Ischemic heart disease (IHD) and cerebrovascular disease (CVD) are two of the leading causes of morbidity and mortality worldwide. Both conditions are closely related, as they share common risk factors and pathophysiological mechanisms. The clinical overlap between IHD and CVD has been elucidated in the “Heart Brains and Vessels” Meeting held in June 2024 in Aosta (Italy). In this document, the authors underline the risk of cardioembolic stroke in heart disease, the updated therapy for treating strokes, and the prevention of embolization. Finally, the authors emphasize the importance of establishing Heart and Brain Teams utilizing multidisciplinary approach to treating these diseases, at least in the medical hub centers.

The notion of a “July effect,” suggesting that the influx of new residents in teaching hospitals every July (JU) may adversely affect patient care and outcomes, remains debatable. This study evaluated the impact of resident turnover in JU on patients admitted for congestive heart failure (CHF) and concomitant sepsis. This retrospective cohort study utilized data from the 2016 to 2020 National Inpatient Sample. Patients with CHF and concomitant sepsis hospitalized at teaching hospitals, as determined by International Classification of Diseases, 10^th Revision (ICD-10) codes, were included. Univariate and multivariate logistic regression analyses were performed to estimate in-hospital mortality and secondary outcomes after adjustment for confounders, including cardiac arrest (CA), cardiogenic shock, non-ST segment elevation myocardial infarction, respiratory failure (RF), use of cardiac and respiratory devices, and healthcare resource utilization metrics such as length of stay (LOS) and total hospitalization charges (TOTCHG). Patients were classified according to the month of admission as JU or other months (OM) to investigate the potential impact of the “July effect” on patient outcomes. The study included 281,874 patients, of which 8% were in the JU group and 92% in the OM group. The mean age was 71 ± 13 years, with a slight male predominance (52% vs 48%), and most patients were White (70%). A total of 34,974 in-hospital deaths occurred, with no significant difference between the JU and OM groups (odds ratio [OR] = 0.95; 95% confidence interval [CI] = 0.85-1.06; p=0.329). Similarly, no significant differences were observed in CA (OR = 0.88; 95% CI = 0.70-1.11; p=0.282), RF (OR = 0.98; 95% CI = 0.90-1.06; p=0.597), ventilator use (OR = 0.99; 95% CI = 0.77-1.25; p=0.879), LOS (11.3 vs. 11.3), and TOTCHG (USD 136,377 vs. USD 136,181). However, lower rates of acute kidney injury were observed in the JU group compared with the OM group (OR 0.90; 95% CI, 0.84-0.98, p=0.011). This study demonstrates that the “July effect” does not significantly influence in-hospital outcomes in patients with CHF and concomitant sepsis. While mortality and major clinical outcomes were comparable across groups, lower rates of acute kidney injury were observed in patients admitted in JU. Further research is needed to understand the complex interplay between healthcare resident turnover and patient outcomes.

Takotsubo syndrome (TTS), also known as broken heart syndrome, is an acute cardiac condition with a poorly understood pathophysiology due to its relative rarity. Once considered benign, it is now recognized as a serious disorder with severe complications and a mortality rate comparable to or exceeding that of acute coronary syndrome. This narrative review aims to summarize current knowledge on the prognostic factors associated with TTS, with a particular focus on its relationship with diabetes mellitus (DM). A thorough analysis of 57 relevant studies, selected from over 98,000 articles retrieved from PubMed and Google Scholar, was conducted based on strict inclusion criteria. The findings indicate that advanced age, female sex, pre-existing cardiovascular diseases, and systemic disorders significantly influence the prognosis and mortality of patients with the syndrome. DM plays a paradoxical role, being associated with increased long-term mortality risk while potentially providing a protective effect during the acute phase of the syndrome, possibly by modulating stress responses involved in its onset. Therefore, a deeper understanding of the prognostic implications of TTS and its interaction with diabetes is crucial for developing appropriate risk stratification tools and improving clinical management of patients.

Atherosclerosis-related diseases such as acute ischemic stroke (AIS), acute myocardial infarction, and chronic kidney disease remain major global health burdens, yet the potential role of autoantibodies in these conditions has only recently begun to be recognized. This review summarizes the methodology and characteristics of atherosclerosis autoantibody biomarkers reported in our previous studies. In our earlier research, we performed a large-scale screening of serum autoantibody markers for atherosclerotic diseases, such as AIS, using expression cloning and protein array methods, and identified 106 antibodies. Among these, 34 markers were selected as potentially useful diagnostic markers, with serum antibody levels found to be higher in patients with atherosclerosis-related diseases than in healthy donors. The autoantibody markers were highly sensitive, with elevated levels observed not only in patients with AIS but also in those with transient ischemic attack, a prodromal stage of AIS. Thus, the autoantibodies may serve as predictive markers for AIS. The potential use of autoantibodies as targets for prevention and/or treatment is also discussed in this review.

Left atrial appendage (LAA) occlusion (LAAO) prevents thromboembolic stroke in patients with atrial fibrillation, particularly those unsuitable for long-term anticoagulation therapy. However, complex and variable LAA morphology challenges LAAO, including device selection and post-procedural device-related thrombosis. To address these issues, in silico/virtual optimization via computational modeling and simulation has been utilized to improve pre-procedural planning, device design, thrombosis prediction, and optimization for LAAO. This review examines the evolving landscape of LAAO, with a focus on computer modeling and simulation. We assess the capabilities, key limitations, and future potential of these computational tools through literature evaluation. These tools demonstrate clinical translatability but face limitations in simulating dynamic physiological interactions. Their broader adoption will drive personalized LAAO strategies, reduce procedural complications, and inform future research aimed at bridging the gap between virtual optimization and real-world clinical outcomes.

Ischemic stroke remains a major contributor to population-level health loss, yet contemporary patterns vary widely across locations and over time. Hence, evidence integrating mortality and disability, and benchmarking prevention potential, is still needed. We characterized the ischemic stroke burden using the Global Burden of Disease 2021 estimates for 1990-2021, reporting prevalence, incidence, and disability-adjusted life years (DALYs) per 100,000 persons. The share of DALYs associated with individual risk factors was derived as population-attributable fractions. For 2021, per 100,000 persons, the global age-standardized prevalence, incidence, and DALY rates for ischemic stroke were 819.5 (95% uncertainty interval [UI]: 760.3-878.7), 92.4 (95% UI: 79.8-105.8), and 837.4 (95% UI: 763.7-905.0). From 1990 to 2021, the prevalence decreased by 3.5% (95% UI: −5.1% to −2.1%), incidence decreased by 15.8% (95% UI: −18.8% to −13.3%), and DALYs decreased by 34.9% (95% UI: −39.5% to −30.0%). Patterns differed substantially across sexes, sociodemographic index (SDI), and geographies. DALY rate attribution was dominated by systolic blood pressure (58.38%), followed by low-density lipoprotein cholesterol (29.82%) and fasting plasma glucose (17.58%). Ischemic stroke incidence shifted from high-SDI regions to middle- and low-SDI regions from 1990 to 2021. Despite declining age-standardized rates, absolute numbers increased due to population growth, aging, and improved screening capabilities.