Publications by authors named "Stephane Fournier"

Introduction: Coronary microvascular dysfunction (CMD) is increasingly recognized as an important cause of anginal symptoms and poor outcomes. Angina with non-obstructive coronary arteries (ANOCA) is often related to CMD. While physiological assessment of microcirculatory function by coronary bolus thermodilution is widely practiced, more precise and reproducible methodology as well as systematic assessment are necessary.

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Mobile health applications have emerged as a novel tool to support secondary prevention after myocardial infarction (MI) or percutaneous coronary intervention (PCI). However, the impact of app-based interventions on clinically meaningful outcomes such as hospital readmissions remains uncertain. To systematically evaluate the effectiveness of smartphone app-based interventions in reducing unplanned hospital readmissions among post-MI/PCI patients.

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Background: Fasting before elective or nonurgent coronary angiography is commonly recommended to reduce the risk of adverse events, such as aspiration pneumonia. This systematic review and meta-analysis aimed to evaluate the impact of fasting versus nonfasting protocols on patient outcomes and satisfaction.

Methods: We systematically searched PubMed, Embase, and Cochrane Library databases for randomized clinical trials comparing fasting and nonfasting states before cardiac catheterization.

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Chronic coronary syndrome involves coronary artery and/or microcirculatory dysfunction leading to ischemia, but also includes patients who have previously undergone revascularization. Diagnosis relies on clinical evaluation and non-invasive or invasive tests to differentiate epicardial obstructive coronary artery disease from non-obstructive forms (Angina with Non-Obstructive Coronary Arteries (ANOCA)/Ischemia with Non-Obstructive Coronary Arteries (INOCA)). Management includes risk factor optimization, antianginal therapy, and revascularization when needed.

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This article explores the relationship between mitral regurgitation and heart failure, a dangerous combination with serious consequences. It reviews the pathophysiological mechanisms and current therapeutic options, ranging from medical treatments to percutaneous approaches, surgical interventions, and advanced modalities such as ventricular assist devices or heart transplantation. Recent studies exploring strategies to break this vicious cycle and improve patient outcomes are also reviewed.

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Recent data suggest that fractional flow reserve derived from coronary computed tomography (FFR-CT) can help select patients with high-risk non-ST-elevation acute coronary syndrome (NSTE-ACS) requiring invasive coronary angiography (ICA). Multiple stenoses are often observed in this population, and while a clear culprit is frequently identified, the management of intermediate lesions remains challenging. The information provided by FFR-CT prior to the ICA could theoretically assist in the management of these lesions.

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Aortic stenosis (AS) is a progressive form of valvular heart disease most commonly associated with aging, with an exponential increase in prevalence after age 50. While men have historically been considered at higher risk, recent studies highlight a similar prevalence between men and women, with a higher prevalence in elderly women driven by longer life expectancy. Sex-related differences in clinical presentation, anatomy, and pathophysiology influence disease progression, severity assessment, and management.

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Background: Stent loss is a rare but serious complication of percutaneous coronary interventions (PCI) that can disrupt coronary flow. This report details the retrieval of an intracoronary stent 3 months after its unnoticed loss during a complex PCI procedure.

Case Summary: A 62-year-old male presented with an inferior STEMI due to right coronary artery (RCA) occlusion, treated by primary PCI.

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Transcatheter aortic valve replacement (TAVR) has revolutionized the treatment of aortic stenosis. As TAVR continues to evolve, precise pre-procedural planning and imaging have become increasingly critical. While transthoracic echocardiography remains indispensable for assessing the severity of aortic stenosis, cardiac computed tomography angiography (CCTA) has emerged as the benchmark imaging modality for pre-procedural planning for TAVR.

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A considerable number of patients with angina undergo invasive coronary angiography, which might reveal non-obstructive coronary arteries (ANOCA). In this setting, they might have coronary microvascular disease (CMD). Its prevalence significantly varies in the literature.

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Background: Periprocedural electrophysiological (EP) testing may be useful to predict high degree atrioventricular block (HAVB) risk in patients undergoing transcatheter aortic valve replacement (TAVR).

Objective: To determine whether pre- and immediate post-TAVR ECG and HV interval findings are predictive of HAVB.

Methods: Consecutive TAVR patients without prior pacemaker (PM) implantation underwent ECG and standardized HV interval measurements pre- and post-TAVR using the quadripolar catheter for rapid pacing.

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Cardiac computed tomography (CT) has become an essential tool in the pre-procedural planning and optimization of coronary interventions. Its non-invasive nature allows for the detailed visualization of coronary anatomy, including plaque burden, vessel morphology, and the presence of stenosis, aiding in precise decision making for revascularization strategies. Clinicians can assess not only the extent of coronary artery disease but also the functional significance of lesions using techniques like fractional flow reserve (FFR-CT).

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Background: Quantitative flow ratio (QFR) and FFRangio are angiography-based technologies used to perform functional assessment of coronary lesions from angiographic images, validated across multiple clinical studies. There is limited information on the learning curves associated with each technology.

Aims: This study aims to compare the learning curves of QFR and FFRangio in evaluating coronary stenoses, focusing on changes in analysis speed and accuracy compared to invasive measurements.

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In patients with coronary artery disease, the prediction of future cardiac events such as myocardial infarction (MI) remains a major challenge. In this work, we propose a novel anatomy-informed multimodal deep learning framework to predict future MI from clinical data and Invasive Coronary Angiography (ICA) images. The images are analyzed by Convolutional Neural Networks (CNNs) guided by anatomical information, and the clinical data by an Artificial Neural Network (ANN).

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Article Synopsis
  • The study assessed how well ChatGPT can help decide if high-risk non-ST-elevation acute coronary syndrome (NSTE-ACS) patients need invasive coronary angiography (ICA) based on clinical data and imaging findings.
  • In a trial involving 86 patients, ChatGPT showed high accuracy at 86%, correctly advising against ICA for 19 patients and recommending it for 67, leading to significant findings in most cases.
  • The results indicate ChatGPT could aid in decision-making to avoid unnecessary procedures, but more extensive studies are needed to truly evaluate AI's effectiveness in clinical settings.
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Background: Coronary computed tomography angiography (CCTA) and fractional flow reserve (FFR) derived from CCTA (FFR-CT) may provide a means of reducing unnecessary invasive coronary angiography (ICA) in patients with suspected non-ST-elevation acute coronary syndromes (NSTE-ACS).

Aims: The aim of this study was to evaluate the capacity of FFR-CT and CCTA to rule out significant lesions in high-risk NSTE-ACS patients, using ICA with invasive FFR as the gold standard.

Methods: High-risk NSTE-ACS patients admitted to 4 European centres were enrolled in this single-arm, prospective core lab-adjudicated study.

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The study investigated gender bias in GPT-4's assessment of coronary artery disease risk by presenting identical clinical vignettes of men and women with and without psychiatric comorbidities. Results suggest that psychiatric conditions may influence GPT-4's coronary artery disease risk assessment among men and women.

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Background: Quantitative coronary angiography (QCA) typically employs traditional edge detection algorithms that often require manual correction. This has important implications for the accuracy of downstream 3D coronary reconstructions and computed haemodynamic indices (e.g.

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