Heart failure (HF) represents a major burden on healthcare systems globally, driven by high rates of hospitalizations and readmissions, as well as prolonged length of stay (LOS). To address this, a wide range of innovative strategies have emerged and evolved in recent years. These approaches span a broad spectrum, ranging from novel routes of medication administration to digital health technologies such as telemonitoring, wearable devices, as well as implantable devices. Given the rapid expansion of available innovations, it can be challenging for clinicians to remain fully up to date with emerging tools and evidence. At the 2026 ESC Heart Failure Congress in Barcelona, Spain, global experts in the field highlighted different technologies and the key clinical trials supporting them. This review aims to synthesize the most recent innovative strategies aimed at reducing HF hospitalizations (HFH), as presented during the congress.

Non-ischemic or dilated cardiomyopathy (DCM) is characterized by abnormal enlargement of the left ventricle, compromising the ability of the heart to pump blood to the body. All patients with DCM are offered the same treatment regimen regardless of individual differences, with highly variable results on disease progression. Some patients fully recover cardiac function, while others continue to deteriorate, requiring heart replacement therapy or palliation. Incomplete molecular knowledge of dilated cardiomyopathy pathophysiology poses challenges for discovery of new therapeutic agents. To address this, we use induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) to assess individual molecular signalling and functional signatures in patients with DCM. Using blood samples from two healthy controls and two patients with DCM, we generated and validated iPSC lines, then differentiated them into cardiomyocytes. Cellular signalling was assessed in each iPSC-CM line after treatment with several disease-relevant G protein-coupled receptor (GPCR)-targeting ligands, measured using nuclear and cytosolic PKA and ERK biosensors at single cell resolution. Differences in functional properties such as calcium handling, contractility, and electrophysiology revealed additional features altered in patients with DCM. We have now established a pipeline to uncover patient-specific molecular mechanisms and disease phenotypes as a pathway to the development of personalized treatment for DCM. One Sentence Summary : Building a pipeline for bench-to-bedside study of DCM

Heart failure with nonreduced ejection fraction (HFnrEF), defined as signs and symptoms of heart failure (HF) with a left ventricular ejection fraction (LVEF) of > 40%, continues to increase in prevalence with significant effects to patients, their care givers, and the health care system broadly. Historically, this population has been divided into HF with mildly reduced (HFmrEF) or HF with preserved ejection fraction (HFpEF). However, contemporary evidence indicates that patients across the spectrum of LVEF > 40% experience similar clinical outcomes and, importantly, respond consistently to several key pharmacotherapies. Adoption of the term HFnrEF provides a practical and unified framework for clinical decision-making, reducing ambiguity and promoting consistent application of evidence-based therapies. To support clinicians in translating evidence into practice, the Canadian Cardiovascular Society (CCS) and the Canadian Heart Failure Society (CHFS) present this guideline, which is focused on pharmacological management of symptomatic heart failure with nonreduced ejection fraction (HFnrEF). Underpinned by Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology and meta-analyses, outcomes of interest include pharmacotherapies shown to reduce the risk of HF hospitalization (HFH) and improve patient well-being in this population. The guideline offers concise recommendations for 4 key classes of pharmacological therapies: sodium-glucose cotransporter-2 inhibitors (SGLT2i), mineralocorticoid receptor antagonists (MRAs), angiotensin receptor-neprilysin inhibitors (ARNIs), and evidence-based drugs with glucagon-like peptide-1 (GLP-1) receptor agonist activity. Recommendations are complemented by practical tips to guide the initiation, titration, and maintenance of these foundational treatments. By emphasizing therapeutic consistency across the > 40% LVEF spectrum, this guideline aims to streamline care pathways and enhance the delivery of guideline-directed medical therapy for patients with symptomatic HFnrEF in real-world settings.

