Reviews in Cardiovascular Medicine

Background Direct comparisons between the drugs are limited, and the dosing remains debatable. Therefore, the study aims to indirectly compare the efficacy and safety of inclisiran, alirocumab, evolocumab, and evinacumab in lipid-lowering through a network meta-analysis. Methods Databases including PubMed, EMBASE, Web of Science, and the Cochrane Library were utilized to retrieve randomized controlled trials (RCTs). The search was conducted up to July 1, 2023. The Cochrane risk of bias tool was employed to appraise the quality of included studies. R software was used to conduct the Bayesian network meta-analysis. Results Twenty-one RCTs with 10,835 patients were included. The network meta-analysis indicated that Evolocumab [mean difference (MD) = –60, 95% credibility interval (CrI) (–72, –49)] was the most effective (87%) in reducing low-density lipoprotein cholesterol (LDL-C), followed by alirocumab (71.4%) and inclisiran (47.2%), with placebo being the least effective (0.01%). In increasing high-density lipoprotein cholesterol (HDL-C), evolocumab [MD = 6.5, 95% CrI (3.2, 10)] ranked first (81.8%), followed by alirocumab (68.2%), with placebo again at the bottom (0.03%). In lowering total cholesterol, evolocumab [MD = –36, 95% CrI (–54, –19)] performed the best (86%), followed by alirocumab (64%), and placebo remained the least effective (0.04%). Regarding adverse events (AEs), evinacumab [odds ratio (OR) = 2, 95% CrI (1.17, 3.44)] ranked the highest (98.9%), followed by inclisiran (59.6%) and evolocumab (15.2%). Conclusions Evolocumab appears to be the most effective in increasing HDL-C and reducing LDL-C and total cholesterol. Evinacumab shows the best safety profile with the lowest incidence of AEs. The PROSPERO registration CRD42024570445, https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=570445.

Background Limited data are available for evaluating the effect of blood glucose on transcatheter aortic valve replacement (TAVR) outcomes in patients with diabetes. We aimed to assess the impact of glucose levels on short-term and long-term adverse outcomes in patients undergoing TAVR. Methods and Results Data from severe aortic stenosis (AS) patients who underwent TAVR from 2010 to 2022 were collected retrospectively. In total, 615 patients were enrolled in the study: Among the total patient population, 43% had diabetes mellitus (DM), with a mean hemoglobin A1c (HbA1c) level of 7.4 ± 2.5. Within this cohort, 33% were classified as having uncontrolled diabetes, while 17% were considered well-controlled. Diabetic patients were younger (80.7 ± 6.8 vs. 82.0 ± 6.8 years, p = 0.001) and had more cardiovascular risk factors. No significant differences were found in outcomes between the two groups during the twelve-year follow-up. A multivariable logistic regression analysis was conducted on 270 DM patients to examine the impact of blood glucose levels and HbA1c on outcomes such as arrhythmia, stroke, and acute kidney injury (AKI). For arrhythmia, the odds ratio for HbA1c and blood glucose were 1.1039 (p = 0.23), and 0.998 (p = 0.76), indicating no significant associations. In stroke cases, HbA1c had an odds ratio of 1.194 (p = 0.36), while an odds ratio of 1.020 (p = 0.013) for blood glucose indicated a significant association. Notably, for AKI, the odds ratio for HbA1c was 2.304 (p = 0.02), indicating a significant link between higher HbA1c levels and increased AKI risk, with blood glucose levels trending toward significance (odds ratio = 1.0137, p = 0.061). Conclusions Diabetic status is a predictor of short-term outcomes following TAVR. Thus, these screening parameters should be included in risk assessment tools for TAVR candidates.

Background This study aimed to identify the risk factors for in-hospital acute kidney injury (AKI) in patients with acute aortic dissection (AAD) and to establish a machine learning model for predicting in-hospital AKI. Methods We extracted data on patients with AAD from the Medical Information Mart for Intensive Care (MIMIC)-IV database and developed seven machine learning models: support vector machine (SVM), gradient boosting machine (GBM), neural network (NNET), eXtreme gradient boosting (XGBoost), K-nearest neighbors (KNN), light gradient boosting machine (LightGBM), and categorical boosting (CatBoost). Model performance was assessed using the area under the receiver operating characteristic curve (AUC), and the optimal model was interpreted using Shapley Additive explanations (SHAP) visualization analysis. Results A total of 325 patients with AAD were identified from the MIMIC-IV database, of which 84 patients (25.85%) developed in-hospital AKI. This study collected 42 features, with nine selected for model building. A total of 70% of the patients were randomly allocated to the training set, while the remaining 30% were allocated to the test set. Machine learning models were built on the training set and validated using the test set. In addition, we collected AAD patient data from the MIMIC-III database for external validation. Among the seven machine learning models, the CatBoost model performed the best, with an AUC of 0.876 in the training set and 0.723 in the test set. CatBoost also performed strongly during the validation, achieving an AUC of 0.712. SHAP visualization analysis identified the most important risk factors for in-hospital AKI in AAD patients as maximum blood urea nitrogen (BUN), body mass index (BMI), urine output, maximum glucose (GLU), minimum BUN, minimum creatinine, maximum creatinine, weight and acute physiology score III (APSIII). Conclusions The CatBoost model, constructed using risk factors including maximum and minimum BUN levels, BMI, urine output, and maximum GLU, effectively predicts the risk of in-hospital AKI in AAD patients and shows compelling results in further validations.

Background This study aimed to develop and validate a predictive model for major adverse cardiovascular events (MACE) following percutaneous coronary intervention (PCI) in patients with new-onset ST-segment elevation myocardial infarction (STEMI) using four machine learning (ML) algorithms. Methods Data from 250 new-onset STEMI patients were retrospectively collected. Feature selection was performed using the Boruta algorithm. Four ML algorithms—K-nearest neighbors (KNN), support vector machine (SVM), Complement Naive Bayes (CNB), and logistic regression—were applied to predict MACE risk. Model performance was evaluated using area under the curve (AUC), sensitivity, and specificity. Shapley Additive Explanations (SHAP) analysis was used to rank feature importance, and a nomogram was constructed for risk visualization. Results Logistic regression showed the best performance (AUC = 0.814 in training, 0.776 in validation) compared to KNN, SVM, and CNB. SHAP analysis identified seven key predictors, including Killip classification, Gensini score, blood urea nitrogen (BUN), heart rate (HR), creatinine (CR), glutamine transferase (GLT), and platelet count (PCT). The nomogram provided accurate risk predictions with strong agreement between predicted and observed outcomes. Conclusions The logistic regression model effectively predicts MACE risk after PCI in STEMI patients. The nomogram serves as a practical tool for clinicians, supporting personalized risk assessment and improving clinical decision-making.

Cardiac sarcoidosis (CS) is a multifaceted inflammatory disease that affects the heart, leading to complications such as arrhythmias, heart failure, and sudden cardiac death. Endomyocardial biopsy is the diagnostic gold standard, but its low sensitivity and risks limit its utility. Imaging modalities, such as cardiac magnetic resonance and positron emission tomography, are critical for diagnosing and managing CS. Additionally, CS treatment primarily involves corticosteroids and immunosuppressive agents to reduce inflammation and control disease progression, although biologics such as tumor necrosis factor-alpha (TNF-α) inhibitors are considered in refractory or steroid-dependent cases. This narrative review revises the existing knowledge on the diagnosis and treatment of CS, providing a comprehensive overview of current strategies.

Background Fibulin 1 and Fibulin 2 are members of the extracellular matrix (ECM) glycoprotein family. ECMs drive prognosis through remodeling, a key step in the pathogenesis of heart failure (HF). We aimed to compare Fibulin 1 and 2 levels in different stages of HF and to investigate their relationship with other prognostic factors of HF. Methods Patients with HF were divided into two groups according to left ventricular ejection fraction (LVEF): reduced and non-reduced LVEF. The control and patient groups consisted of individuals with Stages A and B HF, Stages C and D HF, respectively. Fibulin levels were measured at different stages of HF and in the control group. Additionally, Fibulin levels were measured at admission, discharge, and in the first month in patients who were hospitalized due to decompensated HF. Results Serum Fibulin 1 and N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels were significantly higher in the patient group than in the control group. Serum Fibulin 2 levels were similar between the groups. Although serum Fibulin 2 levels were similar at repeated measurements, serum Fibulin 1 and NT-proBNP levels significantly decreased at discharge and remained similar at 1 month compared with admission. There was a significant positive correlation between Fibulin 1 and NT-proBNP levels and a significant negative correlation between Fibulin 1 levels and LVEF. Fibulin 2 levels were not correlated with LVEF and NT-proBNP. Conclusions Our study demonstrated that serum Fibulin 1 levels differ among different HF stages and have a similar temporal change as observed for NT-proBNP levels. A similar association was not observed for Fibulin 2 in our study.

