Cirrhosis, MASLD - Metabolic Dysfunction-Associated Steatotic Liver Disease
Conditions
Brief summary
The goal of this prospective, multicenter, open-label, blinded end-point pragmatic study is to evaluate an artificial intelligence (AI)-augmented echocardiography screening approach for early detection of metabolic dysfunction associated steatotic liver disease (MASLD) and/or cirrhosis, in patients undergoing routine transthoracic echocardiograms (TTEs). The main question it aims to answer is to: 1. Evaluate notification responsiveness and rates of confirmatory testing for patients identified as high risk for having liver disease to determine whether optimized notifications increase timely confirmatory testing and treatment initiation versus standard of care assessment. 2. Compare time to diagnosis, treatment uptake, and clinical outcomes (hospitalizations, incident ASCVD, mortality) between cohorts identified as high risk by the AI algorithm and comparison groups to determine whether AI guided screening shortens time to diagnosis and increases appropriate treatment.
Interventions
OTHERAI-Enabled Identification (EchoNet-Liver)
AI-generated notifications to clinicians about possible undiagnosed liver disease (MASLD and/or Cirrhosis) detected from Transthoracic Echocardiogram
Sponsors
Kaiser Permanente
Stanford University
Massachusetts General Hospital
Cedars-Sinai Medical Center
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Adults ≥18 years. * Underwent routine TTE within site defined recent timeframe and flagged as high risk for MASLD and/or cirrhosis by the AI model using pre specified threshold. * Able to provide informed consent; reachable for follow up.
Exclusion criteria
* Inability to consent or communicate. * Enrollment in hospice or life expectancy so limited that additional evaluation would not be appropriate per clinician judgment. * Clinical circumstances where immediate alternative diagnostic pathways supersede study procedures (e.g., acute decompensation requiring urgent management). * Prior liver or kidney transplant. * Patient unwilling to undergo prospective testing for liver disease.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Positive Predictive Value (PPV) of the AI algorithm for detecting MASLD and/or cirrhosis confirmed within 12 months of AI identification. | From enrollment to end of follow up at 1 year. | Numerator: Participants with clinician-confirmed diagnosis of later stage MASLD and/or cirrhosis after confirmatory evaluation. Denominator: * Participants with positive AI screen who were enrolled and evaluated. * The intervention is the clinician referral or referral testing workflow. The clinicians ultimately have discretion to avoid further downstream testing if pretest probability is felt to be too low. If a clinician determines no further testing is warranted despite high risk assessment by AI, the participant will be classified as a false positive (still counted in the denominator). |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Hepatic decompensation hospitalization | Followed up to 24 months post notification. | Time (days) from AI identification for hepatic decompensation hospitalization (defined by ascites, hepatic encephalopathy, variceal bleeding, hepatocellular carcinoma, or liver transplantation) |
| New ASCVD diagnosis | Followed up to 24 months post notification. | Time (days) from AI identification |
| All-cause hospitalization | Followed up to 24 months post notification. | Time (days) from AI identification |
| Heart failure hospitalization | Followed up to 24 months post notification. | Time (days) from AI identification (Defined as admission with IV diuretics or elevated BNP) |
| Time to diagnosis of MASLD/cirrhosis | Followed up to 24 months post notification. | Time (days) from AI identification to first confirmatory diagnosis |
| Time to diagnosis for MASLD with F2 fibrosis or greater | Followed up to 24 months post notification. | Time (days) from AI identification to first confirmatory diagnosis |
| Time to diagnosis for steatotic liver disease | Followed up to 24 months post notification. | Time (days) from AI identification to first confirmatory diagnosis |
| Time to confirmatory imaging | Followed up to 24 months post notification. | Time (days) from AI identification |
| Time to initiation of targeted treatment | Followed up to 24 months post notification. | Time (days) from AI identification |
| Cardiovascular hospitalization | Followed up to 24 months post notification. | Time (days) from AI identification for Cardiovascular hospitalization (defined by principal ICD9/10 code) |
| All-cause mortality | Followed up to 24 months post notification. | Time (days) from AI identification |
Countries
United States
Outcome results
None listed