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INTRODUCTION: As surgical technologies grow, so too do demands on surgical trainees to master increasing numbers of skill sets. With the rise of endovascular surgery, trainees have fewer opportunities to practice open vascular techniques in the operating room. Simulation can bridge this gap. However, existing published open vascular simulation curricula are basic or based on expensive models. METHODS: We iteratively developed an open vascular skills curriculum for second-year surgery residents comprising six 2-hour sessions. We refined the curriculum based on feedback from learners and faculty. The curriculum required skilled facilitators, vascular instruments, and tissue models. We evaluated the latest iteration with a survey and by assessing participants technical skills using the Objective Structured Assessment of Technical Skills (OSATS) form. RESULTS: Over the past 10 years, 101 residents have participated in the curriculum. Nine of 13 residents who participated in the latest curricular iteration completed the survey. All respondents rated the sessions as excellent and strongly agreed that they had improved their abilities to perform anastomoses with tissue and prosthetic. Facilitators completed 18 OSATS forms for residents in the fifth and sixth sessions of the latest iteration. Residents scored well overall, with a median 26.5 (interquartile range: 24-29) out of a possible score of 35, with highest scores on knowledge of instruments. DISCUSSION: This simulation-based curriculum facilitates open vascular surgical skill acquisition among surgery residents. The curriculum allows residents to acquire critical vascular skills that are challenging to learn in an increasingly demanding operative setting.

Introduction: Direct current cardioversion (DCCV) remains one of the recommended management strategies for symptomatic atrial fibrillation (AF). Antiarrhythmic drugs (AAD) are prescribed post procedure to maintain sinus rhythm (SR). Limited literature exists on the AAD prescribing practices and their efficacy, post‐DCCV in rural Australia. Objective: The primary aim was to determine the preferred AAD post‐DCCV and the factors affecting AAD prescribing practices. The secondary aim was to assess the efficacy of the AAD in maintaining SR. Design: A retrospective observational audit of patients with non‐valvular AF who underwent successful elective DCCV for symptomatic AF, during 2015–2020 at a regional hospital in New South Wales (NSW) (Dubbo Base Hospital). Patients were followed up for a duration of 12 months post‐DCCV. Results: 233 patients underwent successful DCCV during the study duration. Amiodarone was the preferred AAD of choice post‐DCCV followed by sotalol and flecainide, respectively (36.5% vs. 27.8% vs. 1.3%). 35.2% patients were not prescribed AAD. Amiodarone and sotalol had similar but modest efficacies and neither were superior to no AAD, in maintaining SR 12 months post‐DCCV (AF recurrence rate 61.5% vs. 68.2% vs. 71.6% respectively, p = 0.37). Antecedent cerebrovascular accident (CVA), pulmonary disease, smoking, prior treatment with digoxin, diuretics and left ventricular (LV) dysfunction were factors that influenced AAD prescribing practices. Conclusion: The study demonstrates equal efficacies of amiodarone, sotalol and no AAD in maintaining SR 12 months post‐DCCV. Prescribing practices post‐DCCV at Dubbo Base Hospital differ from observed national trends and guidelines. AAD prescription requires a multifaceted approach with a key consideration to prioritise safety over efficacy, being mindful of challenges in delivering optimal healthcare in a rural setting. [ABSTRACT FROM AUTHOR]

Today, it is almost 22 years since the first transcatheter aortic valve implant (TAVI) and 11 years since the first transcatheter mitral valve implantation (TMVI) was implanted. TMVI never escalated like TAVI. So far, only one transcatheter mitral valve (TMV) has Conformité Européenne approval and none has Food and Drug Administration approval. This means that no TMV is commercial in the United States. There are several TMVs in clinical studies, but because of anatomical limitations, inclusion is slow. This editorial focuses on the challenges and opportunities in TMVI.

Congestive heart failure (CHF) is a multifaceted clinical syndrome characterized by the inability of the heart to pump blood effectively, leading to inadequate oxygen and nutrient delivery to the body tissues. Despite advancements in treatment strategies, including guideline-directed medical treatment (GDMT), end-stage CHF remains a significant cause of morbidity and mortality worldwide. Heart transplantation is considered to be the gold standard treatment of end stage CHF but constrained by the lack of organ donors, lengthening waitlists, and the negative side effects of lifelong immunosuppressive medications. Mechanical circulatory support (MCS) has emerged as a pivotal intervention for patients with end-stage CHF, serving as a bridge to recovery, transplantation, or destination therapy. The aim of this narrative review is to highlight the historical development of MCS, to assess the recent status of MCS device technology and discuss current challenges associated with complications of MCS that need to be solved in the future by device development. The history of MCS dates back to pioneering efforts in the 1960s, with significant progress in device development and utilization over decades. MCS devices, including left ventricular assist devices (LVADs), extracorporeal membrane oxygenation (ECMO), and artificial hearts, play a crucial role in providing circulatory support to patients with end-stage CHF. Recent advancements in MCS technology aim to decrease the device size, enhance blood compatibility, reduce thrombo-embolic complications, and prolong device durability and battery life and improve physiological performance of MCS. Continued research and innovation are essential to address these challenges and improve outcomes in patients with end-stage CHF. Artificial intelligence (AI) has emerged as a valuable tool in cardiovascular medicine to facilitate risk prediction, patient selection, and treatment optimization for MCS and heart transplantation. Despite these advancements, challenges persist in MCS device selection, resource allocation, and integration of AI into clinical practice. Continued research and innovation are essential to address these challenges and improve outcomes in patients with advanced heart failure. [ABSTRACT FROM AUTHOR]

It is thought that ChatGPT, an advanced language model developed by OpenAI, may in the future serve as an AI-assisted decision support tool in medicine. To evaluate the accuracy of ChatGPT's recommendations on medical questions related to common cardiac symptoms or conditions. We tested ChatGPT's ability to address medical questions in two ways. First, we assessed its accuracy in correctly answering cardiovascular trivia questions (n = 50), based on quizzes for medical professionals. Second, we entered 20 clinical case vignettes on the ChatGPT platform and evaluated its accuracy compared to expert opinion and clinical course. Lastly, we compared the latest research version (v3.5; 27 September 2023) with a prior version (v3.5; 30 January 2023) to evaluate improvement over time. We found that ChatGPT latest version correctly answered 92% of the trivia questions, with slight variation in accuracy in the domains coronary artery disease (100%), pulmonary and venous thrombotic embolism (100%), atrial fibrillation (90%), heart failure (90%) and cardiovascular risk management (80%). In the 20 case vignettes, ChatGPT's response matched in 17 (85%) of the cases with the actual advice given. Straightforward patient-to-physician questions were all answered correctly (10/10). In more complex cases, where physicians (general practitioners) asked other physicians (cardiologists) for assistance or decision support, ChatGPT was correct in 70% of cases, and otherwise provided incomplete, inconclusive, or inappropriate recommendations when compared with expert consultation. ChatGPT showed significant improvement over time; as the January version correctly answered 74% (vs 92%) of trivia questions (p = 0.031), and correctly answered a mere 50% of complex cases. Our study suggests that ChatGPT has potential as an AI-assisted decision support tool in medicine, particularly for straightforward, low-complex medical questions, but further research is needed to fully evaluate its potential. [ABSTRACT FROM AUTHOR]

Today, it is almost 22 years since the first transcatheter aortic valve implant (TAVI) and 11 years since the first transcatheter mitral valve implantation (TMVI) was implanted. TMVI never escalated like TAVI. So far, only one transcatheter mitral valve (TMV) has Conformité Européenne approval and none has Food and Drug Administration approval. This means that no TMV is commercial in the United States. There are several TMVs in clinical studies, but because of anatomical limitations, inclusion is slow. This editorial focuses on the challenges and opportunities in TMVI. [ABSTRACT FROM AUTHOR]

Summary: Non-invasive, real-time monitorable indicators for early assessment of sepsis-associated myocardial injury (SMI) are still lacking. We aimed to develop non-invasive, real-time indicators for early assessment of SMI using bedside heart rate (HR) and diastolic arterial pressure (DAP) monitors. In this multi-center cohort study, piece-wise exponential additive mixed models were used to estimate the exposure window and time fraction of the hazardous exposure proportion, and secondarily to analyze the exposure characterization on this basis to identify high-risk exposure pattern. In total, 20,043 patients were finally included; we found that SMI patients had the highest survival rate when HR was 0.3 and 0.2, respectively, and exposure window on admission day 1). H1D-1 exposure pattern using glucocorticoids significantly increased the risk of mortality in H1D-1. Validation against various methodologies and data sources demonstrated acceptable consistency.

Summary: Nowadays cardiorespiratory fitness (CRF) is assessed using summary indexes of cardiopulmonary exercise tests (CPETs). Yet, raw time-series CPET recordings may hold additional information with clinical relevance. Therefore, we investigated whether analysis of raw CPET data using dynamic time warping combined with k-medoids could identify distinct CRF phenogroups and improve cardiovascular (CV) risk stratification. CPET recordings from 1,399 participants (mean age, 56.4 years; 37.7% women) were separated into 5 groups with distinct patterns. Cluster 5 was associated with the worst CV profile with higher use of antihypertensive medication and a history of CV disease, while cluster 1 represented the most favorable CV profile. Clusters 4 (hazard ratio: 1.30; p = 0.033) and 5 (hazard ratio: 1.36; p = 0.0088) had a significantly higher risk of incident adverse events compared to clusters 1 and 2. The model evaluation in the external validation cohort revealed similar patterns. Therefore, an integrative CRF profiling might facilitate CV risk stratification and management.

Summary: Autoimmune patients have a significantly increased risk of developing coronary artery disease (CAD) compared to the general population. However, autoimmune patients often lack traditional risk factors for CAD and there is increasing recognition of inflammation in CAD development. In this study, we leveraged genome-wide association study (GWAS) data to understand whether there is a genetic relationship between CAD and autoimmunity. Statistical genetic comparison methods were used to identify correlated and causal SNPs between various autoimmune diseases and CAD. Pleiotropic SNPs were identified by cross-phenotype association analysis (CPASSOC) and overlap between GWAS. Causal SNPs were identified using Mendelian Randomization (MR) and Colocalization (COLOC). Using SNP-to-gene mapping, we additionally identified pleiotropic and causal genes and pathways associated between autoimmunity and CAD, which were contextualized by documentation of enrichment in individual cell types identified from coronary atherosclerotic plaques by single-cell RNA sequencing. These results provide insight into potential inflammatory therapeutic targets for CAD.

