Accurately predicting future hemorrhagic events in patients with cerebral amyloid angiopathy (CAA) remains a major clinical challenge. It is unknown whether cerebrospinal fluid (CSF) biomarkers of amyloid-beta (Aβ) pathology are associated with increased hemorrhage risk in this population. We analyzed consecutive patients meeting Boston criteria version 2.0 for probable CAA with CSF Aβ data obtained during diagnostic workup. The primary outcome was incident intracranial hemorrhage, including lobar intracerebral, convexity subarachnoid, and non-traumatic subdural hemorrhage. Secondary outcomes were ischemic stroke and all-cause mortality. Associations between low CSF Aβ biomarkers and outcomes were analyzed using Cox proportional hazards models, adjusted for disseminated cortical superficial siderosis, and prior intracerebral hemorrhage. Among 109 patients (median age: 77 years, 42% female), 16 (15%) experienced incident intracranial hemorrhage and 11 (10%) incident ischemic stroke during a median follow-up of 2.93 years (interquartile range: 1.43-5.03). In multivariate Cox regression models low CSF Aβ biomarkers were independently associated with incident intracranial hemorrhage (Aβ40: hazard ratio: 8.04; [95% CI: 2.43-26.59], p < 0.001; Aβ42: hazard ratio 7.10; [95% CI: 1.58-32.00], p = 0.011). CSF Aβ biomarkers were not associated with incident ischemic strokes and all-cause mortality. A composite risk score integrating low CSF Aβ biomarkers and hemorrhagic imaging features identified a high-risk subgroup with 78% hemorrhage incidence (7/9 patients) and a no-risk group without events (0/42 patients). Low CSF Aβ biomarkers are independently associated with future symptomatic hemorrhage in CAA patients. A composite risk score may support individualized risk stratification and guide clinical decision-making. ANN NEUROL 2026.
Improving risk stratification for coronary artery disease (CAD), the leading global cause of death, remains a daily challenge in clinical practice. This highlights the urgent need for innovative approaches to early prediction of future cardiovascular events from invasive coronary angiography (ICA), the gold standard imaging modality for CAD diagnosis. However, current methods, including clinical indices and data-driven deep learning models, fail to tackle this challenge. In this work, we propose AngioGraphCAD, a graph neural network-based framework for patient-level future cardiovascular events prediction from ICA. By design, the framework flexibly accommodates the variable number of coronary lesions per patient, enabling robust patient-level prediction. For each lesion, AngioGraphCAD constructs a geometric graph representation and learns a lesion-level embedding that leverages coronary artery geometry alongside clinical data, together with a lesion-level prediction objective. These lesion-level embeddings are then fused using a novel masked-attention mechanism to form a unified and interpretable patient-level representation. Across two clinical cohorts (FAME2: 563 patients, 1551 stenoses; FCL: 83 patients, 382 stenoses), AngioGraphCAD achieves strong lesion-level performance, significantly outperforming clinical measures and CNN-based models, with AUCs of 0.71 (FAME2) and 0.73 (FCL). Building on these lesion-level representations, AngioGraphCAD further achieves an AUC of 0.70 for patient-level prediction on FAME2. Overall, this study underscores the predictive value of coronary artery geometry from ICA and highlights geometry-aware representations as a promising step toward more personalized CAD management.
Enhanced recovery after surgery (ERAS) has evolved into a well established, evidence-based framework for perioperative care in numerous surgical disciplines. At the same time, advances in minimally invasive and catheter-based techniques have substantially expanded the number and complexity of procedures performed outside the operating room, leading to a rapid growth of nonoperating room anesthesia (NORA). Despite the clear overlap between ERAS principles and NORA patient needs, comprehensive recovery concepts for interventional procedures remain limited. Current evidence on ERAS-based approaches in NORA is sparse and heterogeneous, mainly originating from gastroenterology, cardiology, and interventional radiology. Existing studies suggest that selected enhanced recovery principles are feasible in interventional care and may improve patient comfort, recovery, safety, and procedural efficiency. However, implementation is often fragmented and lacks standardized, pathway-based peri-interventional management. Enhanced recovery principles hold substantial potential to improve peri-interventional care within the rapidly expanding NORA environment. The critical gap is not the absence of ERAS elements, but the absence of structured peri-interventional recovery governance comparable to established surgical ERAS pathways. Future progress will require holistic, multidisciplinary recovery frameworks, standardized concepts with procedure-specific adaptations, and clinical and economic evidence. Given its central role across the peri-interventional continuum, anesthesiology is well positioned to contribute to and potentially lead the development of structured enhanced recovery pathways beyond the operating room.
