Heart failure (HF) is a major health care burden increasing in prevalence over time. Effective, evidence-based interventions for HF prevention and management are needed to improve patient longevity, symptom control, and quality of life. Dietary Approaches to Stop Hypertension (DASH) diet interventions can have a positive impact for HF patients. However, the absence of a consensus for comprehensive dietary guidelines and for pragmatic evidence limits the ability of health care providers to implement clinical recommendations. The refinement of medical nutrition therapy through precision nutrition approaches has the potential to reduce the burden of HF, improve clinical care, and meet the needs of diverse patients. The aim of this review is to summarize current evidence related to HF dietary recommendations including DASH diet nutritional interventions and to develop initial recommendations for DASH diet implementation in outpatient HF management. Articles involving human studies were obtained using the following search terms: Dietary Approaches to Stop Hypertension (DASH diet), diet pattern, diet, metabolism, and heart failure. Only full-text articles written in English were included in this review. As DASH nutritional interventions have been proposed, limitations of these studies are the small sample size and non-randomization of interventions, leading to less reliable evidence. Randomized controlled interventions are needed to offer definitive evidence related to the use of the DASH diet in HF management.

Heart failure (HF) with reduced ejection fraction (HFrEF) remains a leading cause of morbidity and mortality. Heart failure withimproved ejection fraction (HFimpEF) has better prognosis and outcomes. However, improvement only occurs in a subpopulationof HFrEF.

BACKGROUND: Mitochondrial dysfunction is associated with poor allograft prognosis. Mitochondrial-related gene expression (GE) in endomyocardial biopsies (EMBs) could be useful as a nonimmune functional marker of rejection. We hypothesize that acute cardiac allograft rejection is associated with decreased mitochondrial-related GE in EMBs. METHODS: We collected 64 routines or clinically indicated EMB from 47 patients after heart transplant. The EMBs were subjected to mRNA sequencing. We conducted weighted gene coexpression network analysis to construct module-derived eigengenes. The modules were assessed by gene ontology enrichment and hub gene analysis. Modules were correlated with the EMBs following the International Society of Heart and Lung Transplantation histology-based criteria and a classification based on GE alone; we also correlated with clinical parameters. RESULTS: The modules enriched with mitochondria-related and immune-response genes showed the strongest correlation to the clinical traits. Compared with the no-rejection samples, rejection samples had a decreased activity of mitochondrial-related genes and an increased activity of immune-response genes. Biologic processes and hub genes in the mitochondria-related modules were primarily involved with energy generation, substrate metabolism, and regulation of oxidative stress. Compared with International Society of Heart and Lung Transplantation criteria, GE-based classification had stronger correlation to the weighted gene coexpression network analysis-derived functional modules. The brain natriuretic peptide level, ImmuKnow, and Allomap scores had negative relationships with the expression of mitochondria-related modules and positive relationships with immune-response modules. CONCLUSIONS: During acute cardiac allograft rejection, there was a decreased activity of mitochondrial-related genes, related to an increased activity of immune-response genes, and depressed allograft function manifested by brain natriuretic peptide elevation. This suggests a rejection-associated mitochondrial impairment.

BACKGROUND: Endomyocardial biopsy (EMB) is currently considered the gold standard for diagnosing cardiac allograft rejection. However, significant limitations related to histological interpretation variability are well-recognized. We sought to develop a methodology to evaluate EMB solely based on gene expression, without relying on histology interpretation. METHODS: Sixty-four EMBs were obtained from 47 post-heart transplant recipients, who were evaluated for allograft rejection. EMBs were subjected to mRNA sequencing, in which an unsupervised classification algorithm was used to identify the molecular signatures that best classified the EMBs. Cytokine and natriuretic peptide peripheral blood profiling was also performed. Subsequently, we performed gene network analysis to identify the gene modules and gene ontology to understand their biological relevance. We correlated our findings with the unsupervised and histological classifications. RESULTS: Our algorithm classifies EMBs into three categories based solely on clusters of gene expression: unsupervised classes 1, 2, and 3. Unsupervised and histological classifications were closely related, with stronger gene module-phenotype correlations for the unsupervised classes. Gene ontology enrichment analysis revealed processes impacting on the regulation of cardiac and mitochondrial function, immune response, and tissue injury response. Significant levels of cytokines and natriuretic peptides were detected following the unsupervised classification. CONCLUSION: We have developed an unsupervised algorithm that classifies EMBs into three distinct categories, without relying on histology interpretation. These categories were highly correlated with mitochondrial, immune, and tissue injury response. Significant cytokine and natriuretic peptide levels were detected within the unsupervised classification. If further validated, the unsupervised classification could offer a more objective EMB evaluation.

