Heart failure (HF) in older adults emerges from the interplay between biological aging and the totality of environmental and behavioural exposures conceptualized as the exposome. Traditional cardiovascular risk factors and intrinsic cardiac pathology only partially explain HF burden, as chronic exposures to air pollution, traffic noise, temperature extremes, toxic metals and chemicals, artificial light at night, and adverse social environments, along with low greenness and walkability, substantially influence HF incidence, decompensations, and prognosis in older patients with multiple comorbidities. Recently, epidemiological studies have associated many of the exposomic factors with HF incidence and morbidity. Age‑related impairments of the myocardium and vasculature make them particularly vulnerable to external stressors. Mechanistically, aging, HF, and environmental factors converge on shared pathways including, oxidative stress and mitochondrial dysfunction, inflammaging, impaired autophagy and proteostasis, genomic and epigenetic alterations, cellular senescence, dysregulated neurohormonal and circadian signalling, and fibrosis with maladaptive remodelling. Through these mechanisms exposome chronically accelerates cardiovascular aging and lowers the threshold for HF onset and progression. This review considers a shift from an organ‑centred view of HF in older adults to a systems‑level, life‑course perspective that explicitly incorporates exposomic determinants, and argues that reducing harmful exposures while promoting green space, physical activity, walkability, and healthy dietary patterns should be integral to HF prevention and management strategies in aging societies.
Implanted pulmonary artery pressure (PAP) monitoring provides an early window on imminent worsening heart failure (HF). Randomized trials demonstrated that PAP-guided management significantly reduces HF hospitalizations, but substantial residual risk persists despite recent major advances in HF pharmacotherapy. We review lessons from PAP-guided remote patient management and examine how artificial intelligence (AI) could support more individualized eligibility assessment and multimodal longitudinal surveillance within a patient-centered adaptive care cycle to further improve clinical outcomes. HF is increasingly recognized as a systemic disease characterized, across HF phenotypes, by multiple cardiac and non-cardiac comorbidities. CHAMPION, GUIDE-HF, and MONITOR-HF did not systematically incorporate comorbidity-related risk into patient selection, while PAP-guided treatment focused predominantly on diuretic adjustment, and monitoring strategies were not adapted to individual disease trajectories. AI could help integrate multidimensional phenotyping to estimate individual risk and expected benefit pre-implant, use comprehensive longitudinal monitoring data to support personalized, actionable clinical decision-making, and enable dynamic adaptation of monitoring intensity tailored to the disease trajectory. This may improve clinical outcomes, reduce healthcare professional workload, enhance patient experience and treatment adherence, and increase cost-effectiveness.
Heart transplantation is the definitive treatment for end-stage heart failure. While the number of heart transplant performed yearly in the United States has nearly doubled in the last decade, median survival has stagnated, largely due to the complications posed by lifelong immunosuppression. A shift towards precision medicine is needed to achieve the optimal balance between risk of allograft rejection and drug-related toxicities to improve post-transplant outcomes. Novel molecular based diagnostic tools and biomarkers are being investigated, and hold promise in evaluating graft health and assessing immune state. The use of circulating biomarkers and molecular diagnostics such as human and viral cell-free DNA, tissue-based gene expression profiling, and circulating microRNAs, will allow for more comprehensive assessment of post-transplant immune activity and rejection risk to personalize patient care.
This review aims to examine the role of clonal hematopoiesis of indeterminate potential (CHIP) in the pathophysiology of heart failure with preserved ejection fraction (HFpEF), focusing on its contribution to inflammation, disease development, and clinical implications. Recent studies demonstrate that CHIP is enriched in HFpEF populations and is associated with increased disease risk and worse clinical outcomes. Mechanistically, CHIP promotes inflammatory signaling through activation of pathways such as the NLRP3 inflammasome and IL-1β/IL-6 axis. TET2 mutations, in particular, have been consistently linked to diastolic dysfunction and adverse remodeling, especially in patients with high inflammatory burden and cardiometabolic comorbidities. CHIP represents a novel link between ageing, inflammation, and HFpEF, contributing to disease heterogeneity and progression. It may serve as a biomarker for early detection, risk stratification, and patient phenotyping, while also offering potential therapeutic targets. Future research should focus on validating these findings and integrating CHIP into precision medicine approaches for HFpEF.
Heart failure (HF) is characterised by recurrent decompensation leading to worsening of symptoms and unplanned hospitalisations. Patients often experience poor post-hospitalisation recovery, fail to maintain functional capacity, and demonstrate a high risk for re-admission. In this review we discuss these challenges, and explore how non-invasive, digital solutions may improve health outcomes. In contrast to current episodic surveillance, advances in wearable sensor technologies enable continuous, non-invasive monitoring to facilitate physiology-guided management to improve early clinical stabilisation. Additionally, trials have highlighted the potential of exercise-based cardiac rehabilitation to improve functional capacity in HF patients. Finally, continuous monitoring of relevant physiological signals, through developing algorithms, have the potential for early prediction of clinical deterioration. Non-invasive, co-created digital solutions may facilitate early stabilisation, improve functional capacity and predict clinical deterioration following episodes of decompensation. Collectively, they may enhance clinical outcomes and quality of life in patients with HF.
