News & Events Archives - CVIA Journal

Left Bundle Branch Area Pacing: A Promising Strategy to Mitigate Pacing-Induced Cardiomyopathy

Announcing a new article publication for Cardiovascular Innovations and Applications journal. This editorial examines the growing clinical interest in Left Bundle Branch Area Pacing (LBBAP) as a more physiological alternative to conventional right ventricular pacing for patients requiring long-term cardiac pacing. As evidence continues to emerge linking chronic right ventricular pacing with pacing-induced cardiomyopathy and heart failure, the authors review the mechanisms underlying these complications and explore how LBBAP may help preserve ventricular synchrony, maintain cardiac function, and improve clinical outcomes.

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Statistical Methods for Longitudinal Cardiovascular Disease Research Design: A Narrative Review

Announcing a new article publication for Cardiovascular Innovations and Applications journal. Cardiovascular disease develops through gradual accumulation of risk factors and progressive vascular damage. Longitudinal studies are well suited to determine when and how these changes occur, but they introduce several analytic challenges, including repeated measurements on the same individuals, irregular or sparse follow-up schedules, missing data, and non-linear trajectories.

The authors of this article conducted a narrative, application-focused review categorizing methods into five major classes: traditional or marginal models, mixed-effect models, joint models, trajectory and mixture models, and functional or machine-learning approaches. For each class, we provide intuitive descriptions, typical cardiovascular applications, and a balanced discussion of assumptions, strengths, limitations, and recommended sensitivity analyses.

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Association Between Weight Change and the Risk of Atrial Fibrillation: Results from the Kailuan Cohort Study in China

Announcing a new article publication for Cardiovascular Innovations and Applications journal. The long-term effects of sustained weight gain and loss on atrial fibrillation (AF) risk remain unclear. The authors of this article examined associations between long-term weight change and incident AF.

64,119 AF-free participants from the Kailuan cohort whose height and weight were measured in 2006–2007 and 2010–2011 were examined. Weight change was assessed as changes in body mass index (BMI), body weight, and percentage weight changes. Incident AF was ascertained according to International Classification of Diseases codes and biennial electrocardiograms. Multivariable Cox models estimated hazard ratios (HRs) and 95% confidence intervals (CIs).

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Reimagining Heart Failure Care: The Essential Role of Early Palliative Integration

Announcing a new article publication for Cardiovascular Innovations and Applications journal. Thie editorial highlights the growing evidence that type 2 inflammation may represent an important biological link between asthma and cardiovascular disease. The article examines how chronic inflammatory pathways driven by type 2 immune responses can contribute not only to respiratory symptoms but also to vascular dysfunction, atherosclerosis, and adverse cardiovascular outcomes. By exploring shared mechanisms across these conditions, the authors emphasize the need for a more integrated approach to patient care and suggest that targeting type 2 inflammation could offer new opportunities to improve outcomes for patients with both asthma and cardiovascular disease.

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The Impact of Sedentary Behavior on Stroke Prognosis: A Systematic Review and Meta-Analysis of Observational Studies

Announcing a new article publication for Cardiovascular Innovations and Applications journal. The article highlights Stroke survivors often experience physical dysfunction, fatigue, and cognitive impairment, and may also spend prolonged periods engaged in sedentary behavior because of daily living demands. However, the specific effects of sedentary behavior on stroke prognosis remain unclear.A comprehensive search of PubMed, Embase, the Cochrane Library, and Web of Science, covering all records from database inception to March 2026, was conducted through both computer-based and manual methods.

A random-effects model was applied for the meta-analysis. (more…)

Asprosin in Cardiovascular Disease: Mechanistic Insights, Context-Dependent Effects, and Translational Perspectives

Announcing a new article publication for Cardiovascular Innovations and Applications journal highlighting the asprosin biology in the cardiovascular system. The study investigates molecular signaling pathways and tissue‑specific effects, moving beyond a disease‑centered descriptive framework, carefully differentiating exploratory hypotheses from validated conclusions, thereby strengthening the foundation for precision cardiovascular research and therapeutic innovation.

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Performance Comparison of Machine Learning Classifiers and Cardio-Sense Ensemble for Heart Disease Detection

Announcing a new article publication for Cardiovascular Innovations and Applications journal. Heart disease remains a leading cause of global mortality; consequently, accurate, reliable, and interpretable predictive models are needed for early diagnosis. This study was aimed at developing a robust hybrid ensemble learning framework that improves heart disease predictive accuracy while preserving clinical interpretability.

The Cardio-Sense Ensemble Framework (CSEF) for heart disease prediction was developed by using the publicly available Behavioral Risk Factor Surveillance System dataset. Laplacian binary optimization was used for optimized feature selection, to eliminate redundancy and enhance discriminative information. The refined feature set was used to train multiple baseline classifiers, including logistic regression, random forest, (more…)

Small Molecules to Treat Cardiovascular Disease: Cardiac Myosin Inhibitors

Announcing a new article publication for Cardiovascular Innovations and Applications journal. A new study demonstrates that a multimodal large language model (LLM) can accurately support preoperative planning for transcatheter aortic valve replacement (TAVR). By integrating CT imaging and clinical data, the system automatically generates structured surgical plans, including valve selection, access strategy, and risk alerts. Tested across 950 patients, the model showed high agreement with expert heart teams while reducing planning time by over 90%. The findings highlight the potential of LLM-driven tools to improve efficiency and decision-making in complex cardiac procedures. (more…)

LLM-Based Multimodal Planning for TAVR: Independent Validation, Calibration, and Efficiency Gains

Announcing a new article publication for Cardiovascular Innovations and Applications journal. A new study demonstrates that a multimodal large language model (LLM) can accurately support preoperative planning for transcatheter aortic valve replacement (TAVR). By integrating CT imaging and clinical data, the system automatically generates structured surgical plans, including valve selection, access strategy, and risk alerts. Tested across 950 patients, the model showed high agreement with expert heart teams while reducing planning time by over 90%. The findings highlight the potential of LLM-driven tools to improve efficiency and decision-making in complex cardiac procedures. (more…)

Experience in Providing Emergency Care for Myocardial Infarction in Armenia

Announcing a new article publication for Cardiovascular Innovations and Applications journal. The article highlights Armenia’s significant progress in strengthening its cardiology care system, including nationwide access to primary percutaneous coronary intervention (pPCI) and a state-funded program that has treated approximately 23,000 patients since 2015 while reducing in-hospital STEMI mortality to as low as 2–3%. The editorial provides a comprehensive overview of the country’s diagnostic capacity, infrastructure, and evolving national initiatives, including the expansion of free revascularization to all myocardial infarction patients and the introduction of a national registry (ARMI) to support data-driven improvements. While noting ongoing challenges such as regional disparities in access, pre-hospital delays, and the need for enhanced rehabilitation and prevention strategies, the authors emphasize (more…)

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