Racial and ethnic disparities in hospitalizations among heart failure (HF) patients have been well documented. However, little is known about racial and ethnic differences in the long-term trajectories of hospital admissions that follow the diagnosis of HF.

We used electronic health records (EHR) of 5,606 patients with newly-diagnosed HF between January 1, 2015 and July 28, 2018 in the Duke University Health System. Patients were followed for up to 5 years (until July 28, 2023) to identify all-cause hospital admissions after their initial diagnosis of HF. Group-based trajectory models were used to identify major trajectories of hospitalization, and multinomial logistic regression models were used to identify patients' clinical and nonclinical characteristics associated with the trajectories of admissions.

In our study cohort (mean age 74.8 ± 5.8 years), we identified 4 distinct trajectories of hospitalization during follow up: 45.6% (Group 1: N = 2,556) had "low risks" of hospitalization, 36.6% (Group 2: N = 2,052) had elevated risks of admission shortly after diagnosis ("early risk" group), 9.9% (Group 3: N = 553) had elevated risks at later stages of illness ("late risk" group), and 7.9% (Group 4: N = 445) had consistently "high risks" of hospitalization. Non-Hispanic Black patients were more likely to exhibit early risks of hospitalization (odds ratio [OR], 1.33; 95% confidence interval [CI], 1.16-1.52; P < .001), late risks of hospitalization (OR = 1.92; 95% CI, 1.58-2.34; P < .001), or consistently high risks of hospitalization (OR = 1.89; 95% CI, 1.52-2.35; P < .001) compared with non-Hispanic White patients. Diabetes, chronic kidney disease, and residence in a disadvantaged neighborhood significantly contributed to the excess risks of admissions among non-Hispanic Black patients. We found no significant differences in patterns of admissions between patients from other racial and ethnic groups compared with non-Hispanic White patients.

Non-Hispanic Black patients had early, late, and consistently high risks of hospitalization following the diagnosis of HF compared with non-Hispanic White patients. These findings have important implications for targeting interventions to reduce hospitalizations during the course of HF management.

Heart failure is a leading cause of mortality in the United States, with significant disparities in its burden, particularly among underserved populations. A similar pattern exists for diabetes, but less is known about the mortality impact of these two comorbid conditions. This study aims to examine the risk of death from heart failure among people with diabetes, focusing on socio-demographic disparities.

We analysed data from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research Multiple Cause of Death Database, examining patterns of heart failure deaths in which diabetes was a contributing cause. Our analysis was stratified by socio-demographic variables, including race, ethnicity and geography, and we also explored trends over time.

Between 1999 and 2020, there were 82 617 deaths from heart failure in which diabetes was a contributing cause, with an age-adjusted mortality rate of 32.04 deaths per 1 000 000 individuals. The death rate increased by 2.18% during the study period. Death rates were higher among Black Americans compared with White Americans (age-adjusted mortality rate ratio = 1.51, 95% confidence interval: 1.49-1.53), with disparities growing over time (a 10.75% increase for Black Americans vs. a 1.11% increase for White Americans).

Deaths from comorbid heart failure and diabetes are increasing in the United States, with significant and worsening disparities, particularly among minorities. Urgent action is needed to reduce heart failure mortality among people with diabetes, especially in underserved populations.

There is increasing recognition that the pathophysiology of coronary microvascular dysfunction (CMD) plays a pivotal role in the development of heart failure with preserved ejection fraction (HFpEF). However, the mechanisms underlying this role are not known.

The Women's Ischemia Syndrome Evaluation Mechanisms of Coronary Microvascular Dysfunction Leading to Pre-Heart Failure With Preserved Ejection Fraction (WISE Pre-HFpEF) is a prospective cohort study enrolling 180 women and men undergoing clinically indicated invasive coronary angiography for suspected ischemia with no obstructive coronary artery disease. The study aims to investigate (1) CMD-related ischemia contribution to myocellular damage and impaired left ventricular (LV) relaxation as determined invasively by ultra-high sensitivity cardiac troponin I (u-hs-cTnI) measurements in the coronary sinus/great cardiac vein and LV pressure-volume loops, respectively, during provocative stress testing with isometric handgrip, and (2) CMD-related ischemic myocellular damage contribution to LV diastolic dysfunction progression as assessed using cardiac magnetic resonance imaging obtained at enrollment and 1-2 years later, along with prospectively repeated ambulatory u-hs-cTnI measurements.

The WISE pre-HFpEF study is designed to investigate whether ischemic myocardial damage secondary to CMD contributes to the progression of LV diastolic dysfunction. The findings from this study will provide new understanding of the role of CMD in HFpEF development as well as the potential benefits of CMD-directed therapies for the prevention and treatment of HFpEF.

ClilicalTrial.gov, NCT03876223.

Despite the increasing prevalence and substantial burden of heart failure with preserved ejection fraction (HFpEF), which constitutes up to 50% of all heart failure cases, significant challenges persist in its diagnostic and therapeutic strategies. These difficulties arise primarily from the heterogeneous nature of the condition, the presence of various comorbidities and a wide range of phenotypic variations. Considering these challenges, current international guidelines endorse the utilization of invasive haemodynamic assessments, including resting and exercise haemodynamics, as the gold standard for enhancing diagnostic accuracy in cases where traditional diagnostic methods yield inconclusive results. These assessments are crucial not only for confirming the diagnosis but also for delineating the complex underlying pathophysiology, enabling the development of personalized treatment strategies, and facilitating the precise classification of HFpEF phenotypes. In this review, we summarize the haemodynamic changes observed in patients with HFpEF, comparing resting and exercise-induced parameters to those of normal subjects. Additionally, we discuss the current role of invasive haemodynamics in HFpEF assessment and highlight its utility beyond diagnosis, such as identifying HFpEF comorbidities, guiding phenotype-based personalized therapies and characterizing prognostication. Finally, we address the challenges associated with utilizing invasive haemodynamics and propose future directions, focusing on integrating these assessments into routine HFpEF care.

Little is known regarding the clinical and financial implications of varying inpatient and outpatient management strategies for worsening heart failure (WHF). This analysis aimed to compare clinical outcomes, home-time, and healthcare expenditure following various types of inpatient and outpatient WHF events in US clinical practice.

We examined US Medicare beneficiaries 65 years and older discharged from a hospitalization for heart failure (HF) in the Get With The Guidelines-Heart Failure registry from 2010 to 2018. Patients developing subsequent WHF within 12 months were divided into four mutually exclusive groups by type of first event: HF hospitalization, emergency department (ED) visit with ED discharge, observation stay, and outpatient intravenous (IV) diuretic clinic visit. Following each type of WHF event, mortality, home-time (days alive and out of any healthcare institution), and healthcare costs were compared over the subsequent 12 months. Among 181 827 eligible patients discharged alive from a HF hospitalization across 553 US hospitals, 61 159 (33.6%) patients had a subsequent WHF event within 12 months. Of these, 48 612 were managed with HF hospitalization (79.5%), 8139 (13.3%) with an ED visit, 1767 (2.9%) with an observation stay, and 2641 (4.3%) with an outpatient IV diuretic visit. Rates of 12-month mortality were highest following HF hospitalization (cumulative incidence rate [IR] 48.8; 95% confidence interval [CI] 48.3-49.3), lowest following observation unit stay (IR 29.9; 95% CI 27.7-32.0), and intermediate following ED discharge (IR 41.2; 95% CI 40.1-42.3) and outpatient IV diuretic visit (IR 39.3; 95% CI 37.4-41.2). Median (25th-75th) 12-month home-time was lowest following HF hospitalization (251 [47-351] days) and highest following observation unit stays (354 [206-365] days). For the index WHF event itself, median total per-patient costs were highest for HF hospitalization (US$11 335) and lowest for outpatient IV diuretic visit (US$259). Over the 12 months following the WHF event, when accounting for costs of all patients including those who died within 12 months, the median total per-patient costs were highest following outpatient IV diuretic visits (US$29 173). Among patients surviving 12 months after WHF, median total per-patient costs following an outpatient IV diuretic visit (US$29 931) versus HF hospitalization (US$30 971) were similarly high.

In this nationwide analysis of older US adults, high rates of death and substantial reductions in home-time occurred following WHF regardless of inpatient or outpatient management, but were worse following HF hospitalization. Outpatient IV diuretic administration was the least expensive initial management strategy, but over the subsequent 12 months, associated costs were similar or higher than costs following HF hospitalization.

Over the past few decades, the rising burden of metabolic disease, including type 2 diabetes, prediabetes, obesity, and metabolic dysfunction-associated steatotic liver disease, has corresponded with fundamental shifts in the landscape of heart failure (HF) epidemiology, including the rising prevalence of HF with preserved ejection fraction. It has become increasingly important to understand the role of extracardiac contributors and interorgan communication in the pathophysiology and phenotypic heterogeneity of HF. Whereas traditional epidemiological strategies have separately examined individual contributions of specific comorbidities to HF risk, these approaches may not capture the shared mechanisms and more complex, bidirectional relationships between cardiac and noncardiac comorbidities. In this review, we highlight the cardiac, kidney, liver, and metabolism multiorgan interactions and pathways that complicate HF development and progression and propose research strategies to further understand HF in the context of multiple organ disease. This includes evolving epidemiological approaches such as multiomics and machine learning which may better capture common underlying mechanisms and interorgan crosstalk. We review existing preclinical models of HF and how they have enhanced our understanding of the role of multiorgan disease in the development of HF subtypes. We suggest recommendations as to how clinical practice across multiple specialties should screen for and manage multiorgan involvement in HF. Finally, recognizing the advent of novel combinatorial therapeutic agents that may have multiple indications across the cardiac-kidney-liver metabolism continuum, we review the current clinical trials landscape. We specifically highlight a pressing need for the design of more inclusive trials that examine the contributions of multimorbidity and incorporate multiorgan end points, which we propose may lead to outcomes that are evermore clinically relevant today.

The liver and heart are closely interconnected organs, and their bidirectional interaction plays a central role in cardiometabolic disease. In this review, we summarize current evidence linking liver dysfunction-particularly metabolic dysfunction-associated steatotic liver disease, alcohol-associated liver disease, and cirrhosis-with an increased risk of heart failure and other cardiovascular diseases. We discuss how these liver conditions contribute to cardiac remodeling, systemic inflammation, and hemodynamic stress and how cardiac dysfunction in turn impairs liver perfusion and promotes hepatic injury. Particular attention is given to the molecular mediators of liver-heart communication, including hepatokines and cardiokines, as well as the emerging role of advanced research methodologies, including omics integration, proximity labeling, and organ-on-chip platforms, that are redefining our understanding of interorgan cross talk. By integrating mechanistic insights with translational tools, this review aims to support the development of multiorgan therapeutic strategies for cardiometabolic disease.

Minimally invasive approaches to cardiac surgery have been developing over the last several decades, including less invasive strategies to implantation of durable left ventricular assist devices (LVAD). Less invasive approaches to LVAD insertion aim to reduce surgical trauma and promote shorter hospital stay and recovery times; and for those bridged to heart transplantation, they aim to facilitate later reentry.

PubMed was searched from 1980 to present to identify existing literature regarding non-sternotomy approaches to LVAD insertion. This review outlines the history and early attempts of sternal sparing LVAD insertion, commonly utilized surgical approaches in contemporary practice, as well as the experience with concomitant procedures using these approaches. Additionally, a summary of postoperative outcomes described in the literature is provided. Lastly, this review describes the early use of robotic assistance in durable LVAD implantation.

Sternal sparing approaches to LVAD insertion are feasible, safe, and in multiple experiences, have been shown to reduce operative and postoperative blood loss, reoperation, right ventricular dysfunction, and hospital length of stay. The use of surgical robotics in LVAD implantation remains at its infancy but poses a promising avenue to a totally endoscopic approach to durable mechanical assist therapy.

Heart failure (HF) is associated with high mortality rates and substantial health care costs. While there is growing emphasis on integrating palliative care for patients with HF, limited data exist on the locations where adults with HF spend their final days. The study aimed to analyze the location and circumstances of death among adults with HF in the United States using Centers for Disease Control and Prevention's Wide-ranging Online Data for epidemiological Research data.

Mortality data from individuals aged ≥20 years, with HF listed as the cause of death between 1999 and 2023, were analyzed. The places of death were categorized as the emergency room, hospice/nursing home, inpatient medical facility, or home. Multinomial logistic regression was performed to examine the associations between demographic factors and death location.

HF-related mortality rates declined from 1999 (3.60% and 143.6 age-adjusted mortality rate) to 2010 (3.47% and 123.1 age-adjusted mortality rate). However, rates gradually increased thereafter, reaching 5.18% and 168.1 age-adjusted mortality rate in 2023. Deaths at home nearly doubled, rising from 18.41% (50 648 of 275 132) in 1999 to 33.47% (132 470 of 395 826) in 2023. Hospice/nursing home deaths increased from 30.95% (85 144 of 275 132) in 1999 to 34.71% (116 634 of 336 014) in 2017, but declined to 29.54% (116 931 of 395 826) by 2023. Young adults (20-34 years) had the highest proportion of inpatient deaths. Sex, ethnicity, and urbanization were significant predictors of death location, with men, White individuals, and those in large metropolitan areas more likely to die in medical facilities.

This study underscores the shifting trends in the locations of death among patients with HF, with a ≈2-fold increase in HF-related deaths occurring at home over the past 2 decades. The recent decline in hospice/nursing home deaths, following a period of steady growth, calls for an in-depth examination of contributing barriers. Further research is essential to understand the sociodemographic factors driving disparities in HF-related death locations.

In early 2022, new treatment recommendations for heart failure (HF) were introduced in Sweden.

This study aims to evaluate and analyze the pharmaceutical treatment patterns of HF patients over time in Sweden, in relation to the updated treatment recommendations.

This observational study is based on registry data. The study population consisted of patients ≥18 years old who, at any time between 2017 and 2023, had an HF diagnosis, defined using ICD-10 code I50 (n = 212,757). Descriptive statistics were presented for the study population. Based on data from the national drug prescription registry, the treatment patterns between 2021 and 2023 were analyzed using biannual datasets before and after the introduction of treatment recommendations.

The mean age of the study population was 79 years and 56% were men. The utilization of quadruple therapy and SGLT2 inhibitors, both as monotherapy and in combination, increased over time, with a rising trend already apparent prior to the introduction of the updated treatment recommendations. At the end of 2023, about 30% of the incident HF population had at least tried quadruple therapy. Furthermore, a growing number of diverse treatment pathways among HF patients was observed over time, which may indicate an increased consideration for individualized treatment.

Even though the implementation of the treatment recommendations for HF is not yet optimal, this study found a notable adoption of quadruple therapy in Sweden. There was an increased use of SGLT2 inhibitors and quadruple therapy, beginning even before the introduction of the updated Swedish treatment recommendations.

Heart failure with preserved ejection fraction (HFpEF) is a growing public health burden, contributing to significant morbidity, mortality, and healthcare costs. Exercise intolerance, a hallmark of HFpEF, stems from central (cardiac and pulmonary) and peripheral (vascular and skeletal muscle) factors that result in reduced oxygen delivery and utilization by active muscles. With relatively few effective therapies, exercise training has emerged as a reliable and proven therapeutic intervention to improve exercise capacity and physical function in HFpEF. This review synthesizes evidence from the existing literature to describe and evaluate various exercise modalities in HFpEF. Moderate-intensity continuous training significantly improves peak oxygen consumption and symptom burden and is supported by a large evidence base in patients with HFpEF. High-intensity interval training has shown potential as an alternative regimen with particular benefit in highly selected populations. Multi-modality regimens and low-intensity training approaches are potentially suitable for patients with limited exercise tolerance or those who are more vulnerable or frail. The addition of resistance training may further improve muscle strength and functional capacity. Integrating exercise interventions with complementary dietary approaches has also shown potential for enhancing exercise capacity response. Lastly, emerging modalities, such as inspiratory muscle training and functional electrical stimulation, offer additional unique options. Despite robust evidence, challenges in the long-term durability of benefits, poor responder rates (~ 1/3 of participants), and implementation persist. Ongoing and future efforts can focus on evaluating long-term clinical outcomes (i.e., mortality and hospitalizations), developing more personalized exercise protocols, and applying sustainable implementation strategies in clinical practice.

The study investigates the prognostic impact of the native QRS duration in patients with heart failure and mildly reduced ejection fraction (HFmrEF).

The prognostic impact of QRS duration in HFmrEF has rarely been investigated.

Consecutive patients with HFmrEF and available 12-lead electrocardiogram were retrospectively included at one institution from 2016 to 2022. Patients with QRS duration ≥ 120 ms were compared to patients with QRS duration < 120 ms, further risk stratification was performed comparing patients with left and right bundle branch block (LBBB vs. RBBB). The primary endpoint was all-cause mortality at 30 months, secondary endpoints comprised the risk of HF-related rehospitalization.

In total, 1627 patients with HFmrEF were included with a median QRS duration of 90 ms (i.e., QRS duration ≥ 120 ms: 15%). Although the risk of long-term all-cause mortality was not affected by a prolonged QRS duration (35.1% vs. 28.7%; p = 0.057; HR = 1.254; 95% CI 0.993-1.583), patients with QRS duration ≥ 120 ms had a higher risk of HF-related rehospitalization (18.2% vs. 11.9%; p = 0.008; HR = 1.574; 95% CI 1.124-2.204). A QRS duration ≥ 120 ms was associated with long-term HF-related rehospitalization even after multivariable adjustment (HR 1.420, 95% CI 1.008-2.002, p = 0.045). Finally, the risks of long-term all-cause mortality and HF-related rehospitalization did not differ among patients with LBBB and RBBB.

A prolonged native QRS duration is independently associated with a higher risk of HF-related rehospitalization in HFmrEF, but not long-term all-cause mortality.

Heart failure (HF) is a highly prevalent condition characterized by exercise intolerance, an important metric for ambulatory prognostication. However, current methods to assess exercise capacity are often limited to tertiary HF centers, lacking scalability or accessibility. Wearable devices have the potential to provide near-continuous dynamic biometrics including exercise tolerance.

Leveraging the capabilities of Apple Watch and a custom application, the TRUE-HF (Ted Rogers Understanding of Exacerbations in Heart Failure) Apple cardiopulmonary exercise testing study aims to investigate whether HealthKit data from Apple Watch can estimate cardiorespiratory fitness, as compared with the gold standard peak oxygen uptake from cardiopulmonary exercise testing. The TRUE-HF study will evaluate the potential impact of wearable technology in the functional assessment of ambulatory patients with HF. The primary end point is to use HealthKit variables to estimate a TRUE-HF peak oxygen uptake. We outline key features of this trial designed to reduce the burden of wearable technology. In addition, we highlight the benefits of various machine learning analyses, with a particular focus on transformer models for the wearable space.

