Establishment of a Model for Predicting the Prognosis of HBV-related Decompensated Liver Cirrhosis Based on RFH-NPT

Active, not recruiting

• Conditions: Malnutrition; Liver Cirrhosis

• Registration Number: NCT05513651
• Lead Sponsor: First Affiliated Hospital Xi'an Jiaotong University

Brief Summary

For all countries, chronic liver disease and liver cirrhosis is one of the important disease burdens. Malnutrition is an important complication of liver cirrhosis, which always runs through the course of liver cirrhosis. According to a lot of scientific research evidence, as the consensus of experts all over the world, malnutrition in patients with liver cirrhosis is closely related to poor outcome. Therefore, early and accurate identification of the risk of malnutrition is very important to improve the prognosis of patients with liver cirrhosis.

The purpose of this study was to study the relationship between malnutrition-related indexes and prognosis in patients with liver cirrhosis. 2000 patients with liver cirrhosis were prospectively included, laboratory indexes related to malnutrition and other evaluation indexes were recorded, and long-term follow-up was made to observe the short-term and long-term prognosis of patients with liver cirrhosis. At the same time, a prognostic prediction model was established based on multivariate Cox regression, and a series of in-depth studies and verification were carried out on this basis.

Detailed Description

Malnutrition is one of the most common complications associated with liver cirrhosis, which is more likely to occur in patients with decompensated liver cirrhosis. Malnutrition will further lead to muscle loss, that is, the occurrence of myomyositis, which is an important cause of adverse outcome in patients with liver cirrhosis. it is associated with increased risk of death, portal hypertension-related complications, increased infection rates and longer hospital stays. At the same time, liver cirrhosis with portal hypertension leads to esophageal and gastric varices and intestinal mucosal edema, which affects the function of the digestive system and poses a greater challenge to the nutritional maintenance of patients with liver cirrhosis. Therefore, timely nutritional assessment and early intervention decision-making on admission is an important aspect of clinical management of patients with liver cirrhosis.

For the screening of malnutrition in patients with liver cirrhosis, the commonly used screening tools are MST, MUST, NRS-2002, RFH-NPT and so on. For the screened high-risk population, further specific nutritional assessment is needed, there are four main types. The first is a diet-related assessment conducted by a professional dietitian. The second is the body composition analysis represented by muscle mass, such as bioelectrical impedance analysis (BIA), CT, ultrasound and so on. The third is the functional evaluation, of which the more common are five-meter walking speed and grip strength test. The fourth is part of the comprehensive evaluation tools, represented by SGA and RFH-SGA.

Study Timeline

• Study Start: 2016-07-01
• Study First Submitted: 2022-08-22
• Study First Submitted QC: 2022-08-22
• Study First Posted: 2022-08-24
• Status Verified: 2023-12
• Last Update Submitted: 2024-04-02
• Last Update Posted: 2024-04-03
• Primary Completion: 2025-12-30
• Study Completion: 2030-12-30

Recruitment & Eligibility

• Status: ACTIVE_NOT_RECRUITING
• Sex: All
• Target Recruitment: 2000

Inclusion Criteria

• Hospitalized patients with liver cirrhosis

Exclusion Criteria

• Patients who refuse the follow-up of outpatient department

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
All-cause mortality	up to 10 years	All-cause mortality is death caused by any cause.
Liver-related mortality	up to 10 years	Liver-related mortality refers to death from any liver-related disease, such as liver cirrhosis, liver cancer and other related complications.

Trial Locations

Locations (1)

First Affiliated Hospital Xi'an Jiaotong University; 🇨🇳 Xi'an, Shannxi, China