Background This study aimed to develop a machine learning-based predictive model for assessing frailty risk among elderly patients with coronary heart disease (CHD). Methods From November 2020 to May 2023, a cohort of 1170 elderly patients diagnosed with CHD were enrolled from the Department of Cardiology of a tier-3 hospital in Anhui Province, China. Participants were randomly divided into a development group and a validation group, each containing 585 patients in a 1:1 ratio. Least absolute shrinkage and selection operator (LASSO) regression was employed in the development group to identify key variables influencing frailty among patients with CHD. These variables informed the creation of a machine learning prediction model, with the most accurate model selected. Predictive accuracy was subsequently evaluated in the validation group through receiver operating characteristic (ROC) curve analysis. Results LASSO regression identified the activities of daily living (ADL) score, hemoglobin, low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), depression, cardiac function classification, cerebrovascular disease, diabetes, solitary living, and age as significant predictors of frailty among elderly patients with CHD in the development group. These variables were incorporated into a logistic regression model and four machine learning models: extreme gradient boosting (XGBoost), random forest (RF), light gradient boosting machine (LightGBM), and adaptive boosting (AdaBoost). AdaBoost demonstrated the highest accuracy in the development group, achieving an area under the ROC curve (AUC) of 0.803 in the validation group, indicating strong predictive capability. Conclusions By leveraging key frailty determinants in elderly patients with CHD, the AdaBoost machine learning model developed in this study has shown robust predictive performance through validated indicators and offers a reliable tool for assessing frailty risk in this patient population.

Hypertrophic cardiomyopathy (HCM) is the most prevalent hereditary cardiovascular disorder, characterised by left ventricular hypertrophy and cardiac fibrosis. Cardiac fibroblasts, transformed into myofibroblasts, play a crucial role in the development of fibrosis. However, interactions between fibroblasts, cardiomyocytes, and immune cells are considered major mechanisms driving fibrosis progression. While the disease has a strong genetic background, its pathogenetic mechanisms remain complex and not fully understood. Several signalling pathways are implicated in fibrosis development. Among these, transforming growth factor-beta and angiotensin II are frequently studied in the context of cardiac fibrosis. In this review, we summarise the most current evidence on the involvement of signalling pathways in the pathogenesis of HCM. Additionally, we discuss the potential role of monitoring pro-fibrotic molecules in predicting clinical outcomes in patients with HCM.

Background Acute type A aortic dissection (TAAD) is a life-threatening cardiovascular emergency with a high mortality rate. The peri-operative factors influencing in-hospital mortality among surgically treated TAAD patients remain unclear. This study aimed to identify key peri-operative risk factors associated with in-hospital mortality. Methods Peri-operative laboratory data, surgical strategies, and TAAD-related risk factors, associated with mortality, were collected. Machine learning techniques were applied to evaluate the impact of various parameters on in-hospital mortality. Based on the findings, a nomogram model was developed and validated using area under the receiver operating characteristic curve (AUC) analysis, calibration plots, and internal validation methods. Results A total of 199 patients with TAAD were included in the study cohort, which was divided into derivation and validation cohorts. Using the least absolute shrinkage and selection operator (LASSO) regression method, 66 features were narrowed down to six key predictors. These included age, lymphocyte count, use of continuous renal replacement therapy (CRRT), cardiopulmonary bypass (CPB) time, duration of mechanical ventilation, and postoperative interleukin-10 (IL-10) levels, all of which were identified as significant risk factors for in-hospital mortality following TAAD surgery. Conclusions We developed and validated a predictive model, presented as a nomogram, to estimate in-hospital survival in patients with TAAD. Post-operative IL-10 was identified as an independent prognostic factor for patients with TAAD. The combination of IL-10 with five additional indicators significantly improved the predictive accuracy, demonstrating superiority over the use of any single variable alone. Clinical Trial Registration This study protocol was registered at ClinicalTrials.gov (NCT04711889). https://clinicaltrials.gov/study/NCT04711889.

Background One of the most significant long-term toxicities of breast cancer radiotherapy is major adverse cardiac events (MACE). In current radiotherapy practice, the mean heart dose is the most commonly used parameter. The aim of our study was to reduce the doses of organs at risk (OAR) in the left anterior descending artery (LAD) and left ventricle (LV) by including the LAD and LV in planning radiotherapy while maintaining adequate dose coverage for patients with left-sided breast cancer. Methods We retrospectively analyzed left-sided breast cancer cases treated at the Kocaeli University Faculty of Medicine. Only patients with local and locally advanced breast cancer were included in the analysis. A total of 77 patients who were treated between 2020 and 2024 were included. The doses to the LAD and LV were added to the optimization algorithms. Two volumetric modulated arc therapy (VMAT) plans were created for each patient. A total of 154 plans were made, including standard and LAD and LV sparing plans. Results There was no statistically significant difference in all VMAT plans regarding planning target volume (PTV) D2, D50, and D98 (dose receiving volume of PTV 2%, 50%, and 98%) (p > 0.05). However, a significant decrease was observed in heart V5 (the percentage of the heart receiving at least 5 gray (Gy)) and mean heart dose. A decrease in the mean heart dose was observed in the standard plan compared with the LAD and LV sparing plan (p < 0.001). Similarly, the heart V5 value decreased significantly (p < 0.001). Additionally, significant reductions were measured in all LAD and LV parameters after re-optimization. Conclusions We achieved significant reductions in all heart, LAD, and LV parameters without making any changes to the planned treatment volume coverage by adding LAD and LV OARs to the optimization algorithms. The potential risk of MACE can be significantly reduced by implementing this strategy.