Summary: Previous studies have indicated that various blood cell traits are associated with a higher risk of venous thromboembolism (VTE). However, the causal relationship remains uncertain. We collected data from the China pulmonary thromboembolism registry study and the China pulmonary health study, using propensity score matching and two-sample Mendelian randomization analyses with summary statistics from genome-wide association studies of blood cell traits and VTE in the East Asian population. Our findings revealed that platelet (PLT) count and hemoglobin (Hb) levels were significantly higher in VTE patients compared to the general population (p value

Summary: Abdominal and thoracic aortic aneurysms (AAAs, TAAs) remain a major cause of deaths worldwide, in part due to the lack of reliable prognostic markers or early warning signs. Sox6 has been found to regulate renin controlling blood pressure. We hypothesized that Sox6 may serve as an important regulator of the mechanisms contributing to hypertension-induced aortic aneurysms. Phenotype and laboratory-wide association scans in a clinical cohort found that SOX6 gene expression is associated with aortic aneurysm in subjects of European ancestry. Sox6 and tumor necrosis factor alpha (TNF-α) expression were upregulated in aortic tissues from patients affected by either AAA or TAA. In Sox6 knockout mice with angiotensin-II-induced AAA, we found that Sox6 plays critical role in the development and progression of AAA. Our data support a regulatory role of SOX6 in the development of hypertension-induced AAA, suggesting that Sox6 may be a therapeutic target for the treatment of aortic aneurysms.

Summary: Pyruvate dehydrogenase complex (PDC) is a crucial enzyme that connects glycolysis and the tricarboxylic acid (TCA) cycle pathway. It plays an essential role in regulating glucose metabolism for energy production by catalyzing the oxidative decarboxylation of pyruvate to acetyl coenzyme A. Importantly, the activity of PDC is regulated through post-translational modifications (PTMs), phosphorylation, acetylation, and O-GlcNAcylation. These PTMs have significant effects on PDC activity under both physiological and pathophysiological conditions, making them potential targets for metabolism-related diseases. This review specifically focuses on the PTMs of PDC in cardiovascular diseases (CVDs) such as myocardial ischemia/reperfusion injury, diabetic cardiomyopathy, obesity-related cardiomyopathy, heart failure (HF), and vascular diseases. The findings from this review offer theoretical references for the diagnosis, treatment, and prognosis of CVD.

Summary: Increasing cohort studies have examined the link between mitochondrial DNA copy number (mtDNA-CN) and cardiovascular disease (CVD), with inconsistent findings. We searched PubMed, EMBASE, and Web of Science up to July 11, 2023 and used a random-effects model to calculate summary hazard ratios (HRs) and 95% confidence intervals (CIs). This systematic review and meta-analysis included 8 articles encompassing 29 studies with 646,398 participants. Individuals with the lowest mtDNA-CN had a summary HR of 1.27 (95% CI 1.02–1.59) for CVD, 1.18 (95% CI 0.92–1.50) for coronary heart disease (CHD), 1.10 (95% CI 0.89–1.37) for stroke, and 1.30 (95% CI 1.07–1.56) for heart failure (HF). Decreased mtDNA-CN is linked to an increased risk of CVD and HF but not CHD and stroke. These findings suggest mtDNA-CN from leukocytes may be a potential early biomarker for CVD. However, more prospective studies with long follow-up are needed.

Summary: The global outcome of acute aortic dissection (AD) remains poor, with a high risk of the need for urgent dialysis. This study aimed to clarify the association between sex and the requirement for urgent dialysis within 30 days after admission among patients with AD. This study included 79,998 cases who were hospitalized due to AD in Japan from 2010 to 2020 using an administrative claims database. The association between the risk of urgent dialysis and sex was investigated using the Fine and Gray model. Patients were classified into two groups based on the Stanford classification: type A AD (TAAD) and type B AD (TBAD). The lower subdistribution hazard ratio (SHR) in women was observed in both groups: TAAD (SHR: 0.58, 95% confidence interval [CI]: 0.54–0.62); TBAD (SHR: 0.49, 95% CI: 0.41–0.58). Our study revealed that women had a lower risk of requiring urgent dialysis than men in TAAD and TBAD.

Summary: Erythropoietin-producing hepatoma (Eph) receptors, comprising the largest family of receptor tyrosine kinases (RTKs), exert profound influence on diverse biological processes and pathological conditions such as cancer. Interacting with their corresponding ligands, erythropoietin-producing hepatoma receptor interacting proteins (Ephrins), Eph receptors regulate crucial events like embryonic development, tissue boundary formation, and tumor cell survival. In addition to their well-established roles in embryonic development and cancers, emerging evidence highlights the pivotal contribution of the Ephrin/Eph family to cardiovascular physiology and pathology. Studies have elucidated their involvement in cardiovascular development, atherosclerosis, postnatal angiogenesis, and, more recently, cardiac fibrosis and calcification, suggesting a promising avenue for therapeutic interventions in cardiovascular diseases. There remains a need for a comprehensive synthesis of their collective impact in the cardiovascular context. By exploring the intricate interactions between Eph receptors, ephrins, and cardiovascular system, this review aims to provide a holistic understanding of their roles and therapeutic potential in cardiovascular health and diseases.

