ChatGPT and Patients With Heart Failure.

ChatGPT (Generative Pre-trained Transformer) is a large-scale language processing model, with possibilities for professional patient support in a patient-friendly way. The aim of the study was to examine the accuracy and reproducibility of ChatGPT in answering questions about knowledge and management of heart failure (HF). First, we recorded 47 most frequently asked questions by patients about HF. The answers of ChatGPT to these questions were independently assessed by two researchers. ChatGPT was able to render the definition of the disease in a very simple and explanatory way. It listed a number of the most important causes of HF and the most important risk factors for its occurrence. It provided correct answers about the most important diagnostic tests and why they are recommended. In addition, it answered health and dietary questions, such as the daily fluid and the alcohol intake. ChatGPT listed the most important classes of drugs in HF and their mechanism of action. It also answered with arguments to questions about patient's sex life, whether they could work, drive, or travel by plane. The performance of ChatGPT was described as very good as it was able to adequately answer all questions posed to it.

The Role of Capsule Endoscopy in the Diagnosis and Management of Small Bowel Tumors: A Narrative Review.

Small bowel tumors (SBT) are relatively rare, but have had a steadily increasing incidence in the last few decades. Small bowel capsule endoscopy (SBCE) and device-assisted enteroscopy are the main endoscopic techniques for the study of the small bowel, the latter additionally providing sampling and therapeutic options, and hence acting complementary to SBCE in the diagnostic work-up. Although a single diagnostic modality is often insufficient in the setting of SBTs, SBCE is a fundamental tool to drive further management towards a definitive diagnosis. The aim of this paper is to provide a concise narrative review of the role of SBCE in the diagnosis and management of SBTs.

Burnout in healthcare - the Emperor's New Clothes.

Burnout is common among physicians; it severely alters their health and has a negative impact on functioning of healthcare systems. Hypertension, increased cortisol levels, maladaptive behaviors with negative social consequences, and suboptimal quality of care have been associated with healthcare providers' burnout. As the number of patients with cancers, psychiatric and neurodegenerative disorders will rise, we need new solutions to maintain physicians' health and, therefore, quality of care. Coping strategies before the COVID-19 pandemic seem ineffective in scaling all the deficits of the global healthcare systems. Examples of new initiatives include new collaborative projects, such as COH-FIT (The Collaborative Outcomes study on Health and Functioning during Infection Times - https://www.coh-fit.com), which aims to collect global data and understand the impact of the COVID-19 pandemic on physical and mental health in order to identify various coping strategies for patients and healthcare workers during infection times, or MEMO (Minimizing Error, Maximizing Outcome), funded by the Agency of Healthcare Research and Quality (AHRQ). Others: i) Rome Foundation GastroPsych undertake efforts dedicated to the science and practice of psychogastroenterology, a burgeoning field with roots in behavioral intervention, cognitive science and experimental psychology focused on fostering the professional growth and collaboration of those engaged in medical practices, or ii) World Gastroenterology Organisation (WGO), Train The Trainers (TTT) program including a new topic of the impact of burnout on career longevity in order to foster strategies for staying healthy and increasing career satisfaction. There is a need for continuous development of digital technologies (e.g. training simulators, telemedicine, robots and artificial intelligence). Their implementation into medical practice is inevitable. Now more than ever, there is a need for a new spirit in healthcare. Together with others in the field, we believe this article is a desperate call for maximizing the use of novel technologies supported by collaborative interactions among healthcare providers and medical professionals of diverse medical fields.

The Utility of Low-Dose-Dobutamine Stress Echocardiography in Patients with Heart Failure with Reduced Ejection Fraction: An Update.

Despite significant advancements in medical therapy, heart failure with reduced ejection fraction (HFrEF) continues to be a significant cause of death and disability. Reversible ischaemic left ventricular dysfunction due to viable myocardium is one such contributing factor. In these cases, coronary revascularization has shown promise in improving left ventricular function and prognosis. For patients with HFrEF and wide QRS, cardiac resynchronization therapy (CRT) is an effective option to address electromechanical dyssynchrony. However, approximately 30% of patients do not respond positively to CRT, highlighting the need to refine candidate selection for this treatment. In some patients with reduced HFrEF, there is a condition known as classical low-flow, low-gradient aortic stenosis (AS) that may be observed. This condition is characterized by a low transaortic flow, which leads to reductions in both the transaortic mean gradient and aortic valve area. Decision-making regarding revascularization, CRT, and pharmacological treatment play a crucial role in managing HFrEF. Cardiac imaging can be valuable in guiding decision-making processes and assessing the prognosis of patients with HFrEF. Among the imaging modalities, dobutamine stress echocardiography has come a long way in establishing itself as a feasible, safe, effective, relatively cheap non-invasive technique. The aim of this review is to explore the current literature on the utility of low-dose stress echocardiography in diagnosing and prognosticating patients with HFrEF.

