Considering User Experience and Behavioral Approaches in the Design of mHealth Interventions for Atrial Fibrillation: Systematic Review.

BACKGROUND: Atrial fibrillation (AF) is a leading chronic cardiac disease associated with an increased risk of stroke, cardiac complications, and general mortality. Mobile health (mHealth) interventions, including wearable devices and apps, can aid in the detection, screening, and management of AF to improve patient outcomes. The inclusion of approaches that consider user experiences and behavior in the design of health care interventions can increase the usability of mHealth interventions, and hence, hopefully, yield an increase in positive outcomes in the lives of users. OBJECTIVE: This study aims to show how research has considered user experiences and behavioral approaches in designing mHealth interventions for AF detection, screening, and management; the phases of designing complex interventions from the UK Medical Research Council (MRC) were referenced: namely, identification, development, feasibility, evaluation, and implementation. METHODS: Studies published until September 7, 2022, that examined user experiences and behavioral approaches associated with mHealth interventions in the context of AF were extracted from multiple databases. The PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines were used. RESULTS: A total of 2219 records were extracted, with only 55 records reporting on usability, user experiences, or behavioral approaches more widely for designing mHealth interventions in the context of AF. When mapping the studies onto the phases of the UK MRC's guidance for developing and evaluating complex interventions, the following was found: in the identification phase, there were significant differences between the needs of patients and health care workers. In the development phase, user perspectives guided the iterative development of apps, interfaces, and intervention protocols in 4 studies. Most studies (43/55, 78%) assessed the usability of interventions in the feasibility phase as an outcome, although the data collection tools were not designed together with users and stakeholders. Studies that examined the evaluation and implementation phase entailed reporting on challenges in user participation, acceptance, and workflows that could not be captured by studies in the previous phases. To realize the envisaged human behavior intended through treatment, review results highlight the scant inclusion of behavior change approaches for mHealth interventions across multiple levels of sociotechnical health care systems. While interventions at the level of the individual (micro) and the level of communities (meso) were found in the studies reviewed, no studies were found intervening at societal levels (macro). Studies also failed to consider the temporal variation of user goals and feedback in the design of long-term behavioral interventions. CONCLUSIONS: In this systematic review, we proposed 2 contributions: first, mapping studies to different phases of the MRC framework for developing and evaluating complex interventions, and second, mapping behavioral approaches to different levels of health care systems. Finally, we discuss the wider implications of our results in guiding future mHealth research.

The co-benefits of climate change mitigation strategies on cardiovascular health: a systematic review.

Background: Climate change is a significant threat to global human health and a leading cause of premature death. Global warming, leading to more extreme weather (in particular extreme heat events), and air pollution has been associated with increased cardiovascular disease (CVD) morbidity and mortality. According to the Global Burden of Disease Study 2019, 62% of the deaths attributable to climate change were from CVD. Climate change mitigation is a slow, steady process, and the concept of co-benefits has arisen to promote climate action. This systematic review examines how numerous mitigation strategies, such as plant-based diets, increasing green spaces, increasing active transport, using renewable energy sources, and smoking cessation, may have the co-benefit of reducing CVD. Methods: A mixed methods systematic review with narrative synthesis was conducted on four databases, according to the PRISMA guidelines. The articles retrieved (published between 2012 and 2022) had a mitigation strategy as the exposure, and CVD related morbidity or mortality reduction as an outcome. Findings: The review found that renewable energy has a stronger association with cardiovascular co-benefits compared to emission reduction targets. Multimodal transport is more beneficial for both the climate and cardiac health than zero emission vehicles. Diet modification, such as Mediterranean and plant-based-diets, is positively associated with CVD reduction. Proximity to green spaces and reducing urbanisation may also improve cardiac health. Interpretation: This systematic review demonstrates that implementing four mitigation strategies - increasing renewable energy use, active transport, green spaces, and plant-based diets; could lead to the co-benefit of reducing CVD morbidity and mortality. Furthermore, it illustrates the importance of plant-based diets and active transport to improve cardiovascular health. Funding: This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Multisystem Inflammatory Syndrome of the Adults (MIS-A) - The undercover threat for young adults. A systematic review and meta-analysis of medical cases.