Background The complex process of cardiac magnetic resonance (CMR) and the uncertainty of each parameter in the diagnosis and prognosis of cardiotoxicity limit its promotion in the cardiac evaluation of patients treated with immune checkpoint inhibitors (ICI). Methods A comprehensive search was conducted across PubMed, Web of Science, Embase, China National Knowledge Infrastructure (CNKI), and Cochrane databases for relevant articles published up until September 28, 2024. Results After screening, 8 articles were included in this study. The analysis revealed that following ICI treatment, the left ventricular global longitudinal strain (GLS) increased significantly [weighted mean difference (WMD) 2.33; 95% confidence interval (CI) 1.26, 3.41; p < 0.01], while the global radial strain (GRS) decreased [WMD –4.73; 95% CI –6.74, –2.71; p < 0.01]. Additionally, T1 and T2 values increased [standardized mean difference (SMD) 1.14; 95% CI 0.59, 1.68; p < 0.01] and [SMD 1.11; 95% CI 0.64, 1.58; p < 0.01], respectively. An elevated T2 was associated with a higher occurrence of major adverse cardiovascular events (MACE), with a hazard ratio of 1.36 (95% CI 1.12, 1.64). Conclusions Our findings demonstrate that T1, T2, and GLS increase, while GRS decreases following ICI administration. By consolidating these critical metrics, we propose a streamlined, abbreviated (non-contrast) CMR protocol that can be completed within 15 minutes, thereby facilitating the integration of CMR in cardio-oncology. The PROSPERO registration CRD42023437238, https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023437238.

Background Data regarding racial differences in patients with hypertrophic cardiomyopathy (HCM) is sparse. We hypothesized that Hispanic-Latino (HL), Non-Hispanic (NH), and African-American (AA) race impacts the clinical presentation of HCM. Methods A total of 641 HCM patients (HL = 294, NH = 274, AA = 73) were identified retrospectively from our institutional registry between 2005–2021. Clinical characteristics, echocardiographic indices, and outcomes were assessed using analysis of variance, Kruskal-Wallis, and multivariate linear regression statistical analyses, with Dunn-Bonferroni and Tukey test applied in post-hoc pairwise assessments. Results The HL and NH patients were older compared with AA (69.2 ± 14.7 vs 67.9 ± 15.3 vs 59.4 ± 15.8 years; p < 0.001). The HL group had higher prevalence of females compared with NH (62 vs 47%; p = 0.002), and more moderate-severe mitral regurgitation (35 vs 23 vs 12% p < 0.001) and a higher E/e’ ratio (16.4 ± 8.1 vs 14.9 ± 6.6 vs 13.3 ± 4.5; p = 0.002) when compared with NH and AA. Multivariate linear regression analysis revealed HL ethnicity (β = 0.1) was associated with worse New York Heart Association (NYHA) class independent from moderate-severe mitral regurgitation (β = 0.2), chronic obstructive pulmonary disease (β = 0.17), female gender (β = 0.13), coronary artery disease (β = 0.12), atrial fibrillation (β = 0.11), peak trans-mitral E-wave velocity (β = 0.11), left ventricular mass index (β = 0.1), and reverse septal curve morphology (β = 0.1) (model, r = 0.5, p < 0.001). At 2.5-year median follow-up, all-cause mortality (8%) and composite complications (33%) were similar across the cohort. Conclusions HCM patients of HL race have worse heart failure symptoms when compared with NH and AA, with severity independent of cardiovascular co-morbidities.

Remnant cholesterol (RC) is increasingly recognized as a key target in the treatment of atherosclerotic cardiovascular disease (ASCVD), addressing much of the residual risk that persists despite standard therapies. However, integrating RC into clinical practice remains challenging. Key issues, such as the development of accessible RC measurement methods, the identification of safe and effective medications, the determination of optimal target levels, and the creation of RC-based risk stratification strategies, require further investigation. This article explores the complex role of RC in ASCVD development, including its definition, metabolic pathways, and its association with both the overall risk and residual risk of ASCVD in primary and secondary prevention. It also examines the effect of current lipid-lowering therapies on RC levels and their influence on cardiovascular outcomes. Recent research has highlighted promising advancements in therapies aimed at lowering RC, which show potential for reducing major adverse cardiovascular events (MACEs). Inhibitors such as angiopoietin-like protein 3 (ANGPTL3), apolipoprotein C-III (apoCIII), and proprotein convertase subtilisin/kexin type 9 (PCSK9) have demonstrated their ability to modulate RC and reduce MACEs by targeting specific proteins involved in RC synthesis and metabolism. There is a pressing need for larger randomized controlled trials to clarify the role of RC in relevant patient populations. The development of targeted RC-lowering therapies holds the promise of significantly reducing the high rates of morbidity and mortality associated with ASCVD.