Summary: Myocardial remodeling (MR) following myocardial infarction (MI) contributes to heart failure. Inflammation is a key determinant in cardiac remodeling, with potential prognostic improvements by inhibiting inflammatory factors. Pattern recognition receptors, including interferon gamma-inducible protein-16 (IFI-16), play significant roles in this process, yet its specific involvement remains underexplored. This study investigates IFI-16’s role in initiating inflammation via the inflammasome and its direct interaction with galectin-3 protein post-MI. Elevated IFI-16 levels were observed in human and rat myocytes and a mouse MI model under hypoxic, nutrient-deprived conditions, correlating with increased inflammation-associated proteins. Suppression of IFI-16/IFI-204 using short hairpin RNA (shRNA) lentivirus or adeno-associated virus decreased inflammatory factor activation, thereby mitigating remodeling and enhancing cardiac function post-MI. Co-immunoprecipitation (coIP) and double-fluorescence staining confirmed IFI-16’s ability to interact directly with galectin-3. These findings underscore IFI-16’s critical role as a pro-inflammatory factor in post-MI MR, suggesting its inhibition as a potential therapeutic strategy.

Summary: RNA methylation has emerged as a dynamic regulatory mechanism that impacts gene expression and protein synthesis. Among the known RNA methylation modifications, N6-methyladenosine (m6A), 5-methylcytosine (m5C), 3-methylcytosine (m3C), and N7-methylguanosine (m7G) have been studied extensively. In particular, m6A is the most abundant RNA modification and has attracted significant attention due to its potential effect on multiple biological processes. Recent studies have demonstrated that RNA methylation plays an important role in the development and progression of cardiovascular disease (CVD). To identify key pathogenic genes of CVD and potential therapeutic targets, we reviewed several common RNA methylation and summarized the research progress of RNA methylation in diverse CVDs, intending to inspire effective treatment strategies.

Summary: This study investigated the effects of canagliflozin on myocardial dysfunction after cardiac arrest and cardiopulmonary resuscitation in diabetic rats and the underlying mechanisms. Male rats with type 2 diabetes mellitus (T2DM) were subjected to a modified epicardial fibrillation model. Pretreatment with canagliflozin (10 mg/kg/day) for four weeks improved ATP levels, post-resuscitation ejection fraction, acidosis, and hemodynamics. Canagliflozin also reduced myocardial edema, mitochondrial damage and, post-resuscitation autophagy levels. In vitro analyses showed that canagliflozin significantly reduced reactive oxygen species and preserved mitochondrial membrane potential. Using the PI3K/Akt pathway inhibitor Ly294002, canagliflozin was shown to attenuate hyperautophagy and cardiac injury induced by high glucose and hypoxia-reoxygenation through activation of the PI3K/Akt/mTOR pathway. This study highlights the therapeutic potential of canagliflozin in post-resuscitation myocardial dysfunction in diabetes, providing new insights for clinical treatment and experimental research.

Summary: The presence of calcified nodule (CN) is a significant characteristic of atherothrombosis in acute coronary syndrome (ACS). However, its characteristics continue to be understudied. This review aimed to further investigate these characteristics. This study found that CN was a distinctive feature of an atheromatous plaque, representing 6.3% of ACS. CN was more common in NSTE-ACS than in STEMI patients (9.4% vs. 6.6%). CN was also chiefly observed in the left anterior descendant artery (48%), followed by the right coronary (40.4%) and left circumflex (14.5%) arteries. Higher prevalence of hypertension (78.8%), diabetes mellitus (50.8%), multivessel disease (71.7%), and kidney disease (26.43%) were noted in CN compared to non-CN patients. CN-associated ACS also 6-fold increased the risk of target lesion revascularization compared to those without CN.

Summary: We aimed to develop a machine-learning based predictive model to identify 30-day readmission risk in Acute heart failure (AHF) patients. In this study 2232 patients hospitalized with AHF were included. The variance inflation factor value and 5-fold cross-validation were used to select vital clinical variables. Five machine learning algorithms with good performance were applied to develop models, and the discrimination ability was comprehensively evaluated by sensitivity, specificity, and area under the ROC curve (AUC). Prediction results were illustrated by SHapley Additive exPlanations (SHAP) values. Finally, the XGBoost model performs optimally: the greatest AUC of 0.763 (0.703–0.824), highest sensitivity of 0.660, and high accuracy of 0.709. This study developed an optimal XGBoost model to predict the risk of 30-day unplanned readmission for AHF patients, which showed more significant performance compared with traditional logistic regression (LR) model.

Summary: Mitochondrial dysfunction has been known to contribute to the worsening of acute myocardial infarction (AMI). We screened differentially expressed genes (DEGs) between AMI and healthy individuals based on the GSE66360 dataset. We took the intersection of the obtained DEGs with 1,136 mitochondria-related genes. Finally, we screened out mitochondria-related DEGs (MitoDEGs). Eight MitoDEGs were identified as hub genes based on the random forest algorithm. Two mitochondria-related robust molecular clusters were identified by consensus clustering. Immune infiltration analysis showed that immune cell infiltration was significantly increased in the high-expression group of MitoDEGs. We obtained the potential drugs targeted at ALDH2, PMAIP1, and BCL2A1, such as disulfiram, obatoclax mesylate, and bortezomib. Quantitative reverse-transcription polymerase chain reaction further validated the expression of the MitoDEGs in the cell model of AMI. These findings reveal the potential role of MitoDEGs in AMI and provide new insights into risk stratification and individualized treatment of AMI patients.

