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In the last decade, an incredible improvement has been made in elucidating the genetic bases of cardiomyopathies. Here we report the impact of either the European Society of Cardiology (ESC) guidelines or the use of whole exome sequencing (WES) in terms of a number of variants of uncertain significance (VUS) and missed diagnoses in a series of 260 patients affected by inherited cardiac disorders. Samples were analyzed using a targeted gene panel of 128 cardiac-related genes and/or WES in a subset of patients, with a three-tier approach. Analyzing (i) only a subset of genes related to the clinical presentation, strictly following the ESC guidelines, 20.77% positive test were assessed. The incremental diagnostic rate for (ii) the whole gene panel, and (iii) the WES was 4.71% and 11.67%, respectively. The diverse analytical approaches increased the number of VUSs and incidental findings. Indeed, the use of WES highlights that there is a small percentage of syndromic conditions that standard analysis would not have detected. Moreover, the use of targeted sequencing coupled with "narrow" analytical approach prevents the detection of variants in actionable genes that could allow for preventive treatment. Our data suggest that genetic testing might aid clinicians in the diagnosis of inheritable cardiac disorders., (© 2024 The Author(s). Clinical Genetics published by John Wiley & Sons Ltd.)

Different forms of immersive technology, such as Virtual Reality (VR) and Augmented Reality (AR), are getting increasingly invested in medicine. Advances in head-mounted display technology, processing, and rendering power have demonstrated the increasing utility of immersive technology in medicine and the healthcare environment. There are a growing number of publications on using immersive technology in cardiology. We reviewed the articles published within the last decade that reported case studies or research that uses or investigates the application of immersive technology in the broad field of cardiology - from education to preoperative planning and intraoperative guidance. We summarized the advantages and disadvantages of using AR and VR for various application categories. Our review highlights the need for a robust assessment of the effectiveness of the methods and discusses the technical limitations that hinder the complete integration of AR and VR in cardiology, including cost-effectiveness and regulatory compliance. Despite the limitations and gaps that have inhibited us from benefiting from immersive technologies' full potential in cardiology settings to date, its promising, impactful future for standard cardiovascular care is undoubted., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Artificial intelligence (AI) has the potential to fundamentally change radiology workflow., Objectives: This review article provides an overview of AI applications in cardiovascular radiology with a focus on image acquisition, image reconstruction, and workflow optimization., Materials and Methods: First, established applications of AI are presented for cardiovascular computed tomography (CT) and magnetic resonance imaging (MRI). Building on this, we describe the range of applications that are currently being developed and evaluated. The practical benefits, opportunities, and potential risks of artificial intelligence in cardiovascular imaging are critically discussed. The presentation is based on the relevant specialist literature and our own clinical and scientific experience., Results: AI-based techniques for image reconstruction are already commercially available and enable dose reduction in cardiovascular CT and accelerated image acquisition in cardiac MRI. Postprocessing of cardiovascular CT and MRI examinations can already be considerably simplified using established AI-based segmentation algorithms. In contrast, the practical benefits of many AI applications aimed at the diagnosis of cardiovascular diseases are less evident. Potential risks such as automation bias and considerations regarding cost efficiency should also be taken into account., Conclusions: In a market characterized by great expectations and rapid technical development, it is important to realistically assess the practical benefits of AI applications for your own hospital or practice., (© 2024. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.)

Numerous guidelines on the diagnosis and management of hypertrophic cardiomyopathy (HCM) have been published, by learned societies, over the past decade. Although helpful they are often long and less adapted to nonexperts. This writing panel was challenged to produce a document that grew as much from years of practical experience as it did from the peer-reviewed literature. As such, rather than produce yet another set of guidelines, we aim herein to deliver a concentrate of our own experiential learning and distill for the reader the essence of effective and appropriate HCM care. This Clinical Practice Update on HCM is therefore aimed at general cardiologists and other cardiovascular practitioners rather than for HCM specialists. We set the stage with a description of the condition and its clinical presentation, discuss the central importance of "obstruction" and how to look for it, review the role of cardiac magnetic resonance imaging, reflect on the appropriate use of genetic testing, review the treatment options for symptomatic HCM-crucially including cardiac myosin inhibitors, and deal concisely with practical issues surrounding risk assessment for sudden cardiac death, and management of the end-stage HCM patient. Uniquely, we have captured the pediatric experience on our panel to discuss appropriate differences in the management of younger patients with HCM. We ask the reader to remember that this document represents expert consensus opinion rather than dogma and to use their best judgement when dealing with the HCM patient in front of them., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Myocardial perfusion imaging (MPI), using either single photon emission computed tomography (SPECT) or positron emission tomography (PET), is one of the most commonly ordered cardiac imaging tests, with prominent clinical roles for disease diagnosis and risk prediction. Artificial intelligence (AI) could potentially play a role in many steps along the typical MPI workflow, from image acquisition through to clinical reporting and risk estimation. AI can be utilized to improve image quality, reducing radiation exposure and image acquisition times. Once images are acquired, AI can help optimize motion correction and image registration during image reconstruction or provide direct image attenuation correction. Utilizing these image sets, AI can segment a number of anatomic features from associated computed tomographic imaging or even generate synthetic attenuation imaging. Lastly, AI may play an important role in disease diagnosis or risk prediction by combining the large number of potentially important clinical, stress, and imaging-related variables. This review will focus on the most recent developments in the field, providing clinicians and researchers with a timely update on the field. Additionally, it will discuss future trends including applications of AI during multiple points of the typical MPI workflow to maximize clinical utility and methods to maximize the information that can be obtained from hybrid imaging., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Transthoracic echocardiography (TTE) is routinely required during pre-participation screening in the presence of symptoms, family history of sudden cardiac death or cardiomyopathies <40-year-old, murmurs, abnormal ECG findings or in the follow-up of athletes with a history of cardiovascular disease (CVD). TTE is a cost-effective first-line imaging modality to evaluate the cardiac remodeling due to long-term, intense training, previously known as the athlete's heart, and to rule out the presence of conditions at risk of sudden cardiac death, including cardiomyopathies, coronary artery anomalies, congenital, aortic and heart valve diseases. Moreover, TTE is useful for distinguishing physiological cardiac adaptations during intense exercise from pathological behavior due to an underlying CVD. In this expert opinion statement endorsed by the Italian Society of Sports Cardiology, we discussed common clinical scenarios where a TTE is required and conditions falling in the grey zone between the athlete's heart and underlying cardiomyopathies or other CVD. In addition, we propose a minimum dataset that should be included in the report for the most common indications of TTE in sports cardiology clinical practice., Competing Interests: Declaration of competing interest The authors report no relationships that could be construed as a conflict of interest. All authors have seen and approved the manuscript being submitted, have contributed significantly to the work, attest to the validity and legitimacy of the data and its interpretation, and agree to its submission to the International Journal of Cardiology., (Copyright © 2024. Published by Elsevier B.V.)