Robotic-Assisted Solutions for Invasive Cardiology, Cardiac Surgery and Routine On-Ward Tasks: A Narrative Review.

Robots are defined as programmable machines that can perform specified tasks. Medical robots are emerging solutions in the field of cardiology leveraging recent technological innovations of control systems, sensors, actuators, and imaging modalities. Robotic platforms are successfully applied for percutaneous coronary intervention, invasive cardiac electrophysiology procedures as well as surgical operations including minimally invasive aortic and mitral valve repair, coronary artery bypass procedures, and structural heart diseases. Furthermore, machines are used as staff-assisting tools to support nurses with repetitive clinical duties i.e., food delivery. High precision and resolution allow for excellent maneuverability, enabling the performance of medical procedures in challenging anatomies that are difficult or impossible using conventional approaches. Moreover, robot-assisted techniques protect operators from occupational hazards, reducing exposure to ionizing radiation, and limiting risk of orthopedic injuries. Novel automatic systems provide advantages for patients, ensuring device stability with optimized utilization of fluoroscopy. The acceptance of robotic technology among healthcare providers as well as patients paves the way for widespread clinical application in the field of cardiovascular medicine. However, incorporation of robotic systems is associated with some disadvantages including high costs of installation and expensive disposable instrumentations, the need for large operating room space, and the necessity of dedicated training for operators due to the challenging learning curve of robotic-assisted interventional systems.

Artificial Intelligence in Cardiology-A Narrative Review of Current Status.

Artificial intelligence (AI) is an integral part of clinical decision support systems (CDSS), offering methods to approximate human reasoning and computationally infer decisions. Such methods are generally based on medical knowledge, either directly encoded with rules or automatically extracted from medical data using machine learning (ML). ML techniques, such as Artificial Neural Networks (ANNs) and support vector machines (SVMs), are based on mathematical models with parameters that can be optimally tuned using appropriate algorithms. The ever-increasing computational capacity of today's computer systems enables more complex ML systems with millions of parameters, bringing AI closer to human intelligence. With this objective, the term deep learning (DL) has been introduced to characterize ML based on deep ANN (DNN) architectures with multiple layers of artificial neurons. Despite all of these promises, the impact of AI in current clinical practice is still limited. However, this could change shortly, as the significantly increased papers in AI, machine learning and deep learning in cardiology show. We highlight the significant achievements of recent years in nearly all areas of cardiology and underscore the mounting evidence suggesting how AI will take a central stage in the field.

Association of non-alcoholic fatty liver disease with coronary artery calcification progression: a systematic review and meta-analysis.

INTRODUCTION: Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease, which is estimated to affect 20-30% of the adult population in Europe. Several studies have shown an association of NAFLD with multiple cardiovascular risk factors such as abdominal obesity, atherogenic dyslipidaemia, hypertension, insulin resistance, and impaired glucose tolerance. Atherosclerosis is a chronic, progressive, inflammatory disease, which begins early in life and follows a long asymptomatic phase. Coronary artery calcification (CAC) is the radiological confirmation of the presence of atherosclerotic coronary artery disease. The predictive value of CAC for future cardiac events is well established. Also, the progression of CAC is strongly associated with the development of cardiovascular events. AIM: To assess the association of NAFLD with the progression of subclinical atherosclerotic activity, reflected as the dynamic changes in CAC score over time. MATERIAL AND METHODS: The databases PubMed/Medline/Embase from inception until 31 December 2020 were searched for observational studies investigating NAFLD and CAC progression in adults. RESULTS: In total, 5 studies were included, 4 of which, including 10,060 patients, provided data regarding the association of NAFLD with the progression of CAC. The analysis showed that NAFLD is associated with significant odds of progression of CAC; OR = 1.5, 95% CI: 1.34-1.68, p = 0.001. No publication bias was detected (Egger's test p = 0.6). Meta-regression analyses proved that OR toward CAC progression is not significantly influenced by the time of follow-up (coefficient = 0.0083, Z = 1.14, p = 0.25). CONCLUSIONS: NAFLD increases the risk toward CAC progression over time.