Summary: Given the extensive participation of myeloid cells (especially monocytes and macrophages) in both inflammation and resolution phases post-myocardial infarction (MI) owing to their biphasic role, these cells are considered as crucial players in the disease pathogenesis. Multiple studies have agreed on the significant contribution of macrophage polarization theory (M2 vs. M1) while determining the underlying reasons behind the observed biphasic effects; nevertheless, this simplistic classification attracts severe drawbacks. The advent of multiple advanced technologies based on OMICS platforms facilitated a successful path to explore comprehensive cellular signatures that could expedite our understanding of macrophage heterogeneity and plasticity. While providing an overall basis behind the MI disease pathogenesis, this review delves into the literature to discuss the current knowledge on multiple macrophage clusters, including the future directions in this research arena. In the end, our focus will be on outlining the possible therapeutic implications based on the emerging observations.

Summary: Although more and more evidence has supported that metabolic syndrome (MS) is linked to ischemic stroke (IS), the molecular mechanism and genetic association between them has not been investigated. Here, we combined the existing single-cell RNA sequencing (scRNA-seq) data and mendelian randomization (MR) for stroke to understand the role of dysregulated metabolism in stroke. The shared hub genes were identified with machine learning and WGCNA. A total of six upregulated DEGs and five downregulated genes were selected for subsequent analyses. Nine genes were finally identified with random forest, Lasso regression, and XGBoost method as a potential diagnostic model. scRNA-seq also show the abnormal glycolysis level in most cell clusters in stroke and associated with the expression level of hub genes. The genetic relationship between IS and MS was verified with MR analysis. Our study reveals the common molecular profile and genetic association between ischemic stroke and metabolic syndrome.

Summary: Circular RNA (circRNA) has emerged as potential therapeutic targets for cardiovascular diseases. Given the central role of the TGFβ signaling pathway in cardiac remodeling and its potential as a therapeutic target, we hypothesized that a circRNA from this pathway could modulate cardiac remodeling and serve as a heart failure treatment. Therefore, we identified a circRNA, named circSMAD3, that was significantly reduced in murine heart failure models. Functionally, circSMAD3 mitigated cardiomyocyte hypertrophy and inhibited cardiac fibroblast activation in vitro. Mechanistically, circSMAD3 interacts with YBX1, stabilizing it and facilitating its binding to SMAD3 in the nucleus, disrupting the TGFβ/SMAD3 signaling pathway, and ultimately restoring cardiac remodeling. This study highlights circSMAD3 as a promising therapeutic target for heart failure treatment.

Summary: Coronary artery disease (CAD) remains a leading cause of disease burden globally, and there is a persistent need for new therapeutic targets. Instrumental variable (IV) and genetic colocalization analyses can help identify novel therapeutic targets for human disease by nominating causal genes in genome-wide association study (GWAS) loci. We conducted cis-IV analyses for 20,125 genes and 1,746 plasma proteins with CAD using molecular trait quantitative trait loci variant (QTLs) data from three different studies. 19 proteins and 119 genes were significantly associated with CAD risk by IV analyses and demonstrated evidence of genetic colocalization. Notably, our analyses validated well-established targets such as PCSK9 and ANGPTL4 while also identifying HTRA1 and endotrophin (a cleavage product of COL6A3) as proteins whose levels are causally associated with CAD risk. Further experimental studies are needed to confirm the causal role of the genes and proteins identified through our multiomic cis-IV analyses on human disease.

Abstract Background While the augmented incidence of diabetes after COVID-19 has been widely confirmed, controversial results are available on the risk of developing hypertension during the COVID-19 pandemic. Methods We designed a longitudinal cohort study to analyze a closed cohort followed up over a 7-year period, i.e., 3 years before and 3 years during the COVID-19 pandemic, and during 2023, when the pandemic was declared to be over. We analyzed medical records of more than 200,000 adults obtained from a cooperative of primary physicians from January 1, 2017, to December 31, 2023. The main outcome was the new diagnosis of hypertension. Results We evaluated 202,163 individuals in the pre-pandemic years and 190,743 in the pandemic years, totaling 206,857 when including 2023 data. The incidence rate of new hypertension was 2.11 (95% C.I. 2.08–2.15) per 100 person-years in the years 2017–2019, increasing to 5.20 (95% C.I. 5.14–5.26) in the period 2020–2022 (RR = 2.46), and to 6.76 (95% C.I. 6.64–6.88) in 2023. The marked difference in trends between the first and the two successive observation periods was substantiated by the fitted regression lines of two Poisson models conducted on the monthly log-incidence of hypertension. Conclusions We detected a significant increase in new-onset hypertension during the COVID-19 pandemic, which at the end of the observation period affected ~ 20% of the studied cohort, a percentage higher than the diagnosis of COVID-19 infection within the same time frame. This observation suggests that increased attention to hypertension screening should not be limited to individuals who are aware of having contracted the infection but should be extended to the entire population.

Artificial intelligence, specifically advanced language models such as ChatGPT, have the potential to revolutionize various aspects of healthcare, medical education, and research. In this review, we evaluate the myriad applications of artificial intelligence in diverse healthcare domains. We discuss its potential role in clinical decision-making, exploring how it can assist physicians by providing rapid, data-driven insights for diagnosis and treatment. We review the benefits of artificial intelligence such as ChatGPT in personalized patient care, particularly in geriatric care, medication management, weight loss and nutrition, and physical activity guidance. We further delve into its potential to enhance medical research, through the analysis of large datasets, and the development of novel methodologies. In the realm of medical education, we investigate the utility of artificial intelligence as an information retrieval tool and personalized learning resource for medical students and professionals.

