AI can Better Predict Future Risk for Heart Attack Patients

A landmark study led by University' experts has shown that artificial intelligence can better predict how doctors should treat patients following a heart attack.

The study, conducted by an international team of researchers, led by the University of Leicester’s Honorary fellow, Doctor Florian Wenzl working closely with Professor David Adlam, both from the Department of Cardiovascular Sciences, has been published in The Lancet Digital Health.

Doctors caring for patients with the most common form of heart attack caused by a partial blockage, known as non-ST-elevation acute coronary syndrome (NSTE-ACS) - typically rely on the GRACE score to estimate a patients’ risk of dying or having another cardiovascular event. It is used to guide treatment decisions but has long been recognised as being unable to capture the full complexity of each patient.

However, the newly created GRACE 3.0 score is an advanced, AI-based risk assessment tool for patients with acute coronary syndromes. It is able to predict the probability of in-hospital and 1-year mortality by looking at nine widely available variables: age, sex, heart rate, systolic blood pressure, troponin level, ST-deviation, creatinine level, cardiac arrest, and heart failure symptoms.

Dr Wenzl said: "GRACE 3.0 represents the next evolution of the GRACE score, bringing AI methods into one of the most widely used risk tools in cardiology. It was trained and externally validated on data from hundreds of thousands of patients from multiple countries, which gives it a very strong evidence base. Unlike traditional risk scores, GRACE 3.0 captures complex and non-linear relationships that conventional approaches often miss."

"Another key improvement is that GRACE 3.0 is sex-specific and tailored precisely for patients with a partial blockage in their coronary artery, rather than being applied more broadly across those with other types of heart attacks caused by complete blockage in their coronary artery.

"In addition, the GRACE 3.0 score enables physicians to better predict whether or not patients will benefit from early invasive treatment such as angioplasty (to open the artery with a balloon and typically place a stent)."

Professor Adlam, an interventional cardiologist at the University, working within the Leicester NIHR Biomedical Research Centre, added: "This newly developed score, using artificial intelligence helps tailor treatment for patients by better detecting future risk and therefore guiding which health interventions they would benefit from.

"The GRACE 3.0 score is now increasingly being incorporated into international guidelines and may inform the design of future clinical trials."

Wenzl FA, Kofoed KF, Simonsson M, Ambler G, van der Sangen NMR, Lampa E, Bruno F, de Belder MA, Hlasensky J, Mueller-Hennessen M, Smolle MA, Wang P, Henriques JPS, Kikkert WJ, Kelbæk H, Bouček L, Raposeiras-Roubín S, Abu-Assi E, Azzahhafi J, Velders MA, Stellos K, Engstrøm T, Chan Pin Yin DRPP, Weston C, Adlam D, Rickli H, Giannitsis E, Radovanovic D, Parenica J, Antoniades CA, Fox KAA, D'Ascenzo F, Ten Berg JM, Køber LV, James S, Deanfield J, Lüscher TF.
Extension of the GRACE score for non-ST-elevation acute coronary syndrome: a development and validation study in ten countries.
Lancet Digit Health. 2025 Oct 16:100907. doi: 10.1016/j.landig.2025.100907

Most Popular Now

AI Tool Offers Deep Insight into the Imm…

Researchers explore the human immune system by looking at the active components, namely the various genes and cells involved. But there is a broad range of these, and observations necessarily...

Improved Cough-Detection Tech can Help w…

Researchers have improved the ability of wearable health devices to accurately detect when a patient is coughing, making it easier to monitor chronic health conditions and predict health risks such...

AI, Health, and Health Care Today and To…

Artificial intelligence (AI) carries promise and uncertainty for clinicians, patients, and health systems. This JAMA Summit Report presents expert perspectives on the opportunities, risks, and challenges of AI in health...

Multimodal AI Poised to Revolutionize Ca…

Although artificial intelligence (AI) has already shown promise in cardiovascular medicine, most existing tools analyze only one type of data - such as electrocardiograms or cardiac images - limiting their...

Do Fitness Apps do More Harm than Good?

A study published in the British Journal of Health Psychology reveals the negative behavioral and psychological consequences of commercial fitness apps reported by users on social media. These impacts may...

A New AI Model Improves the Prediction o…

Breast cancer is the most commonly diagnosed form of cancer in the world among women, with more than 2.3 million cases a year, and continues to be one of the...

New AI Tool Makes Medical Imaging Proces…

When doctors analyze a medical scan of an organ or area in the body, each part of the image has to be assigned an anatomical label. If the brain is...

AI can Better Predict Future Risk for He…

A landmark study led by University' experts has shown that artificial intelligence can better predict how doctors should treat patients following a heart attack. The study, conducted by an international...

AI System Finds Crucial Clues for Diagno…

Doctors often must make critical decisions in minutes, relying on incomplete information. While electronic health records contain vast amounts of patient data, much of it remains difficult to interpret quickly...

AI Tool Beats Humans at Detecting Parasi…

Scientists at ARUP Laboratories have developed an artificial intelligence (AI) tool that detects intestinal parasites in stool samples more quickly and accurately than traditional methods, potentially transforming how labs diagnose...

Making Cancer Vaccines More Personal

In a new study, University of Arizona researchers created a model for cutaneous squamous cell carcinoma, a type of skin cancer, and identified two mutated tumor proteins, or neoantigens, that...