The concepts of brain health (ie, optimal functioning of the brain across cognitive, emotional, and behavioral domains throughout life) and cognitive resilience (ie, the ability of the brain to recover after an insult) have become increasingly important as the population ages. Previous research has called attention to vascular risk factors underlying cerebrovascular disease, as well as modifiable variables that contribute to premature aging and cognitive dysfunction. In this scientific statement, we focus on the role of nonvascular physical and psychologic variables that affect brain health across the life span. We provide a broad overview of influences such as chronic medical conditions, inflammation, environmental exposures, and socioeconomic drivers that affect the developing brain, along with factors including sleep quality, the gut microbiome, and mental health that contribute to neurodegeneration. We also review the varying strength of evidence supporting biologic mechanisms and mitigating strategies that may help optimize resilience, with the goal of providing a framework for future studies.
A recent systematic review and meta-analysis of randomized trials evaluating digital health interventions for family members of intensive care unit (ICU) patients found no significant improvements in anxiety, depression, posttraumatic stress, quality of life, or communication quality. Rather than concluding that digital approaches are inherently ineffective, we argue that these null findings reflect identifiable and remediable limitations in intervention design, outcome measurement, and trial methodology. In this commentary, we examine four structural barriers that currently constrain the evidence base and outline the conditions that next-generation trials must meet to adequately address the questions raised by this review.
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Accurate measurement and reporting of pulmonary arterial wedge pressure (PAWP) and cardiac output (CO) are essential for diagnosing and managing pulmonary hypertension (PH) and pulmonary arterial hypertension (PAH). Errors in these parameters can lead to misclassification and inappropriate treatment. Recent updates from the 2023 European Respiratory Society/European Society of Cardiology guidelines and the 2024 7th World Symposium on Pulmonary Hypertension emphasize the need for standardized right heart catheterization (RHC) practices. To identify knowledge gaps in RHC practices among interprofessional team members and implement a targeted blended learning program developed for pulmonary critical care and cardiology fellows, with a focus on accurate acquisition and interpretation of PAWP and CO. Using the SQUIRE framework, we conducted a baseline survey assessing RHC practices and knowledge among pulmonary critical care and cardiology attending physicians and fellows, and critical care nurses at an academic medical center. Respondents were actively involved in RHC procedures across the cardiac catheterization laboratory, medical intensive care unit, and cardiac care unit. Survey items with < 70% correct response were used to guide development of a 120-minute blended learning program incorporating lectures, video instruction, and hands-on-simulation. Pre- and post-training assessments were conducted. Of 141 invited participants, 85 responded to the survey (60.3% response rate). Baseline data revealed knowledge gaps and therefore opportunities for learning in CO measurement methods and PAWP interpretation. Assessment post-blended learning program demonstrated knowledge improvements in key areas including identification of indirect FicK (iFick) as the most common CO method, confirmation of zero-reference level by the proceduralist-nurse team, acquisition of PAWP, and obtaining at least three measurements of CO via thermodilution. However, correct identification of end-expiratory PAWP declined, highlighting the need for greater emphasis on this skill in future training sessions. This is the first reported interprofessional training initiative to target CO and PAWP measurement accuracy in RHC. This study identified key knowledge gaps and therefore opportunities for learning. Knowledge improvements measured after the educational intervention support the need for ongoing, structured, and interprofessional training to enhance procedural competency and interpretation of RHC hemodynamic data to optimize PH and PAH care.
