Can routine blood tests be modelled to detect advanced liver disease in the community: model derivation and validation using UK primary and secondary care data.

ABSTRACT:

Objectives

Most patients are unaware they have liver cirrhosis until they present with a decompensating event. We therefore aimed to develop and validate an algorithm to predict advanced liver disease (AdvLD) using data widely available in primary care.

Design, setting and participants

Logistic regression was performed on routinely collected blood result data from the University Hospital Southampton (UHS) information systems for 16 967 individuals who underwent an upper gastrointestinal endoscopy (2005-2016). Data were used to create a model aimed at detecting AdvLD: 'CIRRhosis Using Standard tests' (CIRRUS). Prediction of a first serious liver event (SLE) was then validated in two cohorts of 394 253 (UHS: primary and secondary care) and 183 045 individuals (Care and Health

SUBMITTER: Hydes T 

PROVIDER: S-EPMC7925927 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature