Integrated Diagnostics for Early Diagnosis of Liver Disease

Summary

Participation Requirements

Description

Liver disease is a silent epidemic. Four in ten people in the North West are likely to have evidence of liver disease. A small but significant proportion of these patients develop scarring, leading to end-stage cirrhosis. All too frequently this is detected in very advanced stages, where treatment c...

Liver disease is a silent epidemic. Four in ten people in the North West are likely to have evidence of liver disease. A small but significant proportion of these patients develop scarring, leading to end-stage cirrhosis. All too frequently this is detected in very advanced stages, where treatment cannot reverse the condition. It is one of the UK's largest health challenges. At present clinicians use a wide range of single tests that individually struggle to identify disease and high-risk patients early. The Investigators are implementing a new pathway for the assessment of patients with abnormal liver blood tests or high risk for liver disease. This novel pathway will allow assessment of patients in Community Liver Assessment Clinics (CLAC) with the expectation that only 20% of patients assessed would need to be seen in secondary care for further assessment. The investigators expect, to be assessing, 750 patients per year in this pathway. This pathway will bring together a large group of patients with liver disease. As part of the clinical assessment the investigators will be undertaking investigations to diagnose disease and assess extent. This will generate significant information, that the investigators currently use in isolation to make the aforementioned assessments. In this study, the investigators would like to bring together all this data into a curated database. To this end, the investigators would offer all patients who attend the CLAC for clinical need to enrol into the study. This would generate a database to combine all data, alongside some other, non-invasive tests, done alongside routine clinical tests. This project will address this lack of answers by teaming up with innovative companies to make software that joins together a wide range of different tests to make an algorithm to detect disease earlier.

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