Identifying Metabolic Dysfunction-Associated Steatotic Liver Disease Using Natural Language Processing in a US National Cohort.

ABSTRACT:

Introduction

Although metabolic dysfunction-associated steatotic liver disease (MASLD) and MASLD with increased alcohol intake (MetALD) are identified as clinical entities; tools to identify patients from electronic health records (EHRs) to perform large outcome studies are lacking.

Methods

In this retrospective study of participants from the Veterans Analysis of Liver Disease cohort assembled from 1/1/2013 to 12/31/2022, a rule-based natural language processing (NLP) algorithm searched EHRs for imaging evidence of hepatic steatosis. This was combined with identification of cardiometabolic risk factors and harmful alcohol use. Algorithm-derived diagnoses of MASLD, MetALD, alcohol-associated steatotic liver disease (ALD), and no steatotic liver disease (SLD) were validated us

SUBMITTER: John BV 

PROVIDER: S-EPMC12264024 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature