Heart failure remains a major cause of global morbidity and mortality despite advances in guideline-directed medical therapy. Nanoparticle-based approaches have gained attention as strategies to enhance therapeutic delivery; however, their clinical relevance depends on addressing true pharmacological barriers rather than repackaging existing agents. In this review, we present a conceptual framework to define when nanomedicine provides meaningful therapeutic value in heart failure. We argue that nanotechnology should not be viewed as a replacement for guideline-directed medical therapy, but as an enabling platform for the targeted delivery of potent therapies limited by pharmacokinetic and biodistribution constraints. We summarize the principal nanoparticle platforms used in cardiovascular applications, including lipid-based and polymeric systems, and contextualize their use across key pathophysiological domains in heart failure: TGF-β (transforming growth factor-beta)-mediated fibrosis, IL-1β (interleukin-1 beta) and TNF-α (tumor necrosis factor-alpha)-driven inflammation, reactive oxygen species-mediated injury, regenerative strategies, and gene- and mRNA-based therapies. We propose 3 criteria for translational relevance: (1) a targetable myocardial microenvironment, (2) a therapeutic agent limited by conventional delivery, and (3) a formulation that confers a demonstrable clinical advantage. Although these conditions are met in selected preclinical models, clinical translation remains limited. The field is therefore shifting from an emphasis on delivery feasibility to therapeutic necessity. Nanomedicine is best positioned as a precision adjunct to heart failure therapy-enabling the right therapy to reach the right myocardium at the right time.

Pulmonary atresia with intact ventricular septum management has evolved, with increased use of transcatheter right ventricular decompression, but the impact on contemporary outcomes remains unknown. This study evaluates contemporary national outcomes in patients aged 0 to 18 years.

Internal N7-methylguanosine (m7G) is a recently identified chemical modification of mammalian mRNA. Although the epitranscriptome plays a key role in regulating RNA metabolism and cellular function, the specific contribution of internal m7G to cardiovascular disease remains unknown. Atherosclerosis preferentially develops at sites of disturbed blood flow, which promotes endothelial activation; however, whether internal m7G regulates endothelial mechanotransduction and atherogenesis remains unclear.

Mature mammalian cardiomyocytes (CMs) develop compact sarcomeric structures that inhibit proliferation. Consequently, CMs must dedifferentiate to a fetus-like state, which is accompanied by sarcomere disassembly, to enable successful cytokinesis. However, the regulation and coordination of CM dedifferentiation, cell cycle progression, and sarcomere reorganization remain unclear.

Risk prediction is fundamental to pulmonary hypertension (PH) guideline-based care, yet pediatric-specific risk prediction models remain limited, relying primarily on single predictors, expert opinion, or application of adult models to children. The authors developed and externally validated a data-driven 1-year risk prediction model for pediatric PH.

Cardiomyocytes exhibit marked susceptibility to ferroptosis after myocardial infarction (MI), rendering ferroptosis inhibition a promising therapeutic strategy to mitigate ischemic myocardial injury. Although mitochondrial dysfunction is recognized as a core driver of ferroptosis, the potential role of mitochondrial DNA transcription in regulating cardiomyocyte ferroptosis remains unexplored.

Chagas disease (ChD), a neglected cardiovascular condition, affects 7.5 to 10.5 million people worldwide. Opportunistic screening during routine electrocardiography may allow earlier detection of unrecognized infections, enabling timely antiparasitic therapy or optimized cardiac care. This study prospectively evaluated the feasibility and diagnostic accuracy of an artificial intelligence (AI)-enabled ECG model enriched with 3 epidemiological questions (AI-ECG-EPI model) as an opportunistic screening for ChD in endemic regions of Brazil.

Postcardiac arrest syndrome is a complex multisystem disorder that evolves after return of spontaneous circulation and remains a major determinant of morbidity and mortality following out-of-hospital cardiac arrest. Beyond anoxic brain injury and transient myocardial dysfunction, many patients develop a systemic ischemia/reperfusion response with endothelial and microvascular dysfunction, vasoplegia, and immune dysregulation-features that contribute to shock and organ failure. Hemodynamic instability is often mixed with low systemic vascular resistance despite preserved or recovering cardiac output, but management is still largely supportive and centered on achieving a target mean arterial pressure. An increasing understanding of the central role of inflammation, including gastrointestinal barrier disruption, cytokine release, complement activation, nitric oxide-cGMP signaling, and immune phenotypic heterogeneity has prompted evaluation of targeted adjunctive therapies. However, randomized trials of immunomodulators and other vasoactive strategies have yielded mixed results, reflecting biological heterogeneity and limited phenotypic stratification. This review synthesizes contemporary understanding of the inflammatory and hemodynamic mechanisms underpinning postcardiac arrest syndrome, examines current and emerging pharmacologic strategies, and highlights priorities for future investigation, including mechanistic phenotyping, prospective biobanking, and prospective trial requirements to guide more precise management strategies in postcardiac arrest care.

Although diabetes is a known driver of heart failure with preserved ejection fraction, whether antecedent hyperinsulinemia drives preclinical diastolic dysfunction (DD) progression before overt hyperglycemia remains unknown. Therefore, we investigated whether elevated endogenous insulin and insulin resistance independently predict longitudinal DD progression and adverse cardiovascular outcomes.

Frequent transthoracic echocardiograms (TTEs) are required to monitor for left ventricular systolic dysfunction (LVSD) in patients with obstructive hypertrophic cardiomyopathy receiving myosin inhibitors. This requirement may be cumbersome and limit access in underserved and rural areas. The objective of this study was to evaluate the performance of an artificial intelligence (AI)-enabled ECG tool in predicting LVSD in hypertrophic cardiomyopathy patients on mavacamten.

With evolving therapy for heart failure with reduced ejection fraction, the benefits of adding a defibrillator in patients undergoing cardiac resynchronization therapy (CRT) remain unclear, particularly for nonischemic cardiomyopathy (NICM). This study evaluates long-term survival among patients with NICM treated with CRT defibrillator (CRT-D) versus CRT pacemaker (CRT-P).