Screening Cardiometabolic Opportunities Using Transformative Echocardiography Artificial Intelligence (SCOUT Echo-AI)

NCT07216859 — Not applicable, Not yet recruiting, 2000 participants, Kaiser Permanente

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Registry	NCT07216859, acronym SCOUT Echo-AI
Status	Not yet recruiting
Phase	Not applicable
Study type	Interventional; na, single group, masking: none, diagnostic
Enrollment	2000 (Estimated)
Sponsor	Kaiser Permanente (Other); collaborators: Stanford University, Massachusetts General Hospital, Cedars-Sinai Medical Center
Conditions	MASLD - Metabolic Dysfunction-Associated Steatotic Liver Disease, Cirrhosis
Interventions	AI-Enabled Identification (EchoNet-Liver) (Other)
Dates	start 2028-01-01 (estimated), primary completion 2028-11-01 (estimated), completion 2028-11-01 (estimated), first posted 2025-10-15, last updated 2026-08-13
Locations	6 sites in United States

-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.

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+Arms and interventions

Arm	Type	Interventions	Description
AI Notification (EchoNet-Liver-Flagged patients)	Experimental	Other: AI-Enabled Identification (EchoNet-Liver)	Participants whose prior transthoracic echocardiograms are flagged by an AI model (EchoNet-Liver) as high risk for MASLD and/or cirrhosis, a notification is delivered to the primary treating clinician, or undergoes a structured diagnostic workflow for standard of care at their site.

AI-Enabled Identification (EchoNet-Liver) (Other): AI-generated notifications to clinicians about possible undiagnosed liver disease (MASLD and/or Cirrhosis) detected from Transthoracic Echocardiogram

+Outcome measures

Primary outcomes

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 outcomes

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
All-cause mortality [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)
Cardiovascular hospitalization [Followed up to 24 months post notification.]: Time (days) from AI identification for Cardiovascular hospitalization (defined by principal ICD9/10 code)
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

+Eligibility

Sex: All, ages: 18 Years to any

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.

+Locations (6)

Facility	City	Country
Cedars-Sinai Medical Center	Los Angeles, California	United States
UCLA	Los Angeles, California	United States
Stanford Healthcare	Palo Alto, California	United States
Kaiser Permanente	Pleasanton, California	United States
Northwestern Medicine	Chicago, Illinois	United States
Massachusetts General Hospital	Boston, Massachusetts	United States