BACKGROUND:In a recent multicenter Canadian study in heart failure (HF), model predictions proved more accurate than physicians. OBJECTIVES:Simulating clinical practice, the authors evaluated the predictive value of combining model predictions with physician estimated 1-year mortality in HF outpatients. METHODS:This post hoc analysis of a Canadian multicenter cohort study included HF outpatients (left ventricular ejection fraction ≤40%). HF cardiologists and family doctors estimated patient 1-year mortality using clinical judgment. The Seattle HF Model (SHFM) predicted mortality. All patients were followed for 1 year to collect mortality. Stratified by specialty, we compared the performance of SHFM and physician estimates alone, with a model integrating physician and SHFM predictions using a random forest survival model, evaluating discrimination (C-statistic), calibration (observed vs predicted event rate), risk reclassification, and clinical net benefit. RESULTS:In 1,643 HF patients, 1-year mortality was 9% (95% CI: 8%-11%). The SHFM had adequate discrimination (C-statistic 0.76; 95% CI: 0.72-0.80) and excellent calibration. Physicians showed adequate discrimination (0.75; 95% CI: 0.71-0.79 for cardiologists; 0.72; 95% CI: 0.66-0.78 for family doctors) and poor calibration with significant risk overestimation. Integrating SHFM and physician predictions, discrimination significantly improved (0.82; 95% CI: 0.78-0.86 for cardiologists; 0.87; 95% CI: 0.83-0.91 for family doctors) with excellent calibration. By risk reclassification, among patients without events, the integrated model better risk-classified 71% (95% CI: 70%-72%) vs cardiologists and 60% (95% CI: 58%-61%) vs family doctors; among patients with events, the model misclassified 45% (95% CI: 58%-63%) vs cardiologists and 11% (95% CI: 25% to 3%) vs family doctors. The integrated model led to higher clinical benefit. CONCLUSIONS:Integrating SHFM predictions with physician judgment improved accuracy. Model-informed assessment provides prognostic accuracy for clinical decision-making. (Predicted Prognosis in Heart Failure Intuition; NCT04009798).

This case report describes a complex presentation of dilated cardiomyopathy (DCM) in a 14-year-old boy of Indian origin, initially presenting with nonspecific abdominal pain, who was eventually found to have severe biventricular dilatation and a rare genetic mutation in PLEKHM2, associated with increased trabeculations and DCM. His condition rapidly progressed to critical cardiogenic shock, necessitating advanced heart failure therapies. This case emphasizes the importance of considering DCM in pediatric patients with atypical presentations and underscores the utility of genetic testing in identifying rare pathologic conditions. It also highlights the challenges and successful management strategies in a pediatric patient treated within an adult health care setting, demonstrating the vital role of tailored multidisciplinary approaches in managing complex cardiomyopathies. The findings contribute to the limited literature on PLEKHM2-associated cardiomyopathy.

Chronic Obstructive Pulmonary Disease (COPD) and Heart failure (HF) are often concomitant, they are overlooked in practice. The objectives of this study were to determine the prevalence of HF in diagnosed COPD and COPD in diagnosed HF from a specialized clinics and determine patients’ characteristics which could be used to in clinical practice for active screening.We conducted a prospective cohort study in a specialized COPD clinic and HF clinic. Patients underwent detailed cardiopulmonary evaluation to establish diagnosis and were followed for 12 months.The prevalence of unrecognized COPD and HF were respectively 26.1% and 26.8%, and these patients were older, more likely to be male and heavy smokers. COPD patients with abnormal vs those with normal echocardiography had an increased rate of mod-severe exacerbation like events (1.3 vs 0.6). They also had a higher prevalence of self- reported heart disease, diabetes, abnormal ECG, cardiovascular medication use, higher blood eosinophil and troponin but no difference on lung function, computed tomography-assessed emphysema and gas trapping, symptom burden and health status.HF patients with abnormal vs those with normal spirometry had increased exacerbation like-events (16.7% vs 6.3% but reach statistical significance). They also had more heart disease, worse lung function by definition and gas trapping, higher blood eosinophil but no difference in symptom burden and health status.In two specialized clinics the prevalence of concomitant disease -undiagnosed HF in COPD patients and undiagnosed COPD in HF patients was common. Distinctive features were limited to clinical characteristics, but specific biomarkers cannot be recommended.

Background:Excluding spontaneous coronary artery dissection (SCAD) as an aetiology of acute coronary syndrome in young adults is imperative.Case summary:A previously healthy 39-year-old woman experienced sudden severe chest pain, ST-segment elevation on electrocardiogram, necessitating high-dose aspirin and urgent transfer to a revascularization centre. Suffering ventricular tachycardia (VT) and ventricular fibrillation (VF), she underwent two rounds of advanced life support and venoarterial extracorporeal membrane oxygenation. Diagnosed with left main coronary artery (LMCA) SCAD, she was initially started on conservative therapy for declining left ventricular ejection fraction. However, she continued to experience an escalating anginal symptoms, worsening biomarkers, and LMCA SCAD progression, which urged the need for surgical intervention with coronary artery bypass graft surgery (CABG). Following her CABG, she experienced a worsening of her functional mitral regurgitating, which she underwent transcatheter edge-to-edge repair of her severe mitral regurgitation. Despite being listed for orthotopic heart transplantation (OHTx), her low body mass index and elevated antibodies necessitated the HeartMate III left ventricular assist device (LVAD) for bridge to transplant. After treating frequent VT episodes with medications, she eventually received a LVAD as a bridge to cardiac transplantation. Within 1 year of her receiving LVAD, she underwent a successful OHTx.Discussion:The pathogenesis of SCAD involves intramural haematoma formation through intimal tears or vasa vasorum haemorrhage. Adverse outcomes that could occur in SCAD patients include cardiac arrest, cardiogenic shock, reduced left ventricle systolic function, and occasionally serious cardiac arrhythmia-such as VF-which can lead to sudden cardiac death. Although most SCAD cases heal spontaneously, revascularization can be considered in case of worsening SCAD progression. Advanced therapeutic intervention including mechanical circulatory support and OHTx should be considered in refractory cases.