Background Lowering low-density lipoprotein cholesterol (LDL-C) is a well-established strategy for the secondary prevention of coronary heart disease (CHD). However, the effectiveness of specific LDL-C parameters in predicting myocardial infarction (MI) recurrence in real-world settings remains inadequately explored. This study aims to examine the relationship between MI recurrence and various LDL-C parameters in young CHD patients. Methods This retrospective cohort study involved 1013 patients aged 18–44 at the time of initial CHD diagnosis, collected from the cardiology department clinics at Beijing Anzhen Hospital between October 2022 and October 2023. LDL-C levels were assessed at the time of CHD diagnosis and at the final follow-up. The primary outcome was MI events, analyzed using survival analysis and logistic regression models to determine associations with LDL-C parameters. Results The study included 1013 patients (mean age: 38.5 ± 3.9 years; 94.7% men), with a median follow-up time of 1.7 years. Initially, 13.6% had LDL-C levels <1.8 mmol/L, which increased to 37.8% by the study’s end. During follow-up, 96 patients (9.5%) experienced MI. While LDL-C <1.8 mmol/L at baseline showed a slightly lower cumulative incidence of MI than LDL-C ≥1.8 mmol/L, the difference was not statistically significant (log-rank p = 0.335). Reductions in LDL-C levels of ≥50% and the patterns of change did not correlate with decreased MI risk. However, LDL-C <1.4 mmol/L at the final measurement was associated with a reduced MI risk (adjusted odds ratio [OR]: 0.57, 95% confidence interval [CI]: 0.33–0.98) compared with LDL-C ≥2.6 mmol/L. Conclusions This study suggests that the most important parameter related to LDL-C for predicting the recurrence of MI in young patients with a history of CHD is the ideal target LDL-C level. Lowering LDL-C to <1.4 mmol/L could potentially reduce MI risk, regardless of baseline LDL-C levels.

Background To explore the sex-specific risk factors of associated with arterial stiffness. Methods A total of 28,291 participants from the Kailuan study cohort were enrolled in this study. A multivariate linear regression analysis and a multivariate logistic regression model were used to analyze the influencing factors of arteriosclerosis (indexed using the brachial–ankle pulse wave velocity, baPWV) between different sexes. Results The incidence of arteriosclerosis (baPWV greater than or equal to 1400 cm/s) was 54.70%. The incidence of arteriosclerosis in males (62.13%) was higher than in females (37.41%) (p < 0.01). According to age stratification (5 years difference for each group), the baPWV values of males in all age groups <70 years were higher than in females (p < 0.01). The increase in baPWV values was higher in females over 45 years than in males and correlated with males in the 70–75 age group. The multivariate linear regression model showed that for every 5-year increase in age, the baPWV increased by 62.55 cm/s in males and 71.86 cm/s in females. Furthermore, for every 10 mmHg increase in systolic blood pressure (SBP), the baPWV increased by 61.01 cm/s in males and 51.86 cm/s in females. Regular physical exercise reduced the baPWV in males, but there was no statistical correlation in females. The waist-to-hip ratio (WHR) increased the baPWV in females yet was not statistically significant in males. Multivariate logistic regression analysis showed that after adjusting for confounding factors (age, WHR, SBP, heart rate, triglyceride, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), high-sensitivity C-reactive protein (hs-CRP), estimated glomerular filtration rate (eGFR), diabetes, higher education, higher income, smoking, drinking, and physical exercise), males were 1.89 times more likely than females to develop arteriosclerosis (p < 0.05). A stratified analysis of males and females showed that the risk of arteriosclerosis was higher in females than in males in the 45–60 and over 60 age groups compared with those in the under 44 age group (p < 0.01). Diabetes, LDL-C, and hs-CRP were more likely to be correlated with arteriosclerosis in females than in males (odds ratio (OR): 2.32, 1.26, 1.08 vs. 1.83, 1.17, 1.02, respectively, p < 0.05). Higher education levels reduced the risk of arteriosclerosis in males and females, with OR values of 0.64 and 0.84, respectively (p < 0.05). Conclusions The arteriosclerosis detection rate in males was higher than in females. Conversely, the increase in baPWV in females older than 45 years was higher than in males. Meanwhile, WHR, diabetes, LDL-C, and hs-CRP were more likely to be correlated with arteriosclerosis in females. Clinical Trial Registration Chinese Clinical Trail Registry, URL: https://www.chictr.org.cn/showproj.html?proj=8050. Unique identifier: ChiCTR-TNRC-11001489 .

