Obesity and cardiovascular risk. Systematic intervention is the key for prevention

Obesity is a serious public health issue and associated with an increased risk of cardiovascular disease events and mortality. The risk of cardiovascular complications is directly related to excess body fat mass and ectopic fat deposition, but also other obesity-related complications such as pre-type 2 diabetes, obstructive sleep apnoea, and non-alcoholic fatty liver diseases. Body mass index and waist circumference are used to classify a patient as overweight or obese and to stratify cardiovascular risk. Physical activity and diet, despite being key points in preventing adverse events and reducing cardiovascular risk, are not always successful strategies. Pharmacological treatments for weight reduction are promising strategies, but are restricted by possible safety issues and cost. Nonetheless, these treatments are associated with improvements in cardiovascular risk factors, and studies are ongoing to better evaluate cardiovascular outcomes. Bariatric surgery is effective in reducing the incidence of death and cardiovascular events such as myocardial infarction and stroke. Cardiac rehabilitation programs in obese patients improve cardiovascular disease risk factors, quality of life, and exercise capacity. The aim of this review was to critically analyze the current role and future aspects of lifestyle changes, medical and surgical treatments, and cardiac rehabilitation in obese patients, to reduce cardiovascular disease risk and mortality, and to highlight the need for a multidisciplinary approach to improving cardiovascular outcomes

An overview of sport participation and exercise prescription in mitral valve disease

The incidence of heart valve disease (HVD) has been rising over the last few decades, mainly due to the increasing average age of the general population, and mitral valve (MV) disease is the second most prevalent HVD after calcific aortic stenosis, but MV disease is a heterogeneous group of different pathophysiological diseases. It is widely proven that regular physical activity reduces all-cause mortality rates, and exercise prescription is part of the medical recommendations for patients affected by cardiovascular diseases. However, changes in hemodynamic balance during physical exercise (including the increase in heart rate, preload, or afterload) could favor the progression of the MV disease and potentially trigger major cardiac events. In young patients with HVD, it is therefore important to define criteria for allowing competitive sport or exercise prescription, balancing the positive effects as well as the potential risks. This review focuses on mitral valve disease pathophysiology, diagnosis, risk stratification, exercise prescription, and competitive sport participation selection, and offers an overview of the principal mitral valve diseases with the aim of encouraging physicians to embody exercise in their daily practice when appropriate

The utility of artificial intelligence and machine learning in the diagnosis of Takotsubo Cardiomyopathy: A systematic review

Introduction: Takotsubo cardiomyopathy (TTC) is a cardiovascular disease caused by physical/psychological stressors with significant morbidity if left untreated. Because TTC often mimics acute myocardial infarction in the absence of obstructive coronary disease, the condition is often underdiagnosed in the population. Our aim was to discuss the role of artificial intelligence (AI) and machine learning (ML) in diagnosing TTC. Methods: We systematically searched electronic databases from inception until April 8, 2023, for studies on the utility of AI- or ML-based algorithms in diagnosing TTC compared with other cardiovascular diseases or healthy controls. We summarized major findings in a narrative fashion and tabulated relevant numerical parameters. Results: Five studies with a total of 920 patients were included. Four hundred and forty-seven were diagnosed with TTC via International Classification of Diseases codes or the Mayo Clinic diagnostic criteria, while there were 473 patients in the comparator group (29 of healthy controls, 429 of myocardial infarction, and 14 of acute myocarditis). Hypertension and smoking were the most common comorbidities in both cohorts, but there were no statistical differences between TTC and comparators. Two studies utilized deep-learning algorithms on transthoracic echocardiographic images, while the rest incorporated supervised ML on cardiac magnetic resonance imaging, 12-lead electrocardiographs, and brain magnetic resonance imaging. All studies found that AI-based algorithms can increase the diagnostic rate of TTC when compared to healthy controls or myocardial infarction patients. In three of these studies, AI-based algorithms had higher sensitivity and specificity compared to human readers. Conclusion: AI and ML algorithms can improve the diagnostic capacity of TTC and additionally reduce erroneous human error in differentiating from MI and healthy individuals

Electrocardiographic features of immune checkpoint inhibitor-associated myocarditis.

Immune checkpoint inhibitors (ICIs) are associated with immune-related adverse events including myocarditis, whilst improving cancer-related outcomes. There is thus a clinical need to identify electrocardiographic manifestations of ICI-related myocarditis to guide clinical management. PubMed was searched for clinical studies and case reports describing electrocardiographic changes in patients with ICI-related myocarditis. A total of six clinical studies and 79 case reports were included. This revealed a range of presentations for patients on ICIs, including supraventricular arrhythmias, ventricular arrhythmias and heart block, and new changes of ST-T segment unrelated to coronary artery disease, ST-segment elevation or depression and T-wave abnormalities. Several patients showed low voltages in multiple leads and new onset Q-wave development. Patients with ICI-related myocarditis may develop new arrhythmia and ST-T changes, and infrequently low voltages in multiple leads. [Abstract copyright: Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.

