Despite significant goals achieved in diagnosis and treatment in recent decades, coronary artery disease (CAD) remains a high mortality entity and continues to pose substantial challenges to healthcare systems globally. After the latest guidelines, novel data have emerged and have not been yet considered for routine practice. The scope of this review is to go beyond the guidelines, providing insights into the most recent clinical updates in CAD, focusing on non-invasive diagnostic techniques, risk stratification, medical management and interventional therapies in the acute and stable scenarios. Highlighting and synthesizing the latest developments in these areas, this review aims to contribute to the understanding and management of CAD helping healthcare providers worldwide.

Background: The aim of this research is to describe the performance over time of transcatheter aortic valve implantations (TAVIs) in a high-volume center with a contemporary, real-world population. Methods: Patients referred for TAVIs at the University Hospital of Verona were prospectively enrolled. By cumulative sum failures analysis (CUSUM), procedural-control curves for standardized combined endpoints—as defined by the Valve Academic Research Consortium-2 (VARC-2)—were calculated and analyzed over time. Acceptable and unacceptable limits were derived from recent studies on TAVI in intermediate and low-risk patients to fit the higher required standards for current indications. Results: A total of 910 patients were included. Baseline risk scores significantly reduced over time. Complete procedural control was obtained after approximately 125 and 190 cases for device success and early safety standardized combined endpoints, respectively. High risk patients (STS ≥ 8) had poorer outcomes, especially in terms of VARC-2 clinical efficacy, and required a higher case load to maintain in-control and proficient procedures. Clinically relevant single endpoints were all influenced by operator’s experience as well. Conclusions: Quality-control analysis for contemporary TAVI interventions based on standardized endpoints suggests the need for relevant operator’s experience to achieve and maintain optimal clinical results, especially in higher-risk subjects.

Background: During the COVID-19 pandemic, the risk of SARS-CoV-2 infection, the public health measures of social distancing, the freedom limitations, quarantine, and the enforced homeworking under the lockdown period, as well as medical causes including COVID-19 infection per se, may have caused major emotional distress, especially in the most vulnerable patients. We aimed to evaluate the variations in the number of admissions due to Takotsubo syndrome (TTS) during the COVID-19 pandemic in the Veneto region. Methods: We retrospectively reviewed and analyzed the number of admissions because of TTS in 13 Divisions of Cardiology located in the Veneto region, the northeastern area of Italy, covering a population of more than 2.5 million inhabitants, during the two major pandemic waves of COVID-19 (the first between 15 March and 30 April 2020 and the second between 15 November and 30 December 2020) that occurred in 2020. Results: In total, 807 acute coronary syndromes were admitted in the 13 enrolling hospitals. Among these, 3.9% had TTS. Compared to the corresponding 2018 and 2019 time periods, we observed a significant increase in the number of TTS cases (+15.6%, p = 0.03 and +12.5%, p = 0.04, comparing 2018 to 2020 and 2019 to 2020, respectively). Geographical distribution of the TTS cases reflected the broad spread of the SARS-CoV-2 infection with a significant direct relationship between TTS incidence and the number of COVID-19 infections according to Pearson’s correlation (r = 0.798, p < 0.001). Conclusions: The higher incidence of TTS during the 2020 COVID-19 pandemic waves, especially in the areas that were hit hardest in terms of morbidity and mortality by the SARS-CoV-2 infection, suggest a strong direct and/or indirect role of COVID-19 in the pathogenesis of TTS.

Objective. Diffuse idiopathic skeletal hyperostosis (DISH) is a common disorder characterized by ossification of tendons and ligaments. DISH has been largely associated with an increased risk of metabolic syndrome and type 2 diabetes. The objective of the present study is to investigate the role of DISH in the risk of coronary artery disease (CAD). Methods. We conducted an observational cross-sectional study of patients without a history of rheumatic musculoskeletal diseases who underwent coronary angiography between March 2016 and April 2021. The SYNergy between percutaneous coronary intervention with TAXus and cardiac surgery (SYNTAX) score was calculated based on coronary angiography images. DISH diagnosis was based on standard X-ray images and computed tomography scans (Resnick criteria). Demographic and clinical characteristics were retrieved from electronic medical records. Multinomial and binary logistic regression models were employed to determine the association between SYNTAX score (dependent variable) and DISH (independent variable). Results. The study included 187 patients, 82.9% of whom were men, with valid radiological imaging. 83 (44.4%) patients had a confirmed radiological diagnosis of DISH. Diagnosis of DISH was associated with a higher SYNTAX score [adjusted odds ratio (aOR) 34.1, 95% confidence interval (CI) 1.41-79.2 p=0.049], independently from traditional cardiovascular risk factors. In patients aged <70 years, DISH was associated with a 7-fold higher risk of belonging to the highest category of SYNTAX (≥34), compared to non-DISH (aOR 7.23, 95% CI 1.08-48.4; p=0.041). The extension of vertebral calcification was significantly associated with SYNTAX score (r2 0.378, p<0.0001). Conclusions. DISH diagnosis is common in patients at high risk of cardiovascular disease or with definitive CAD. DISH was independently associated with higher CAD complexity.

Background: Artificial intelligence (AI) is increasingly being integrated into cardiovascular medicine, with potential applications across image analysis, procedural planning, risk stratification, decision support, and workflow optimization. However, its adoption in interventional cardiology remains heterogeneous and may be influenced by several factors. We aimed to conduct a nationwide survey to assess attitudes towards AI among Italian interventional cardiologists. Methods: We conducted a nationwide, cross-sectional, web-based survey of Italian interventional cardiologists. A structured questionnaire collected information on professional characteristics, familiarity with and current use of AI, perceived clinical applications, expected benefits, trust, implementation barriers, and training needs. Conditional branching was used to obtain additional details from respondents who reported current use of AI-based tools, while all responses were collected voluntarily and analyzed in anonymized, aggregate form. Categorical variables and Likert-scale responses were summarized using descriptive statistics, with exploratory comparisons performed across prespecified professional and institutional subgroups. Results: Among 129 respondents, 70.5% reported at least moderate familiarity with AI and 77.5% reported some current use, although only 60.5% reported regular or occasional professional use, and applications were concentrated mainly in research, education, and information synthesis rather than direct procedural support. Nearly half (48.1%) expected AI to become standard in many procedures within 5 years, while 69.0% anticipated either routine use or particular value in complex cases. Attitudes were broadly favorable, with 85.3% agreeing that AI could improve diagnostic and procedural precision, 86.8% expressing strong interest in future use, and 76.7% stating that AI should support rather than replace physician judgment. The leading barriers were medico-legal uncertainty (45.0%), poor integration with existing clinical systems (34.9%), and cultural resistance or operator distrust (29.5%), whereas preservation of physician control was the most frequently cited requirement for adoption (58.9%). Greater AI familiarity was independently associated with current AI use (p < 0.001) and good or high trust (p < 0.001). Compared with no prior training, one and multiple AI training experiences were independently associated with good or high familiarity (both p < 0.05). Conclusions: Italian interventional cardiologists showed substantial exposure to AI, strong interest in future adoption, and generally favorable expectations regarding its contribution to diagnostic precision, workflow, and procedural support. Acceptance remained conditional on physician oversight, stronger clinical validation, reliable interoperability, and clear medico-legal governance, and previous AI-focused education appeared independently associated with greater familiarity.