Cardiovascular diseases as a primary driver of global morbidity and mortality. Despite the array of therapeutic avenues in clinical practice, predominantly pharmaceutical and surgical interventions, they often fall short of fully addressing the clinical exigencies of cardiovascular patients. In recent years, nanocarriers have shown great potential in the treatment and diagnose of cardiovascular diseases. They can enhance drug targeting and bioavailability while reducing side effects. Additionally, by improving imaging and detection technologies, they enhance early diagnosis and disease monitoring capabilities. These advancements in technology offer new solutions for precision medicine in cardiovascular diseases, advancing treatment efficacy and disease management. Crafted from biomaterials, metals, or their amalgamations, these nanocarriers approximate the dimensions of biologically active molecules like proteins and DNA. Cardiovascular nanomedicine, in its infancy, has only recently burgeoned. Yet, with continual refinement in nanocarrier architecture, drug delivery mechanisms, and therapeutic outcomes, the potential of nanomedical technologies in clinical contexts becomes increasingly evident. This review aims to consolidate the strides made in nanocarrier research concerning the treatment and diagnose of cardiovascular diseases., Competing Interests: Declaration of competing interest The authors have no conflict of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Interventional cardiology is on the cusp of a significant transformation as we approach 2050, driven by emerging trends and groundbreaking technological innovations. This mini review explores the pivotal developments shaping the field, focusing on three key areas: Emerging Trends in Interventional Cardiology, Technological Innovations: The Next Frontier, and the Future Era of Intervention Cardiology from 2024 to 2050. Emerging trends, including advancements in imaging and artificial intelligence, are revolutionizing diagnosis and treatment, allowing for more precise and personalized interventions. Technological innovations, such as robotic-assisted procedures and bioresorbable stents, are redefining the landscape, enhancing procedural accuracy, and expanding access to care through remote interventions. Looking ahead to 2050, we anticipate a future where interventional cardiology is increasingly driven by minimally invasive techniques, AI-driven decision-making, and personalized medicine, offering unprecedented improvements in patient outcomes and reshaping the way cardiovascular diseases are managed., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests that can influence the work reported in this article., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: For an optimal interplay based on the data-secure exchange of diagnostic data between patients, ambulatory care, and hospital care, we implemented the first tele-medical network for pediatric cardiology in Germany, the Congenital Cardiology Cloud. This study focuses on its feasibility, technical characteristics, and implementation in routine clinical work., Methods: Tele-medical traffic comprised numbers of incoming/outgoing data, related file types, treatment options for tele-medically processed patients, and patient classification with respect to the severity of disease. Proof of feasibility was related to the number of successful tele-medical transmissions of discharge documents at the end of the observation period (02/2020-10/2020)., Results: Analysis of Congenital Cardiology Cloud's data communication showed a number of 1178 files for a total of 349 patients, favoring transmissions towards the clinic. Incoming traffic was predominantly characterized by diagnostic data regarding tele-consultations (76.6%), consisting of a multitude of file types, whereas 93.4% of the dispatched data corresponded to discharge letters. The number of tele-consultations counted up to 61, with a necessary subsequent treatment or diagnostic procedure in 90.2% of the presented cases. Tele-medically processed patients generally showed to be more complex (severe chronic heart disease 42.4% vs. 23.7%). At the end of the observation period, 97.6% of the discharge documents were transmitted via telemedicine., Discussion: The implementation of the first tele-medical network for pediatric cardiology in Germany proves recent technological developments to successfully enable innovative patient care, connecting the ambulatory and hospital sector for a joint patient advice, predominantly in more complex cases. Possible governmentally guided refinancing concepts will show its long-term feasibility., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

This Special Issue of Biomolecules , entitled "Molecular Biomarkers in Cardiology 2022-2023", presents a comprehensive collection of research and reviews exploring the rapidly evolving field of cardiovascular biomarkers [...].

The development of percutaneous coronary intervention (PCI) has been one of the greatest advances in cardiology and has changed clinical practice for patients with coronary artery disease (CAD). Despite continuous improvements in operators' experience, techniques, and the development of new-generation devices, significant challenges remain in improving the efficacy of PCI, including calcification, bifurcation, multivascular disease, stent restenosis, and stent thrombosis, among others. The present review aims to provide an overview of the current status of knowledge of endovascular revascularization in CAD, including relevant trials, therapeutic strategies, and new technologies addressing particular scenarios that can impact the prognosis of this vulnerable population.

Introduction: Myocardial perfusion imaging (MPI) is one of the most commonly ordered cardiac imaging tests. Accurate motion correction, image registration, and reconstruction are critical for high-quality imaging, but this can be technically challenging and has traditionally relied on expert manual processing. With accurate processing, there is a rich variety of clinical, stress, functional, and anatomic data that can be integrated to guide patient management., Areas Covered: PubMed and Google Scholar were reviewed for articles related to artificial intelligence in nuclear cardiology published between 2020 and 2024. We will outline the prominent roles for artificial intelligence (AI) solutions to provide motion correction, image registration, and reconstruction. We will review the role for AI in extracting anatomic data for hybrid MPI which is otherwise neglected. Lastly, we will discuss AI methods to integrate the wealth of data to improve disease diagnosis or risk stratification., Expert Opinion: There is growing evidence that AI will transform the performance of MPI by automating and improving on aspects of image acquisition and reconstruction. Physicians and researchers will need to understand the potential strengths of AI in order to benefit from the full clinical utility of MPI.

Background: COVID-19 spurred rapid adoption and expansion of telemedicine. We investigated the factors driving visit modality (telemedicine vs. in-person) for outpatient visits at a large cardiovascular center., Methods: We used electronic health record data from March 2020 to February 2021 from four cardiology subspecialties (general cardiology, electrophysiology, heart failure, and interventional cardiology) at a large academic health system in Northern California. There were 21,912 new and return visits with 69% delivered by telemedicine. We used hierarchical logistic regression and cross-validation methods to estimate the variation in visit modality explained by patient, clinician, and visit factors as measured by the mean area under the curve., Results: Across all subspecialties, the clinician seen was the strongest predictor of telemedicine usage, while primary visit diagnosis was the next most predictive. In general cardiology, the model based on clinician seen had a mean area under the curve of 0.83, the model based on the primary diagnosis had a mean area under the curve of 0.69, and the model based on all patient characteristics combined had a mean area under the curve of 0.56. There was significant variation in telemedicine use across clinicians within each subspecialty, even for visits with the same primary visit diagnosis., Conclusion: Individual clinician practice patterns had the largest influence on visit modality across subspecialties in a large cardiovascular medicine practice, while primary diagnosis was less predictive, and patient characteristics even less so. Cardiovascular clinics should reduce variability in visit modality selection through standardized processes that integrate clinical factors and patient preference., Competing Interests: Declaration of conflicting interestsThe authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: NK reports consulting fees from Ultromics and equity in Gordy Health outside the submitted work. FR reports consulting fees from Novartis, NovoNordisk, and HealthPals outside the submitted work. RD reports research funding from Bayer AG and consulting fees from HealthPals outside the submitted work. The remaining authors have nothing to disclose.

Background: Amyloid deposition in tenosynovial structures precedes cardiac involvement up to 20 years. Therefore, a cardiological screening in patients with a history of tenosynovial manifestations of cardiac amyloidosis (CA) could lead to an increased number of early diagnoses., Methods: Patients with tenosynovial manifestations of CA (carpal tunnel syndrome, atraumatic biceps tendon rupture, lumbar spinal stenosis) have been identified by general practitioners and evaluated in a Referral Center for CA. Patients with a high suspicion of CA underwent the CA diagnostic pathway., Results: Among 50 General Practitioners (GP) contacted, 10 (20%) agreed to participate in the study for a total of 5615 patients ≥60 years. One hundred forty-five patients met the inclusion criteria, 2 of them already had a diagnosis of CA, and 57 agreed to undergo a cardiological evaluation (electrocardiography, echocardiography, NTproBNP assay). The median age was 73 [67-80] years and 31 (54%) were women. Eight patients were suggested to start the CA diagnostic pathway, five of them underwent a complete diagnostic evaluation for CA, three refused to complete the diagnostic exams and no new diagnoses were made., Conclusion: A screening program for CA in patients with tenosynovial manifestations identified by general practitioners is feasible, but may not yield a high rate of new diagnosis. In this study, we identified two patients who already had a diagnosis of CA, and among patients at high risk for CA, 37% refused to complete the diagnostic pathway. Increased awareness of CA among patients might increase participation and diagnostic yield in screening studies. Further validation of this protocol is needed to evaluate its diagnostic performance., Competing Interests: Declaration of competing interest The authors declare that there is no conflict of interest., (Copyright © 2023. Published by Elsevier B.V.)

Artificial intelligence (AI) has the potential to transform every facet of cardiovascular practice and research. The exponential rise in technology powered by AI is defining new frontiers in cardiovascular care, with innovations that span novel diagnostic modalities, new digital native biomarkers of disease, and high-performing tools evaluating care quality and prognosticating clinical outcomes. These digital innovations promise expanded access to cardiovascular screening and monitoring, especially among those without access to high-quality, specialized care historically. Moreover, AI is propelling biological and clinical discoveries that will make future cardiovascular care more personalized, precise, and effective. The review brings together these diverse AI innovations, highlighting developments in multimodal cardiovascular AI across clinical practice and biomedical discovery, and envisioning this new future backed by contemporary science and emerging discoveries. Finally, we define the critical path and the safeguards essential to realizing this AI-enabled future that helps achieve optimal cardiovascular health and outcomes for all., Competing Interests: Funding Support and Author Disclosures This work was supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health (under awards R01HL167858 and K23HL153775 to Dr Khera, F32HL170592 to Dr Oikonomou, R01HL155915 and R01HL167050 to Dr Nadkarni, R01HL158626 to Dr Wiens, and UM1 TR004407 to Dr Topol). Dr Khera is an Associate Editor of JAMA; receives research support, through Yale, from the Blavatnik Foundation, Bristol Myers Squibb, Novo Nordisk, and BridgeBio; is a coinventor of U.S. Provisional Patent Applications 63/177,117, 63/428,569, 63/346,610, 63/484,426, 63/508,315, 63/580,137, 63/606,203, 63/562,335; and is a co-founder of Ensight-AI, Inc and Evidence2Health, LLC. Dr Oikonomou is an academic cofounder of Evidence2Health LLC; has been a consultant for Caristo Diagnostics, Ltd and Ensight-AI, Inc; is a co-inventor in patent applications (US17/720,068, 63/619,241, 63/177,117, 63/580,137, 63/606,203, 63/562,335, WO2018078395A1, WO2020058713A1); and has received royalty fees from technology licensed through the University of Oxford. Dr Nadkarni is an academic cofounder of Renalytix, Pensieve, and Data2Wisdom; has patents licensed to Heart Test Laboratories; and acts as a consultant to Renalytix, Pensieve, and Heart Test Laboratories. Dr Butte is a cofounder and consultant to Personalis and NuMedii; has served as a consultant or advisor to National Institutes of Health, JAMA, Mango Tree Corporation, Samsung, Geisinger Health, Washington University in Saint Louis, University of Utah, and in the recent past, 10x Genomics, Helix, Pathway Genomics, and Verinata (Illumina); has served on paid advisory panels or boards for Regenstrief Institute, Gerson Lehman Group, AlphaSights, Covance, Novartis, Genentech, Merck, and Roche; is a shareholder in Personalis and NuMedii; is a minor shareholder in Apple, Meta (Facebook), Alphabet (Google), Microsoft, Amazon, NVIDIA, AMD, Snap, 10x Genomics, Doximity, Regeneron, Sanofi, Pfizer, Royalty Pharma, Moderna, BioNtech, Invitae, Pacific Biosciences, Editas Medicine, Eli Lilly, Nuna Health, Assay Depot (Scientist.com), Vet24seven, Snowflake, Sophia Genetics, and several other nonhealth-related companies and mutual funds; has received honoraria and travel reimbursement for invited talks from Johnson and Johnson, Roche, Genentech, Pfizer, Merck, Lilly, Takeda, Varian, Mars, Siemens, Optum, Abbott, Celgene, AstraZeneca, AbbVie, Westat, Applied Research Works, Acentrus, ALDA, and many academic institutions, medical- or disease-specific foundations and associations, and health systems; has received royalty payments through Stanford University, for several patents and other disclosures licensed to NuMedii and Personalis; and his research has been funded by the National Institutes of Health, U.S. Food and Drug Administration, Peraton (as the prime on an National Institutes of Health contract), Priscilla Chan and Mark Zuckerberg, the Barbara and Gerson Bakar Foundation, Genentech, Johnson and Johnson, Chan Zuckerberg Science, Robert Wood Johnson Foundation, Leon Lowenstein Foundation, Intervalien Foundation, and in the past, the March of Dimes, Juvenile Diabetes Research Foundation, California Governor’s Office of Planning and Research, California Institute for Regenerative Medicine, L’Oreal, and Progenity (none of these entities had any role in the design, planning, or execution of the study, or interpretation of the findings). Dr Topol is on the scientific advisory board of Tempus, Abridge, and Pheno.ai. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Recent artificial intelligence (AI) advancements in cardiovascular care offer potential enhancements in diagnosis, treatment, and outcomes. Innovations to date focus on automating measurements, enhancing image quality, and detecting diseases using novel methods. Applications span wearables, electrocardiograms, echocardiography, angiography, genetics, and more. AI models detect diseases from electrocardiograms at accuracy not previously achieved by technology or human experts, including reduced ejection fraction, valvular heart disease, and other cardiomyopathies. However, AI's unique characteristics necessitate rigorous validation by addressing training methods, real-world efficacy, equity concerns, and long-term reliability. Despite an exponentially growing number of studies in cardiovascular AI, trials showing improvement in outcomes remain lacking. A number are currently underway. Embracing this rapidly evolving technology while setting a high evaluation benchmark will be crucial for cardiology to leverage AI to enhance patient care and the provider experience., Competing Interests: Funding Support and Author Disclosures Dr Elias has research support provided to his institution from Eidos Therapeutics, Pfizer, Janssen, Edwards Lifesciences, New York Academy of Medicine, and Google. Dr Jain has consulting relationships with Bristol Myers Squibb, ARTIS Ventures, and Broadview Ventures. Dr Poterucha owns stock in Abbott Laboratories and Baxter International; and research support is provided to his institution from the Amyloidosis Foundation, American Heart Association (Award #933452 and #23SCISA1077494), Eidos Therapeutics, Pfizer, Janssen, Edwards Lifesciences, and the Glorney-Raisbeck Fellowship Award from the New York Academy of Medicine. Dr Avram is a co-inventor in the patent 63/208,406 (Method and System for Automated Analysis of Coronary Angiograms); and has received speaker fees from Abbott, Boston Scientific, Boehringer Ingelheim, and Novartis. Dr Avari Silva is the co-founder and consultant to and holds equity in SentiAR; the technology has been licensed by Washington University to SentiAR. Dr Maddox has received grant funding from the National Institutes of Health (NHLBI UG3HL165065: The Rhythm Evaluation for Anticoagulation with Continuous Monitoring of Atrial Fibrillation Trial [REACT-AF]); has received honoraria and/or expense reimbursement in the past 3 years from the University of Chicago, George Washington University, Baylor College of Medicine, the New York Cardiological Society, and Medscape (Dec 2022); has received compensation and travel expense reimbursement for American College of Cardiology leadership roles and meetings; is currently employed as a cardiologist and Vice President, Digital Products and Innovation at BJC HealthCare/Washington University School of Medicine, and in this capacity, he is advising Myia Labs, for which his employer is receiving equity compensation in the company, he is receiving no individual compensation from the company, and he is a compensated director for a New Mexico-based foundation, the J.F Maddox Foundation. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Objective . Very few predictive models have been externally validated in a prospective cohort following the implementation of an artificial intelligence analytic system. This type of real-world validation is critically important due to the risk of data drift, or changes in data definitions or clinical practices over time, that could impact model performance in contemporaneous real-world cohorts. In this work, we report the model performance of a predictive analytics tool developed before COVID-19 and demonstrate model performance during the COVID-19 pandemic. Approach . The analytic system (CoMETⓇ, Nihon Kohden Digital Health Solutions LLC, Irvine, CA) was implemented in a randomized controlled trial that enrolled 10 422 patient visits in a 1:1 display-on display-off design. The CoMET scores were calculated for all patients but only displayed in the display-on arm. Only the control/display-off group is reported here because the scores could not alter care patterns. Main results. Of the 5184 visits in the display-off arm, 311 experienced clinical deterioration and care escalation, resulting in transfer to the intensive care unit, primarily due to respiratory distress. The model performance of CoMET was assessed based on areas under the receiver operating characteristic curve, which ranged from 0.725 to 0.737. Significance. The models were well-calibrated, and there were dynamic increases in the model scores in the hours preceding the clinical deterioration events. A hypothetical alerting strategy based on a rise in score and duration of the rise would have had good performance, with a positive predictive value more than 10-fold the event rate. We conclude that predictive statistical models developed five years before study initiation had good model performance despite the passage of time and the impact of the COVID-19 pandemic., (Creative Commons Attribution license.)

Interventional cardiology is characterized by high radiation exposure for both the patient and the operator. Adequate shielding and monitoring of the operator are fundamental to comply with radiation protection principles. In a previous work, the effect on the dose of the dosemeter position on the chest was studied. In this paper, the investigation has been completed, employing an anthropomorphic thorax phantom, equipped with arms. Although there are differences between the Monte Carlo simulations and the measurements, similar trends are observed, showing that the reduction in dose, due to the arms, is between 20 and 60%, compared with the situation without arms. For that reason, considering a dosemeter placed on the chest, the upper position, which is the least affected by the arms, should be preferred while the extreme lateral position, near the armpit, should be avoided., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Transthoracic echocardiography (TTE) is the most widely available and utilised imaging modality for the screening, diagnosis, and serial monitoring of all abnormalities related to cardiac structure or function. The primary objectives of this document are to provide (1) a guiding framework for treating clinicians of the acceptable indications for the initial and serial TTE assessments of the commonly encountered cardiovascular conditions in adults, and (2) the minimum required standard for TTE examinations and reporting for imaging service providers. The main areas covered within this Position Statement pertain to the TTE assessment of the left and right ventricles, valvular heart diseases, pericardial diseases, aortic diseases, infective endocarditis, cardiac masses, pulmonary hypertension, and cardiovascular diseases associated with cancer treatments or cardio-oncology. Facilitating the optimal use and performance of high quality TTEs will prevent the over or under-utilisation of this resource and unnecessary downstream testing due to suboptimal or incomplete studies., (Copyright © 2024. Published by Elsevier B.V.)

Background: The recent guidelines from the European Society of Cardiology recommends using high-sensitivity cardiac troponin (hs-cTn) in either 0/1-h or 0/2-h algorithms to identify or rule out acute myocardial infarction (AMI). Several studies have reported good diagnostic accuracy with both algorithms, but few have compared the algorithms directly., Objective: We aimed to compare the diagnostic accuracy of the algorithms head-to-head, in the same patients., Methods: This was a secondary analysis of data from a prospective observational study; 1167 consecutive patients presenting with chest pain to the emergency department at Skåne University Hospital (Lund, Sweden) were enrolled. Only patients with a hs-cTnT sample at presentation AND after 1 AND 2 h were included in the analysis. We compared sensitivity, specificity, and negative (NPV) and positive predictive value (PPV). The primary outcome was index visit AMI., Results: A total of 710 patients were included, of whom 56 (7.9%) had AMI. Both algorithms had a sensitivity of 98.2% and an NPV of 99.8% for ruling out AMI, but the 0/2-h algorithm ruled out significantly more patients (69.3% vs. 66.2%, p < 0.001). For rule-in, the 0/2-h algorithm had higher PPV (73.4% vs. 65.2%) and slightly better specificity (97.4% vs. 96.3%, p = 0.016) than the 0/1-h algorithm., Conclusion: Both algorithms had good diagnostic accuracy, with a slight advantage for the 0/2-h algorithm. Which algorithm to implement may thus depend on practical issues such as the ability to exploit the theoretical time saved with the 0/1-h algorithm. Further studies comparing the algorithms in combination with electrocardiography, history, or risk scores are needed., Competing Interests: Declaration of competing interest None., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

For the first time, the European Society of Cardiology has drafted guidelines which encompass the management of the entire spectrum of patients with acute coronary syndrome, ranging from cardiogenic shock or cardiac arrest to ST-segment as well as non-ST-segment elevation myocardial infarction, to unstable angina. Some of the modified, as well as new recommendations include cardiac arrest, cardiogenic shock, diagnostic workup, antithrombotic therapy, timing of invasive strategy, intravascular imaging and revascularization in multivessel coronary artery disease. In addition, and for the first time, one entire section is dedicated to the patient's perspective and shared decision., Competing Interests: Le Pr M. Roffi déclare des fonds de recherche en faveur de l’institution de la part de Cordis, Terumo, Medtronic, Boston Scientific et Biotronik sans lien avec l’article publié. Le Dr J. F. Iglesias déclare des fonds de recherche en faveur de l’institution de la part de Abbott Vascular, Astra Zeneca, Biosensors, Biotronik, Concept Medical, Philips, and Terumo Corporation sans lien avec l’article publié ainsi que des honoraires d’orateurs de la part de AstraZeneca, Biosensors, Biotronik, Bristol Myers Squibb, Cordis, Concept Medical, Medalliance, Medtronic, Novartis, Terumo Corporation, Pfizer, et Philips, sans lien avec l’article publié. La Dre S. Degrauwe déclare des fonds de recherche en faveur de l’institution de la part de Biotronik et Abbott sans lien avec l’article publié ainsi que des honoraires d’orateurs de la part de Biotronik, Medalliance, Medtronic, SIS Medical, Vascular Medical, Cordis, Shockwave, Orbus Neich, Boston Scientific, sans lien avec l’article publié.

Ensuring the safety of healthcare workers in interventional cardiology necessitates effective monitoring of occupational radiation exposure. This study aims to assess the accuracy of the over-apron single dosimetric approach compared with double dosimetric methods and explore the relationship between under-apron and over-apron doses. This investigation showed that the prescribed annual dose constraint of 20 mSv year-1 was not exceeded by the maximum annual occupational doses determined by dosimetric algorithms, which were 0.13 ± 0.02, 0.15 ± 0.02 and 0.27 ± 0.04 mSv, respectively. The study demonstrated excellent statistically significant correlations among single and double dosimetric algorithms and between direct under-apron and over-apron doses. Consequently, single dosimetric algorithms could effectively estimate doses for double dosimetric algorithms, highlighting the limited added value of under-apron measurements. These findings significantly impact the practice of interventional cardiology in Sri Lanka, playing a crucial role in enhancing radiation protection measures., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Heart failure (HF) is a complex clinical syndrome associated with significant morbidity, mortality, and healthcare costs. It is characterized by various structural and/or functional abnormalities of the heart, resulting in elevated intracardiac pressure and/or inadequate cardiac output at rest and/or during exercise. These dysfunctions can originate from a variety of conditions, including coronary artery disease, hypertension, cardiomyopathies, heart valve disorders, arrhythmias, and other lifestyle or systemic factors. Identifying the underlying cause is crucial for detecting reversible or treatable forms of HF. Recent epidemiological studies indicate that there has not been an increase in the incidence of the disease. Instead, patients seem to experience a chronic trajectory marked by frequent hospitalizations and stagnant mortality rates. Managing these patients requires a multidisciplinary approach that focuses on preventing disease progression, controlling symptoms, and preventing acute decompensations. In the outpatient setting, patient self-care plays a vital role in achieving these goals. This involves implementing necessary lifestyle changes and promptly recognizing symptoms/signs such as dyspnea, lower limb edema, or unexpected weight gain over a few days, to alert the healthcare team for evaluation of medication adjustments. Traditional methods of HF monitoring, such as symptom assessment and periodic clinic visits, may not capture subtle changes in hemodynamics. Sensor-based technologies offer a promising solution for remote monitoring of HF patients, enabling early detection of fluid overload and optimization of medical therapy. In this review, we provide an overview of the CardioMEMS device, a novel sensor-based system for pulmonary artery pressure monitoring in HF patients. We discuss the technical aspects, clinical evidence, and future directions of CardioMEMS in HF management.

Fulminant myocarditis is an acute diffuse inflammatory disease of myocardium. It is characterized by acute onset, rapid progress and high risk of death. Its pathogenesis involves excessive immune activation of the innate immune system and formation of inflammatory storm. According to China's practical experience, the adoption of the "life support-based comprehensive treatment regimen" (with mechanical circulation support and immunomodulation therapy as the core) can significantly improve the survival rate and long-term prognosis. Special emphasis is placed on very early identification,very early diagnosis,very early prediction and very early treatment., (© 2024. Science China Press.)

Personalized medicine is a novel and rapidly evolving approach to clinical practice that involves making decisions about disease prediction, prevention, diagnosis, and treatment by utilizing modern technologies. The concepts of precision medicine have grown as a result of ongoing developments in genomic analysis, molecular diagnostics, and technology. These advancements have enabled a deeper understanding and interpretation of the human genome, allowing for a personalized approach to clinical care. The primary objective of this research is to assess personalized medicine in terms of its indications, advantages, practical clinical uses, potential future directions, problems, and effects on healthcare. An extensive analysis of the scientific literature regarding this topic demonstrated the new medical approach's relevance and usefulness, as well as the fact that personalized medicine is becoming increasingly prevalent in various sectors. The online, internationally indexed databases PubMed and Cochrane Reviews were used to conduct searches for and critically evaluate the most relevant published research including original papers and reviews in the scientific literature. The findings suggest that precision medicine has a lot of potential and its implementation lowers the incidence of stroke as well as coronary heart disease and improves patient health in cardiology., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Altered metabolic function has many detrimental effects on the body that can manifest as cardiovascular and liver diseases. Traditional approaches to understanding and treating metabolic dysfunction-associated disorders have been organ-centered, leading to silo-type disease care. However, given the broad impact that systemic metabolic dysfunction has on the human body, approaches that simultaneously involve multiple medical specialists need to be developed and encouraged to optimize patient outcomes. In this review, we highlight how several of the treatments developed for cardiac care may have a beneficial effect on the liver and vice versa, suggesting that there is a need to target the disease process, rather than specifically target the cardiovascular or liver specific sequelae of metabolic dysfunction., Competing Interests: Declaration of competing interest GG received research grants from Gilead, ViiV, MERCK, Jansen and Pfizer; attended advisory boards and received speaker honoraria from Gilead, ViiV, MERCK and Pfizer. JM received speaker honoraria from Gilead and ViiV. MGS has served as an advisor for Gilead, Ipsen, Advanz, Pfizer, Roche, Abbott and Novo Nordisk; as speaker for Abbott; and has received clinical trial or research grant support from Gilead, BMS, CymaBay, Intercept, Genfit, Pfizer, Ipsen, Novartis, Astra Zeneca, GSK, Celgene, Novo Nordisk, Axcella Health Inc., Merck, Galectin Therapeutics, Calliditas Therapeutics, AbbVie, Kowa. Giada Sebastiani has acted as speaker for Merck, Gilead, AbbVie, Novo Nordisk, Pfizer, served as an advisory board member for Pfizer, Merck, Novo Nordisk, Gilead, and has received unrestricted research funding from Theratecnologies Inc. PR is a member of the advisory board of Amgen, Novo Nordisk, and Novartis., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