Artificial intelligence (AI) is rapidly reshaping cardiovascular (CV) medicine, driving a paradigm shift toward truly personalized and data-driven care. This comprehensive review examines the conceptual foundations, clinical applications, and future implications of AI across the CV continuum, spanning prevention, diagnosis, risk stratification, and therapy. Core AI methodologies (including machine learning, deep learning, natural language processing, and computer vision) are discussed in the context of cardiology's uniquely data-rich environment, encompassing imaging, electrocardiography, electronic health records, wearable devices, and multi-omics data. This systematic review highlights major clinical domains where AI has demonstrated a substantial impact, including CV imaging, ECG interpretation, hypertension and heart failure management, coronary artery disease, acute coronary syndromes, interventional cardiology, and cardiac surgery. AI-driven predictive analytics enable early detection of subclinical disease, improved prognostication, and individualized prevention strategies, while wearable technologies and remote monitoring platforms facilitate continuous, real-world patient surveillance. Emerging applications in pharmacotherapy, drug repurposing, and genomics further reinforce AI's role in advancing precision cardiology. Equally emphasized are the ethical, legal, and social challenges accompanying AI adoption, such as algorithmic bias, data privacy, cybersecurity, interpretability, and regulatory oversight. Our review underscores the necessity of rigorous clinical validation, transparent model design, and seamless integration into clinical workflows to ensure safety, equity, and physician trust. Ultimately, AI is best positioned as an augmentative tool that complements (but does not replace!) clinical expertise. By fostering hybrid intelligence that integrates human judgment with computational power, AI has the potential to redefine CV care delivery, improve outcomes, and support a more proactive, patient-centered healthcare model.
Kounis syndrome-acute coronary events triggered by allergic or hypersensitivity reactions-remains underrecognized across emergency and cardiology settings. Its heterogeneous presentation and overlapping mechanisms (vasospasm, plaque erosion/rupture, stent thrombosis) challenge timely diagnosis and tailored therapy.This review synthesizes contemporary evidence on pathophysiology, clinical spectrum, and management of Kounis syndrome (Types I-III), and map how artificial intelligence (AI) could enhance care pathways. We outline data streams relevant to AI (ECG, biomarkers, imaging, clinical narratives), modeling approaches (machine learning, sequence models), and decision-support scenarios (early detection, risk stratification, treatment selection, and monitoring). We also address implementation barriers, including dataset shift, bias, transparency, and governance.Kounis syndrome is a prime candidate for AI-enabled diagnostic support given its pattern-based signatures at the interface of allergy and acute coronary syndromes. Near-term priorities include curated multicenter datasets with harmonized phenotyping, prospective validation of models embedded in clinical workflows, and hybrid rules-plus-learning systems aligned with guideline-based care. Integrating allergy severity, hemodynamics, and ischemic burden into dynamic risk tools may reduce missed diagnoses and optimize anti-allergic and antithrombotic strategies while safeguarding patient safety. Kounis syndrome is a rare medical condition in which an allergic reaction can trigger a heart problem, such as chest pain or even a heart attack. It can happen after exposure to certain foods, medications, insect stings, or other allergens. Because its symptoms combine features of both allergy and heart disease, it is often difficult to recognize quickly. This delay can lead to inappropriate treatment or complications.Currently, there are no specific clinical guidelines designed only for Kounis syndrome. Doctors usually rely on a combination of allergy and heart attack treatment protocols. However, some medications used for heart problems may worsen allergic reactions, and some allergy treatments may affect the heart. This makes medical decisions particularly complex.Artificial intelligence (AI) has already been successfully used in cardiology to detect heart rhythm problems and predict cardiovascular risk. In this review, we explore how similar AI tools might one day help doctors recognize Kounis syndrome more quickly by analyzing different types of medical information at the same time, such as electrocardiograms, blood test results, and allergy markers.At present, no AI systems specifically designed for Kounis syndrome exist. Therefore, the applications discussed here are theoretical and require future research and validation. With further study, AI-supported tools may help improve early diagnosis and safer treatment decisions for this uncommon but potentially serious condition.
This review is based on interviews with internationally recognized female leaders in congenital cardiac interventions. The discussions explore diverse career pathways and professional experiences across different health care systems. The interviews are structured around 8 core themes: entry into the field, training, key turning points, leadership and professional survival, science and recognition, mentoring and legacy, the "Water or Warrior" paradigm, and messages for the future. Together, these perspectives offer a global view of shared challenges, career development, and the evolving role of women in congenital interventional cardiology.
