Food insecurity (FI) is a social driver that profoundly affects the health of children. Nutritional optimization is essential in patients with congenital heart disease (CHD). We performed a cross-sectional survey screening for FI among patients aged 0-21 years at an outpatient pediatric cardiology clinic between September 2023 and December 2024. Sociodemographic and clinical data from encounters were collected, and diagnostic codes were used to classify CHD severity. The zip code-level median household income was determined using data from the U.S. Census. The Childhood Opportunity Index categorization was used to determine neighborhood-level resources. Univariate and multivariate logistic regression were used to assess sociodemographic associations with FI. There were 955 encounters with completed FI screening. Positive screens were demonstrated in 200 surveys (20.9%). Compared to English-speaking White families, those with FI were more likely to be of Hispanic ethnicity (66% vs. 45.2%) and primarily speak Spanish (42.5% vs. 15.0%). Families with FI also lived in areas with lower median household income and fewer available resources. In multivariable analysis, after adjusting for ethnicity, income, and neighborhood-level resource availability, Spanish primary language was the only independent risk factor associated with FI (OR 2.7, 95% CI 1.7-4.2, p < 0.0001). There were no differences in FI status by CHD severity. FI was highly prevalent in this cohort and was associated with low-income and low-resource neighborhoods, Hispanic ethnicity, and a Spanish primary language. These results may have implications for targeting future FI interventions.
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.
Cardiovascular disease (CVD) remains the leading global cause of death, with dyslipidemia as its most modifiable driver of atherosclerotic CVD. The burden is especially severe in India, where early-onset disease and a distinct lipid profile, marked by elevated triglycerides, low high-density lipoprotein cholesterol (HDL-C), and small dense low-density lipoprotein (sdLDL) particles, contribute to increased lifetime risk. The pathophysiology of atherosclerosis has evolved from the cholesterol-centric model to the response-to-retention hypothesis, highlighting the role of apolipoprotein B (ApoB)-containing lipoproteins in initiating vascular inflammation and plaque formation. Advances in lipid science have revealed complex interactions between lipid metabolism, endothelial dysfunction, and immune activation. The Lipid Association of India 2023 guidelines recommend lifetime risk-based assessment and early intervention using coronary artery calcium scoring (CACS), carotid and femoral plaque imaging, and ankle-brachial index (ABI) to refine risk stratification. Therapeutic options have expanded beyond statins to include ezetimibe, PCSK9 inhibitors, bempedoic acid, and RNA-based agents, offering deeper and safer lipid reduction. Emerging therapies targeting ANGPTL3, liver X receptor (LXR) β, and PPAR-β/δ pathways promise further innovation in lipid modulation. These developments mark a shift toward precision lipidology, integrating genomics, imaging, and long-acting therapeutics to enable early, aggressive, and individualized prevention. As India faces a rising tide of cardiovascular events in younger populations, the future of lipid management lies in personalized, multimodal strategies that address both traditional and residual risk, aiming for sustained cardiovascular protection and improved public health outcomes.
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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.
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.
Background: Artificial intelligence (AI) and deep learning (DL) are rapidly changing the field of diagnostics and imaging in cardiology, offering tools for automatic segmentation, quantification of changes, and risk stratification. These technologies have the potential to increase diagnostic accuracy, work efficiency, and individualization of patient care. Methods: This structured narrative review critically evaluates clinically validated applications of artificial intelligence (AI) and deep learning (DL) in cardiovascular medicine, focusing on imaging (echocardiography, coronary CT angiography, cardiac MRI, and ECG), risk stratification, and biomarker integration. A systematic literature search was conducted in PubMed for studies published between January 2015 and December 2026, supplemented by references from key articles. Original English-language studies reporting quantitative clinical outcomes were included, with 78 studies ultimately analyzed. Results: AI and DL models, including convolutional neural networks and transformers, achieved performance comparable to experts in cardiac imaging, myocardial perfusion assessment, valve defect detection, and coronary event prediction. Multimodal approaches improved diagnostic accuracy and reproducibility, while explainable AI enhanced transparency and clinical confidence. Deep learning also enabled faster image acquisition and processing without compromising precision. Conclusions: AI and DL have transformative potential in cardiology, offering fast, accurate, and scalable diagnostic tools. The integration of multimodal data, the validation of algorithms in prospective studies, and ensuring the transparency of models are key. Future research should focus on prospective, multicenter validations and the ethical and safe implementation of AI in everyday clinical practice.
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.