Background The study was aimed at assessing clinical status and outcome of patients affected by aorto-left ventricular tunnel (ALVT). Methods A systematic search of keywords relating to ALVT was conducted to identify papers published between 1965 and February 2024 present on Pubmed/Medline and Scopus. Results A total of 109 studies, which in all consisted of case reports and case series comprising 177 patients (64.2% males, p < 0.02) met the inclusion criteria. The median age of patients was 9.5 ± 8.9 years. Initial diagnosis was based on echocardiographic findings in 86.4% of patients, and confirmed by computed tomography (CT) and/or magnetic resonance imaging (MRI) in 17%. Of the 177 patients identified, 47.1% were diagnosed with a heart murmur and 32.4% with congestive heart failure. Associated cardiac abnormalities were detected in 39.8% (unicuspid/bicuspid aortic valve with or without stenosis/atresia in 14.8%, coronary artery abnormalities in 9.6%). A total of 90.3% of patients underwent surgery, whilst 4.5% were treated by means of transcatheter closure. Outcomes were largely favorable (death was reported in 5.7%). Mild residual aortic regurgitation continued to be present in 22.7% of the sample. In terms of statistics, no risk factors for death were found. Conclusions ALVT, an extremely rare congenital cardiac abnormality, may be diagnosed in both newborns and adults. Initial diagnostic observations are usually made using echocardiography, and subsequently refined by means of catheterization, CT or MRI. Surgery should be performed as soon as possible following diagnosis, particularly due to the inefficacy of medical treatment. In selected cases, transcatheter closure may represent a valid option. The condition is associated with a high mortality rate. Moreover, complications, particularly in the form of residual aortic valve regurgitation, may hamper postoperative prognosis. Due to the rarity of the disease, the setting up of an international registry is recommended.

Hypertrophic cardiomyopathy (HCM) is the most prevalent inherited cardiomyopathy transmitted in an autosomal dominant manner to offspring. It is characterized by unexplained asymmetrical hypertrophy primarily affecting the left ventricle and interventricular septum while potentially causing obstruction within the left ventricular outflow tract (LVOT). The clinical manifestations of HCM are diverse, ranging from asymptomatic to severe heart failure (HF) and sudden cardiac death. Most patients present with obvious symptoms of left ventricular outflow tract obstruction (LVOTO). The diagnosis of HCM mainly depends on echocardiography and other imaging examinations. In recent years, myosin inhibitors have undergone clinical trials and gene therapy, which is expected to become a new treatment for HCM, has been studied. This article summarizes recent clinical updates on the epidemiology, pathogenesis, diagnostic methods, treatment principles, and complication prevention and treatment of HCM, to provide new ideas for follow-up research.

Cardiovascular disease (CVD) is the leading cause of death worldwide, with physical inactivity being a known contributor to the global rates of CVD incidence. CVD incidence, however, is not uniform with recognized sex differences as well and racial and ethnic differences. Furthermore, gut microbiota have been associated with CVD, sex, and race/ethnicity. Researchers have begun to examine the interplay of these complicated yet interrelated topics. This review will present evidence that CVD (risk and development), and gut microbiota are distinct between the sexes and racial/ethnic groups, which appear to be influenced by acculturation, discrimination, stress, and lifestyle factors like exercise. Furthermore, this review will address the beneficial impacts of exercise on the cardiovascular system and will provide recommendations for future research in the field.

Type B aortic dissection (TBAD) is a severe cardiovascular condition that requires timely diagnosis and intervention to prevent life-threatening complications. The aim of this review was to focus on the most crucial and controversial aspects of contemporary TBAD management. It is recognized that in the acute phase, computed tomography angiography (CTA) plays an essential role in evaluating the extent of the dissection and monitoring disease progression. CTA has significantly improved the management of TBAD by providing detailed assessments of aortic anatomy and dynamic flow changes, positioning it as the cornerstone imaging modality for identifying acute high-risk patients who may require early intervention. Recently, new advances in magnetic resonance imaging (MRI) and positron emission tomography (PET) technology have the potential to provide further information beyond imaging alone. However, such sophisticated techniques should be reserved for stable patients after the acute phase. After decades of medical therapy and high risk surgery, thoracic endovascular aortic repair (TEVAR) has emerged as a minimally invasive alternative to open surgery for complicated TBAD, offering lower perioperative morbidity and mortality. Nevertheless, its use in uncomplicated TBAD remains a topic of ongoing debate. While recent studies suggest that preemptive TEVAR combined with optimal medical therapy may reduce late adverse events and improve long-term outcomes, these findings remain controversial. This review critically analyzes the current literature on both diagnosis and TEVAR treatment, evaluating these controversies in the context of clinical practice.

The steady increase in life expectancy throughout the world is contributing to an increased incidence of atrial fibrillation (AF), which imposes a significant socioeconomic toll on affected patients and societies. The mechanisms underlying atrial fibrillation are multifaceted and vary among individuals. Hypoxia is a process that is closely linked to AF onset and progression. Hypoxia-inducible factor 1-alpha (HIF-1α) is a transcription factor that serves as a key regulator of oxygen homeostasis within cells through its activation under hypoxic conditions and subsequently coordinates various pathophysiological responses. High levels of HIF-1α expression are evident in AF patients, and facilitate the progression from persistent AF to permanent AF. Thus, HIF-1α may serve as a promising target for novel therapeutic strategies aimed at the prevention and treatment of AF. This review provides an overview and synthesis of recent studies probing the relationship between HIF-1α and AF, providing a foundation for future studies and the development targeted drug therapies.