Background: COVID-19 related syndromes are not yet well described and understood. Multisystem inflammatory syndrome of the adults (MIS-A) is a recently characterized syndrome affecting multiple organs of young adults, causing serious complications, even shock and death. Objectives: To determine the clinical characteristics, course, and complications of MIS-A in a systematic way and summarize currently used treatments. Methods: Literature search in March 2023 in PubMed and Scopus databases. Case reports and case-series that fulfilled the CDC criteria for MIS-A were eligible for inclusion. Results: A total of 71 patients from 60 reports were included. 66% of the patients were male and the mean age of the synthetic cohort was 32.9 years old. The majority (70.4%) of the enrolled cases had no significant medical history. MIS-A was diagnosed after a median of 4 weeks period. All but two patients presented with cardiac symptoms, while the most common secondary diagnostic criterion was abdominal pain, vomiting or diarrhea followed by shock or hypotension. Heart failure therapy and immunomodulation were used as therapeutic options. Although more than half of the cohort was admitted to the Intensive Care Unit (ICU) (n=39) only 4 deaths were reported. Conclusion: MIS-A can affect patients independently of age, sex, and co-morbidity status, resulting in serious complications, often including severe cardiac disease, shock, acute kidney injury and sometimes death. It can occur immediately after SARS-CoV-2 acute infection until two months later, usually manifesting four weeks after acute disease.

The Study of Echocardiography of Left Ventricle Segmentation Combining Transformer and Convolutional Neural Networks.

Accurate prediction of echocardiographic parameters is essential for diagnosis and treatment of cardiac disease, especially for segmentation of the left ventricle to obtain measurements such as left ventricular ejection fraction and volume. However, manually outlining left ventricle on echocardiographic images is a time-consuming and physician experience-dependent task. Therefore, it is crucial to develop an accurate and efficient automatic segmentation tool. Therefore, we aimed to explore a model to perform echocardiography of left ventricle segmentation by combining transformer and convolutional neural networks (CNN).ResNet-50 was used in CNN branch. The encoder-decoder architecture was used for transformer branch, which was fused to the corresponding feature maps of the CNN branches. Fusion module was used to effectively combine feature information from the CNN and transformer. Bridge attention used to increase sensitivity and prediction accuracy of model. The entire network was trained end-to-end using the binary cross-entropy with logits loss L.In this work, we propose an automatic left ventricular (LV) segmentation model based on Transformer and CNN that efficiently captures global dependencies and spatial details and create a fusion module using CBAM that fuses Transformer and CNN features. In addition, attention is also computed using multi-level fusion features to obtain the final attention segmentation map. The model was trained and evaluated on a large cardiac image dataset, EchoNet-Dynamic, with test dice coefficient of 92.4%.The results show that our model can better segment left ventricle. We also tested our model on clinical patient ultrasound images, and visualization results proved effectiveness of the model.

Life Expectancy and Causes of Death in Patients with Myotonic Dystrophy Type 2.

Background: Myotonic Dystrophy type 2 (DM2) is a dominantly inherited multisystem disease caused by a CCTG repeat expansion in intron 1 of the CNBP gene. Although in the last two decades over 1500 patients with DM2 have been diagnosed worldwide, our clinical impression of a reduced life expectancy in DM2 has not been investigated previously. Objective: The aim of this observational study was to determine the life expectancy and the causes of death in patients with genetically confirmed DM2. Methods: We identified the data of all deceased patients with DM2 in the Dutch neuromuscular database between 2000 and 2023. Ages and causes of death and the patients' clinical features during lifetime were determined. Age of death in DM2 was compared to the general population by using life tables with prognostic cohort life expectancy (CLE) and period life expectancy (PLE) data of the Dutch electronic database of statistics (CBS StatLine). Results: Twenty-six deceased patients were identified in the Dutch DM2 cohort (n = 125). Median age of death in DM2 (70.9 years) was significantly lower compared to sex- and age-matched CLE (78.1 years) and PLE (82.1 years) in the Netherlands. Main causes of death were cardiac diseases (31%) and pneumonia (27%). Seven patients (27%) had a malignancy at the time of death. Conclusion: These results provide new insights into the phenotype of DM2. Life expectancy in patients with DM2 is reduced, possibly attributable to multiple causes including increased risk of cardiac disease, pneumonia, and malignancies. The occurrence of a significantly reduced life expectancy has implications for clinical practice and may form a basis for advanced care planning, including end-of-life care, to optimize quality of life for patients with DM2 and their family. Research in larger cohorts should be done to confirm these findings and to ascertain more about the natural course in DM2.

