Breakthrough in cardiology: AI could revolutionize heart attack treatments

Artificial intelligence could revolutionize the way heart attacks are treated. Researchers from the University of Zurich and several European partner institutions have presented a new AI model in The Lancet Digital Health that predicts risks and treatment outcomes for patients with acute coronary syndrome (ACS) far more accurately than previous methods. ACS is a circulatory disorder that affects the coronary arteries and significantly increases the risk of heart attacks.

The GRACE 3.0 model is based on health data from more than 600,000 patients across ten European countries and applies machine learning techniques such as XGBoost and Rboost to detect complex patterns in clinical data. Unlike the traditional GRACE 2.0 score, which relies on older datasets and linear models, the new version was developed specifically for patients with non-ST-elevation myocardial infarction (NSTEMI) – the most common type of heart attack.

The AI-powered models delivered impressive results. The in-hospital mortality model – which predicts whether a patient will die during their hospital stay – achieved an AUC of 0.90, clearly outperforming the previous scoring system. Predictions for one-year mortality were also considerably more accurate, with a time-dependent AUC of 0.84.

Individualized treatment strategies for myocardial infarction

The third component of GRACE 3.0 is particularly groundbreaking: individualized treatment prediction. Using the R-Learner algorithm, researchers were able to estimate for the first time how much a patient would personally benefit from early invasive treatment, such as cardiac catheterization. The results showed that only a subset of patients gained significant benefit from early intervention – particularly younger individuals, more often women, with stable kidney function and clear signs of ischemia.

For other patient groups, the treatment showed little to no benefit – or even a negative effect. According to the researchers, this insight could lead to a shift in clinical decision-making: instead of relying on fixed risk thresholds, future care should place greater emphasis on the individual treatment effect. “AI-based analysis could significantly improve post–heart attack care and enhance long-term cardiovascular health,” the research team from the University of Zurich emphasizes.

Despite its strengths – including a large dataset, high model quality and user-friendly design – the authors acknowledge several limitations. The data originates exclusively from Europe, and the findings on treatment effectiveness are still considered preliminary, requiring further validation in future studies. In the long term, however, GRACE 3.0 has strong potential to shape future clinical guidelines.