Medly is a remote patient management (RPM) tool that allows patients with heart failure (HF) to record daily measures to inform health status and receive personalized care instructions by a validated algorithm. Medly has been standard-of-care for patients with HF in the Cardiology Division at University Health Network since 2016. While patients with HF are often admitted to general internal medicine (GIM), there are few HF RPM programs used in the GIM setting. We piloted Medly for patients discharged from GIM in the summer of 2023. The purpose of this study was to understand staff factors that enabled or inhibited spread and scale of Medly into a GIM setting. Semistructured interviews were conducted with 13 staff involved in the planning, delivery, and implementation of Medly in the GIM setting. Interviews were recorded and transcribed verbatim. Data were analyzed using deductive thematic analysis informed by the Consolidated Framework for Implementation Research. Implementation factors included: (1) communicative staff, (2) Medly adaptability and relative advantage, (3) need for long-term funding, (4) leadership engagement and learning-centered culture, and (5) sociodemographic characteristics of patients. This study offers valuable insight into how an RPM can be adopted from the Cardiology to GIM context. Key enablers include providing appropriate staff time and compensation, engaging leadership early and often, modifying the application for the setting, and considering equity with respect to language barriers. A larger pilot with more than 10 patients actively embedded in the GIM pathway is required for further scale of the program.
Cancer therapy-related cardiac dysfunction (CTRCD) is among the most important adverse effects of treatment of childhood cancer. In the EARLY study (Early detection of acute and early-onset cARdiovascuLar toxicity in children with cancer using a multiparametric approach), cardiac function in children treated for cancer was monitored during and shortly after treatment, using advanced echocardiography, electrocardiography, and cardiac magnetic resonance (CMR) techniques. In this prospective pilot study, 100 children newly diagnosed with childhood cancer receiving anthracyclines as part of their cancer treatment were included. A subgroup of 30 children was included in the CMR sub-study. Echocardiography, electrocardiography, and CMR were performed before (T0), three and a half months after (T1), and one year after (T2) start of anthracycline treatment. In this article, we focus on the methodological aspects of the EARLY study, including patient enrollment and characteristics of the study cohort, as well as the feasibility of advanced echocardiography. The last patient was included in August 2022. Follow-up for the last patient was finalized in August 2023. Follow-up was completed by 92% of the total study population and 97% of the CMR sub-study. Protocol adherence was high (92%-97%) and a full collection of data on each included individual was achieved. Advanced echocardiography, i.e., 4D ejection fraction and global longitudinal strain, was feasible in 76% and 69% of measurements, respectively. Cardiac outcomes during and shortly after treatment, as well as associations with known risk factors for CTRCD, such as anthracycline dose, dose of radiotherapy involving the heart, childhood cancer disease profile, age at diagnosis and sex will be reported in a future publication. The feasibility of the study allows for future insight into the correlation between early-onset CTRCD and heart failure during long-term follow-up of childhood cancer patients. ClinicalTrials.gov identifier: NL-OMON22737.
Objective: Back pain is a multifactorial condition commonly associated with degenerative spinal changes. Spondylophytes are frequent outgrowths of the vertebral bodies that may be influenced by arterial hypertension via a possible increased pulsation of the aorta and its effects on bone remodeling. If it can be demonstrated that an increased pulse pressure in the aorta due to hypertension promotes the growth of spondylophytes and thereby increases the likelihood of back pain, future studies may investigate how the effectiveness of blood pressure management can be improved in order to reduce the prevalence of degenerative changes in the spine and, consequently, prevent back pain. This study investigated the association between arterial hypertension and thoracic spondylophyte formation using whole-body MRI data from the population-based Study of Health in Pomerania (SHIP). Materials and Methods: Spondylophyte presence and area were assessed for their association with hypertension status in 859 SHIP-START-3 participants who underwent whole-body MRI. Right-sided spondylophytes at T8-T11 were measured on axial T2-weighted sequences. Hypertension was defined by self-report or antihypertensive medication use; a sensitivity analysis was conducted using the 2024 European Society of Cardiology definition (systolic blood pressure ≥ 140 mmHg). Multivariate regression models adjusted for age, sex, obesity, and smoking were used to assess associations. Machine learning algorithms were applied for validation. Results: Spondylophytes were present in 87.7% of participants. Hypertension was significantly associated with spondylophyte presence (OR = 2.07, 95% CI: 1.15-3.81) but not consistently associated with spondylophyte size. Spondylophyte size increased from T8 to T11, and was associated with age, male sex, and obesity. Sensitivity analyses widely confirmed robustness of the analysis. Conclusions: This population-based MRI study investigates the still insufficiently studied relationship between arterial hypertension and the formation of thoracic spondylophytes. The findings are consistent with the hypothesis that hypertension may be associated with spinal bone remodelling, though causal inference remains limited by the cross-sectional study design. Further longitudinal studies are needed to clarify causality and clinical relevance for spinal degeneration and back pain.
