The function of the kidney is tightly linked to the function of the heart. Dysfunction/disease of the kidney may initiate, accentuate, or precipitate of the cardiac dysfunction/disease and vice versa, contributing to a negative spiral. Further, the reciprocal association between the heart and the kidney may occur on top of other entities, usually diabetes, hypertension, and atherosclerosis, simultaneously affecting the two organs. Chronic kidney disease (CKD) can influence cardiac function through altered hemodynamics and salt and water retention, leading to venous congestion and therefore, not surprisingly, to heart failure (HF). Management of HF in CKD is challenging due to several factors, including complex interplays between these two conditions, the effect of kidney dysfunction on the metabolism of HF medications, the effect of HF medications on kidney function, and the high risk for anemia and hyperkalemia. As a result, in most HF trials, patients with severe renal impairment (i.e., eGFR 30 mL/min/1.73 m² or less) are excluded. The present review discusses the epidemiology, pathophysiology, and current medical management in patients with HF developing in the context of CKD.

In recent times, there have been notable changes in cardiovascular medicine, propelled by the swift advancements in artificial intelligence (AI). The present work provides an overview of the current applications and challenges of AI in the field of heart failure. It emphasizes the “garbage in, garbage out” issue, where AI systems can produce inaccurate results with skewed data. The discussion covers issues in heart failure diagnostic algorithms, particularly discrepancies between existing models. Concerns about the reliance on the left ventricular ejection fraction (LVEF) for classification and treatment are highlighted, showcasing differences in current scientific perceptions. This review also delves into challenges in implementing AI, including variable considerations and biases in training data. It underscores the limitations of current AI models in real-world scenarios and the difficulty in interpreting their predictions, contributing to limited physician trust in AI-based models. The overarching suggestion is that AI can be a valuable tool in clinicians’ hands for treating heart failure patients, as far as existing medical inaccuracies have been addressed before integrating AI into these frameworks.

Patients with heart failure (HF) patients may die either suddenly (sudden cardiac death/SCD) or progressively from pump failure. The heightened risk of SCD in patients with HF may expedite important decisions about medications or devices. We used the Larissa Heart Failure Risk Score (LHFRS), a validated risk model for all-cause mortality and HF rehospitalization, to investigate the mode of death in 1363 patients enrolled in the Registry Focused on Very Early Presentation and Treatment in Emergency Department of Acute Heart Failure (REALITY-AHF). Cumulative incidence curves were generated using a Fine–Gray competing risk regression, with deaths that were not due to the cause of death of interest as a competing risk. Likewise, the Fine–Gray competing risk regression analysis was used to evaluate the association between each variable and the incidence of each cause of death. The AHEAD score, a well-validated HF risk score ranging from 0 to 5 (atrial fibrillation, anemia, age, renal dysfunction, and diabetes mellitus), was used for the risk adjustment. Patients with LHFRS 2–4 exhibited a significantly higher risk of SCD (HR hazard ratio adjusted for AHEAD score 3.15, 95% confidence interval (CI) (1.30–7.65), p = 0.011) and HF death (adjusted HR for AHEAD score 1.48, 95% CI (1.04–2.09), p = 0.03), compared to those with LHFRS 0,1. Regarding cardiovascular death, patients with higher LHFRS had significantly increased risk compared to those with lower LHFRS (HR 1.44 adjusted for AHEAD score, 95% CI (1.09–1.91), p = 0.01). Lastly, patients with higher LHFRS exhibited a similar risk of non-cardiovascular death compared to those with lower LHFRS (HR 1.44 adjusted for AHEAD score, 95% CI (0.95–2.19), p = 0.087). In conclusion, LHFRS was associated independently with the mode of death in a prospective cohort of hospitalized HF patients.