Clinical trials in IBD face difficulties of escalating complexity, high costs and challenges in recruitment. Digital twins are virtual, data-driven replicas of individual patients that model disease trajectories and treatment responses, which offer a potential innovative change in the conduct of clinical trials in IBD. Built from multimodal datasets integrating clinical, molecular, imaging and real-world data, digital twins can generate synthetic control arms, enable adaptive randomisation and predict disease relapse or treatment response. Early studies across oncology, cardiology and endocrinology demonstrate their feasibility and potential to improve statistical power while reducing patient burden. However, the integration of digital twins into clinical trials in IBD will require rigorous validation frameworks, transparent data governance and attention to algorithmic bias and consent. In this review, we explore how digital twins may transform IBD research-from in silico simulation to adaptive, patient-centred trial design-and outline the regulatory, ethical and logistical challenges to be considered in order to successfully integrate them into future trials.
Cardiac sarcoidosis (CS) is associated with a significant risk of ventricular arrhythmias (VAs). Recently, late gadolinium enhancement (LGE) phenotypes have been described; the 'pathology-frequent' phenotype has been shown to be strongly associated with future VA risk. The aim of our study was to compare the relative predictability of quantitative LGE burden and LGE phenotype. Secondary aims were to contrast the reproducibility and speed of LGE burden quantification and LGE phenotyping. This is a two-centre sub-study of the Cardiac Sarcoidosis Multi-Center Prospective Cohort Study (CHASM-CS; NCT01477359). All patients underwent CMR at baseline. A total of 206 patients (112/206 (54.4%) with CS and 94/206 (45.6%) with extra-cardiac sarcoidosis) were included in the study. Pathology-frequent LGE phenotype occurred in 85/206 (41.3%) and 22/206 (10.7%) patients had sustained VA during a mean follow-up period of 5.1 ± 2.8 years. All events occurred in patients with a pathology-frequent phenotype. LGE phenotype and categorical LGE% had similar high discriminative accuracy in predicting future VA; however, only LGE phenotyping had 100% negative predictive value (NPV). Interobserver reproducibility of LGE phenotype was very high (Cohen's κ = 0.97, P < 0.001) and much better than LGE categorical quantification (Cohen's κ = 0.41, P = 0.04). LGE phenotyping was on average five-fold faster (1.75 ± 0.9 min compared to 10 ± 2.2 min, P = 0.012). Our study confirms, for the first time in a fully prospective cohort, the prognostic importance of the pathology-frequent phenotype of LGE. This phenotype had 100% NPV, indicating the absence of VA events among patients without a pathology frequent phenotype. LGE phenotyping showed much higher interobserver reproducibility than LGE quantification and was five-fold faster.
Cardiovascular diseases is the most common cause of mortality in the world. B vitamins (B₁-B₁₂) control how mitochondria make energy, how nitric oxide is made, how one-carbon is used, and how genes work. A deficiency leads to hyperhomocysteinemia, oxidative stress, and endothelial dysfunction, all of which are important to vascular disease. Observational studies consistently associate low B-vitamin levels with an elevated risk of cardiovascular diseases; nevertheless, randomized supplementation trials have demonstrated only modest reductions in significant events. This narrative review summarizes molecular, epidemiological, and clinical evidence on the role of B vitamins in cardiovascular health. Special focus was paid to functional biomarkers and gene-nutrient interactions that affect how well a therapy works. The literature was identified through targeted searches of PubMed, Scopus, and Google Scholar. Priority was given to high-quality evidence, including mechanistic studies, observational cohorts, randomized controlled trials, meta-analyses, and major review articles relevant to cardiovascular outcomes. Functional indicators, such as methylmalonic acid and holotranscobalamin, offer superior accuracy compared to blood levels in assessing vitamin status. Nutrigenetic interactions, particularly the effects of folate and riboflavin on methylenetetrahydrofolate reductase polymorphisms, exhibit blood pressure-lowering and stroke-preventive advantages. The clinical efficacy of B-vitamin supplementation is highly dependent on baseline nutritional status and regional food fortification policies. For example, folic acid supplementation significantly reduces stroke incidence in populations who lack mandatory folate fortification, whereas trials conducted in folate-sufficient cohorts generally demonstrated no added cardiovascular benefit. Recognizing this population-specific variability helps explain the historical discrepancy between the strong mechanistic potential of B-vitamins and the mixed results observed in large-scale clinical trials. While adequate B-vitamin status remains mechanistically essential for cardiovascular homeostasis, the clinical benefits of routine supplementation are nuanced and highly population-dependent. Consequently, ubiquitous supplementation is unlikely to produce extensive advantages. A precision strategy that combines biomarkers, genotype stratification, and population context can help find their therapeutic potential. Future methods should integrate diet with precision cardiology to enhance vascular prevention.