Significance of detecting cardiac troponin I and creatine kinase MB in critically Ill children without primary cardiac illness.

Objective: To investigate the incidence of myocardial injury in children with critically ill children without primary cardiac disease and the association between elevated cardiac troponin I (cTnl) and creatine kinase MB (CK-MB) concentrations and disease progression and prognosis to guide early treatment. Methods: The serum cTnI and CK-MB concentrations of 292 children with critically ill children without primary cardiac disease in Yantai Yuhuangding Hospital between January 2021 and January 2024 were retrospectively analyzed within 24 h after entering the Pediatric Intensive Care Unit (PICU). The children were divided into normal and abnormal groups according to the myocardial marker results. The abnormal group was further divided into the cTnI-elevated, CK-MB-elevated, single-elevated (cTnI- or CK-MB-elevated) and double-elevated (cTnI- and CK-MB-elevated) groups. The differences in the clinical indicators and their relationships with prognosis for the groups were compared. Results: The incidence of myocardial injury among the critically ill children without primary cardiac disease was 55.1%. The incidence of myocardial injury in children with infectious diarrhea combined with moderate and severe dehydration reached 85.19%. The pediatric critical illness score; frequency of use of vasoactive drugs; hypotension, shock, heart failure, respiratory failure, and multiple organ dysfunction syndrome; and mortality indexes differed significantly for the normal and abnormal myocardial marker groups (P < 0.05). The single-elevated and normal groups only showed a difference in mortality (P < 0.017). The cTnI and CK-MB concentrations were negatively correlated with prognosis (P < 0.01). Conclusion: Myocardial injury, as evidenced by elevated cardiac biomarkers, is common in critically ill children without primary cardiac illness. cTnI and CK-MB are associated with outcomes. Shock, heart failure, and multiple organ dysfunction syndromes are independently associated with simultaneous elevations of CK-MB and cTnI concentrations. Further prospective studies are needed to elucidate the clinical utility of these biomarkers.

Evaluation of Galectin-3 in Dogs with Atrial Fibrillation.

Galectin-3 (Gal-3) is a lectin associated with fibrosis and inflammation, and increased circulating concentrations are considered a risk factor for atrial fibrillation (AF) in humans. This retrospective study aimed to evaluate the serum concentration of Gal-3 in dogs with cardiac disease, both with and without AF. Dogs with AF associated with acquired heart diseases were selected, while cardiac healthy dogs and dogs with heart diseases but without AF served as controls. We statistically compared the serum concentration of Gal-3, which was assessed using a commercial canine-specific ELISA kit, among healthy dogs and dogs with heart disease with and without AF. Additionally, associations between Gal-3 and clinical and echocardiographic variables were evaluated. A total of 73 dogs were included, of which 17/73 (23.3%) were cardiac healthy and 56/73 (76.7%) had heart disease, with 26/56 (46.4%) having AF. No significant difference in Gal-3 concentration was found between cardiac healthy dogs (3.90 ± 1.65 ng/mL) and dogs with heart disease, either with or without AF (3.37 ± 1.04 ng/mL, p = 0.436 and 4.68 ± 1.80 ng/mL, p = 0.332, respectively). Gal-3 showed a significant positive correlation with age (r = 0.47, p < 0.001) and a negative correlation with body weight (r = -0.45, p < 0.001). The results of this study suggest that Gal-3 does not have an important role in the development of AF in dogs, but it is associated with advanced age.

Mendelian randomization study of sodium-glucose cotransporter 2 inhibitors in cardiac and renal diseases.

