359\] A recent analysis of healthcare costs in Italy showed that out of the 9,729 NAFLD/NASH patients who were hospitalized and analyzed, the vast majority (97%) did not have advanced liver disease, while 1.3% had compensated advanced liver disease (cACLD), 3.1% had decompensated cirrhosis, 0.8% had hepatocellular carcinoma, and 0.1% underwent liver transplantation. The burden of comorbidities was high across all patient cohorts, and patients with cACLD required a greater number of inpatient services, outpatient visits, and the pharmacy fills compared to those without advanced liver disease. As disease severity increased, mean total annual costs also increased primarily due to higher inpatient services costs. In Italy, as in other EU countries, most of the healthcare costs for patients were attributed to NAFLD/NASH-related liver complications. Thus, the optimization of the non-invasive diagnosis of cACLD represents an urgent need in dysmetabolic liver disease. These advancements will play a crucial role in early detection, risk stratification, and effective management of highly prevalent liver diseases such as NAFLD/NASH and their progression.

Eligibility

Inclusion Criteria:

* age\>=18; sex (M,F);
* dysmetabolic liver disease according new nomenclature definition;
* suspicion of cACLD by LSM\>=10 with VCTE;
* routine esogastroduodenoscopy report within 12 months of VCTE for identification of high-risk varices (HRV).

Exclusion Criteria:

* portal vein thrombosis,
* infiltrative liver neoplasms, and conditions are known for their potential influence on the LSM results (congestive liver disease, extrahepatic biliary obstruction, ALT \> 5x upper normal limit).

Conditions3

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