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HeartSciences’ Announces Peer-Reviewed Publication Evaluating Use of MyoVista® Technology to Detect Asymptomatic Left Ventricular Dysfunction in Patients with Type 2 Diabetes

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HeartSciences (NASDAQ: HSCS) announces a study showing MyoVista AI-ECG model outperforms NT-proBNP and ARIC HF score in Stage B Heart Failure screening among type 2 diabetes patients. The study highlights the potential of AI-ECG technology to enhance heart disease detection and screening processes.
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The recent study highlighting the MyoVista AI-ECG model's superior performance in detecting Stage B Heart Failure (SBHF) in patients with type 2 diabetes (T2DM) represents a significant advancement in cardiovascular diagnostics. The traditional biomarker NT-proBNP and the ARIC HF risk score have been widely used in clinical settings to screen for heart failure. However, the MyoVista AI-ECG model's ability to outperform these methods suggests a potential shift in the standard of care towards more technologically advanced screening tools.

From a cardiological perspective, the implications of this study are profound. Early detection of SBHF can significantly alter patient management and outcomes. AI-ECG models like MyoVista can potentially lead to earlier interventions, tailored treatment plans and improved patient education on disease management. Moreover, the non-invasive nature of ECG screening compared to blood tests offers a more patient-friendly approach to regular monitoring, which is critical in managing chronic conditions like T2DM.

As a Medical Research Analyst, the focus would be on the robustness of the study's design and its implications for future research and development in medical technology. The peer-reviewed nature of the study and its publication in a reputable journal like Cardiovascular Diabetology lend credibility to the findings. Additionally, the potential for AI-ECG to act as a guidance tool for echocardiogram confirmation could streamline the diagnostic process and reduce healthcare costs associated with unnecessary testing.

One must consider the scalability of MyoVista's technology and the associated training required for healthcare professionals to interpret AI-ECG results accurately. It's also critical to evaluate the long-term clinical outcomes from using AI-ECG models. Further research would be needed to confirm these findings across diverse populations and to assess the economic impact on healthcare systems.

The economic implications of introducing AI-ECG technology into standard practice for heart failure screening are multifaceted. On one hand, the use of AI-ECG could reduce the long-term costs of heart failure management by enabling earlier detection and treatment, potentially decreasing hospital readmission rates and the need for more expensive interventions later in the disease course.

On the other hand, the initial investment in AI technology and the associated costs of integrating it into existing healthcare infrastructure must be considered. There is a balance to be struck between the upfront costs of adopting new technologies and the long-term savings from improved patient outcomes. Additionally, the widespread adoption of AI-ECG could have a significant impact on the market for traditional diagnostic tests and may lead to shifts in healthcare spending.

Data Demonstrated MyoVista AI-ECG model significantly outperformed NT-proBNP and ARIC HF score, the conventional standards of care for Stage B Heart Failure screening

Southlake, Texas, March 12, 2024 (GLOBE NEWSWIRE) -- Heart Test Laboratories, Inc. d/b/a HeartSciences (NASDAQ: HSCS; HSCSW) (“HeartSciences” or the “Company”), an artificial intelligence (AI)-powered medical technology company focused on transforming ECGs/EKGs to save lives through earlier detection of heart disease, today announced the publication, in Cardiovascular Diabetology, of an independent, peer-reviewed study utilizing its MyoVista® proprietary technology.

Recent guidelines propose N-terminal pro-B-type natriuretic peptide (blood test for NT-proBNP protein marker) for recognition of asymptomatic left ventricular (LV) dysfunction (Stage B Heart Failure, SBHF) in type 2 diabetes (T2DM) patients. Accordingly, the study sought to evaluate whether an AI-ECG model based on MyoVista® wavECG™ features was superior to NT-proBNP, as well as a conventional screening tool—the Atherosclerosis Risk in Communities (ARIC) HF risk score, in SBHF screening among patients with T2DM.

The authors of the publication stated, “Among patients with T2DM, the accuracy of ewECG (MyoVista® wavECG™) model in SBHF screening was shown to be significantly higher than both NT-proBNP and the ARIC HF risk score,” and concluded, “Machine learning based modelling using additional ewECG extracted features are superior to NT-proBNP and ARIC HF in SBHF screening among patients with T2DM, providing an alternative HF screening strategy for asymptomatic patients and potentially act as a guidance tool to determine those who required echocardiogram to confirm diagnosis.” 1

“Around 38 million people in the United States and approximately 500 million people globally have diabetes, a major cause of cardiovascular health issues. This independent study provides evidence of the clinical and diagnostic capabilities of AI-ECG, and specifically our MyoVista wavECG technology, to potentially advance current standards of care for heart screening in diabetic patients.” said Andrew Simpson, Chief Executive Officer of HeartSciences. “Globally cardiovascular disease accounts for approximately one-third of all annual deaths and AI-ECG is set to change medicine by providing the opportunity to detect heart disease earlier and more effectively, not only for diabetic patients, but also for a significant number of at-risk patients. We look forward to continued progress developing our extensive portfolio of AI-based ECG/EKG algorithms and bring new AI-powered ECG capabilities to the healthcare community.”