We review the evidence for the presence of stem/progenitor cells in the heart and the preclinical and clinical data using diverse cell types for the therapy of cardiac diseases. We highlight the failure of adult stem/progenitor cells to ameliorate heart function in most cardiac diseases, with the possible exception of refractory angina. The use of pluripotent stem cell-derived cardiomyocytes is analysed as a viable alternative therapeutic option but still needs further research at preclinical and clinical stages. We also discuss the use of direct reprogramming of cardiac fibroblasts into cardiomyocytes and the use of extracellular vesicles as therapeutic agents in ischemic and non-ischemic cardiac diseases. Finally, gene therapies and genome editing for the treatment of hereditary cardiac diseases, ablation of genes responsible for atherosclerotic disease, or modulation of gene expression in the heart are discussed., Competing Interests: Declaration of interests Authors declare no conflict of interest., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Infective endocarditis (IE) is a life-threatening disease with an increasing incidence despite improved preventive measures. The revision of the European Society of Cardiology (ESC) guidelines on infective endocarditis in 2023 brings significant innovations in prevention, diagnostics, and treatment. Many measures for prophylaxis and prevention have been more clearly defined and given higher recommendation levels. In the diagnostics of IE the use of other imaging modalities besides echocardiography, such as cardiac computed tomography (CT), positron emission tomography (PET)/CT or single photon emission computed tomography (SPECT)/CT with radioactively labeled leukocytes was more strongly emphasized. The diagnostics and treatment of IE associated with a cardiac implantable electronic device (CIED) were also revised. An essential innovation is also the possibility of an outpatient antibiotic treatment for certain patients after initial treatment in hospital. The indications for surgery have also been revised and, in particular, the timing of surgery has been more clearly defined. This article provides an overview of the most important changes., (© 2024. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.)

The goal of this Special Issue was to collect original pieces as well as state-of-the-art review articles from scientists and research groups with specific interests in atherosclerosis research [...].

Introduction and Objectives: Concerns surrounding the consequences of ionizing radiation (IR) have increased in interventional cardiology (IC). Despite this, the ever-growing complexity of diseases as well as procedures can lead to greater exposure to radiation. The aim of this survey, led by Portuguese Association of Interventional Cardiology (APIC), was to evaluate the level of awareness and current practices on IR protection among its members., Methods: An online survey was emailed to all APIC members, between August and November 2021. The questionnaire consisted of 50 questions focusing on knowledge and measures of IR protection in the catheterization laboratory. Results were analyzed using descriptive statistics., Results: From a response rate of 46.9%, the study obtained a total sample of 159 responses (156 selected for analysis). Most survey respondents (66.0%) were unaware of the radiation exposure category, and only 60.4% reported systematically using a dosimeter. A large majority (90.4%) employed techniques to minimize exposure to radiation. All participants used personal protective equipment, despite eyewear protection only being used frequently by 49.2% of main operators. Ceiling suspended shields and table protectors were often used. Only two-thirds were familiar with the legally established limit on radiation doses for workers or the dose that should trigger patient follow-up. Most of the survey respondents had a non-certified training in IR procedures and only 32.0% had attended their yearly occupational health consultation., Conclusions: Safety methods and protective equipment are largely adopted among interventional cardiologists, who have shown some IR awareness. Despite this, there is room for improvement, especially concerning the use of eyewear protection, monitoring, and certification., (Copyright © 2023 Sociedade Portuguesa de Cardiologia. Publicado por Elsevier España, S.L.U. All rights reserved.)

Aim: Evaluation of the performance of ChatGPT-4.0 in providing prediagnosis and treatment plans for cardiac clinical cases by expert cardiologists. Methods: 20 cardiology clinical cases developed by experienced cardiologists were divided into two groups according to preparation methods. Cases were reviewed and analyzed by the ChatGPT-4.0 program, and analyses of ChatGPT were then sent to cardiologists. Eighteen expert cardiologists evaluated the quality of ChatGPT-4.0 responses using Likert and Global quality scales. Results: Physicians rated case difficulty (median 2.00), revealing high ChatGPT-4.0 agreement to differential diagnoses (median 5.00). Management plans received a median score of 4, indicating good quality. Regardless of the difficulty of the cases, ChatGPT-4.0 showed similar performance in differential diagnosis (p: 0.256) and treatment plans (p: 0.951). Conclusion: ChatGPT-4.0 excels at delivering accurate management and demonstrates its potential as a valuable clinical decision support tool in cardiology.

The integration of artificial intelligence (AI) technologies is evolving in different fields of cardiology and in particular in sports cardiology. Artificial intelligence offers significant opportunities to enhance risk assessment, diagnosis, treatment planning, and monitoring of athletes. This article explores the application of AI in various aspects of sports cardiology, including imaging techniques, genetic testing, and wearable devices. The use of machine learning and deep neural networks enables improved analysis and interpretation of complex datasets. However, ethical and legal dilemmas must be addressed, including informed consent, algorithmic fairness, data privacy, and intellectual property issues. The integration of AI technologies should complement the expertise of physicians, allowing for a balanced approach that optimizes patient care and outcomes. Ongoing research and collaborations are vital to harness the full potential of AI in sports cardiology and advance our management of cardiovascular health in athletes., Competing Interests: Conflict of interest: none declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Personalized medicine and precision medicine, frequently used synonymously, shall be clearly differentiated. Accordingly, personalization in cardiac medicine is based on the clinical presentation of a patient, as well as his/her cardiovascular risk factors and comorbidities, electrocardiography, imaging, and biomarkers for myocardial load and ischemia. Personalization is based on large clinical trials with detailed subgroup analyses and is practiced on the basis of guidelines. Further in depth personalization is achieved by precision medicine, which is based on innovative imaging for myocardial structure, coronary morphology, and electrophysiology. From the clinical perspective, genome analyses are relevant for comparatively rare monogenetic cardiovascular diseases. While these as well as transcriptome and metabolome analyses play a significant role in cardiovascular research with great translation potential, they have not yet been broadly introduced in the diagnosis, prevention, and treatment of complex cardiovascular diseases. Furthermore, digital technologies have considerable potential in cardiovascular precision medicine. On the one hand, this is based on the frequency of the diseases with the availability of Big Data and, on the other hand, on the availability of bio-signals and sensors of those signals in cardiovascular diseases., (© 2024. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.)