Using cutting-edge wearable technology and machine learning analytics, TRUE-HF may provide state-of-the-art assessment of functional capacity by measuring participant-generated free-world data.

URL: https://www.clinicaltrials.gov; Unique identifier: NCT05008692.

Unplanned admissions for worsening heart failure (WHF) are the largest resource cost in heart failure (HF) management. Despite advances in pharmacological agents and interventional therapy, HF remains a global epidemic. One crucial-and costly-gap in HF management is the inability to obtain objective information to identify and quantify congestion and personalize treatment plans to effectively manage WHF events without resorting to expensive, invasive methods. Although the causes of WHF are varied and complex, the universal effect of HF decompensation is the significant decline in quality of life due to symptoms of hypervolemic congestion and the resultant reduction in cardiac output, which can be quantified via increased pulmonary venous congestion due to high intracardiac filling pressures. Accessible and reliable markers of congestion could more precisely quantify the severity of WHF events and stabilize patients earlier by interrupting and reversing this process with timely introduction or modification of evidence-based treatments. Pulmonary artery and cardiac pressure sensing tools have gained evidential credence and increased clinical uptake in recent years for the prevention and treatment of WHF, as studies of implantable hemodynamic devices have iteratively and reliably demonstrated substantial reductions in WHF events. Recent advances in sensing technologies have ranged from single-parameter invasive pulmonary artery monitors to completely non-invasive multi-parameter devices incorporating multi-sensor concept technologies aided by machine learning or artificial intelligence, although many remain investigational. This review aims to evaluate the potential for novel pulmonary artery and cardiac pressure sensing technology to reshape the management of WHF from within the hospitalized and ambulatory care environments.

The transplantation of human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) and hPSC-derived cardiac progenitors (hPSC-CPs) represents a promising strategy for regenerating hearts damaged by myocardial infarction (MI). After nearly two decades of experience testing these cell populations in various small- and large-animal MI models, multiple clinical trials have recently been initiated. In this review, we consider the principal lessons learned from preclinical experience with hPSC-CMs and -CPs, focusing on three conclusions that have been supported by the majority of reported transplantation studies. First, hPSC-CMs and -CPs stably engraft in injured hearts and partially remuscularize the infarct scar, but more progress is needed to improve graft cell retention and survival. Second, the transplantation of hPSC-CMs and -CPs has been found to improve contractile function in infarcted hearts, but the mechanistic basis for these effects remains incompletely elucidated. Third, the graft tissue formed by these cells can integrate and activate synchronously with host myocardium, but this capacity for electromechanical integration has been associated with an elevated risk of graft-related arrhythmias. Here, we summarize the preclinical evidence supporting these three observations, identify the relevant gaps and barriers to translation, and summarize ongoing efforts to improve the safety and efficacy of hPSC-CM- and -CP-based regenerative therapies.

Clinical guidelines recommend medications from four drug classes, collectively referred to as quadruple therapy, to improve outcomes for patients with heart failure with reduced ejection fraction (HFrEF). Wide gaps in uptake of these therapies persist across a range of settings. In this qualitative study, we identified determinants (i.e., barriers and facilitators) of quadruple therapy intensification, defined as prescribing a new class or increasing the dose of a currently prescribed medication.

We conducted interviews with physicians, nurse practitioners, physician assistants, and pharmacists working in primary care or cardiology settings in an integrated health system or federally qualified health centers (FQHCs). We report results with a conceptual model integrating two frameworks: (1) the Theory of Planned Behavior (TPB), which explains how personal attitudes, perception of others' attitudes, and perceived behavioral control influence intentions and behaviors; and (2) the Consolidated Framework for Implementation Research (CFIR) 2.0 to understand how multi-level factors influence attitudes toward and intention to use quadruple therapy.

Thirty-one clinicians, including 18 (58%) primary care and 13 (42%) cardiology clinicians, participated in the interviews. Eight (26%) participants were from FQHCs. A common facilitator in both settings was the belief in the importance of quadruple therapy. Common barriers included challenges presented by patient frailty, clinical inertia, and time constraints. In FQHCs, primary care comfort and ownership enhanced the intensification of quadruple therapy while limited access to and communication with cardiology specialists presented a barrier. Results are presented using a combined TPB-CFIR framework to help illustrate the potential impact of contextual factors on individual-level behaviors.

Determinants of quadruple therapy intensification vary by clinician specialty and care setting. Future research should explore implementation strategies that address these determinants by specialty and setting to promote health equity.

Cancer is a life-threatening disease and a leading cause of death worldwide, with an estimated 611,000 deaths and over 2 million new cases in the United States in 2024. The rising incidence of major cancers, including among younger individuals, highlights the need for early screening and monitoring of risk factors to manage and decrease cancer risk.