Purpose: In recent analyses from a multicenter heart failure (HF) cohort, model predictions proved significantly more accurate than HF cardiologists who significantly overestimated mortality. In this study, simulating practice, by combining model and physician estimates we evaluated the incremental value of model predictions to refine physician estimated 1-year mortality.

Background: In recent studies from a multicenter Canadian cohort of outpatients with heart failure (HF), we found that model predictions were significantly more accurate than HF cardiologists. In this study, trying to mimic practice, we evaluated the additional predictive value and clinical impact of model predictions to refine physician estimated risk of 1-year mortality by combining model and physician estimates. Methods: We included consented consecutive HF outpatients (LVEF <40%) followed at 11 HF clinics in Canada. HF cardiologists estimated patient 1-year mortality using their clinical judgment. We calculated model predicted mortality using the Seattle HF Model (SHFM). We followed patients for at least a year to record mortality (or urgent heart transplant or ventricular assist device implant as mortality-equivalent events). Using random forest survival model and cross-validation, we compared the performance SHFM and the HF cardiologist alone, and the integrated HF cardiologist and the SHFM predictions by evaluating model discrimination (c-statistic), calibration (observed vs predicted event rate), risk reclassification and clinical net benefit analyses. Results: Among 1,643 HF patients, 1-year event rate was 9% (95%CI 8%-11%). The SHFM had the adequate discrimination (c-statistic 0.76) and excellent calibration while cardiologists showed adequate discrimination (c-statistic 0.75) and poor calibration with significant risk overestimation ( Figure 1 ). When the SHFM estimates were added physician predictions, discrimination significantly improved (0.82, 95%CI 0.78-0.86) with excellent calibration. By risk reclassification analysis, among patients with events, HF cardiologist better reclassified 44% than the SHFM or the integrated model. Among patients without event, however, HF cardiologists worse risk-classified 52% in comparison to SHFM and 71% to the integrated model. By net clinical benefit analysis ( Figure 2 ), when the decision to treat involves patients with 1-year mortality of >5%, SHFM predictions would lead to higher benefit than guiding care by physician judgement. Integrating model and HF cardiologist predictions led to minimally increased benefit in comparison to SHFM alone. Conclusions: Integrating prediction from the SHFM to physician judgment or using the SHFM alone showed superior accuracy than HF cardiologist predictions, proving that model-informed care may provide more accurate prognostic information to tailor clinical decision making.

During a heart attack, ischemia causes losses of billions of cells; this is especially concerning given the minimal regenerative capability of cardiomyocytes (CMs). Heart remuscularization utilizing stem cells has improved cardiac outcomes despite little cell engraftment, thereby shifting focus to cell-free therapies. Consequently, we chose induced pluripotent stem cells (iPSCs) given their pluripotent nature, efficacy in previous studies, and easy obtainability from minimally invasive techniques. Nonetheless, using iPSC secretome-based therapies for treating injured CMs in a clinical setting is ill-understood. We hypothesized that the iPSC secretome, regardless of donor health, would improve cardiovascular outcomes in the CM model of ischemia–reperfusion (IR) injury. Episomal-generated iPSCs from healthy and dilated cardiomyopathy (DCM) donors, passaged 6–10 times, underwent 24 h incubation in serum-free media. Protein content of the secretome was analyzed by mass spectroscopy and used to treat AC16 immortalized CMs during 5 h reperfusion following 24 h of hypoxia. IPSC-derived secretome content, independent of donor health status, had elevated expression of proteins involved in cell survival pathways. In IR conditions, iPSC-derived secretome increased cell survival as measured by metabolic activity (p < 0.05), cell viability (p < 0.001), and maladaptive cellular remodelling (p = 0.052). Healthy donor-derived secretome contained increased expression of proteins related to calcium contractility compared to DCM donors. Congruently, only healthy donor-derived secretomes improved CM intracellular calcium concentrations (p < 0.01). Heretofore, secretome studies mainly investigated differences relating to cell type rather than donor health. Our work suggests that healthy donors provide more efficacious iPSC-derived secretome compared to DCM donors in the context of IR injury in human CMs. These findings illustrate that the regenerative potential of the iPSC secretome varies due to donor-specific differences.