BACKGROUND: Higher-than-expected heart failure (HF) readmissions affect half of US hospitals every year. The Hospital Reduction Readmission Program has reduced risk-adjusted readmissions, but it has also produced unintended consequences. Shared care models have been advocated for HF care, but the association of shared care networks with HF readmissions has never been investigated. OBJECTIVE: This study aims to evaluate the association of shared care networks with 30-day HF excessive readmission rates using a longitudinal observational study. METHODS: We curated publicly available data on hospital discharges and HF excessive readmission ratios from hospitals in California between 2012 and 2017. Shared care areas were delineated as data-driven units of care coordination emerging from discharge networks. The localization index, the proportion of patients who reside in the same shared care area in which they are admitted, was calculated by year. Generalized estimating equations were used to evaluate the association between the localization index and the excessive readmission ratio of hospitals controlling for race/ethnicity and socioeconomic factors. RESULTS: A total of 300 hospitals in California in a 6-year period were included. The HF excessive readmission ratio was negatively associated with the adjusted localization index (β=-.0474, 95% CI -0.082 to -0.013). The percentage of Black residents within the shared care areas was the only statistically significant covariate (β=.4128, 95% CI 0.302 to 0.524). CONCLUSIONS: Higher-than-expected HF readmissions were associated with shared care networks. Control mechanisms such as the Hospital Reduction Readmission Program may need to characterize and reward shared care to guide hospitals toward a more organized HF care system.

Introduction

Guideline-directed medical therapy (GDMT) is the recommended treatment for heart failure with reduced ejection fraction (HFrEF). However, the implementation remains limited, with suboptimal use and dosing. The study aimed to assess the feasibility and effect of a remote monitoring titration program on GDMT implementation.

Methods

HFrEF patients were randomly assigned to receive either usual care or a quality-improvement remote titration with remote monitoring intervention. The intervention group used wireless devices to transmit heart rate, blood pressure, and weight data daily, which were reviewed by physicians and nurses every 2-4 weeks. Medication tolerance was assessed via phone, and dosage instructions were given. This workflow was repeated until target doses were reached or further adjustments were not tolerated. A 4-GDMT score measured use and target dosage, with the primary endpoint being the score at 6 months follow-up.

Results

Baseline characteristics were similar (n = 55). A median of 85% of patients complied with transmitting device data every week. At the 6-month follow-up, the intervention group had a 4-GDMT score of 64.6% compared to 56.5% in the usual care group (p = 0.01), with a difference of 8.1% (95% CI: 1.7%-14.5%). Similar results were seen at the 12-month follow-up [difference 12.8% (CI: 5.0%-20.6%)]. The intervention group showed a positive trend in ejection fraction and natriuretic peptides, with no significant difference between groups.

Conclusions

The study suggests that a full-scale trial is feasible and that utilizing a remote titration clinic with remote monitoring has the potential to enhance the implementation of guideline-directed therapy for HFrEF.

Heart failure with improved ejection fraction (HFimpEF) has better outcomes than HF with reduced EF (HFrEF). However, factors contributing to HFimpEF remain unclear. This study aimed to evaluate clinical and longitudinal characteristics associated with subsequent HFimpEF. This was a single-center retrospective HFrEF cohort study. Data were collected from 2014 to 2022. Patients with HFrEF were identified using International Classification of Diseases codes, echocardiographic data, and natriuretic peptide levels. The main end points were HFimpEF (defined as EF >40% at ≥3 months with ≥10% increase) and mortality. Cox proportional hazards and mixed effects models were used for analyses. The study included 1,307 patients with HFrEF with a median follow-up of 16.3 months (interquartile range 8.0 to 30.6). The median age was 65 years; 68% were male whereas 57% were White. On follow-up, 38.7% (n = 506) developed HFimpEF, whereas 61.3% (n = 801) had persistent HFrEF. A multivariate Cox regression model identified gender, race, co-morbidities, echocardiographic, and natriuretic peptide as significant covariates of HFimpEF (p <0.05). The HFimpEF group had better survival compared with the persistent HFrEF group (p <0.001). Echocardiographic and laboratory trajectories differed between groups. In this HFrEF cohort, 38.7% transitioned to HFimpEF and approximately 50% met the definition within the first 12 months. In a HFimpEF model, gender, co-morbidities, echocardiographic parameters, and natriuretic peptide were associated with subsequent HFimpEF. The model has the potential to identify patients at risk of subsequent persistent or improved HFrEF, thus informing the design and implementation of targeted quality-of-care improvement interventions.