Citizen science is a transformative approach to advancing health research by bridging the gap between researchers and the public. The Dutch CIRCULAR model, which addresses atrial fibrillation (AF), the most common cardiac arrhythmia worldwide, offers a unique example of applying citizen science in biomedical and public health research. The project was established to systematically include people with AF and their families as partners in research, ensuring that their lived experiences inform priorities, study designs, and interventions. A central role is played by the online health community of the AFIP foundation, which engages the AF community through blog articles, forums, social media, and outreach campaigns. These activities stimulate dialogue, enhance health literacy, empower individuals to contribute hypotheses and solutions, and function as a marketing strategy to attract and retain diverse participants. By sharing outcomes through open-access formats and direct communication with participants, CIRCULAR creates a feedback loop between citizens and researchers that fuels new research directions in AF. Early activities have demonstrated the value of this approach. Patient-reported triggers and suppressors of AF episodes, including psychological stress and lifestyle factors, informed laboratory investigations and led to the co-design of clinical interventions such as dietary programs. These examples illustrate how co-creation can shape both preclinical and clinical research as well as citizen and student education. This review discusses how citizen science is conceptualized and implemented in the CIRCULAR model, presents ongoing and future activities, and reflects on the added value of patient involvement for public health and biomedical innovation. By embedding citizens throughout the research process, and actively engaging them through targeted outreach, CIRCULAR advances patient-centered innovation, strengthens empowerment and health literacy, and provides lessons for future participatory initiatives in complex chronic disease research.
Since its initial introduction to interventional cardiology over two decades ago, optical coherence tomography (OCT) has emerged as a powerful tool in neurovascular intervention. This intravascular imaging modality uses near-infrared light to provide cross-sectional visualization of the vessel wall with a resolution approaching 10 μm. The resolution of OCT far surpasses that of other imaging techniques. This higher resolution enables radiologists to directly assess arterial wall disease, including atherosclerotic plaque, aneurysm, and thrombus, as well as the interaction between therapeutic devices and the arterial wall in real time, providing actionable information during neurovascular interventions. The growing reliance on endovascular approaches to treat intracranial aneurysms and ischemia underscores the importance of precise vessel evaluation during treatment to provide accurate imaging guidance. However, digital subtraction angiography and cone beam computed tomography angiography often fail to reveal underlying arterial disease and other key features, such as the presence of thrombi, dissections, and malapposed stents, that could lead to incomplete treatment and acute and chronic complications. By enabling direct visualization of these microstructural details, OCT may overcome some of the most persistent challenges in neurovascular practice, ultimately improving diagnostic accuracy, procedural safety, and long-term patient outcomes. Nevertheless, integrating OCT into neurovascular settings remains challenging. There is still a lack of large-scale clinical validation, and existing coronary devices are not suitable for reliable use in tortuous intracranial vascular circulations. To overcome the technical limitations of current technologies, neuroOCT technology was designed specifically for neurovascular use and was evaluated in a first-in-human study. This technology will enable future clinical studies to investigate using neuroOCT to guide and optimize neurovascular treatments. This review article aims to provide a comprehensive perspective on the potential of neuroOCT in neurovascular practice. It highlights the technology's technical principles, current applications, limitations, and prospects for reshaping vascular imaging and therapy in the brain.