The Role of Multimodality Imaging Approach in Acute Aortic Syndromes: Diagnosis, Complications, and Clinical Management

Acute aortic syndromes are life-threatening conditions with high morbidity and mortality. The principal pathological feature is acute wall damage with possible evolution towards aortic rupture. Accurate and timely diagnosis is mandatory to avoid catastrophic consequences. Indeed, misdiagnosis with other conditions mimicking acute aortic syndromes is associated with premature death. In this view, cardiovascular imaging is necessary for the correct diagnosis and management. Echocardiography, computed tomography, magnetic resonance imaging, and aortography allow for diagnosis, guarantee immediate treatment, and detect associated complications. Multimodality imaging is essential in the diagnostic work-up to confirm or rule out acute aortic syndromes. The aim of this review is to highlight the contemporary evidence on the role of single cardiovascular imaging techniques and multimodality imaging in the diagnosis and management of acute aortic syndromes

The utility of artificial intelligence and machine learning in the diagnosis of Takotsubo cardiomyopathy: a systematic review

Introduction: Takotsubo cardiomyopathy (TTC) is a cardiovascular disease caused by physical/psychological stressors with significant morbidity if left untreated. Because TTC often mimics acute myocardial infarction in the absence of obstructive coronary disease, the condition is often underdiagnosed in the population. Our aim was to discuss the role of artificial intelligence (AI) and machine learning (ML) in diagnosing TTC. Methods: We systematically searched electronic databases from inception until April 8, 2023, for studies on the utility of AI- or ML-based algorithms in diagnosing TTC compared with other cardiovascular diseases or healthy controls. We summarized major findings in a narrative fashion and tabulated relevant numerical parameters. Results: Five studies with a total of 920 patients were included. Four hundred and forty-seven were diagnosed with TTC via International Classification of Diseases codes or the Mayo Clinic diagnostic criteria, while there were 473 patients in the comparator group (29 of healthy controls, 429 of myocardial infarction, and 14 of acute myocarditis). Hypertension and smoking were the most common comorbidities in both cohorts, but there were no statistical differences between TTC and comparators. Two studies utilized deep-learning algorithms on transthoracic echocardiographic images, while the rest incorporated supervised ML on cardiac magnetic resonance imaging, 12-lead electrocardiographs, and brain magnetic resonance imaging. All studies found that AI-based algorithms can increase the diagnostic rate of TTC when compared to healthy controls or myocardial infarction patients. In three of these studies, AI-based algorithms had higher sensitivity and specificity compared to human readers. Conclusion: AI and ML algorithms can improve the diagnostic capacity of TTC and additionally reduce erroneous human error in differentiating from MI and healthy individuals

Electrocardiographic features of immune checkpoint inhibitor-associated myocarditis

Immune checkpoint inhibitors (ICIs) are associated with immune-related adverse events including myocarditis, whilst improving cancer-related outcomes. There is thus a clinical need to identify electrocardiographic manifestations of ICI-related myocarditis to guide clinical management. PubMed was searched for clinical studies and case reports describing electrocardiographic changes in patients with ICI-related myocarditis. A total of six clinical studies and 79 case reports were included. This revealed a range of presentations for patients on ICIs, including supraventricular arrhythmias, ventricular arrhythmias and heart block, and new changes of ST-T segment unrelated to coronary artery disease, ST-segment elevation or depression and T-wave abnormalities. Several patients showed low voltages in multiple leads and new onset Q-wave development. Patients with ICI-related myocarditis may develop new arrhythmia and ST-T changes, and infrequently low voltages in multiple leads

Rethinking ‘Rational Imitation’ in 14-Month-Old Infants: A Perceptual Distraction Approach

In their widely noticed study, Gergely, Bekkering, and Király (2002) showed that 14-month-old infants imitated an unusual action only if the model freely chose to perform this action and not if the choice of the action could be ascribed to external constraints. They attributed this kind of selective imitation to the infants' capacity of understanding the principle of rational action. In the current paper, we present evidence that a simpler approach of perceptual distraction may be more appropriate to explain their results. When we manipulated the saliency of context stimuli in the two original conditions, the results were exactly opposite to what rational imitation predicts. Based on these findings, we reject the claim that the notion of rational action plays a key role in selective imitation in 14-month-olds