A Flavor of the Future of GI Endoscopy-New Solutions Shape the Field of Modern Gastrointestinal Care.

Gastrointestinal (GI) cancers remain high on the list of the leading causes of death worldwide; however, the recent emergence of new and ongoing global healthcare threats, such as the COVID-19 pandemic, has led to a temporary reduction in elective endoscopic procedures [...].

A Constructive Fuzzy Representation Model for Heart Data Classification.

The early detection of Heart Disease (HD) and the prediction of Heart Failure (HF) via telemonitoring and can contribute to the reduction of patients' mortality and morbidity as well as to the reduction of respective treatment costs. In this study we propose a novel classification model based on fuzzy logic applied in the context of HD detection and HF prediction. The proposed model considers that data can be represented by fuzzy phrases constructed from fuzzy words, which are fuzzy sets derived from data. Advantages of this approach include the robustness of data classification, as well as an intuitive way for feature selection. The accuracy of the proposed model is investigated on real home telemonitoring data and a publicly available dataset from UCI.

Conventional cardiac risk factors associated with trastuzumab-induced cardiotoxicity in breast cancer: Systematic review and meta-analysis.

BACKGROUND: Trastuzumab has had a major impact on the treatment of human epidermal growth factor receptor 2 (HER2) positive breast cancer patients. However, it is associated with cardiotoxicity, expressed as an asymptomatic decrease in left ventricular ejection fraction (LVEF) and less often as clinical HF. The aim of this meta-analysis is to identify the association of conventional cardiovascular risk factors with the development of trastuzumab-induced cardiotoxicity (TIC). METHODS: A literature search of PubMed was conducted to identify studies examining the association between cardiovascular risk factors and TIC. Data were extracted and pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated examining the odds of developing TIC for each of the risk factors. RESULTS: A total of 35 studies were included in the analysis. Age (OR:0.7; 95%CI 0.318-1.09; P= 0.0004), hypertension (OR:0.69; 95%CI 0.26-1.12; P = 0.001), smoking(OR:0.35; 95%CI 0.01- 0.69; P = 0.038), diabetes mellitus (OR:0.44; 95%CI 0.24- 0.68; P = 0.0001) and family history of CAD (OR:5.51, 95%CI 1.76-17.25; P< 0.00001)were significantly associated with the development of cardiotoxicity. Known history of CAD (OR: 3.72; 95%CI 2.11-6.57; P = 0.0005) was also associated with the development of TIC. CONCLUSION(S): Identifying women at risk for TIC have several important potential applications. Clinicians may decide to assess LVEF more frequently in patients at highest risk for TIC in order to detect LV systolic dysfunction earlier. Additionally, this could help identify patients who would benefit most from prophylactic therapy for preventing TIC.

Reversed Apico-Basal Myocardial Relaxation Sequence During Exercise in Long QT Syndrome Mutations Carriers With History of Previous Cardiac Events.

BACKGROUND: Recent echocardiography studies in inherited long QT syndrome (LQTS) have shown left ventricular (LV) myocardial relaxation disturbances to follow markedly prolonged and dispersed mechanical contraction. AIM: We used speckle-tracking echocardiography to assess disturbances in LV myocardial relaxation sequence during exercise and their relationship to symptoms. METHODS: Forty seven LQTS patients (45 ± 15 years, 25 female and 20 symptomatic, LVEF: 65 ± 6%) and 35 controls underwent exercise echocardiogram using Bruce protocol. ECG and echo parameters were recorded at rest, peak exercise (p.e.) and recovery. RESULTS: Between patients and controls there were no differences in age, gender, HR or LVEF. At p.e, patients had longer time to LV longitudinal ESR (tESR) at all three LV segments; basal (p < 0.0001), mid- cavity (p = 0.03) and apical (p = 0.03) whereas at rest such difference was noted only at base (p = 0.0007). Patients showed reversed apico-basal relaxation sequence (ΔtESRbase-apex) with early relaxation onset occurring later at base than at apex, both at rest (49 ± 43 vs. -29 ± 19 ms, p < 0.0001) and at p.e. (46 ± 38 vs. -40 ± 22 ms, p < 0.0001), particularly in symptomatic patients (69 ± 44 vs. 32 ± 26, p < 0.0007). ΔtESRbase-apex correlated with longer QTc interval, lower ESR and attenuated LV stroke volume. CONCLUSION: LQTS patients show reversed longitudinal relaxation sequence, which worsens with exercise, particularly in those with previous cardiac events.