OBJECTIVE: Sodium-glucose cotransporter 2 inhibitors (SGLT2i) target the reabsorption of sodium and glucose in the kidney proximal tubules to reduce blood sugar levels. However, clinical randomized controlled trials on SGLT2i have yielded inconsistent results, necessitating further research into their efficacy and safety for specific cardiac and renal diseases. METHODS: "Sodium in urine" was selected as a downstream biomarker of SGLT2i. Single nucleotide polymorphisms were extracted from genome-wide association study data as instrumental variables. Mendelian randomization analysis was then conducted for cardiac and renal diseases and potential adverse events. The causal effects of SGLT2i on these diseases were determined based on inverse variance weighted results, followed by sensitivity and pleiotropy tests. RESULTS: SGLT2i had a significant protective effect against nephrotic syndrome (odds ratio [OR] 0.0011, 95% confidence interval [CI] 0.000-0.237), chronic glomerulonephritis (OR 0.0002, 95% CI 0.000-0.21), and hypertensive nephropathy (OR 0.0003, 95% CI 0.000-0.785). No causal effects were observed between SGLT2i and cardiac diseases or potential adverse events. CONCLUSIONS: SGLT2i can act as protective factors against nephrotic syndrome, chronic glomerulonephritis, and hypertensive nephropathy.

Systematic Review of Randomized Clinical Trials on Direct Oral Anticoagulants in Pediatric Heart Diseases.

BACKGROUND: Direct oral anticoagulants (DOACs) have been widely applied in adults for thrombosis prophylaxis. However, the effect of DOACs in pediatric patients with congenital or acquired heart diseases who need anticoagulation therapy remains unclear. METHODS: We systematically searched the databases of PubMed, Embase, and the Cochrane Library, as well as the ClinicalTrials.gov registry and the World Health Organization's International Clinical Trials Registry Platform until June 2024 to identify relevant randomized clinical trials (RCTs). If the number of included studies was less than 5, we performed a narrative review to assess the effect of DOACs in pediatric patients. RESULTS: Four studies were included. In the UNIVERSE study, thrombotic events occurred in 2% of the rivaroxaban group and 9% of the aspirin group, with bleeding events in 36% and 41%, respectively. The ENNOBLE-ATE study showed no thromboembolic events in the edoxaban group and 1.7% in the SOC group (rate difference: -0.07%, 95% CI: -0.22 to 0.07%). Major bleeding rates were similar (rate difference: -0.03%, 95% CI: -0.18 to 0.12%). The SAXOPHONE trial showed no thromboembolic events in either group and similar major bleeding rates (-0.8%, 95% CI: -8.1 to 3.3%). In the DIVERSITY trial, 81% of dabigatran patients achieved the primary outcome versus 59.3% in the SOC group (Odds ratio: 0.342, 95% CI: 0.081-1.229). No major bleeding occurred in either group. CONCLUSION: Existing studies suggest that the use of DOACs hold promise as an effective and safe alternative for preventing and treating thromboembolism in pediatric patients with heart conditions.

Cardiac natriuretic peptides.

Over the last four decades, cardiac natriuretic peptides have changed our understanding of patients with chronic heart failure. From the discovery of the heart as an endocrine organ with its own hormones and receptors, the biochemistry and physiology of the system have been translated into useful biomarkers and drug targets in cardiovascular disease. The purpose of this review is to provide medical researchers not working in the field with a simple introduction to the system and its molecular components, its quantitative methods, and its physiology and pathophysiology. The hope is that this overview may help to broaden the knowledge of the endocrine heart with the intent that researchers in other areas of medical research will be inspired to seek new facets of the system, both in translational science and in clinical practice.

The Burden of Inpatient Hospitalizations with Cardiac and Cerebrovascular Diseases in Patients with Type 1 Diabetes: Insights from the National Inpatient Sample in the US.

