Mcfarlandsellers6653

In contrast, dynamic substrates comprise increased amplitude of APD alternans, steeper APD restitution gradients, transient reversal of transmural repolarization gradients and impaired depolarization-repolarization coupling. The following review article will summarize the molecular mechanisms that generate these electrophysiological abnormalities and subsequent arrhythmogenesis.Since the approval of the first immune checkpoint inhibitor (ICI) 9 years ago, ICI-therapy have revolutionized cancer treatment. Lately, antibodies blocking the interaction of programmed cell death protein (PD-1) and ligand (PD-L1) are gaining momentum as a cancer treatment, with multiple agents and cancer types being recently approved for treatment by the US Food and Drug Administration (FDA). Unfortunately, immunotherapy often leads to a wide range of immune related adverse events (IRAEs), including several severe cardiac effects and most notably myocarditis. While increased attention has been drawn to these side effects, including publication of multiple clinical observational data, the underlying mechanisms are unknown. In the event of IRAEs, the most widely utilized clinical solution is administration of high dose corticosteroids and in severe cases, discontinuation of these ICIs. This is detrimental as these therapies are often the last line of treatment options for many types of advanced cancer. In this review, we have systematically described the pathophysiology of the PD-1/PD-L1 axis (including a historical perspective) and cardiac effects in pre-clinical models, clinical trials, autoimmune mechanisms, and immunotherapy in combination with other cancer treatments. We have also reviewed the current challenges in the diagnosis of cardiac events and future directions in the field. In conclusion, this review will delve into this expanding field of cancer immunotherapy and the emerging adverse effects that should be quickly detected and prevented.Transcatheter techniques for the treatment of tricuspid regurgitation (TR) are being more frequently used and several new devices are in development. Since 90% of patients with TR have secondary TR, catheter based systems which reduce the dilated tricuspid annulus area are of particular interest. In order to perform an annuloplasty procedure effectively and safely, knowledge about the anatomy of the tricuspid valve apparatus and especially of the annulus in relation to the important neighboring structures such as the aortic root, the RCA, the electrical pathways and the CS is fundamental. In addition, comprehensive understanding of the device itself, the delivery system, its maneuverability and the individual procedural steps is required. Furthermore, the use of multi-modality imaging is important. For each step of the procedure the appropriate imaging modality as well as the optimal; imaging planes are crucial to provide the necessary information to best guide the individual procedural step.Background and Objective The optimum duration of dual antiplatelet therapy (DAPT) remains uncertain in patients with acute coronary syndrome treated with new generation stents. This meta-analysis was performed to investigate ischemia and bleeding outcomes with different DAPT strategies. Methods PubMed, Embase, Cochrane and Web of science from inception to May 27, 2020, were systematically searched. Randomized controlled trials were included to compare short-term (6 months or less) with standard (12 months) DAPT in patients with acute coronary syndrome treated with new generation stents. The primary endpoints were myocardial infarction, definite or probable stent thrombosis and major bleeding. The secondary endpoints included all-cause death, cardiovascular death, stroke, target vessel revascularization and net adverse clinical events. Random effect model and fixed effect model were used to calculate the odds ratio (OR) and 95% confidence interval (CI) of each endpoint. find more Results Four randomized controlled trialeduction in the risk of major bleeding compared with the standard DAPT. This benefit is achieved without increasing the risk of mortality or ischemic outcomes. The study protocol was registered in PROSPERO (CRD42020189871).Introduction Congenital long QT syndrome (LQTS) is a cardiac ion channelopathy that predisposes affected individuals to spontaneous ventricular tachycardia/fibrillation (VT/VF) and sudden cardiac death (SCD). The main aims of the study were to (1) provide a description of the local epidemiology of LQTS, (2) identify significant risk factors of ventricular arrhythmias in this cohort, and (3) compare the performance of traditional Cox regression with that of random survival forests. Methods This was a territory-wide retrospective cohort study of patients diagnosed with congenital LQTS between 1997 and 2019. The primary outcome was spontaneous VT/VF. Results This study included 121 patients [median age of initial presentation 20 (interquartile range 8-44) years, 62% female] with a median follow-up of 88 (51-143) months. Genetic analysis identified novel mutations in KCNQ1, KCNH2, SCN5A, ANK2, CACNA1C, CAV3, and AKAP9. During follow-up, 23 patients developed VT/VF. Univariate Cox regression analysis revealed that age [hazard ratio (HR) 1.02 (1.01-1.04), P = 0.007; optimum cut-off 19 years], presentation with syncope [HR 3.86 (1.43-10.42), P = 0.008] or VT/VF [HR 3.68 (1.62-8.37), P = 0.002] and the presence of PVCs [HR 2.89 (1.22-6.83), P = 0.015] were significant predictors of spontaneous VT/VF. Only initial presentation with syncope remained significant after multivariate adjustment [HR 3.58 (1.32-9.71), P = 0.011]. Random survival forest (RSF) model provided significant improvement in prediction performance over Cox regression (precision 0.80 vs. 0.69; recall 0.79 vs. 0.68; AUC 0.77 vs. 0.68; c-statistic 0.79 vs. 0.67). Decision rules were generated by RSF model to predict VT/VF post-diagnosis. Conclusions Effective risk stratification in congenital LQTS can be achieved by clinical history, electrocardiographic indices, and different investigation results, irrespective of underlying genetic defects. A machine learning approach using RSF can improve risk prediction over traditional Cox regression models.