BACKGROUND:A recent study showed that the accuracy of heart failure (HF) cardiologists and family doctors to predict mortality in outpatients with HF proved suboptimal, performing less well than models. OBJECTIVES:The authors sought to evaluate patient and physician factors associated with physician accuracy. METHODS:The authors included outpatients with HF from 11 HF clinics. Family doctors and HF cardiologists estimated patient 1-year mortality. They calculated predicted mortality using the Seattle HF Model and followed patients for 1 year to record mortality (or urgent heart transplant or ventricular assist device implant as mortality-equivalent events). Using multivariable logistic regression, the authors evaluated associations among physician experience and confidence in estimates, duration of patient-physician relationship, patient-physician sex concordance, patient race, and predicted risk, with concordant results between physician and model predictions. RESULTS:Among 1,643 patients, 1-year event rate was 10% (95% CI: 8%-12%). One-half of the estimates showed discrepant results between model and physician predictions, mainly owing to physician risk overestimation. Discrepancies were more frequent with increasing patient risk from 38% in low-risk to ∼75% in high-risk patients. When making predictions on male patients, female HF cardiologists were 26% more likely to have discrepant predictions (OR: 0.74; 95% CI: 0.58-0.94). HF cardiologist estimates in Black patients were 33% more likely to be discrepant (OR: 0.67; 95% CI: 0.45-0.99). Low confidence in predictions was associated with discrepancy. Analyses restricted to high-confidence estimates showed inferior calibration to the model, with risk overestimation across risk groups. CONCLUSIONS:Discrepant physician and model predictions were more frequent in cases with perceived increased risk. Model predictions outperform physicians even when they are confident in their predictions. (Predicted Prognosis in Heart Failure [INTUITION]; NCT04009798).

Mobile health (mHealth) fitness applications are increasingly being used for research and physical activity promotion; however, which features facilitate and impede routine engagement, a known predictor of application retention, are not well understood. To understand facilitators and barriers in the use of mobile applications relating to physical activity promotion. We distributed a pan-Canadian online questionnaire via the behavioral research platform Prolific.co to evaluate what features associated with the use and routine engagement (i.e., daily, or weekly use) of mHealth fitness applications, and attitudes about data sharing. Binary logistic regression was used to quantify the association between these endpoints and exploratory factors such as the perceived utility of various mHealth application features. The survey received 694 responses. Most people were women (62%), the median age was 28 (range: 18–78), and most people reported current use of an mHealth fitness application (48%). The perceived importance of personal health (OR 2.40; 95%·CI 1.34–4.50) was the factor most associated with the current use of an mHealth fitness application. The feature most associated with routine engagement was the ability to track progress toward a goal (OR 5.10, 95%·CI 2.73–9.61) while the most significant barrier was the absence of goal customization features (OR 0.44, 95%·CI 0.25–0.81). The acceptance of sharing health data for research was high (56%) and privacy concerns did not significantly affect routine engagement (OR 0.81, 95%·CI 0.40–1.77). Results were consistent across race and gender. Our results demonstrate that mHealth applications have the potential to be scaled across populations. Optimizing applications to improve self-monitoring and personalization could increase routine engagement and thus user retention and intervention effectiveness.

Synchronized contractions of cardiomyocytes within the heart are tightly coupled to electrical stimulation known as excitation-contraction coupling. Calcium plays a key role in this process and dysregulated calcium handling can significantly impair cardiac function and lead to the development of cardiomyopathies and heart failure. Here, we describe a method and analytical technique to study myofilament-localized calcium signaling using the intensity-based fluorescent biosensor, RGECO-TnT. Dilated cardiomyopathy is a heart muscle disease that negatively impacts the heart’s contractile function following dilatation of the left ventricle. We demonstrate how this biosensor can be used to characterize 2D hiPSC-CMs monolayers generated from a healthy control subject compared to two patients diagnosed with dilated cardiomyopathy. Lastly, we provide a step-by-step guide for single-cell data analysis and describe a custom Transient Analysis application, specifically designed to quantify features of calcium transients. All in all, we explain how this analytical approach can be applied to phenotype hiPSC-CM behaviours and stratify patient responses to identify perturbations in calcium signaling.