Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

medicine

Predicting portal hypertension and variceal bleeding using non-invasive measurements of metabolic variables

Annals of Hepatology, Volume 12, No. 4, Year 2013

Background & aim. This study assessed the involvement of metabolic factors (anthropometric indices, insulin resistance (IR) and adipocytokines) in the prediction of portal hypertension, esophageal varices and risk of variceal bleeding in cirrhotic patients. Material and methods. Two prospective and retrospective cohorts of cirrhotic patients were selected (n = 357). The first prospective cohort (n = 280) enrolled consecutively in three centers, underwent upper gastrointestinal endoscopy, seeking evidence of esophageal varices. Clinical, anthropometric, liver function tests, ultrasonographic, and metabolic features were recorded at the time of endoscopy, patients were followed-up every 6 months until death, liver transplantation or variceal bleeding. The second retrospective cohort (n = 48 patients) had measurements of the hepatic venous pressure gradient (HVPG). Statistical analyses of the data were with the SPSS package. Results. The presence of esophageal varices was independently associated with lower platelet count, raised HOMA index and adiponectin levels. This relationship extended to subset analysis in patients with Child A cirrhosis. HOMA index and adiponectin levels significantly correlated with HVPG. Beside Child-Pugh class, variceal size and glucagonemia, HOMA index but not adiponectin and leptin plasma levels were associated with higher risk of variceal bleeding. Conclusion. In patients with cirrhosis, HOMA score correlates with HVPG and independently predict clinical outcomes. Three simple markers i.e. platelet count, IR assessed by HOMA-IR and adiponectin significantly predict the presence of esophageal varices in cirrhotic patients.
Statistics
Citations: 37
Authors: 14
Affiliations: 3
Research Areas
Maternal And Child Health
Noncommunicable Diseases
Study Design
Cohort Study
Study Approach
Quantitative