Trajectories of Heart Failure in Structural Heart Disease: Progression, Prediction, and Prevention

Structural heart disease (SHD) sits at the center of modern cardiovascular medicine and includes a wide range of conditions such as valvular disorders, cardiomyopathies, congenital abnormalities, and sequelae of cardiac interventions. Heart failure (HF) remains a major and life-altering complication across these populations, yet its course is often difficult to anticipate. While some patients remain stable for years, others experience gradual decline or abrupt decompensation driven by structural remodeling, comorbidities, and external stressors. Despite advances in diagnostics and therapeutics, clinicians still face a core challenge: identifying who will worsen, how, and when, and using that insight to intervene earlier and tailor care.This Research Topic aims to highlight the dynamic pathways linking SHD to HF progression, with the goal of advancing more precise, predictive, and preventive strategies. We seek contributions that integrate clinical research, advanced imaging, biomarker discovery, digital health, and patient monitoring to better characterize HF trajectories and clinically meaningful phenotypes. By combining mechanistic insights, real-world data, and emerging technologies, this collection aims to support earlier risk recognition, improved timing of interventions, and better long-term outcomes for patients with SHD at risk of HF progression.We welcome original research, reviews, meta-analyses, clinical reports, and translational or methodological studies. Authors are encouraged to address the following themes:• Patterns and predictors of heart failure progression in structural heart disease;• Novel biomarkers and imaging tools for early detection and risk assessment;• Machine learning and big data approaches for personalized prediction models;• Artificial intelligence-driven clinical decision support tools for prediction, phenotyping, and management of heart failure in structural heart diseases;• Integration of digital health, wearables, and remote monitoring for proactive management;• Prevention strategies, including optimization of medical therapies, timing of interventions, and holistic care models;• The influence of comorbid conditions, environmental factors, and social determinants of health on disease trajectory.By bringing together perspectives across disciplines, this Topic aims to strengthen the evidence base for predicting HF progression in SHD and to accelerate translation into practical, patient-centered care. Topic editors: Aryan Ayati, Alireza Hadizadeh, Mohammad Keykhaei Source: https://www.frontiersin.org/research-topics/77591/trajectories-of-heart-failure-in-structural-heart-disease-progression-prediction-and-prevention