Institute of Cardiology

The study goal was to evaluate the outcomes associated with albumin use in children with sepsis and shock compared with those without shock, using causal inference analysis in a multicenter cohort. This was a secondary analysis of electronic health record data collected from 13 U.S. PICUs between 2012 and 2018, consisting of children younger than 18 years who met Phoenix sepsis criteria within the first 24 hours of PICU admission. Covariate-balancing propensity score weighting was applied to adjust for indication bias in the albumin use. Patients receiving at least 0.5 g/kg albumin within 24 hours of PICU admission were assigned to the albumin group; others to the control. Only 24-hour survivors were included to address immortal time bias. Overall, 17,307 children with sepsis survived at least 24 hours. Of these, 1,344 patients (7.8%) who received albumin within the first 24 hours, and 9,678 (55.9%) met the criteria for septic shock. A significant interaction between albumin use and shock status was observed (interaction: -0.353, p = 0.007), with albumin administration in pediatric septic shock patients associated with lower in-hospital mortality: odds ratio equals to 0.698 (95% CI, 0.629-0.774), risk ratio equals to 0.746 (95% CI, 0.625-0.891), and hazard ratio equals to 0.688 (95% CI, 0.558-0.848). In contrast, there was no difference in outcomes between the albumin and control groups in the non-shock group. Early albumin administration was associated with improved outcomes in children with septic shock, but not in those without shock. These results highlight the importance of considering clinical heterogeneity, such as the presence of shock, in identifying treatment-responsive subgroups and enabling more targeted interventions in pediatric sepsis. Further prospective validation is warranted.

Epicardial adipose tissue (EAT) is a metabolically active fat depot located between the myocardium and visceral pericardium, directly interacting with cardiomyocytes and coronary vasculature. Emerging evidence suggests that EAT plays a significant role in the pathophysiology and prognosis of heart failure (HF) across different left ventricular ejection fraction (LVEF) phenotypes. This review summarizes current data on the prognostic role of EAT in HF, including volume, thickness, and density, measured by echocardiography, computed tomography, and cardiac magnetic resonance imaging. In HF with preserved (HFpEF) and mildly reduced ejection fraction (HFmrEF), increased EAT consistently associates with adverse outcomes, including higher rates of hospitalization and mortality, independent of systemic obesity. In HF with reduced ejection fraction (HFrEF), the relationship is more complex, with studies showing both protective and detrimental associations depending on EAT quantity, density, and spatial distribution. EAT also appears to contribute to ventricular arrhythmogenesis, particularly in patients with preserved myocardial structure. Mechanistically, EAT may promote inflammation, fibrosis, and electrophysiological remodeling, while moderate amount EAT may exert metabolic or mechanical protection. Overall, EAT emerges as a promising imaging-derived biomarker for risk stratification in HF, highlighting the need for phenotype-specific evaluation and potential therapeutic targeting. Future studies should focus on EAT quality, remodeling, and its interaction with myocardial tissue to guide individualized HF management.

The present Reply addresses the commentary by Pagnoni et al. on our recent study exploring explainable artificial intelligence (AI) for mortality risk prediction in pulmonary arterial hypertension (PAH). We acknowledge the importance of several key issues raised by the authors, including endpoint selection, calibration, decision thresholds, and external validation, all of which are central to translating AI-based prognostic models into clinical practice. Our original endpoint, defined as death by the next follow-up visit, was driven by the structure of nationwide registry data and reflects real-world clinical workflows, although we recognize the advantages of predefined time horizons and time-to-event approaches for future analyses. We discuss the trade-off between sensitivity and precision, emphasizing our deliberate prioritization of minimizing false-negative classifications in high-risk patients, while acknowledging the need for structured clinical pathways to manage false-positive results. We further address calibration and threshold selection, underscoring the necessity of additional clinical studies to support intervention-oriented recommendations. The role of phenotypic determinants and modifiable risk factors in enhancing personalization is highlighted as a key direction for future model development. We reaffirm the value of SHAP-based explainability for improving model transparency, while recognizing the need for continued refinement and clinical validation. Finally, we emphasize the strengths and challenges inherent to registry-based analyses, the importance of external validation, and the need for methodologically sound comparisons with established risk calculators. Overall, this exchange underscores the critical role of interdisciplinary collaboration in advancing clinically actionable and interpretable AI solutions for PAH.

Abstract Recurrence scores based on a 21-gene assay are clinically useful for predicting prognosis and chemotherapy benefit in postmenopausal node-positive breast cancer patients, but its performance in premenopausal patients is inconsistent. Here, we evaluated Ataraxis Breast RISK (ATX), an AI test that predicts recurrence risk, and compared it with the genomic assay. ATX identified high risk patients misclassified as low risk by the genomic assay and therefore may refine selection of patients for adjuvant chemotherapy.

Obstructive HCM (oHCM) affects people across all geographic regions, ethnicities, and socioeconomic groups. In the SEQUOIA-HCM trial (NCT05186818), aficamten, an oral selective cardiac myosin inhibitor, improved exercise capacity, left ventricular outflow gradients (LVOT-G), and symptoms in oHCM. It is unknown if dosing, safety, or treatment response may vary by geographic region. Participants were randomized 1:1 to daily aficamten (5-20 mg) or placebo for 24 weeks. Participants were grouped by geographic region (North America, China, and Europe, including Israel). Baseline characteristics and treatment effects on peak oxygen uptake (pVO2) and secondary endpoints were compared across geographic groups. In all, 282 patients were enrolled in 14 countries: 142 (50%) in Europe, including Israel; 94 (33%) in North America; and 46 (16%) in China. Patients had a higher body mass index and older age in Europe (59.7 years) and North America (61.7 years) than in China (51.8 years). More patients were New York Heart Association (NYHA) class II in Europe (81.7%) and China (93.5%) than North America (58.5%). Baseline Kansas City Cardiomyopathy Questionnaire Clinical Summary Score (KCCQ-CSS) was higher in China (82.4) than Europe (73.1) or North America (73.2). The benefit of aficamten on pVO2 was not modified by region (interaction p=0.88) and all secondary endpoints improved with aficamten treatment, acknowledging the analysis was underpowered to detect regional differences. The occurrences of serious adverse events and left ventricular ejection fraction <50% were low and similar by region. In SEQUOIA-HCM, the dosing, safety, and treatment effects of aficamten were consistent across geographic regions despite differences in baseline characteristics of patients with oHCM.