Clinical Decision Support for Heart Failure Risk in Diabetes

Overseen By Ambarish Pandey, MD

Age: Any Age

Sex: Any

Trial Phase: Academic

Sponsor: University of Texas Southwestern Medical Center

Must not be taking: SGLT2-inhibitors, GLP1-RAs

Disqualifiers: History of HF, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

800 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial aims to test a new tool that helps doctors predict and prevent heart failure in people with type 2 diabetes. The tool, called the Ultromics EchoGo HFpEF Algorithm, uses advanced analysis to alert doctors about potential heart issues and suggests treatments like SGLT-2 inhibitors and GLP-1 RAs, which help manage diabetes and can reduce heart risk. One group of doctors will receive these alerts, while another group will receive standard treatment messages. People with type 2 diabetes who have a recent echocardiogram (a heart ultrasound) and no history of heart failure might be a good fit for this trial. As an unphased trial, this study offers a unique opportunity to contribute to groundbreaking research that could improve heart health management for people with type 2 diabetes.

Will I have to stop taking my current medications?

If you are currently using SGLT2-inhibitors or GLP1-RA medications, you will need to stop taking them to participate in this trial.

What prior data suggests that the Ultromics EchoGo HFpEF Algorithm is safe for use in clinical decision support?

Research has shown that the Ultromics EchoGo HFpEF Algorithm is safe. The FDA has approved it, confirming it meets safety standards. A study found the algorithm effective and safe for detecting heart failure with preserved ejection fraction (HFpEF). This tool uses artificial intelligence to identify and manage heart failure risks in people with diabetes.

No specific reports have indicated problems caused by the algorithm itself. It primarily aids doctors in recommending standard treatments for preventing heart failure. Since it suggests treatments that are already approved, it is well-tolerated. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about this trial because it aims to enhance heart failure management in diabetes patients by providing doctors with real-time, AI-driven insights. Unlike traditional treatments that rely on standard guidelines, the Ultromics EchoGo HFpEF Algorithm offers a cutting-edge approach by analyzing echocardiogram data to detect subclinical heart failure with preserved ejection fraction (HFpEF). This AI-based alert system can guide healthcare providers with personalized recommendations for using medications like SGLT-2 inhibitors and GLP-1 receptor agonists, especially in patients with obesity. By integrating advanced AI diagnostics into routine care, this trial could lead to more precise, timely interventions, potentially improving patient outcomes significantly.

What evidence suggests that the Ultromics EchoGo HFpEF Algorithm is effective for heart failure risk prevention in diabetes?

This trial evaluates the Ultromics EchoGo HFpEF Algorithm for its ability to diagnose a type of heart failure called HFpEF with 90% accuracy. Providers of participants in the EHR Alert Group will receive a computer-based alert from the EchoGo algorithm, notifying them of subclinical HFpEF and providing guideline recommendations for management. This AI tool identifies patients who might need hospital care for heart failure, potentially reducing the need for expensive tests. By alerting doctors to early signs of HFpEF, it aids in following recommended treatments. Early detection and treatment may help prevent heart failure in patients with diabetes. ^{1 2 3 4 6}

Who Is on the Research Team?

Ambarish Pandey, MD

Principal Investigator

UT Southwestern Medical Center

Are You a Good Fit for This Trial?

This trial is for patients with Type 2 Diabetes who are at risk of developing heart failure. Specific eligibility criteria have not been provided, but typically participants would need to meet certain health conditions and agree to follow the study procedures.

Inclusion Criteria

I have Type 2 diabetes with a high WATCH DM score.

Echocardiogram available in last 6-months

Exclusion Criteria

I am currently using GLP1-RA medication.

I am currently taking SGLT2-inhibitor medication.

No echocardiogram within 6-months

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Intervention

Providers receive alerts for patients with subclinical HFpEF, guiding them on standard-of-care recommendations

6 months

Ongoing monitoring through EHR

Follow-up

Adherence to SGLT-2i and GLP-1 RA medications assessed, and heart failure hospitalization events monitored

12 months

What Are the Treatments Tested in This Trial?

Interventions

• Ultromics EchoGo HFpEF Algorithm

Trial Overview The trial is testing a new tool called Ultromics EchoGo that works within electronic health records. It analyzes patient data to identify those at high risk of heart failure and suggests treatments to prevent it.

How Is the Trial Designed?

Group I: EHR Alert Group Experimental Treatment 1 Intervention

Provider will receive a computer-based alert notifying them that the patient has subclinical HFpEF as determined by the Ultromics EchoGo algorithm and associated guideline recommendations for the management of these patients. The alert will include guideline-based and standard-of-care recommendations for the use of SGLT-2 inhibitors and/or GLP-1 RA (if obesity is present). The purpose of the alert is to inform the providers about the risk of heart failure and provide them guidance regarding the guideline-recommended standard of care. The providers can choose to provide care as deemed fit based on the information provided

Group II: Standard Message Group Active Control 1 Intervention

We will provide a standard message to the provider detailing guideline-recommended medications for type 2 diabetes. This will not contain information about the Ultromics EchoGo algorithm. The providers can choose to provide care as deemed fit based on the information provided

Who Is Running the Clinical Trial?

University of Texas Southwestern Medical Center

Lead Sponsor

Trials

1,102

Recruited

1,077,000+

Citations

1. clinicaltrials.gov clinicaltrials.gov/study/NCT06593314

NCT06593314 | Using Ultromics EchoGo HFpEF Algorithm ... This alert will inform the provider of guideline directed treatment options for patients with diabetes to prevent heart failure. What is the study measuring?

2. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC11937413/

External validation of artificial intelligence for detection ... As such, in this study, we aimed to externally validate the performance of an AI HFpEF model (EchoGo Heart Failure, Ultromics Ltd) in an ...

3. ultromics.com ultromics.com/products/echogo-heart-failure

Next-generation Echocardiography is here Quickly and accurately diagnose heart failure with preserved ejection fraction (HFpEF) with EchoGo Heart Failure - 90% accuracy, less costly procedures..

4. ultromics.com ultromics.com/press-releases/study-confirms-ai-based-detection-of-hfpef-is-linked-to-cardiac-outcomes

Study Confirms AI-Based Detection of HFpEF is Linked to ... Our study demonstrates that the AI model not only accurately identifies patients at increased risk of heart failure hospitalization and cardiac ...

5. ultromics.com ultromics.com/proof/jcf-2024-unmasking-hfpef-with-artificial-intelligence-a-disruptive-opportunity-for-disease-detection

Unmasking HFpEF with Artificial Intelligence A Disruptive ... Discover how Automated Echocardiographic Detection of Heart Failure With Preserved Ejection Fraction Using Artificial Intelligence explores ...

6. prnewswire.com prnewswire.com/news-releases/ultromics-introduces-ai-powered-probability-scoring-on-echogo-heart-failure-for-enhanced-hfpef-diagnosis-302414266.html

Ultromics Introduces AI-Powered Probability Scoring on ... A first-of-its-kind AI-powered probability scoring system for assessing heart failure with preserved ejection fraction (HFpEF).