This study aimed to leverage explainable machine learning models to identify and analyze the key risk factors associated with breast, colorectal, lung, and prostate cancers. By uncovering significant associations between risk factors and these major cancer types, we sought to enhance the understanding of cancer diagnosis risk profiles. Our goal was to facilitate more precise screening, early detection, and personalized prevention strategies, ultimately contributing to better patient outcomes and promoting health equity.

Deidentified electronic health record data from Medical Information Mart for Intensive Care (MIMIC)-III was used to identify patients with 4 types of cancer who had longitudinal hospital visits prior to their diagnosis presence. Their records were matched and combined with those of patients without cancer diagnoses using propensity scores based on demographic factors. Three advanced models, penalized logistic regression, random forest, and multilayer perceptron (MLP), were conducted to identify the rank of risk factors for each cancer type, with feature importance analysis for random forest and MLP models. The rank biased overlap was adopted to compare the similarity of ranked risk factors across cancer types.

Our framework evaluated the prediction performance of explainable machine learning models, with the MLP model demonstrating the best performance. It achieved an area under the receiver operating characteristic curve of 0.78 for breast cancer (n=58), 0.76 for colorectal cancer (n=140), 0.84 for lung cancer (n=398), and 0.78 for prostate cancer (n=104), outperforming other baseline models (P<.001). In addition to demographic risk factors, the most prominent nontraditional risk factors overlapped across models and cancer types, including hyperlipidemia (odds ratio [OR] 1.14, 95% CI 1.11-1.17; P<.01), diabetes (OR 1.34, 95% CI 1.29-1.39; P<.01), depressive disorders (OR 1.11, 95% CI 1.06-1.16; P<.01), heart diseases (OR 1.42, 95% CI 1.32-1.52; P<.01), and anemia (OR 1.22, 95% CI 1.14-1.30; P<.01). The similarity analysis indicated the unique risk factor pattern for lung cancer from other cancer types.

The study's findings demonstrated the effectiveness of explainable ML models in assessing nontraditional risk factors for major cancers and highlighted the importance of considering unique risk profiles for different cancer types. Moreover, this research served as a hypothesis-generating foundation, providing preliminary results for future investigation into cancer diagnosis risk analysis and management. Furthermore, expanding collaboration with clinical experts for external validation would be essential to refine model outputs, integrate findings into practice, and enhance their impact on patient care and cancer prevention efforts.

Ventricular arrhythmias (VAs) are highly prevalent in patients with advanced heart failure (AHF), a condition characterized by severe signs and symptoms despite conventional HF therapy. The management of VAs in this setting remains challenging. Antiarrhythmic drug therapy options are limited and only amiodarone has demonstrated effectiveness in suppressing VA, albeit this agent is associated with a substantial risk of cardiac and noncardiac adverse effects. Catheter ablation is effective for the reduction of VAs in patients with AHF. Identification of patients at high risk for periprocedural hemodynamic decompensation has important implications in terms of procedural planning and improving patient safety and procedural outcomes. Herein, we review the current state of scientific evidence for the management of VA in patients with AHF.

Neighborhood environments play a key role in the development of individual risk factors for heart failure (HF) and impact health outcomes across the spectrum of HF. The area deprivation index (ADI) is an important composite measure of neighborhood depravity that has been associated with poor cardiovascular outcomes. The objective of our review is to discuss how neighborhood deprivation, with an emphasis on ADI, influences the spectrum of HF among patients and to propose solutions for ADI applications to improve the implementation of equitable care across the HF spectrum. MEDLINE/Pubmed was systematically searched to identify observational studies published between 2016 and 2024, examining the impact of ADI on HF risk, management, and outcomes. The search involved crossing two sets of terms included in article titles and abstracts: (1) social deprivation, area deprivation index, and neighborhood deprivation; (2) cardiovascular disease risk, heart failure, heart failure medications, and heart failure outcomes. Additional references were identified through searching relevant author reference lists and review articles. Key findings suggest that (1) the prevalence of HF risk is increased in individuals residing in neighborhoods with higher ADI; (2) HF patients living in more deprived neighborhoods have increased odds of being hospitalized for HF; (3) after HF admission, the relationship between ADI and risk for readmissions varies by race; and (4) there is an excess 30-day mortality of HF associated with race and neighborhood deprivation. The ADI is an important value to consider in patients with HF, given its association with clinical outcomes. Therefore, we suggest practical ways to incorporate ADI into the management of patients with HF to improve equitable outcomes.

To assess if future time perspective (FTP) moderates the relationship between heart failure (HF) caregiver coping style and preparedness to make a surrogate medical decision.

Cross-sectional data was analyzed to assess associations among three different coping styles (i.e. avoidance, active, minimizing), FTP, and odds of feeling prepared to make a medical decision on behalf of a loved one with heart failure.