BACKGROUND: This study aimed to evaluate the burden and impact of cardiac and cerebrovascular disease (CCD) on hospital inpatients with type 1 diabetes mellitus (T1DM). METHODS: This is a retrospective nationwide cohort study of people with T1DM with or without CCD in the US National Inpatient Sample between 2016 and 2019. The in-hospital mortality rates, length of stay (LoS), and healthcare costs were determined. RESULTS: A total of 59,860 T1DM patients had a primary diagnosis of CCD and 1,382,934 did not. The median LoS was longer for patients with CCD compared to no CCD (4.6 vs. 3 days). Patients with T1DM and CCD had greater in-hospital mortality compared to those without CCD (4.1% vs. 1.1%, p < 0.001). The estimated total care cost for all patients with T1DM with CCD was approximately USD 326 million. The adjusted odds of mortality compared to patients with non-CCD admission was greatest for intracranial hemorrhage (OR 17.37, 95%CI 12.68-23.79), pulmonary embolism (OR 4.39, 95%CI 2.70-7.13), endocarditis (OR 3.46, 95%CI 1.22-9.84), acute myocardial infarction (OR 2.31, 95%CI 1.92-2.77), and stroke (OR 1.47, 95%CI 1.04-2.09). CONCLUSIONS: The burden of CCD in patients with T1DM is substantial and significantly associated with increased hospital mortality and high healthcare expenditures.

Cardiac disease risk prediction using machine learning algorithms.

Heart attack is a life-threatening condition which is mostly caused due to coronary disease resulting in death in human beings. Detecting the risk of heart diseases is one of the most important problems in medical science that can be prevented and treated with early detection and appropriate medical management; it can also help to predict a large number of medical needs and reduce expenses for treatment. Predicting the occurrence of heart diseases by machine learning (ML) algorithms has become significant work in healthcare industry. This study aims to create a such system that is used for predicting whether a patient is likely to develop heart attacks, by analysing various data sources including electronic health records and clinical diagnosis reports from hospital clinics. ML is used as a process in which computers learn from data in order to make predictions about new datasets. The algorithms created for predictive data analysis are often used for commercial purposes. This paper presents an overview to forecast the likelihood of a heart attack for which many ML methodologies and techniques are applied. In order to improve medical diagnosis, the paper compares various algorithms such as Random Forest, Regression models, K-nearest neighbour imputation (KNN), Naïve Bayes algorithm etc. It is found that the Random Forest algorithm provides a better accuracy of 88.52% in forecasting heart attack risk, which could herald a revolution in the diagnosis and treatment of cardiovascular illnesses.

Siddha Self-Inquiry for Flow, Bliss, and Uvagai: Mindfulness for Intuitive Lifestyle in Complex Cardiac Disease.

Cardiovascular disease (CVD) and mental health disorders contribute to significant healthcare expenses. Lifestyle approaches that empower and enable patients to participate in their recovery are needed with the increasing complexity of cardiac patients. Traditional Tamil medical practice of Siddha self-inquiry meditation targets holistic health through intuitive lifestyle transformation. We describe 4 complex cardiac patients who explored Siddha based Hunger Gratitude Experience (HUGE) mindful eating and reported elevated levels of optimism and deeper experience of life as outlined by the 5000-year-old secular Siddha medical tradition. We cannot exclude the role of suggestion and placebo effect in descriptive series. However, the simultaneous improvement in physical health and emotional wellbeing along with demonstrated resilience against unforeseen adversities suggests this is Uvagai, the true essence of Siddha higher consciousness. Uvagai is extreme happiness and may be accessible universally with little formal training and targets positive psychology to improve wellbeing. While flow and bliss states are transient transcendental experiences, Uvagai may be more profound and therapeutic in CVD despite age and comorbidities. Seeking Uvagai can potentially overcome health disparities, including rural, minority, and underprivileged populations for better health. HUGE allows CVD patients to safely engage in Uvagai, experience higher consciousness and intuitively sustain lifestyle transformation.

Corrigendum: Classification of feline hypertrophic cardiomyopathy-associated gene variants according to the American College of Medical Genetics and Genomics guidelines.

[This corrects the article DOI: 10.3389/fvets.2024.1327081.].

Sex-Based Performance Disparities in Machine Learning Algorithms for Cardiac Disease Prediction: Exploratory Study.

