Background: Beta-blockers are widely prescribed across cardiovascular indications, yet their real-world cardiovascular adverse-event profiles across drug generations remain incompletely characterised in large pharmacovigilance datasets. Objective: The objective was to describe and compare cardiovascular adverse-event reporting patterns for atenolol, bisoprolol and nebivolol in the FDA Adverse Event Reporting System (FAERS). Methods: We performed a retrospective disproportionality analysis of FAERS reports using OpenVigil 2.1, covering each drug’s available reporting history from the first quarter of 2004 (2007 for nebivolol) through the third quarter of 2025 (FAERS 2025 Q3). Cardiovascular events were defined as individual MedDRA Preferred Terms; signals were assessed with the Reporting Odds Ratio (ROR, 95% CI) and Information Component (IC) under Evans’ criteria. Individual case safety reports were also analysed for demographics, seriousness and outcomes. Results: Atenolol was most strongly associated with bradycardia (ROR = 10.513), followed by pericardial haemorrhage (ROR = 7.067) and ventricular hypertrophy (ROR = 6.999). Bisoprolol showed the highest signals for diastolic dysfunction (ROR = 24.875), atrial tachycardia (ROR = 23.283) and chronic cardiac failure (ROR = 23.222). Nebivolol had the lowest overall reporting volume, although counts were not adjusted for exposure; its strongest signals were bradycardia (ROR = 9.619) and coronary artery stenosis (ROR = 9.351). Paediatric reports (0–17 years) were uncommon for atenolol and bisoprolol and nearly absent for nebivolol; none of the three is FDA-approved in this group. Reports mainly involved older adults (60–89 years), and a substantial proportion were classified as serious. Conclusions: All three agents generated significant signals across a broad range of cardiovascular events. Nebivolol had the lowest reporting volume, but this should not be interpreted as evidence of a safer profile. Because FAERS disproportionality cannot establish causality, these findings are hypothesis-generating and require prospective confirmation before they can inform beta-blocker selection.
Postoperative atrial fibrillation remains one of the most common complications after cardiac surgery. Although it is often transient, it can complicate recovery, prolong hospitalization, and identify patients at higher risk of future atrial fibrillation. In daily practice, however, management remains largely reactive, as most patients are recognized only after the arrhythmia has already occurred. This creates an important opportunity for earlier risk stratification. Cardiac surgery is a particularly attractive setting because the event is common, perioperative monitoring is dense, and preoperative 12-lead electrocardiograms are routinely available. Many of these electrocardiograms are recorded in sinus rhythm and may appear normal on clinical review, yet they may still contain subtle signs of latent atrial vulnerability. In this perspective, we argue that postoperative atrial fibrillation after cardiac surgery is a promising use case for clinically meaningful artificial intelligence in 2026. The most compelling next step is to test whether preoperative electrocardiograms add useful information to clinical and biomarker-based risk assessment before the first postoperative episode occurs.
Cardiac sarcoidosis (CS) is an inflammatory cardiomyopathy with heterogeneous presentation and potentially life-threatening complications, including ventricular arrhythmia, atrioventricular block, and heart failure. Early diagnosis is challenging and a multidisciplinary approach is pivotal for optimal treatment and better outcome. We report the case of a 47-year-old man with newly diagnosed systemic sarcoidosis who rapidly developed heart failure and therapy-refractory ventricular arrhythmias despite combined immunosuppressive and antiarrhythmic therapy. Within eight months from the first diagnosis of CS, the patient required four hospitalizations, ICD implantation, ventricular tachycardia ablation, and ultimately orthotopic heart transplantation. Histological examination of the explanted heart revealed extensive myocardial fibrosis without residual granulomas or inflammation, consistent with end-stage, burned-out CS—highlighting the irreversibility of myocardial damage once the fibrotic phase has developed. This case illustrates the potentially devastating course of CS despite aggressive immunosuppressive therapy, emphasizing that the overall prognosis of sarcoidosis disease is largely influenced by cardiac manifestation. Indeed, complete metabolic remission based on a serial FDG-PET/CT scan did not prevent progressive functional deterioration—underscoring that irreversible myocardial fibrosis may progress beyond maximal medical therapy, including anti-inflammatory, immunosuppressive and neuro-humoral treatment. Therefore, prompt screening for CS is essential, and once cardiac involvement is suspected and respectively confirmed, the therapy window may become particularly narrow in the case of rapidly progressive CS.
Myocardial infarction with non-obstructive coronary arteries (MINOCA) is a clinically important but heterogeneous syndrome associated with substantial long-term morbidity and adverse cardiovascular outcomes. Pharmacologic management remains largely extrapolated from obstructive coronary artery disease, creating a persistent mismatch between treatment strategies and the diversity of underlying mechanisms. Accurate diagnostic adjudication using cardiac magnetic resonance imaging, intracoronary imaging, coronary functional testing, and mechanistic biomarkers is therefore central to a phenotype-guided therapeutic approach. Inflammation, endothelial dysfunction, oxidative stress, autonomic dysregulation, coronary microvascular dysfunction, plaque-related injury, and adverse ventricular remodeling represent potentially targetable biological domains across selected MINOCA phenotypes. Empagliflozin and colchicine exert overlapping but distinct effects on several of these pathways and have demonstrated cardiovascular benefits in related clinical settings; however, direct evidence in MINOCA remains limited and predominantly observational. This article integrates the available mechanistic and clinical evidence into a comparative, phenotype-linked therapeutic framework and proposes a pragmatic trial strategy incorporating diagnostic adjudication, phenotype enrichment, biomarker-guided stratification, and adaptive or factorial designs. The proposed framework is hypothesis-generating and is intended to inform prospective investigation rather than support off-label prescribing or changes to current clinical practice.
The recent rise of artificial intelligence (AI) has become unstoppable in cardiovascular medicine [...]