A total of 231 caregivers were included in analyses. No significant interaction effects emerged among coping style and FTP on odds of feeling prepared to make a surrogate medical decision. Caregiver burden was significantly and inversely related to feeling prepared across each coping style model. Reports of having the provider present for the medical wishes conversation was significantly related to odds of feeling prepared across each coping style model.

FTP did not appear to moderate the relationship between coping styles and preparedness to make a medical decision on behalf of a loved one with heart failure. Future research should continue to explore possible characteristics that can be targeted to improve feelings of decision-making preparedness among caregivers of loved ones with HF.

The aim of this study was to compare arterial stiffness between young adults with perinatally acquired HIV (YAPHIV) and young adults' perinatally HIV exposed but uninfected (YAPHEU).

A cross-sectional analysis of pulse wave velocity (PWV) measures among participants with echocardiography in the PHACS Cardiac Toxicity Substudy.

A total of 150 participants (95 YAPHIV, 55 YAPHEU, mean 23.4 years, 60% female, 72% Black, 24% Hispanic) had echocardiography and PWV measured. We compared PWV between groups. Among YAPHIV, we fit linear regression models to evaluate the association of measures of HIV disease severity and antiretroviral treatment (ART) with PWV. We computed correlations between PWV and measures of left ventricular structure and function.

Mean PWV did not differ by group (YAPHIV 5.63 vs. YAPHEU 5.39 m/s; P  = 0.50). HIV control was good (82% with viral load <400 copies/ml); 91% used combination ART. Mean PWV was normal, but three of 95 YAPHIV (3%) had values above 11.8 m/s (level associated with cardiovascular events in adults). Weak correlations (<0.20) were observed between PWV and echocardiographic measures. Among YAPHIV, current and historical HIV severity measures were not associated with PWV. YAPHIV on protease inhibitor based ART had higher mean PWV than those on integrase strand inhibitors (1.68 m/s higher, 95% confidence interval -0.36, 3.72) or nonnucleoside transcriptase inhibitors (1.58 m/s higher, 95% confidence interval -0.94, 4.11).

Our data show no difference in PWV between those perinatally exposed to and perinatally infected with HIV. Therefore, cardiovascular risk reduction guidelines should be followed to prevent cardiovascular disease in all young adults.

Despite randomized data for survival benefit (with class 1 recommendations) for treating heart failure (HF) with reduced ejection fraction using quadruple medical therapy (QMT)-defined as evidence-based β-blockers, sodium-glucose cotransporter 2 inhibitor, preferably angiotensin receptor/neprilysin inhibitor, and mineralocorticoid receptor antagonist-it is underutilized. IMPLEMENT-HF is a multiregional HF quality improvement initiative to improve care and outcomes for patients with HF by enhancing the use of QMT in routine practice.

This analysis of HF with reduced ejection fraction treatment in patients from hospitals participating in the American Heart Association's Get With The Guidelines-HF who volunteered to participate in IMPLEMENT-HF in 7 US regions. IMPLEMENT-HF included multidisciplinary learning to share strategies for formulary changes, electronic health record tools, and patient resources with site-level feedback reports. Participants gathered QMT data at discharge and 30 days after discharge. We evaluated QMT utilization and variation, in addition to other prespecified performance measures, from Q1 2021 to Q2 2023.

The median (interquartile range) age of 43 558 admitted patients at 61 hospitals was 74 (63-83) years; 16 530 (38%) belonged to racial and ethnic minorities, and 22 228 (51%) were women. Between Q1 2021 and Q2 2023, defect-free QMT improved from 4.7% to 44.6% at discharge and from 0% to 44.8% at 30 days (both P<0.0001). There was also substantially improved incorporation of health-related social needs assessments. The magnitude of improvements was similar when stratified by sex or race and ethnicity, yet there was significant regional variation.

Among healthcare systems participating in IMPLEMENT-HF, there was a marked increase in QMT use among eligible patients over the course of the initiative. This quality improvement initiative supports a learning collaborative model to promote improvements in QMT use.

According to the latest Society for Vascular Surgery guidelines, carotid revascularization for asymptomatic individuals should be offered if the perioperative stroke/death rate does not exceed 3%. Heart failure (HF) has been associated with reduced survival rates following carotid revascularization, which may significantly impact the risk-benefit decision of treating asymptomatic patients with HF. This study aimed to evaluate the 30-day postoperative risks in asymptomatic patients with newly diagnosed and/or decompensated HF undergoing carotid endarterectomy (CEA) and carotid artery stenting (CAS).

Asymptomatic patients who underwent CEA and CAS were identified in the American College of Surgeons-National Surgery Quality Improvement Program targeted databases from 2011 through 2023. HF was defined as newly diagnosed HF and/or an acute exacerbation of chronic HF within 30 days of the surgery. A 1:3 propensity-score matching was used to balance preoperative differences between patients with and without HF. Patients who underwent CEA and CAS were analyzed separately. Thirty-day postoperative outcomes were examined.

