A study involving IDIAPJGol, Rovira i Virgili University (URV), and the Catalan Health Institute (ICS) proposes a new strategy for the early identification of individuals at high risk of stroke, particularly older women. The research, published in the scientific journal Journal of Clinical Medicine, employed a mathematical model to assess the potential clinical and economic benefits of an early detection system based on artificial intelligence.
This research is part of the doctoral thesis of Anna Panisello, a family physician with the ICS in the Terres de l’Ebre region and recipient of a predoctoral grant from IDIAPJGol. The thesis is co-supervised by Sílvia Reverté, a researcher with the CARING Advanced Nursing research group at URV, and Josep Lluís Clua, principal investigator of the EBRICTUS primary care research group in Terres de l’Ebre.
The study drew on real-world primary care data from the Terres de l’Ebre region, analyzing a population of 9.677 individuals aged 65 to 95 who were at high risk of atrial fibrillation, a heart rhythm disorder that increases the likelihood of a stroke and often goes unnoticed until a serious event occurs.
The researchers evaluated a strategy developed as part of the MATHIAS project, which combines data from electronic health records with artificial intelligence tools. This system could help identify individuals who might benefit from more targeted heart rhythm monitoring and an individualized assessment of preventive measures.
“Preventive strategies have not always sufficiently taken into account the specific risks faced by women, especially those under 60, a stage when intervention is crucial to avoid complications later on,” explains Reverté. In this regard, the study suggests that early identification of individuals at high cardiovascular risk could help prevent strokes and reduce associated disabilities. These potential benefits would be particularly significant for older women, who face a higher risk of thromboembolic events and may experience more severe functional consequences following a stroke.
The authors note, however, that this is a proof-of-concept study. The model will need to be validated in other populations, and prospective studies must be conducted to determine whether the estimated benefits translate into an actual reduction in strokes within clinical practice.
Bibliographic reference: Panisello-Tafalla, A.; Clua-Espuny, J.L.; Muria-Subirats, E.; Clua-Queralt, J.; Lucas-Noll, J.; Forcadell-Arenas, T.; Reverte-Villarroya, S. Sex-Specific Health and Economic Benefits in Older Women at Risk of Atrial Fibrillation: A Proof-of-Concept Evaluation of an AI-Enabled Strategy for Early Thromboembolic Risk Detection. J. Clin. Med. 2026, 15, 2861. https://doi.org/10.3390/jcm15082861