1 - Use of the energy waveform electrocardiogram to detect subclinical left ventricular dysfunction in patients with type 2 diabetes mellitus Cheng Hwee Soh1,2, Alex G. C. de Sá2,3,4,5, Elizabeth Potter1, Amera Halabi1, David B. Ascher2,3,4,5 and Thomas H. Marwick1,2,6*

About HeartSciences

Heart Test Laboratories, Inc. d/b/a HeartSciences is a medical technology company focused on applying innovative AI-based technology to an ECG (also known as an EKG) to expand and improve an ECG's clinical utility. Millions of ECGs are performed every week and the Company's objective is to improve healthcare by making it a far more valuable cardiac screening tool, particularly in frontline or point-of-care clinical settings. HeartSciences has one of the largest libraries of AI-ECG algorithms and intends to provide these AI-ECG algorithms on a device agnostic cloud-based solution as well as a low-cost ECG hardware platform. Working with clinical experts, HeartSciences ensures that all solutions are designed to work within existing clinical care pathways, making it easier for clinicians to use AI-ECG technology to improve their patient's care and lead to better outcomes. HeartSciences' first product candidate for FDA clearance, the MyoVista® wavECG™, or the MyoVista®, is a resting 12-lead ECG that is also designed to provide diagnostic information related to cardiac dysfunction which has traditionally only been available through the use of cardiac imaging. The MyoVista® also provides conventional ECG information in the same test.

For more information, please visit: https://www.heartsciences.com. X: @HeartSciences

Safe Harbor Statement

This announcement contains forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. These forward-looking statements are made under the "safe harbor" provisions of the Private Securities Litigation Reform Act of 1995 and relate to the Company's future financial and operating performance. All statements, other than statements of historical facts, included herein are "forward-looking statements" including, among other things, statements about HeartSciences' beliefs and expectations. These statements are based on current expectations, assumptions and uncertainties involving judgments about, among other things, future economic, competitive and market conditions and future business decisions, all of which are difficult or impossible to predict accurately and many of which are beyond the Company's control. The expectations reflected in these forward-looking statements involve significant assumptions, risks and uncertainties, and these expectations may prove to be incorrect. Investors should not place undue reliance on these forward-looking statements, which speak only as of the date of this press release. Potential risks and uncertainties include, but are not limited to, risks discussed in HeartSciences' Annual Report on Form 10-K for the fiscal year ended April 30, 2023, filed with the U.S. Securities and Exchange Commission (the "SEC") on July 18, 2023, HeartSciences' Quarterly Report on Form 10-Q for the fiscal quarter ended October 31, 2023, filed with the SEC on December 14, 2023, and in HeartSciences' other filings with the SEC at www.sec.gov. Other than as required under the securities laws, the Company does not assume a duty to update these forward-looking statements.

Contacts:

HeartSciences
Gene Gephart
+1-682-244-2578 (US)
info@heartsciences.com

Investors
Gilmartin Group
Vivian Cervantes
investorrelations@heartsciences.com


FAQ

How does MyoVista AI-ECG model compare to NT-proBNP and ARIC HF score in Stage B Heart Failure screening?

The study demonstrated that the MyoVista AI-ECG model outperformed both NT-proBNP and ARIC HF score in screening for Stage B Heart Failure among patients with type 2 diabetes.

What publication featured the study on MyoVista AI-ECG technology?

The study was published in Cardiovascular Diabetology, showcasing the effectiveness of MyoVista AI-ECG technology in detecting subclinical left ventricular dysfunction in type 2 diabetes patients.

How many people in the United States and globally have diabetes?

Around 38 million people in the United States and approximately 500 million people globally have diabetes, making it a significant contributor to cardiovascular health issues.

What did the study conclude about the use of AI-ECG technology in heart screening for diabetic patients?

The study concluded that AI-ECG technology, specifically MyoVista wavECG technology, has the potential to advance current standards of care for heart screening in diabetic patients by providing a more effective screening strategy.

Who is the Chief Executive Officer of HeartSciences?

Andrew Simpson is the Chief Executive Officer of HeartSciences.

HeartSciences Inc.

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