Background Elevated homocysteine (Hcy) levels have been linked to poorer outcomes in acute coronary syndrome. This study aimed to assess the predictive value of elevated Hcy levels for major adverse cardiac events (MACE) in patients with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PCI). Methods This retrospective cohort study included 183 STEMI patients who underwent primary PCI at a tertiary university hospital in southern China from January 2020 to December 2021. Laboratory values, including Hcy levels, were obtained within 24 hours of admission. Patients were categorized into elevated and normal Hcy groups using a threshold of 12 μmol/L. The study outcome was the occurrence of 6-point MACE, defined as cardiac death, nonfatal myocardial infarction, stroke, ischemia-driven revascularization (PCI or coronary artery bypass grafting), heart failure and all-cause death. Survival analyses were conducted using Kaplan-Meier and Cox proportional hazard methods. Propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) approaches were employed to minimize bias. Results The mean age of the patients was 64.8 years, with 76.0% being male. After adjusting with PSM or IPTW, covariate imbalances between the two groups were corrected. Over a median follow-up period of 25.8 months, 55 MACE events occurred, resulting in an event rate of 30.1%. Patients with elevated Hcy levels had a higher incidence of MACE in both unadjusted (hazard ratio [HR] = 2.778; 95% confidence interval [CI]: 1.591–4.850; p < 0.001) and adjusted analyses (PSM: HR = 2.995; 95% CI: 1.397–6.423, p = 0.005; IPTW: HR = 3.2; 95% CI: 1.631–6.280, p < 0.001). Multivariate Cox regression further confirmed that elevated Hcy levels were associated with a worse prognosis across the entire cohort (HR = 1.062, 95% CI: 1.029–1.097, p < 0.001), PSM cohort (HR = 1.089, 95% CI: 1.036–1.145, p < 0.001), and IPTW cohort (HR = 1.052, 95% CI: 1.020–1.086, p = 0.001). Conclusions Elevated plasma levels of Hcy (≥12 μmol/L) are associated with worse outcomes in STEMI patients undergoing primary PCI, highlighting the potential role of Hcy as a prognostic marker in this population.

Background Tumor characteristics are associated with the risk of cardiovascular death (CVD) in cancer patients. However, the influence of tumor characteristics on CVD risk among prostate cancer (PC) patients who have received radiotherapy (RT) or chemotherapy (CT) is often overlooked. This study explored the association between PC tumor characteristics and CVD risk in PC patients who had received RT or CT. Methods Fine-gray competitive risk analysis was employed to identify CVD risk factors. Sensitivity analyses were conducted to adjust for confounding factors. The predicted prostate-specific antigen (PSA) and Gleason score values were visualized using a nomogram, which was subsequently validated through calibration curves and concordance indexes (C-indexes). Results A total of 120,908 patients were enrolled in the study, with a mean follow-up time of 80 months. PSA values between 10 and 20 ng/mL (adjusted hazard ratio (HR): 1.28, 95% confidence interval (CI): 1.20–1.36, p < 0.001) and >20 ng/mL (adjusted HR: 1.27, 95% CI: 1.21–1.35, p < 0.001), and a Gleason score >7 (adjusted HR: 1.23, 95% CI: 1.07–1.41, p = 0.004) were identified as risk factors of CVD for PC patients after RT or CT. The C-index of the training cohort was 0.66 (95% CI: 0.66–0.67), and the C-index of the validation cohort was 0.67 (95% CI: 0.65–0.68). Consistency was observed between the actual observations and the nomogram. Risk stratification was also significant (p < 0.001). Conclusions PSA values ≥10 ng/mL and Gleason scores >7 may be associated with an increased risk of CVD in PC patients after RT or CT. These patients may require more long-term follow-up and monitoring of CVD risk.