Background: While the augmented incidence of diabetes after COVID-19 has been widely confirmed, controversial results are available on the risk of developing hypertension during the COVID-19 pandemic. Methods: We designed a longitudinal cohort study to analyze a closed cohort followed up over a 7-year period, i.e., 3 years before and 3 years during the COVID-19 pandemic, and during 2023, when the pandemic was declared to be over. We analyzed medical records of more than 200,000 adults obtained from a cooperative of primary physicians from January 1, 2017, to December 31, 2023. The main outcome was the new diagnosis of hypertension. Results: We evaluated 202,163 individuals in the pre-pandemic years and 190,743 in the pandemic years, totaling 206,857 when including 2023 data. The incidence rate of new hypertension was 2.11 (95% C.I. 2.08–2.15) per 100 person-years in the years 2017–2019, increasing to 5.20 (95% C.I. 5.14–5.26) in the period 2020–2022 (RR = 2.46), and to 6.76 (95% C.I. 6.64–6.88) in 2023. The marked difference in trends between the first and the two successive observation periods was substantiated by the fitted regression lines of two Poisson models conducted on the monthly log-incidence of hypertension. Conclusions: We detected a significant increase in new-onset hypertension during the COVID-19 pandemic, which at the end of the observation period affected ~ 20% of the studied cohort, a percentage higher than the diagnosis of COVID-19 infection within the same time frame. This observation suggests that increased attention to hypertension screening should not be limited to individuals who are aware of having contracted the infection but should be extended to the entire population. [ABSTRACT FROM AUTHOR]

Artificial intelligence, specifically advanced language models such as ChatGPT, have the potential to revolutionize various aspects of healthcare, medical education, and research. In this review, we evaluate the myriad applications of artificial intelligence in diverse healthcare domains. We discuss its potential role in clinical decision-making, exploring how it can assist physicians by providing rapid, data-driven insights for diagnosis and treatment. We review the benefits of artificial intelligence such as ChatGPT in personalized patient care, particularly in geriatric care, medication management, weight loss and nutrition, and physical activity guidance. We further delve into its potential to enhance medical research, through the analysis of large datasets, and the development of novel methodologies. In the realm of medical education, we investigate the utility of artificial intelligence as an information retrieval tool and personalized learning resource for medical students and professionals. [ABSTRACT FROM AUTHOR]

This study aimed to assess the methods and outcomes of The Measurement Tool to Assess systematic Reviews (AMSTAR) 2 appraisals in overviews of reviews (overviews) of interventions in the cardiovascular field and identify factors that are associated with these outcomes. MEDLINE, Scopus, and the Cochrane Database of Systematic Reviews were searched until November 2022. Eligible were overviews of cardiovascular interventions, analyzing systematic reviews (SRs) of randomized controlled trials (RCTs). Extracted data included characteristics of overviews and SRs and AMSTAR 2 appraisal methods and outcomes. Data were synthesized using descriptive statistics and logistic regression to explore potential associations between the characteristics of SRs and extracted AMSTAR 2 overall ratings ("High‐Moderate" vs. "Low‐Critically low"). The original results on individual AMSTAR 2 items were entered into the official AMSTAR 2 online tool and the recalculated overall confidence ratings were compared to those provided in overviews. All 34 overviews identified were published between 2019 and 2022. Rating of overall confidence following the algorithm suggested by AMSTAR 2 developers was noted in 74% of overviews. The 679 unique included SRs were mainly of "Critically low" (53%) or "Low" (18.7%) confidence and underperformed in items 2 (Protocol, no = 65.2%) and 7 (List of excluded studies, no = 84%). The following characteristics of SRs were significantly associated with higher overall ratings: Cochrane origin, pharmacological interventions, including exclusively RCTs, citation of methodological and reporting guidelines, protocol, absence of funding and publication after AMSTAR 2 release. Generally, overviews' authors tended to deviate from the original rating scheme and ascribe higher ratings to SRs compared to the official AMSTAR 2 online tool. Most SRs included in overviews of cardiovascular interventions have critically low or low confidence in their results. Overviews' authors should be more transparent about the methods used to derive the overall confidence in SRs. [ABSTRACT FROM AUTHOR]

