Applications of ChatGPT in Heart Failure Prevention, Diagnosis, Management, and Research: A Narrative Review.

Heart failure (HF) is a leading cause of mortality, morbidity, and financial burden worldwide. The emergence of advanced artificial intelligence (AI) technologies, particularly Generative Pre-trained Transformer (GPT) systems, presents new opportunities to enhance HF management. In this review, we identified and examined existing studies on the use of ChatGPT in HF care by searching multiple medical databases (PubMed, Google Scholar, Medline, and Scopus).

Clinical parameters of death and heart failure hospitalization in biventricular systolic dysfunction assessed via cardiac magnetic resonance.

Aims: While factors associated with adverse events are well elucidated in setting of isolated left ventricular dysfunction, clinical and imaging-based prognosticators of adverse outcomes are lacking in context of biventricular dysfunction. The purpose of this study was to establish role of clinical variables in prognosis of biventricular heart failure (HF), as assessed by cardiac magnetic resonance imaging.

Methods: Study cohort consisted of 840 patients enrolled in DERIVATE registry with coexisting CMR-derived right ventricular (RV) and left ventricular (LV) dysfunction, as defined by RV and LV ejection fractions ≤45 % and ≤ 50 %, respectively.

Percutaneous pericardiocentesis using the apical approach: case series and review of the literature.

Background: Pericardiocentesis offers a definitive diagnostic and a life-saving therapeutic modality through removal of pericardial fluid and relief of high intrapericardial pressure. Percutaneous pericardiocentesis has been performed via different approaches depending on different institutional experiences. In this paper, we present our institutional experience and review the current literature of the different approaches for performing percutaneous pericardiocentesis.

COVID-19 in the Initiation and Progression of Atherosclerosis: Pathophysiology During and Beyond the Acute Phase.

The incidence of atherosclerotic cardiovascular disease is increasing globally, especially in low- and middle-income countries, despite significant efforts to reduce traditional risk factors. Premature subclinical atherosclerosis has been documented in association with several viral infections. The magnitude of the recent COVID-19 pandemic has highlighted the need to understand the association between SARS-CoV-2 and atherosclerosis.

Renal Biomarkers in Heart Failure: Systematic Review and Meta-Analysis.

Background: Cystatin C, neutrophil gelatinase-associated lipocalin (NGAL), and kidney injury molecule (KIM)-1 are renal biomarkers increasingly appreciated for their role in the risk stratification and prognostication of heart failure (HF) patients. However, very few have been adopted clinically, owing to the lack of consistency.

Objectives: The authors aimed to study the association between cystatin C, NGAL, and KIM-1 and outcomes, mortality, hospitalizations, and worsening renal function (WRF) in patients with acute and chronic HF.

Hidden Flaws Behind Expert-Level Accuracy of Multimodal GPT-4 Vision in Medicine.

Recent studies indicate that Generative Pre-trained Transformer 4 with Vision (GPT-4V) outperforms human physicians in medical challenge tasks. However, these evaluations primarily focused on the accuracy of multi-choice questions alone. Our study extends the current scope by conducting a comprehensive analysis of GPT-4V's rationales of image comprehension, recall of medical knowledge, and step-by-step multimodal reasoning when solving (NEJM) Image Challenges - an imaging quiz designed to test the knowledge and diagnostic capabilities of medical professionals.

Low-cost prototyping of nitinol wires/frames using polymeric cores and sacrificial fixtures with application in individualized frames anchoring through the atrial septum.

Self-expanding frames for minimally invasive implants are typically made from nitinol wires and are heat treated to maintain the desired shapes. In the process of heat treatment, nitinol structures are placed in a high-temperature oven, while they are confined by a fixture. During this process, nitinol exerts a high amount of force.

Application of deep neural networks for inferring pressure in polymeric acoustic transponders/sensors.

Passive sensor-transponders have raised interest for the last few decades, due to their capability of low-cost remote monitoring without the need for energy storage. Their operating principle includes receiving a signal from a source and then reflecting the signal. While well-established transponders operate through electromagnetic antennas, those with a fully acoustic design have advantages such as lower cost and simplicity.

Machine Learning in Cardiovascular Risk Prediction and Precision Preventive Approaches.

Purpose Of Review: In this review, we sought to provide an overview of ML and focus on the contemporary applications of ML in cardiovascular risk prediction and precision preventive approaches. We end the review by highlighting the limitations of ML while projecting on the potential of ML in assimilating these multifaceted aspects of CAD in order to improve patient-level outcomes and further population health.

Recent Findings: Coronary artery disease (CAD) is estimated to affect 20.

The journal of cardiovascular computed tomography: A year in review: 2022.

This review aims to summarize key articles published in the Journal of Cardiovascular Computed Tomography (JCCT) in 2022, focusing on those that had the most scientific and educational impact. The JCCT continues to expand; the number of submissions, published manuscripts, cited articles, article downloads, social media presence, and impact factor continues to grow. The articles selected by the Editorial Board of the JCCT in this review highlight the role of cardiovascular computed tomography (CCT) to detect subclinical atherosclerosis, assess the functional relevance of stenoses, and plan invasive coronary and valve procedures.

Comparing the pooled cohort equations and coronary artery calcium scores in a symptomatic mixed Asian cohort.

Background: The value of pooled cohort equations (PCE) as a predictor of major adverse cardiovascular events (MACE) is poorly established among symptomatic patients. Coronary artery calcium (CAC) assessment further improves risk prediction, but non-Western studies are lacking. This study aims to compare PCE and CAC scores within a symptomatic mixed Asian cohort, and to evaluate the incremental value of CAC in predicting MACE, as well as in subgroups based on statin use.

