Health
Artificial intelligence guides personalized treatment for heart patients
A groundbreaking international study led by the University of Zurich has shown that artificial intelligence can more accurately assess a patient's risk for the most common types of heart attack than existing methods. This could allow doctors to guide more individualized treatment decisions for patients.
Physicians treating patients with the most common type of heart attack, so-called non-ST-elevation acute coronary syndrome (NSTE-ACS), have traditionally relied on standardized scoring systems. The GRACE score can be used to estimate risk and determine the optimal timing for catheter treatment. This score is widely used and increasingly incorporated into international clinical guidelines. However, it has long been recognized that existing tools do not always fully capture the complexity of these patients.
Data from over 600,000 patients
New research published in lancet digital health It has now been suggested that many patients may need to be reclassified, which could have important implications for how heart attacks are treated around the world. In the largest NSTE-ACS risk modeling study to date, an international research team led by the University of Zurich (UZH) analyzed health data for more than 600,000 patients in 10 countries.
They used artificial intelligence (AI) to analyze clinical trial data from the landmark VERDICT trial, allowing the model to recognize which patients would benefit most from early invasive treatments such as angiography and stent placement.
New risk classification required
“The results were surprising: some patients benefited greatly from early intervention, while others showed little benefit,” said lead author Florian A. Wenzl, from the UZH Center for Molecular Cardiology, who also conducts research in the UK's National Health Service. The researchers say this shows that current treatment strategies may be targeting the wrong patients in some cases. Therefore, significant re-stratification of patient care that assesses the individual benefits of established treatment strategies may be required in hospitals around the world.
According to Wenzl, this study shows how AI can transform heart attack treatment. “By reanalyzing clinical trial data, our model GRACE 3.0 learned who actually benefits from early invasive treatment and who doesn't. This may imply changes in how these patients are managed.”
More personalized and effective care
“GRACE 3.0 is the most advanced and practical tool to date for treating patients with the most common types of heart attacks,” explains final author Thomas F. Ruscher, who is conducting research at the Center for Molecular Cardiology in Zurich and the Royal Brompton and Harefield Hospitals in London. The new score can be used not only to more accurately predict risk, but also to guide more personalized treatment decisions. “This could help reshape future clinical guidelines and save lives,” Luscher added.
Researchers hope that the new GRACE 3.0 score will provide everyday clinicians with a simple, validated, AI-powered tool to provide more personalized and effective care for heart attack patients.
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