BACKGROUND: The presence of bias in artificial intelligence has garnered increased attention, with inequities in algorithmic performance being exposed across the fields of criminal justice, education, and welfare services. In health care, the inequitable performance of algorithms across demographic groups may widen health inequalities. OBJECTIVE: Here, we identify and characterize bias in cardiology algorithms, looking specifically at algorithms used in the management of heart failure. METHODS: Stage 1 involved a literature search of PubMed and Web of Science for key terms relating to cardiac machine learning (ML) algorithms. Papers that built ML models to predict cardiac disease were evaluated for their focus on demographic bias in model performance, and open-source data sets were retained for our investigation. Two open-source data sets were identified: (1) the University of California Irvine Heart Failure data set and (2) the University of California Irvine Coronary Artery Disease data set. We reproduced existing algorithms that have been reported for these data sets, tested them for sex biases in algorithm performance, and assessed a range of remediation techniques for their efficacy in reducing inequities. Particular attention was paid to the false negative rate (FNR), due to the clinical significance of underdiagnosis and missed opportunities for treatment. RESULTS: In stage 1, our literature search returned 127 papers, with 60 meeting the criteria for a full review and only 3 papers highlighting sex differences in algorithm performance. In the papers that reported sex, there was a consistent underrepresentation of female patients in the data sets. No papers investigated racial or ethnic differences. In stage 2, we reproduced algorithms reported in the literature, achieving mean accuracies of 84.24% (SD 3.51%) for data set 1 and 85.72% (SD 1.75%) for data set 2 (random forest models). For data set 1, the FNR was significantly higher for female patients in 13 out of 16 experiments, meeting the threshold of statistical significance (-17.81% to -3.37%; P<.05). A smaller disparity in the false positive rate was significant for male patients in 13 out of 16 experiments (-0.48% to +9.77%; P<.05). We observed an overprediction of disease for male patients (higher false positive rate) and an underprediction of disease for female patients (higher FNR). Sex differences in feature importance suggest that feature selection needs to be demographically tailored. CONCLUSIONS: Our research exposes a significant gap in cardiac ML research, highlighting that the underperformance of algorithms for female patients has been overlooked in the published literature. Our study quantifies sex disparities in algorithmic performance and explores several sources of bias. We found an underrepresentation of female patients in the data sets used to train algorithms, identified sex biases in model error rates, and demonstrated that a series of remediation techniques were unable to address the inequities present.

How accurate are NT-proBNP, ANP, and cTnI levels in diagnosing dogs with myxomatous mitral valve disease?

Background: Myxomatous mitral valve disease (MMVD) is prevalent in dogs. Specialized diagnostics (radiography and echocardiography) may be unavailable in some veterinary settings. Cardiac biomarkers offer potential alternatives. Aim: This study evaluated the diagnostic value of N-terminal fragments of pro-brain natriuretic peptides (NT-proBNPs), atrial natriuretic peptides (ANPs), and cardiac troponin I (cTnI) levels in dogs with MMVD. Methods: 69 dogs with MMVD (asymptomatic and symptomatic) and 19 healthy controls were assessed. Biomarker levels were measured using commercial kit rapid tests. Results: Our results showed that the median NT-proBNP level in the symptomatic group was higher than those in the asymptomatic (p < 0.001) and control (p < 0.001) groups. Moreover, the median NT-proBNP level in the asymptomatic group was higher than that in the control group (p < 0.001). The cTnI level in the control group was lower than those in the asymptomatic (p = 0.039) and symptomatic (p = 0.001) groups. No statistically significant difference in the cTnI level was noted between the asymptomatic and symptomatic groups. The best cutoff value of the NT-proBNP level to differentiate the normal controls from dogs with MMVD with or without congestive heart failure was > 505.65 pmol/l [sensitivity, 76.8%; specificity, 89.5%; and area under the curve (AUC), 0.862]. The suggested cutoff value of the NT-proBNP level to differentiate symptomatic MMVD from asymptomatic MMVD was >787.65 pmol/l (sensitivity, 78.38%; specificity, 72.55%; and AUC, 0.792). Conclusion: NT-proBNP and cTnI may serve as point-of-care tests for dyspneic dogs, aiding MMVD assessment where specialized diagnostics are limited.

