Atrial fibrillation (AF) is the most common cardiac arrhythmia, increasing the risk of ischemic stroke fivefold. However, up to 30% of strokes remain of undetermined cause, even after a comprehensive evaluation. Atrial cardiomyopathy, an emerging concept, could explain this discrepancy. It encompasses alterations in atrial cardiac tissue, from its histological structure to its electrophysiological function, promoting the formation of blood clots independently of AF.
Our Research Axes:
- Population Studies Through the Dijon Stroke Registry, led by Prof. Yannick Béjot, we have analyzed the evolution of atrial fibrillation (AF) and its risk factors in stroke patients within the Dijon population. This approach revealed an underuse of anticoagulants in at-risk patients, highlighting the importance of raising awareness among prescribing physicians(1). Our research also shows a link between cognitive disorders and AF, independent of visible brain lesions(2). These results suggest that AF could contribute to cognitive disorders well before the onset of a stroke. Additionally, we have identified differences in patient profiles based on the duration of AF, emphasizing the need for a more precise approach to this disease(3, 4).
- Physiopathological Approach – SAFAS Study The SAFAS study, conducted at the Dijon University Hospital, aimed to characterize atrial cardiomyopathy through a multimodal approach(5): echocardiography, innovative biomarkers, and intensive cardiac monitoring. The results show that this approach better predicts the occurrence of AF after a stroke(6). By comparing traditional atrial cardiomyopathy criteria with new biomarkers, we have identified more reliable predictors, offering promising prospects for preventive management(7). We have also identified specific characteristics in patients with a patent foramen ovale, a common cardiac anomaly(8).
- Innovative Diagnostic Strategies Since 2018, the Dijon University Hospital has systematically combined a cardiac scan with emergency brain imaging during suspected stroke cases. This innovation, made possible by an advanced AI-guided scanner, allows for the simultaneous analysis of the brain and heart. We have found that 11% of stroke patients have intracardiac thrombi, even without a history of AF(9). By analyzing the volume of the left atrium and epicardial fat, we refine the diagnosis and prediction of AF (10, 11). These results pave the way for early detection of at-risk patients and the rapid implementation of appropriate anticoagulant treatments.
Ongoing Projects
FIBROSIS-MR: This study, initiated in 2024, employs cardiac MRI to quantify left atrial fibrosis in patients following cryptogenic stroke. The aim is to demonstrate that these parameters can predict the onset of AF.
RHU TALENT: In collaboration with the Bordeaux University Hospital, this project aims to develop a predictive tool using artificial intelligence to identify patients at risk of cardioembolic stroke through accessible data such as ECG or chest scan.
ANR METAPROFIL: Establishment of two cohorts of 150 patients post-stroke and post-ablation of persistent AF, aiming to understand the role of BDNF as a marker of atrial cardiopathy and its cardioembolic and rhythmic complications. This clinical study complements the fundamental research conducted within the PEC2 laboratory in partnership with the Montpellier team.
Our ambition is to transform stroke prevention by integrating these new insights into clinical practice. By enhancing the screening of atrial cardiopathy, we aim to significantly reduce the risk of cardioembolic stroke and prevent associated neurocognitive complications.
1. Gabet A, Guenancia C, Duloquin G, Olie V, Bejot Y. Ischemic Stroke With Atrial Fibrillation: Characteristics and Time Trends 2006 to 2017 in the Dijon Stroke Registry. Stroke. 2021;52(6):2077-85.
2. Mitaine A, Duloquin G, Pommier T, Vergely C, Guenancia C, Bejot Y. Prevalence and Characteristics of Known versus Newly Detected Atrial Fibrillation in Ischemic Stroke: A Population-Based Study. Neuroepidemiology. 2024;58(4):284-91.
3. Guenancia C, Bejot Y. Atrial Fibrillation Already Known Versus Detected After Stroke: Same Battle? J Am Heart Assoc. 2024;13(17):e036138.
4. Pommier T, Duloquin G, Pinguet V, Comby PO, Guenancia C, Bejot Y. Atrial fibrillation and preexisting cognitive impairment in ischemic stroke patients: Dijon Stroke Registry. Arch Gerontol Geriatr. 2024;123:105446.
5. Benali K, Duloquin G, Noto-Campanella C, Garnier L, Didier R, Pommier T, et al. Efficacy and clinical implications of a stepwise screening strategy for atrial fibrillation after stroke: Insights from the SAFAS study. Arch Cardiovasc Dis. 2024;117(11):616-23.
6. Garnier L, Duloquin G, Meloux A, Benali K, Sagnard A, Graber M, et al. Multimodal Approach for the Prediction of Atrial Fibrillation Detected After Stroke: SAFAS Study. Front Cardiovasc Med. 2022;9:949213.
7. Didier R, Garnier L, Duloquin G, Meloux A, Sagnard A, Graber M, et al. Distribution of atrial cardiomyopathy markers and association with atrial fibrillation detected after ischaemic stroke in the SAFAS study. Stroke Vasc Neurol. 2024;9(2):165-73.
8. Pommier T, Lafont A, Didier R, Garnier L, Duloquin G, Meloux A, et al. Factors associated with patent foramen ovale-related stroke: SAFAS study. Rev Neurol (Paris). 2024;180(1-2):33-41.
9. Bernard A, Leclercq T, Comby PO, Duloquin G, Ricolfi F, Bejot Y, et al. High rate of cardiac thrombus diagnosed by adding cardiac imaging in acute stroke computed tomography protocol. Int J Stroke. 2021;16(6):692-700.
10. Braillon A, Bernard A, Leclercq T, Duloquin G, Pommier T, Benali K, et al. Incremental value of the combined brain-cardiac CT protocol on prediction of atrial fibrillation after stroke. Eur Stroke J. 2023;8(1):175-82.
11. Philippe D, Bernard A, Ricolfi F, Bejot Y, Duloquin G, Comby PO, et al. Prevalence of major embolic findings and incidental findings on early cardiac CT in patients with suspected ischemic stroke. Diagn Interv Imaging. 2024;105(9):336-43.