Cardiology, as a pivotal field in modern healthcare, grapples with the escalating global burden of cardiovascular diseases. This ongoing challenge necessitates continuous innovation in prevention, diagnosis, and treatment. In recent years, the fusion of cardiology and technology has ushered in remarkable advancements, with Artificial Intelligence (AI) emerging as a transformative force. This review explores the intricate relationship between cardiology and AI, addressing the complex challenges faced by clinicians and researchers. The symbiosis between traditional methodologies and AI-driven solutions offers unprecedented capabilities, promising to revolutionize patient outcomes and public health globally. From early diagnostics to personalized treatment plans, and from population health management to telemedicine, cardiology experiences a paradigm shift driven by AI's rapid evolution. This examination of the current state of cardiology illuminates the dynamic interplay between conventional medical practices and cutting-edge technologies, showcasing the transformative applications of AI shaping both the present and the promising future of cardiovascular medicine. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Summary: The mutated SCN5A gene encoding defective Nav1.5 protein causes arrhythmic ailments and is associated with enhanced cardiac fibrosis. This study investigated whether SCN5A mutation directly affects cardiac fibroblasts and explored how defective SCN5A relates to cardiac fibrosis. SCN5A knockdown (SCN5AKD) human cardiac fibroblasts (HCF) had higher collagen, α-SMA, and fibronectin expressions. Micro-RNA deep sequencing and qPCR analysis revealed the downregulation of miR-452-5p and bioinformatic analysis divulged maladaptive upregulation of transforming growth factor β (TGF-β) signaling in SCN5AKD HCF. Luciferase reporter assays validated miR-452-5p targets SMAD4 in SCN5AKD HCF. Moreover, miR-452-5p mimic transfection in SCN5AKD HCF or AAV9-mediated miR-452-5p delivery in isoproterenol-induced heart failure (HF) rats, resulted in the attenuation of TGF-β signaling and fibrogenesis. The exogenous miR-452-5p significantly improved the poor cardiac function in HF rats. In conclusion, miR-452-5p regulates cardiac fibrosis progression by targeting the TGF-β/SMAD4 axis under the loss of the SCN5A gene.

Summary: Prader-Willi syndrome (PWS) is a genetic disorder characterized by behavioral disturbances, hyperphagia, and intellectual disability. Several surveys indicate that PWS is also associated with cardiac abnormalities, possibly contributing to a high incidence of sudden death. However, the pathological mechanisms underlying cardiac dysfunction in PWS remain unclear. In this study, we found that deficiency in necdin, an intronless gene within PWS region, led to heart systolic and diastolic dysfunction in mice. Through yeast two-hybrid screening, we identified an interaction between necdin and non-muscle myosin regulatory light chain 12a/b (MYL12 A/B). We further showed that necdin stabilized MYL12 A/B via SGT1-heat shock protein 90 (HSP90) chaperone machinery. The zebrafish lacking the MYL12 A/B analog, MYL12.1, exhibited impaired heart function, while cardiac-specific overexpression of MYL12A normalized the heart dysfunction in necdin-deficient mice. Our findings revealed necdin dysfunction as a contributing factor to cardiomyopathy in PWS patients and emphasized the importance of HSP90 chaperone machinery and non-muscle myosin in heart fitness.

Summary: The field of small-diameter vascular grafts remains a challenge for biomaterials scientists. While decades of research have brought us much closer to developing biomimetic materials for regenerating tissues and organs, the physiological challenges involved in manufacturing small conduits that can transport blood while not inducing an immune response or promoting blood clots continue to limit progress in this area. In this short review, we present some of the most recent methods and advancements made by researchers working in the field of small-diameter vascular grafts. We also discuss some of the most critical aspects biomaterials scientists should consider when developing lab-made small-diameter vascular grafts.

Summary: The liver X receptor (LXR) is considered a therapeutic target for atherosclerosis treatment, but synthetic LXR agonists generally also cause hepatic steatosis and hypertriglyceridemia. Desmosterol, a final intermediate in cholesterol biosynthesis, has been identified as a selective LXR ligand that suppresses inflammation without inducing lipogenesis. Δ24-Dehydrocholesterol reductase (DHCR24) converts desmosterol into cholesterol, and we previously showed that the DHCR24 inhibitor SH42 increases desmosterol to activate LXR and attenuate experimental peritonitis and metabolic dysfunction-associated steatotic liver disease. Here, we aimed to evaluate the effect of SH42 on atherosclerosis development in APOE∗3-Leiden.CETP mice and low-density lipoproteins (LDL) receptor knockout mice, models for lipid- and inflammation-driven atherosclerosis, respectively. In both models, SH42 increased desmosterol without affecting plasma lipids. While reducing liver lipids in APOE∗3-Leiden.CETP mice, and regulating populations of circulating monocytes in LDL receptor knockout mice, SH42 did not attenuate atherosclerosis in either model.

Introduction As surgical technologies grow, so too do demands on surgical trainees to master increasing numbers of skill sets. With the rise of endovascular surgery, trainees have fewer opportunities to practice open vascular techniques in the operating room. Simulation can bridge this gap. However, existing published open vascular simulation curricula are basic or based on expensive models. Methods We iteratively developed an open vascular skills curriculum for second-year surgery residents comprising six 2-hour sessions. We refined the curriculum based on feedback from learners and faculty. The curriculum required skilled facilitators, vascular instruments, and tissue models. We evaluated the latest iteration with a survey and by assessing participants’ technical skills using the Objective Structured Assessment of Technical Skills (OSATS) form. Results Over the past 10 years, 101 residents have participated in the curriculum. Nine of 13 residents who participated in the latest curricular iteration completed the survey. All respondents rated the sessions as excellent and strongly agreed that they had improved their abilities to perform anastomoses with tissue and prosthetic. Facilitators completed 18 OSATS forms for residents in the fifth and sixth sessions of the latest iteration. Residents scored well overall, with a median 26.5 (interquartile range: 24–29) out of a possible score of 35, with highest scores on knowledge of instruments. Discussion This simulation-based curriculum facilitates open vascular surgical skill acquisition among surgery residents. The curriculum allows residents to acquire critical vascular skills that are challenging to learn in an increasingly demanding operative setting.