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.
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.
Background/Objectives: Myocardial ischemia-reperfusion injury (MIRI) remains an ever-growing threat in the field of cardiology, as it has become a major risk factor for unfavorable outcomes following reperfusion therapies. Oxidative stress and inflammation remain the key pathophysiological mechanisms underlying MIRI, and the presently available treatments fail to prevent this process effectively. This systematic review aimed to summarize and critically assess the latest preclinical research (2020-2026) on nanocarrier-based interventions targeting oxidative stress in MIRI, highlighting the potential of the new nanostructures in cardioprotection. Methods: A total of 24 studies meeting the PRISMA criteria have been found through a literature search of PubMed, Embase, and Web of Science databases published between 2020 and 2026. The studies eligible for inclusion had focused on the efficacy of nanocarrier-based interventions in preclinical studies of MIRI. Results: Of the 24 included studies, all investigated nanocarrier-based interventions in preclinical models of MIRI. In vitro, ex vivo, and in vivo models were diverse, with most studies being a combination of both in vitro and in vivo models. Commonly studied were lipid-based nanocarriers, polymeric nanoparticles, and biomimetic nanocarriers. Across studies assessed for this review, treatments with nanocarriers were seen to suppress inflammatory and oxidative stress pathways, with a few studies showing a suppression of cardiomyocyte apoptosis. Cardiac function was restored as determined by echocardiography analyses or ex vivo models of the myocardium, thus validating that the nanocarrier-mediated therapies are effective against MIRI. Conclusions: The analyzed preclinical studies indicate that the described therapies could provide a promising basis for future clinical trials in the treatment of MIRI, provided their safety and efficacy are confirmed in clinical trials.
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.
Acute coronary syndromes (ACS) are a major cause of mortality worldwide, and although interventional treatment has significantly improved mortality and morbidity related to ischemic heart disease, there is constant concern about optimizing drug treatment. In this regard, multiple studies have been conducted on inflammation in myocardial infarction (MI), starting from its implications in the atherosclerosis process. The aim of this review is to analyse the current evidence related to the subject and the correlation between the inflammatory state at presentation and the prognosis of patients with MI, identifying key points, possible therapeutic limitations, and future research directions. Both innate and acquired immune components are involved in the inflammatory cascade, with an increase in inflammatory cell and cytokine levels. To analyse the degree of inflammation and determine when it is excessive, numerous inflammatory markers have been studied, from acute phase proteins such as high-sensitivity C-reactive protein (hsCRP) and fibrinogen, to the ratios between inflammatory cells and interleukins involved in the main inflammatory pathways. Their association with post-infarction mortality and morbidity has been observed, but they must be integrated into the clinical context for the selection of patients who would benefit most from their reduction. New anti-inflammatory therapies are being studied in light of these findings, and progress is expected. Early trials with non-selective anti-inflammatory drugs have highlighted the importance of selective inhibition so as not to disrupt healing, and drugs are now being studied that target specific pathways that are exacerbated in infarction and lead to excessive remodelling. Several inflammatory pathways have been investigated but the results are inconclusive in terms of improving prognosis, requiring further studies to formulate future therapeutic indications.
Pulmonary vein isolation (PVI) has been established as the standard catheter ablation (CA) strategy for atrial fibrillation (AF). However, approximately 20-40% of patients experience recurrence after CA. Although three-dimensional (3D) maps generated during CA provide valuable electrophysiological information, they may not be fully utilized in clinical decision-making. To develop an artificial intelligence (AI) model that analyses 3D voltage maps and long-term AF recurrence to guide best practices in CA for AF. A dedicated multicentre registry recording detailed CA data for AF and recurrence was used to develop the AI model. The model was designed to evaluate the completion of PVI and ablation beyond-PVI (be-PVI), considering future AF recurrence with the need for additional PVI and be-PVI interventions. The AI model was trained and validated via fivefold cross-validation with 1268 maps. It effectively stratified cases for predicting 1-year AF recurrence after CA (P < 0.001) and identified those likely to benefit from additional ablations (PVI: P = 0.032, be-PVI: P < 0.001, and a combination of PVI and be-PVI: P < 0.001). The developed AI model predicts AF recurrence based on the completion of PVI and be-PVI and accurately identifies patients who may require further intervention. AI analysis of intraoperative 3D maps could guide optimal CA strategy planning, considering long-term AF recurrence.