In the UK, the Recommended Summary Plan for Emergency Care and Treatment (ReSPECT) process and form are used to support shared decision-making and advance care planning, but ReSPECT has not been used in other countries. The aim of this study was to translate the English ReSPECT form into Danish and to pilot-test the Danish form in several healthcare-settings. The ReSPECT form was translated into Danish using a forward and back translation process in line with standard international translation guidelines. The translated form was then pilot tested by patients, relatives and physicians in different health care settings. The participants subsequently completed a questionnaire about its usefulness. 36 patients participated in the conversations; 15 patients, 11 relatives and 13 physicians completed the questionnaire. Most patients and relatives found that the document contained the information they needed, and that it was useful during a conversation about future wishes for treatment and care. Nearly two-thirds of the physicians considered the ReSPECT form to be highly useful for the conversations; and one-third thought it useful for clarifying the patient's healthcare status and recommending treatment. Half of the physicians identified missing or redundant information in the form. The Danish ReSPECT form was considered beneficial for conducting conversations about future treatment and care and clarifying patients' wishes in emergency situations. Further adjustments were identified to adapt the form to the Danish healthcare system. Translating and piloting the ReSPECT process into another languages is feasible and acceptable to patients and providers.
Ongoing neurodevelopmental care is essential for children with congenital heart disease (CHD). Understanding delivery and uptake of neurodevelopmental care pathways can inform implementation and resource planning. This study applied simulation modelling to explore outcomes from a neurodevelopmental care pathway for children with CHD. The model was developed using data from a Queensland program to explore health service interactions for neurodevelopmental screening, formal assessment, and early intervention, up to five years. Modelling was intended to provide a baseline understanding of the pathway, rather than evaluating against a reference standard. Hypothetical scenarios explored how changes in screening and referrals influenced the identification of developmental concerns, and how developmental concern severity affected intervention referrals. Based on available data, 58% of the cohort remained under routine surveillance and 25% had accessed early intervention for one or more developmental delays. Scenarios defined by increased screening projected up to 55% of the cohort having a developmental concern identified during screening and 45% having a developmental delay identified following assessment. Simulation modelling was useful for understanding outcomes from a neurodevelopmental pathway and how differences in screening and assessment affected health service interactions. Findings may inform policy and resource planning for future neurodevelopmental pathways. This study shows that simulation modelling is a useful approach for evaluating a neurodevelopmental care pathway for children with CHD, to understand movement through neurodevelopmental screening, assessment, and interventions. Scenario-based modelling provides insights into factors influencing pathway engagement, contributing evidence to strengthen understanding of service gaps and areas where improvements can most effectively impact engagement and resourcing. This study identifies neurodevelopmental screening as the most influential stage impacting downstream outcomes, underscoring its importance as a strategic intervention point. This study's approach provides a general framework for evaluating similar pathways and a potential baseline for assessing future policy or service changes.
Transcatheter aortic valve implantation (TAVI) has become a paradigm shift in the treatment of elderly and frail patients with severe aortic stenosis, offering a minimally invasive alternative to conventional surgical aortic valve replacement. As the indications for TAVI expand to include lower-risk patients, there is a growing need for sophisticated patient assessment methodologies that capture the complex interplay between physical and functional status, quality of life, and treatment outcomes. This review aims to synthesize the current evidence on the use of patient-reported outcome measures (PROMs) and frailty assessments before and after TAVI, with a focus on their utility in predicting treatment outcomes and improving patient-centered care. A comprehensive literature search was conducted to identify studies published in peer-reviewed journals that investigated the use of PROMs and frailty assessments in the context of TAVI. The review found that PROMs and frailty assessments are increasingly being used to evaluate the pre- and post-procedural status of patients undergoing TAVI. These assessments have been shown to predict treatment outcomes, including mortality, morbidity, and quality of life, and to inform treatment decisions. The review also highlights the importance of integrating PROMs and frailty assessments into routine clinical practice to optimize patient outcomes and improve patient-centered care. In conclusion, this review demonstrates the growing body of evidence supporting the use of PROMs and frailty assessments in the context of TAVI. By incorporating these assessments into routine clinical practice, healthcare providers can better identify patients at risk of poor outcomes, optimize treatment strategies, and improve patient-centered care. Future research should focus on developing and validating PROMs and frailty assessments that are specific to the TAVI population and on exploring the impact of these assessments on treatment outcomes and healthcare utilization.