Over the past decades, coronary revascularization has evolved dramatically with the introduction of bioresorbable scaffolds (BRSs), designed to provide temporary vessel support, elute antiproliferative drugs, and then fully resorb, ideally restoring natural vasomotion and eliminating long-term foreign-body reactions. Early enthusiasm for first-generation polymeric devices, such as the Absorb bioresorbable vascular scaffold, was tempered by increased rates of scaffold thrombosis and late adverse events, largely attributed to thick struts, suboptimal implantation techniques, and unpredictable degradation kinetics. Subsequent developments in polymeric (e.g., MeRes-100, NeoVas) and metallic magnesium-based scaffolds (e.g., Magmaris) have focused on thinner struts, improved radial strength, and refined resorption profiles. Clinical trials and meta-analyses, including ABSORB, AIDA, BIOSOLVE, and BIOSTEMI, reveal that optimized procedural strategies, especially the “PSP” approach (Prepare–Size–Post-dilate) and routine intravascular imaging, substantially reduce thrombosis and restenosis rates, aligning outcomes closer to those of contemporary drug-eluting stents (DESs). Nonetheless, challenges persist regarding inflammatory responses to degradation by-products, mechanical fragility in complex lesions, and patient selection. Ongoing innovations include hybrid polymer–metal designs, stimuli-responsive drug coatings, and AI-assisted imaging for precision implantation. While early-generation BRSs demonstrated both promise and pitfalls, next-generation platforms show steady progress toward achieving the dual goals of transient scaffolding and long-term vessel restoration. The current trajectory suggests that bioresorbable technology, supported by optimized technique and material science, may soon fulfill its original vision; offering safe, effective, and fully resorbable alternatives to permanent metallic stents in coronary artery disease. This review provides an updated synthesis of the design principles, clinical outcomes, and procedural considerations of drug-eluting bioresorbable scaffolds (BRSs). It integrates recent meta-analytic evidence and emerging insights on device mechanics, including the influence of strut thickness on radial strength and the potential role of non-invasive imaging in pre-implantation planning. Special focus is given to magnesium-based scaffolds and future directions in patient selection and implantation strategy.

Background and Objectives: Remote ischemic preconditioning (RIPC) has demonstrated efficacy in protecting against myocardial ischemia–reperfusion injury when applied before percutaneous coronary revascularization. Ranolazine, an anti-ischemic drug, has been utilized to minimize ischemic events in chronic angina patients. However, there is a lack of trials exploring the combined effects of ranolazine pretreatment and RIPC in patients undergoing percutaneous coronary interventions (PCIs). Materials and Methods: The present study is a prospective study which enrolled 150 patients scheduled for nonemergent percutaneous coronary revascularization. Three groups were formed: a control group undergoing only PCIs, an RIPC group with RIPC applied to either upper limb before the PCI (preconditioning group), and a group with RIPC before the PCI along with prior ranolazine treatment for stable angina (ranolazine group). Statistical analyses, including ANOVAs and Kruskal–Wallis tests, were conducted, with the Bonferroni correction for type I errors. A repeated-measures ANOVA assessed the changes in serum enzyme levels (SGOT, LDH, CRP, CPK, CK-MB, troponin I) over the follow-up. Statistical significance was set at p < 0.05. Results: The ranolazine group showed (A) significantly lower troponin I level increases compared to the control group for up to 24 h, (B) significantly lower CPK levels after 4, 10, and 24 h compared to the preconditioning group (p = 0.020, p = 0.020, and p = 0.019, respectively) and significantly lower CPK levels compared to the control group after 10 h (p = 0.050), and (C) significantly lower CK-MB levels after 10 h compared to the control group (p = 0.050). Conclusions: This study suggests that combining RIPC before scheduled coronary procedures with ranolazine pretreatment may be linked to reduced ischemia induction, as evidenced by lower myocardial enzyme levels.

Myocarditis is a rare adverse event of vaccination. Recently, mRNA vaccines for COVID-19 have been reported to correlate with myocarditis, specifically in adolescents and young men. We report a rare case of a 50-year-old man who presented with symptoms of myocardial infarction 3 days after the second dose of vaccination for COVID-19. Cardiac magnetic resonance (CMR) imaging revealed acute myopericarditis. Clinicians should be aware of that rare side effect of mRNA vaccines for COVID-19 that can affect not only younger recipients but also middle-aged patients presenting with symptoms mimicking acute coronary syndrome.