NEW RESEARCH has demonstrated that an AI-enabled ECG tool can double early detection of liver cirrhosis in primary care, allowing clinicians to intervene before irreversible damage and serious complications develop.
Why Liver Cirrhosis Often Goes Unnoticed
Liver cirrhosis represents the end stage of advanced chronic liver disease, which affects an estimated 2–5% of the general population. Rising rates of obesity, type 2 diabetes, high blood pressure, and sleep apnea are driving increases in undiagnosed disease. Patients frequently present late, once symptoms such as jaundice, gastrointestinal bleeding, or fluid retention appear. These signs indicate significant scarring has already occurred, limiting treatment options. Because early liver cirrhosis is often asymptomatic, primary care clinicians need accessible screening tools that fit into routine practice without adding complexity or cost.
AI ECG Trial Targets Liver Cirrhosis Detection
In a pragmatic cluster randomised clinical trial, 98 primary care teams were assigned to either an intervention arm with access to ECG based machine learning results or usual care. A total of 15,596 adults undergoing routine 12 lead ECGs met inclusion criteria, including 8,034 in the intervention group and 7,562 controls. Clinicians were alerted when ECG patterns suggested higher risk of advanced liver disease, prompting targeted follow up testing. Within 180 days, new diagnoses of advanced chronic liver disease were higher in the intervention group at 1.0% compared with 0.5% in controls, with an odds ratio of 2.09 and P = 0.007. Among ECG ML positive patients, detection rose to 4.4% versus 1.1%, with an odds ratio of 4.37 and P < 0.001. Detection of any fibrosis also increased to 1.7% versus 0.5% overall, and 8.4% versus 1.1% among ECG ML positive patients.
Implications for Clinical Practice
These findings suggest ECG-based AI could support earlier identification of liver cirrhosis in everyday primary care settings. Earlier diagnosis enables timely lifestyle interventions, disease modifying treatment, and specialist referral, potentially reducing future need for liver transplantation. As clinician adherence improves and AI guidance becomes embedded in workflows, ECG screening may become a practical case finding tool for high-risk populations.
Reference
Simonetto DA et al. Detection of undiagnosed liver cirrhosis via AI-enabled electrocardiogram: a pragmatic, cluster-randomized clinical trial. Nat Med. 2025;DOI:10.1038/s41591-025-04058-y.


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