This review presents a targeted examination of the application of comprehensive geriatric assessment tools across various cardiovascular pathologies, including acute coronary syndrome, myocardial infarction, acute and chronic heart failure, and aortic stenosis. It has been demonstrated that assessing patient frailty in cardiovascular pathology is crucial for determining both short-term and long-term prognosis, as well as for evaluating the risk of various complications during cardiac surgical interventions. Currently, there is active research into necessary measures aimed at improving outcomes in frail elderly patients with cardiovascular diseases, such as interdisciplinary rehabilitation and geriatric approaches. Frail patients with cardiovascular diseases should be considered as requiring a personalized approach in the provision of cardiological care, with a deep understanding of geriatric issues in the elderly, to reduce complications and improve prognosis.

The purpose of this review is to demonstrate the importance of using a comprehensive geriatric examination in cardiology, including geriatric aspects of the management of this patient population. Until now, the Russian Federation has completely lacked a geriatric approach to the management of cardiological patients, which provides for consideration of international experience in this survey. The curation of elderly and elderly patients is complicated by the presence of geriatric syndromes and age-associated diseases leading to deterioration of quality of life, repeated hospitalizations, disability and risk of death. The leading geriatric syndrome in geriatric practice is senile asthenia and multiple comorbid polymorbid pathologies of the geriatric patient. A patient admitted to an acute care hospital with a history of cardiovascular comorbid pathology is primarily viewed as a patient at high risk for cardiovascular complications, omitting the risk of adverse outcomes, including loss of independence and impaired functional status. The following literature review demonstrates the importance of defining senile asthenia outside of the geriatrician's office, justifying the need for advanced training for cardiologists in geriatrics.

Artificial intelligence (AI) represents a rapidly developing field. Its use can improve diagnosis and therapy in many areas of medicine. Despite this enormous progress, many physicians perceive it as a black box and are skeptical about it. This review will present the basics of machine learning. Different classifications of artificial intelligence, such as supervised versus unsupervised and discriminative versus generative AI, are given. Analogies to human intelligence are discussed as far as algorithms are oriented toward it. In the second step, the most common models like random forest, k-means clustering, convolutional neural network, and transformers will be presented in a way that the underlying idea can be understood. Corresponding medical applications in cardiovascular medicine will be named for all models, respectively. The overview is intended to show that the term artificial intelligence covers a wide range of different concepts. It should help physicians understand the principles of AI to make up one's minds about its application in cardiology. It should also enable them to evaluate results obtained with AI's help critically., (© 2023 The Authors. Clinical Cardiology published by Wiley Periodicals LLC.)

Driven by advances in computing power, the past decade has seen rapid developments in artificial intelligence (AI) which now offers potential enhancements to every aspect of nuclear cardiology workflow including acquisition, reconstruction, segmentation, direct image analysis, and interpretation; as well as facilitating clinical and imaging big-data integration for superior personalized risk stratification. To understand the relevance and potential of AI in their field, this review provides a primer for nuclear cardiologists in 2022. The aim is to explain terminology and provide a summary of key current implementations, challenges, and future aspirations of AI-based enhancements to nuclear cardiology., (© 2022. Crown.)

X-rays are widely used in interventional cardiology (IC). Medical staff is exposed to ionising radiations with difficulties to accurately estimate the absorbed dose, on the other hand, it is well known that eye lens and extremities are the most exposed. In most IC units, radiological monitoring is performed by measuring the personal dose equivalent with a dosemeter worn under the operator's apron. The ambient dose equivalent is, usually, also measured. Furthermore, doses to the lens and extremities are often not measured because of the absence or difficulty of wearing the appropriate dosemeters. The main aim of our study is to estimate the extremities doses, of the interventional cardiologists, from the personal dose equivalent, the patient's received doses or to the ambient dose equivalent. For this purpose, we use a radiological monitoring, of four (04) interventional cardiologists, carried out at Algiers hospital. A Monte Carlo calculation is performed for comparison. This paper reports the preliminary results of this study., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Artificial intelligence (AI) technology is poised to alter the flow of daily life, and in particular, medicine, where it may eventually complement the physician's work in diagnosing and treating disease. Despite the recent frenzy and uptick in AI research over the past decade, the integration of AI into medical practice is in its early stages. Cardiology stands to benefit due to its many diagnostic modalities and diverse treatments. AI methods have been applied to various domains within cardiology: imaging, electrocardiography, wearable devices, risk prediction, and disease classification. While many AI-based approaches have been developed that perform equal to or better than the state-of-the-art, few prospective randomized studies have evaluated their use. Furthermore, obstacles at the intersection of medicine and AI remain unsolved, including model understanding, bias, model evaluation, relevance and reproducibility, and legal and ethical dilemmas. We summarize recent and current applications of AI in cardiology, followed by a discussion of the aforementioned complications., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

The omnipresence and deep impact of artificial intelligence (AI) in today's society are undeniable. While the technology has already established itself as a powerful tool in several industries, more recently it has also started to change the practice of medicine. The aim of this review is to provide healthcare providers working in the field of cardiovascular medicine with an overview of AI and machine learning (ML) algorithms that have passed the initial tests and made it into contemporary clinical practice. The following domains where AI/ML could revolutionize cardiology are covered: (i) signal processing, (ii) image processing, (iii) clinical risk stratification, (iv) natural language processing, and (v) fundamental clinical discoveries., (Copyright © 2022. Published by Elsevier Inc.)

Artificial intelligence (AI) encompasses a variety of computer algorithms that have a wide range of potential clinical applications in nuclear cardiology. This article will introduce core terminology and concepts for AI including classifications of AI as well as training and testing regimens. We will then highlight the potential role for AI to improve image registration and image quality. Next, we will discuss methods for AI-driven image attenuation correction. Finally, we will review advancements in machine learning and deep-learning applications for disease diagnosis and risk stratification, including efforts to improve clinical translation of this valuable technology with explainable AI models., (Copyright © 2023 Elsevier Inc. All rights reserved.)