AI Article Synopsis

  • * Researchers analyzed data from 858 CLD patients, determining that 26% had sarcopenia and varying rates of malnutrition based on GLIM, SGA, and RFH-GA assessments.
  • * Results showed that the GLIM criteria significantly predict sarcopenia and mortality, indicating their usefulness in clinical settings for managing malnutrition in these patients.

Article Abstract

Aim: The Global Leadership Initiative on Malnutrition (GLIM) criteria, a newly developed global consensus around core diagnostic criteria for malnutrition, needs validation studies for use in daily clinical settings. This study aimed to determine whether the GLIM criteria could predict sarcopenia and mortality in patients with chronic liver disease (CLD).

Methods: We retrospectively reviewed 858 patients with CLD who were treated at our hospital between March 2013 and December 2019. Sarcopenia was diagnosed based on the criteria proposed by the Japan Society of Hepatology. Malnutrition was assessed using the GLIM criteria, subjective global assessment (SGA), and Royal Free Hospital-global assessment (RFH-GA) and their predictive ability for sarcopenia and mortality were assessed using the logistic regression analysis and the Cox proportional hazards regression model, respectively.

Results: Among the eligible 406 patients, 67% were men, the median age was 74 years, and 26% had sarcopenia. The prevalence of malnutrition according to the GLIM criteria, SGA, and RFH-GA was 21%, 35%, and 26%, respectively. Comparing malnourished with well-nourished patients, the odds ratio for complicating sarcopenia was 2.54 (95% confidence interval [CI], 1.44-4.49) for the GLIM criteria, 2.13 (95% CI, 1.09-4.15) for the SGA, and 2.78 (95% CI, 1.56-4.95) for the RFH-GA. During a median follow-up period of 2.0 years, 176 (43%) patients died. After adjusting for confounding factors, the GLIM criteria could independently predict mortality (hazard ratio, 1.95; 95% CI, 1.37-2.81).

Conclusions: The GLIM criteria are useful in identifying sarcopenia and predicting mortality in patients with CLD.

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Source
http://dx.doi.org/10.1111/hepr.13816DOI Listing

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