Artificial Intelligence, Wearables and Remote Monitoring for Heart Failure: Current and Future Applications.

Substantial milestones have been attained in the field of heart failure (HF) diagnostics and therapeutics in the past several years that have translated into decreased mortality but a paradoxical increase in HF-related hospitalizations. With increasing data digitalization and access, remote monitoring via wearables and implantables have the potential to transform ambulatory care workflow, with a particular focus on reducing HF hospitalizations. Additionally, artificial intelligence and machine learning (AI/ML) have been increasingly employed at multiple stages of healthcare due to their power in assimilating and integrating multidimensional multimodal data and the creation of accurate prediction models.

Influence of Iron Deficiency on Clinical and Haemodynamic Parameters in Pulmonary Arterial Hypertension Cohorts.

Background: Iron deficiency (Fe) has been shown to be common in patients with group 1 or pulmonary arterial hypertension (PAH). Several studies have shown a negative impact of Fe on clinical and haemodynamic parameters of the disease, but data from individual studies have not been strong enough to lead to incorporation of the finding of Fe into prognostic or therapeutic algorithms. The goal of this meta-analysis was to combine data from available studies to better define any associations between Fe and established variables of prognostic importance in PAH.

Prolactin Inhibition in Peripartum Cardiomyopathy: Systematic Review and Meta-analysis.

Heart failure (HF) is one of the leading causes of maternal mortality and morbidity in the United States. Peripartum cardiomyopathy (PPCM) constitutes up to 70% of all HF in pregnancy. Cardiac angiogenic imbalance caused by cleaved 16kDa prolactin has been hypothesized to contribute to the development of PPCM, fueling investigation of prolactin inhibitors for the management of PPCM.

Contemporary Applications of Machine Learning for Device Therapy in Heart Failure.

Despite a better understanding of the underlying pathogenesis of heart failure (HF), pharmacotherapy, surgical, and percutaneous interventions do not prevent disease progression in all patients, and a significant proportion of patients end up requiring advanced therapies. Machine learning (ML) is gaining wider acceptance in cardiovascular medicine because of its ability to incorporate large, complex, and multidimensional data and to potentially facilitate the creation of predictive models not constrained by many of the limitations of traditional statistical approaches. With the coexistence of "big data" and novel advanced analytic techniques using ML, there is ever-increasing research into applying ML in the context of HF with the goal of improving patient outcomes.

Early versus late acute coronary syndrome risk patterns of coronary atherosclerotic plaque.

Aims: The temporal instability of coronary atherosclerotic plaque preceding an incident acute coronary syndrome (ACS) is not well defined. We sought to examine differences in the volume and composition of coronary atherosclerosis between patients experiencing an early (≤90 days) versus late ACS (>90 days) after baseline coronary computed tomography angiography (CCTA).

Methods And Results: From a multicenter study, we enrolled patients who underwent a clinically indicated baseline CCTA and experienced ACS during follow-up.

HDL cholesterol levels and susceptibility to COVID-19.

Background: Host cell-membrane cholesterol, an important player in viral infections, is in constant interaction with serum high-density lipoprotein-cholesterol (HDL-C) and low-density lipoprotein-cholesterol (LDL-C). Low serum lipid levels during hospital admission are associated with COVID-19 severity. However, the effect of antecedent serum lipid levels on SARS-CoV-2 infection risk has not been explored.

Cardiac magnetic resonance for prophylactic implantable-cardioverter defibrillator therapy international study: prognostic value of cardiac magnetic resonance-derived right ventricular parameters substudy.

Aims: Right ventricular systolic dysfunction (RVSD) is an important determinant of outcomes in heart failure (HF) cohorts. While the quantitative assessment of RV function is challenging using 2D-echocardiography, cardiac magnetic resonance (CMR) is the gold standard with its high spatial resolution and precise anatomical definition. We sought to investigate the prognostic value of CMR-derived RV systolic function in a large cohort of HF with reduced ejection fraction (HFrEF).

Age related compositional plaque burden by CT in patients with future ACS.

Background: We examined age differences in whole-heart volumes of non-calcified and calcified atherosclerosis by coronary computed tomography angiography (CCTA) of patients with future ACS.

Methods: A total of 234 patients with core-lab adjudicated ACS after baseline CCTA were enrolled. Atherosclerotic plaque was quantified and characterized from the main epicardial vessels and side branches on a 0.

Significance of indeterminate and abnormal stress electrocardiography despite normal imaging in patients with suspected coronary artery disease - An analysis of the PROMISE trial.

Background: Abnormal and indeterminate electrocardiographic (ECG) changes during cardiac stress imaging are not uncommon. While the prognostic importance of abnormal ECG despite normal imaging has been previously studied, prognosis of indeterminate stress ECG changes is uncertain.

Methods: We studied the prognostic value of stress ECG changes in symptomatic patients without known CAD and normal stress imaging from the PROMISE trial.

Evaluating the Coronary Artery Disease Consortium Model and the Coronary Artery Calcium Score in Predicting Obstructive Coronary Artery Disease in a Symptomatic Mixed Asian Cohort.

Background The utility of a given pretest probability score in predicting obstructive coronary artery disease (CAD) is population dependent. Previous studies investigating the additive value of coronary artery calcium (CAC) on pretest probability scores were predominantly limited to Western populations. This retrospective study seeks to evaluate the CAD Consortium (CAD2) model in a mixed Asian cohort within Singapore with stable chest pain and to evaluate the incremental value of CAC in predicting obstructive CAD.