Background Unexpected cardiovascular events are likely to occur within a short period following an acute myocardial infarction (AMI). The sodium-glucose co-transporter 2 inhibitor (SGLT2-I) is a recently recommended drug for the treatment of AMI. However, its role in the risk of the outcomes following an AMI, including all-cause death and heart failure readmission, remains controversial. Therefore, in this study, we explored the effect of SGLT2-Is on cardiovascular outcomes after an AMI. Methods PubMed, Web of Science, and Embase were searched without language restrictions to retrieve case-control studies published before April 2024. Citations were independently screened by two authors, and the studies meeting the predefined inclusion criteria were retained. Data on author names, year of publication, location of the study group, gender and age of participants, outcome assessment, adjusted odds ratios (ORs) and 95% confidence intervals (CIs), and the follow-up period were extracted. Results Eight studies were eligible for inclusion, and these studies showed that the use of SGLT2-Is after an AMI was significantly associated with a lower risk of hospitalization for heart failure (OR: 0.66, 95% CI 0.57–0.76, p < 0.01) and a lower incidence of major cardiovascular adverse events (OR: 0.79, 95% CI 0.70–0.89, p < 0.01), but was unrelated to a lower incidence of all-cause mortality (OR: 0.84, 95% CI 0.69–1.02, p = 0.07). Conclusions Compared with placebo, SGLT2-I therapy following an AMI can reduce the risk of heart failure hospitalization and the incidence of major cardiovascular adverse events, but has no effect on all-cause mortality. The PROSPERO registration CRD42024542335, https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024542335.

Background The blood glucose levels in people with prediabetes mellitus (PDM) are regarded as too high to be normal but below the cutoff for diabetes mellitus (DM). Clinical indicators for PDM patients include impaired glucose tolerance (IGT), impaired fasting glucose (IFG), and/or hemoglobin A1c (HbA1c) levels between 5.7 and 6.4% (39–47 mmol/mol). PDM has been shown to raises the risk of cardiovascular disease (CVD) and mortality. Meanwhile, death and morbidity can be predicted by the new ventricular repolarization features of the electrocardiogram (ECG). Several studies have analyzed the connection between DM and the ventricular repolarization characteristics of ECG; however, few studies have examined the connection between PDM and these ventricular repolarization characteristics. This study evaluated the ECG ventricular repolarization parameters in individuals with PDM. Methods A retrospective case-control design was used. Randomly selected participants included 79 PDM patients (30 men, mean age: 39.7 ± 5.7 years) and 79 controls (30 men, mean age: 39.8 ± 5.2 years). ECG intervals analyzed were the distance from the beginning of the Q wave to the end of the T wave (QT), the distance between Q and S waves (QRS), the distance between the T wave’s termination and point J (JT), and the distance between the peak and endpoint of the T wave (Tp-e), along with corrected and derived measures (corrected QT interval (QTc), the difference between the maximum and smallest QT intervals (QTd), corrected QTd (QTdc), corrected JT interval (JTc), Tp-e/QT, Tp-e/QTc, Tp-e/JT, Tp-e/JTc). Patient records were retrieved from the institution’s database. Results Both groups had comparable averages for age, gender, smoking, hyperlipidemia, body mass index (BMI), (p > 0.05 for each). Similarly, both groups had similar QT, QRS, and JT intervals. PDM patients had significantly greater heart rates (bpm), and QTc, QTd, QTdc, JTc, and Tp-e intervals (millisecond, ms) than the control group. The results were deemed significant when HbA1c levels were associated with every employed ECG measurement in our investigation. Conclusions In our study, the HbA1c value was shown to be moderately positively correlated with the heart rate and QTc, QTd, QTdc, JTc, and Tp-e intervals, all of which were determined to be significant. Additionally, the HbA1c value showed a weak positive correlation with Tp-e/QT, Tp-e/JT ratios, which were statistically significant. This study showed that patients with PDM are prone to ventricular arrhythmia in the early period of the disorder.

Background Statin therapy is associated with an increased risk of new-onset diabetes (NOD), possibly due to a reduction in coenzyme Q10 (CoQ10) levels as a result of statin use. This study aimed to investigate the relationship between exogenous CoQ10 supplementation and the development of NOD. Methods This study included 4394 participants from the National Health and Nutrition Examination Survey (NHANES). Baseline characteristics were compared between those with and without NOD and between those with and without CoQ10. Univariate logistic regression was performed to identify factors associated with NOD. Two models were used for confounding factors, including demographics and various covariates. Multifactor logistic regression further assessed the association between CoQ10 supplementation and NOD. Additionally, restricted cubic spline (RCS) analysis was conducted to evaluate the potential nonlinear relationship between daily CoQ10 dose and NOD. Results Univariate logistic regression showed an association between CoQ10 supplementation and a reduced risk of NOD (odds ratio [OR] = 0.323, 95% confidence interval [CI] 0.157–0.668, p = 0.003), which remained significant after adjustments in model 1 (OR = 0.344, 95% CI 0.160–0.737, p = 0.006) and model 2 (OR = 0.232, 95% CI 0.057–0.942, p = 0.041). There was no evidence of a linear association between daily CoQ10 dose and NOD in logistic regression analysis (OR = 0.999, 95% CI 0.994–1.004, p = 0.720), and no evidence of a nonlinear correlation in the RCS analysis (p > 0.05). Conclusions CoQ10 supplementation in individuals taking statins was associated with a reduced risk of NOD, and this association was independent of the CoQ10 dose.