Introduction Foundational and clinical science integration, a long-standing goal of undergraduate medical education, benefits learners by promoting retention of critical knowledge and skills as well as their transfer to the clinical setting. We implemented a team-based learning (TBL) module in which foundational knowledge and skills from the disciplines of biochemistry, nutrition, and genetics were leveraged in a simulated patient encounter for diagnosis and management of a patient with dyslipidemia. Methods The TBL was deployed in a first-year medical student cardiovascular system course with 125 students over three academic years. Following individual and team readiness assurance tests (iRAT and tRAT, respectively), teams participated in an initial application exercise requiring consideration of clinical and laboratory data and other risk factors to engage the patient in a shared decision-making process. Using dietary and family history narratives in subsequent application exercises, teams completed recommendations for an individualized diet plan and an assessment of potential disease inheritance patterns to formulate appropriate patient care management strategies. Results Student engagement with prelearning materials and session team activities was high as judged by RAT performance and application exercise outcomes: iRAT question performance ranged from 89% to 99% for individual items, and tRAT performance was routinely 100%. Learners reported that the exercises were impactful and believed the learned foundational knowledge and skills were transferable to future patient care. Discussion The dyslipidemia TBL module provides an illustration for early clinical learners of how foundational knowledge and skills can be operationalized and transferred for optimal patient care.

Summary: Early detection of left ventricular remodeling (LVR) is crucial. While cardiac magnetic resonance (CMR) provides valuable information, it has limitations. Coronary angiography-derived fractional flow reserve (caFFR) and index of microcirculatory resistance (caIMR) offer viable alternatives. 157 patients with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention were prospectively included. 23.6% of patients showed LVR. Machine learning algorithms constructed three LVR prediction models: Model 1 incorporated clinical and procedural parameters, Model 2 added CMR parameters, and Model 3 included echocardiographic and functional parameters (caFFR and caIMR) with Model 1. The random forest algorithm showed robust performance, achieving AUC of 0.77, 0.84, and 0.85 for Models 1, 2, and 3. SHAP analysis identified top features in Model 2 (infarct size, microvascular obstruction, admission hemoglobin) and Model 3 (current smoking, caFFR, admission hemoglobin). Findings indicate coronary physiology and echocardiographic parameters effectively predict LVR in patients with STEMI, suggesting their potential to replace CMR.

Summary: Clonal hematopoiesis (CH) is a risk factor for atherosclerotic cardiovascular disease, but the impact of smaller clones and the effect on inflammatory parameters is largely unknown. Using ultrasensitive single-molecule molecular inversion probe sequencing, we evaluated the association between CH and a first major adverse cardiovascular event (MACE) in patients with angiographically documented stable coronary artery disease (CAD) and no history of acute ischemic events. CH was associated with an increased rate of MACE at four years follow-up. The size of the clone predicted MACE at an optimal cut-off value of 1.07% variant allele frequency (VAF). Mutation carriers had no change in monocytes subsets or cytokine production capacity but had higher levels of circulating tissue factor, matrilysin, and proteinase-activated receptor-1. Our study identified CH driver mutations with a VAF as small as 1.07% as a residual cardiovascular risk factor and identified potential biomarkers and therapeutic targets for patients with stable CAD.

Summary: Maternal hyperhomocysteinemia is widely considered as an independent risk of congenital heart disease (CHD). However, whether high paternal homocysteine causes CHD remains unknown. Here, we showed that increased homocysteine levels of male mice caused decreased sperm count, sperm motility defect and ventricular septal defect of the offspring. Moreover, high levels of paternal homocysteine decrease sperm DNMT3A/3B, accompanied with changes in DNA methylation levels in the promoter regions of CHD-related genes. Folic acid supplement could decrease the occurrence of VSD in high homocysteine male mice. This study reveals that increased paternal homocysteine level increases VSD risk in the offspring, indicating that decreasing paternal homocysteine may be an intervening target of CHD.

Summary: Epicardial adipose tissue (EAT) is a fat depot located between the myocardium and the visceral layer of the epicardium, which, owing to its location, can influence surrounding tissues and can act as a local transducer of systemic inflammation. The mechanisms upon which such influence depends on are however unclear. Given the role EAT undoubtedly has in the scheme of cardiovascular diseases (CVDs), understanding the impact of its cellular components is of upmost importance. Extracellular vesicles (EVs) constitute promising candidates to fill the gap in the knowledge concerning the unexplored mechanisms through which EAT promotes onset and progression of CVDs. Owing to their ability of transporting active biomolecules, EAT-derived EVs have been reported to be actively involved in the pathogenesis of ischemia/reperfusion injury, coronary atherosclerosis, heart failure, and atrial fibrillation. Exploring the precise functions EVs exert in this context may aid in connecting the dots between EAT and CVDs.

Summary: This study significantly enhances the accuracy of exercise state identification in wearable devices through improved denoising techniques for sEMG and ECG signals. By adopting an optimized Variational Mode Decomposition (VMD) method, combined with the Improved Sparrow Search Algorithm and Second Generation Wavelet Transform (ISSA-VMD-SWT), and introducing chaos mapping to strengthen the algorithm’s initial population, this approach effectively reduces noise while preserving key fatigue-related features. In tests conducted on data from 32 participants, the method achieved accuracy rates of 93.25%, 95.16%, and 93.05% for identifying “Easy,” “Transition,” and “Tired” exercise states, respectively, showing significant advantages over traditional denoising techniques. These results indicate that the denoising technology developed in this study represents a significant technological advancement for the application of ECG and sEMG fatigue identification technologies in wearable health monitoring devices.