Occult liver disease burden: Analysis from a large general practitioners' database. Issue 7 (1st November 2017)

• Record Type: Journal Article
• Authors: Martini, Andrea; Ceranto, Elena; Gatta, Angelo; Angeli, Paolo; Pontisso, Patrizia
• Is Part Of: United European Gastroenterology journal. Volume 5:Issue 7(2017)
• Page Start: 982
• Page End: 986
• Publication Date: 2017-11-01
• Subjects: Chronic liver disease -- liver cirrhosis -- liver disease epidemiology -- surrogate indicators -- metabolic syndrome; Gastroenterology -- Periodicals; Periodicals; 616.33005
• DOI: 10.1177/2050640617696402
• Languages: English
• ISSNs: 2050-6406

Abstract

Abstract : Background: Cirrhosis represents the end stage of chronic liver disease, characterized by high mortality and morbidity. The prevalence of liver disease is difficult to assess, given its clinical latency up to the late stage. Objective: We aimed to assess the prevalence of unrecognized chronic liver disease and cirrhosis using surrogate indicators from medical records of family physicians. Methods: Medical records of 139, 104 subjects, collected from 99 family physicians of the Veneto region, were used. Persistently high transaminases were used as indicators of occult chronic liver disease; thrombocytopenia, unrelated to haematological malignancies, was used as indicator of occult cirrhosis. Diagnosis of chronic liver disease and cirrhosis was assessed using ICD9‐CM‐1997 codes. Results: Alteration of transaminases was found in 32.7% of the subjects, and among them only one‐third had an already diagnosed liver disease. Patients with diagnosis of cirrhosis were 0.3%, while thrombocytopenia, indicator of occult cirrhosis, was detected in 1.3% of the remaining population. Patients with overt and occult cirrhosis showed a higher metabolic profile, with significantly higher prevalence of arterial hypertension, obesity and diabetes than the general population. Conclusion: A large proportion of patients with chronic liver disease is still undiagnosed. Surrogate biochemical indicators might be useful for disease recognition.