Bile Acids as Emerging Players at the Intersection of Steatotic Liver Disease and Cardiovascular Diseases.

Affecting approximately 25% of the global population, steatotic liver disease (SLD) poses a significant health concern. SLD ranges from simple steatosis to metabolic dysfunction-associated steatohepatitis and fibrosis with a risk of severe liver complications such as cirrhosis and hepatocellular carcinoma. SLD is associated with obesity, atherogenic dyslipidaemia, and insulin resistance, increasing cardiovascular risks. As such, identifying SLD is vital for cardiovascular disease (CVD) prevention and treatment. Bile acids (BAs) have critical roles in lipid digestion and are signalling molecules regulating glucose and lipid metabolism and influencing gut microbiota balance. BAs have been identified as critical mediators in cardiovascular health, influencing vascular tone, cholesterol homeostasis, and inflammatory responses. The cardio-protective or harmful effects of BAs depend on their concentration and composition in circulation. The effects of certain BAs occur through the activation of a group of receptors, which reduce atherosclerosis and modulate cardiac functions. Thus, manipulating BA receptors could offer new avenues for treating not only liver diseases but also CVDs linked to metabolic dysfunctions. In conclusion, this review discusses the intricate interplay between BAs, metabolic pathways, and hepatic and extrahepatic diseases. We also highlight the necessity for further research to improve our understanding of how modifying BA characteristics affects or ameliorates disease.

Demoralization and well-being among self-employed individuals with cardiac disease: the role of intolerance of uncertainty.

Background: Individuals with cardiac disease (CD) who are self-employed may experience ability limitations and especially intensive challenges and uncertainties. These challenges may cause demoralization and impaired well-being. Objectives: To examine: (a) whether work ability limitations are related to demoralization and well-being among self-employed people with CD; (b) rates of demoralization; and (c) how demoralization and intolerance of uncertainty (IU) are associated with well-being. Methods: The study involved 120 self-employed individuals with CD. The PROCESS macro was used to analyze mediation and moderation processes. Results: The prevalence of demoralization syndrome was 37.4%. Work ability-limitations were associated with higher demoralization levels. Demoralization was associated with well-being only among participants with high IU. Further, demoralization mediated the relationship between work ability limitations and well-being only for individuals with high IU. Conclusion: Encountering limitations among self-employed was associated with demoralization and lower levels of well-being, especially among those with high IU. In addition, demoralization syndrome is prevalent among individuals with CD in general. Early recognition and treatment of demoralization as a treatable psychological syndrome are essential for preventing its degeneration into more complex forms. In addition to uncertainty related to health, it is important to pay special attention to other sources of uncertainty.

Warning Function of Frank's Sign in Pre-Existing Cardiac Disease Patients: A Case Report.

Frank's sign (FS) refers to a diagonal skin fold between the tragus and the outer edge of the earlobe. FS has been identified as an independent variable in coronary artery disease (CAD). Young patients with FS and previous myocardial infarction are still rarely reported in clinical studies. We report the case of a 49-year-old male smoker and diabetic, with a history of myocardial infarction, who presented to the emergency department due to 2 h typical cardiac chest pain. His urgent electrocardiography (ECG) showed ST elevation, and cardiac biomarkers were elevated after admission. A diagonal earlobe crease (DELC) was observed in physical tests. The preliminary diagnosis considered acute coronary syndrome (ACS). Subsequently, acute coronary artery angiography demonstrated a slit-like contrast defect in the proximal right coronary artery (RCA), with stenosis and occlusion in the distal segment. The percutaneous coronary intervention (PCI) was performed immediately. The patient's chest pain symptoms were relieved significantly after intervention. Our case indicates that FS should be highly regarded as a routine cardiovascular clinical examination, which can be effortlessly applied and be easily interpreted for screening to suspect the presence of ischemic heart disease. This may set strategies for primary screening in a younger population and prompt early diagnosis and treatment.