dium-glucose transporter-2 (SGLT-2) inhibitors, IL-1β inhibitors, and metformin may be promising drugs for repurposing to treat multi morbidity. We propose that targeting the metabolic and inflammatory pathways that are common to HF and comorbidities may provide a promising therapeutic strategy.Background Arrhythmogenic cardiomyopathy is a hereditary cause of ventricular arrhythmias and sudden death. Identifying the healthy genetic carriers who will develop the disease remains a challenge. A novel approach to the analysis of the digital electrocardiograms of mutation carriers through signal processing may identify early electrocardiographic abnormalities. Methods A retrospective case-control study included a population of healthy genetics carriers and their wild-type relatives. Genotype-positive/phenotype-negative individuals bore mutations associated with the development of arrhythmogenic cardiomyopathy. The relatives included had a non-pathological 12-lead electrocardiogram, echocardiogram, and a cardiac magnetic resonance. Automatic digital electrocardiographic analyses comprised QRS and terminal activation delay duration, the number of QRS fragmentations, ST slope, and T-wave voltage. Results Digital 12-lead electrocardiograms from 41 genotype-positive/ phenotype-negative (29 simple carriers and 12 double mutation carriers) and 73 wild-type relatives were analyzed. No differences in the QRS length, the number of QRS fragmentations, and the voltage of the T-wave were observed. After adjusting for potential confounders, double carriers showed an average ST-slope flatter than those of the simple carriers and wild type [5.18° (0.73-8.01), 7.15° (5.14-11.05), and 11.46° (3.94-17.49), respectively, p = 0.005]. There was a significant negative correlation between the ST slope and the age in genotype-positive/phenotype-negative relatives (r = 0.376, p = 0.021) not observed in their wild-type counterparts (r = 0.074, p = 0.570). Conclusions A flattened ST segment may be an early sign of electrical remodeling that precedes T-wave inversion in healthy genetic carriers. A thorough analysis of the digital electrocardiographic signal may help identify and measure early electrical abnormalities.Background Right ventricular (RV) function predicts survival in numerous cardiac conditions, including left heart disease. The reference standard for non-invasive assessment of RV function is cardiac magnetic resonance imaging (CMR). The aim of this study was to investigate the association between pre-procedural CMR-derived RV functional parameters and mortality in patients undergoing transcatheter aortic valve implantation (TAVI). Methods Patients scheduled for TAVI were recruited to undergo pre-procedural CMR. Volumetric function and global longitudinal and circumferential strain (GLS and GCS) of the RV and left ventricle (LV) were measured. The association with the primary endpoint (1-year all-cause mortality) was analyzed with Cox regression. Elamipretide chemical structure Results Of 133 patients undergoing CMR, 113 patients were included in the analysis. Mean age was 81.8 ± 5.8 years, and 65% were female. Median follow-up was 3.9 [IQR 2.3-4.7] years. All-cause and cardiovascular mortality was 14 and 12% at 1 year, and 28 and 20% at 3 years, respectively. One-year all-cause mortality was significantly predicted by RV GLS [HR = 1.109 (95% CI 1.023-1.203); p = 0.012], RV ejection fraction [HR = 0.956 (95% CI 0.929-0.985); p = 0.003], RV end-diastolic volume index [HR = 1.009 (95% CI 1.001-1.018); p = 0.025], and RV end-systolic volume index [HR = 1.010 (95% CI 1.003-1.017); p = 0.005]. In receiver operating characteristic (ROC) analysis for 1-year all-cause mortality, the area under the curve was 0.705 (RV GLS) and 0.673 (RV EF). Associations decreased in strength at longer follow-up. None of the LV parameters was associated with mortality. Conclusions RV function predicts intermediate-term mortality in TAVI patients while LV parameters were not associated with outcomes. Inclusion of easily obtainable RV GLS may improve future risk scores.Heart disease is the leading cause of death in both men and women in developed countries. Heart failure (HF) contributes to significant morbidity and mortality and continues to remain on the rise. While advances in pharmacological therapies have improved its prognosis, there remain a number of unanswered questions regarding the impact of these therapies in women. Current HF guidelines recommend up-titration of neurohormonal blockade, to the same target doses in both men and women but several factors may impair achieving this goal in women more adverse drug reactions, reduced adherence and even lack of evidence on the optimal drug dose. Systematic under-representation of women in cardiovascular drug trials hinders the identification of sex differences in the efficacy and safety of cardiovascular medications. Women are also under-represented in device therapy trials and are 30% less likely to receive a device in clinical practice. Despite presenting with fewer ventricular arrythmias and having an increased risk of implant complications, women show better response to resynchronization therapy, with lower mortality and HF hospitalizations. Fewer women receive advanced HF therapies. They have a better post-heart transplant survival compared to men, but an increased immunological risk needs to be acknowledged. Technological advances in mechanical circulatory support, with smaller and more hemocompatible devices, will likely increase their implantation in women. This review outlines current evidence regarding sex-related differences in prescription, adherence, adverse events, and prognostic impact of the main management strategies for HF.Background Idiopathic pulmonary arterial hypertension (IPAH) is a life-threatening disease. Owing to its high fatality rate and narrow therapeutic options, identification of the pathogenic mechanisms of IPAH is becoming increasingly important. Methods In our research, we utilized the robust rank aggregation (RRA) method to integrate four eligible pulmonary arterial hypertension (PAH) microarray datasets and identified the significant differentially expressed genes (DEGs) between IPAH and normal samples. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed to analyze their functions. The interaction network of protein-protein interaction (PPI) was constructed to explore the correlation between these DEGs. The functional modules and hub genes were further identified by the weighted gene coexpression network analysis (WGCNA). Moreover, a miRNA microarray dataset was involved and analyzed to filter differentially expressed miRNAs (DE-miRNAs). Potential target genes of screened DE-miRNAs were predicted and merged with DEGs to explore a miRNA-mRNA network in IPAH.