There were 23,274 patients who underwent CEA, where 601 (2.58%) had HF, who were matched to 1803 non-HF patients. Among 1361 patients who underwent CAS, 87 (6.38%) had HF and were matched to 222 non-HF counterparts. Patients with HF had a much higher comorbidity burden. After CEA, patients with HF had higher risks of stroke/mortality (4.83% vs 2.55%; P = .01), cardiac (6.66% vs 3.38%; P < .01), pulmonary (4.49% vs 2.44%; P = .02), and renal complications (1.66% vs 0.44%; P = .01), as well as sepsis (1.50% vs 0.44%; P = .02), distal embolization (0.50% vs 0.00%; P = .02), unplanned operation (5.99% vs 3.49%; P = .01), prolonged hospital stay (P < .01), and 30-day readmission (13.14% vs 8.65%; P < .01). After CAS, patients with HF had similarly high risks of stroke/mortality (5.75% vs 3.60%; P = .53).

For newly diagnosed and/or decompensated patients with HF and asymptomatic carotid stenosis, the 30-day postoperative stroke/mortality risks after both CEA and CAS greatly exceed the Society for Vascular Surgery guideline recommendations. Coupled with the substantially higher risk of other major complications, the decision to pursue surgical revascularization in asymptomatic patients with HF should be approached with extreme caution, and conservative management may be prioritized.

Person-centered care (PCC) has been advanced as an optimal model for chronic heart failure management in multiple guidelines. However, fulfilling the ideal of this model requires overcoming healthcare fragmentation via effective provider-to-patient communication. One potential communication tool is the after-visit summary (AVS), a core feature of modern electronic health records (EHR); however, little is known regarding its quality from a PCC lens and whether an optimal AVS for the heart failure (HF) population has been created previously. We evaluate the history of AVS use in U.S. healthcare as well as map the extent and type of evidence on its quality, stakeholder perspectives, and attempts to perform PCC-related modifications across various healthcare settings as well as in acute-on-chronic or chronic HF specifically, evaluating if a HF-specific AVS (HF-AVS) has been reported. A search of the peer-reviewed literature was conducted of MEDLINE (via Pubmed) and SCOPUS. Select gray literature was included if cited by peer-reviewed articles. Articles were included if they were: 1) written in English, 2) discussed an EHR-generated documented intended for provider-to-patient communication, and 3) were situated within the U.S. healthcare system. Two authors screened relevant articles, with disagreements resolved by consensus. If a resolution was not found the senior author broke ties. Data were extracted by 1 abstractor and checked by at least 1 additional abstractor. This scoping review found that the AVS became a part of the modern electronic health record via legislative action. Incentives for continued use are still in place. While AVS use is widespread its quality is poor, without the necessary readability for PCC models. Patient, provider, and care partner perspectives suggest the need to reduce medical jargon and streamline workflows; however, barriers exist at the level of EHR vendors, preventing large PCC modifications. In contrast, small "embeddable" interventions appear more likely to be successful. No HF-AVS was identified; however, the modification of an existing patient-oriented discharge summary for heart failure (PODS-HF) was present, warranting exploration of embedding the document into EHRs. One potential HF specific "embeddable" intervention is free text prompting patient initiation and up titration of guideline-directed medical therapy and routing to HF nursing and pharmacist teams. If pursued, teams should secure funding, collaborate with EHR vendors, and trial these interventions with objective medication and/or exercise adherence. Limitations to this scoping review are present including the lack of a preregistered protocol. Future work is needed to increase the quality of the AVS evidence base.

Renin angiotensin aldosterone system inhibitors (RAASi) are a mainstay treatment in patients with heart failure with reduced ejection fraction (HFrEF) in part to prevent hospitalizations. However, whether RAASi reduce the risk of hospitalization in Black patients is not entirely clear because enrollment of Black patients in previous clinical trials was low and a previous meta-analysis showed a significant racial disparity: reduction in hospitalizations with an RAASi in White patients but not Black patients. Previous studies relied on the use of self-identified race instead of genomic ancestry. Therefore, this study aimed to investigate the role of self-identified race and genomic ancestry in the racial disparity in RAASi-associated reductions in HFrEF hospitalizations.

The primary outcome was time to first heart failure hospitalization. Data from the Henry Ford Heart Failure Pharmacogenomic Registry (HFPGR) and the GUIDE-IT multi-center randomized control trial were analyzed with Cox proportional hazards models un/adjusted for clinical risk factors, death as a competing risk, and time-varying RAASi exposure. The proportion of Yoruba African ancestry was quantified. Analyses of self-identified race were performed in both the HFPGR and GUIDE-IT. Analysis of genomic ancestry was only performed in the HFPGR since this information was not available in GUIDE-IT. A fixed effect meta-analysis combined results of both the HFPGR and GUIDE-IT for race.

The HFPGR had 1010 total HFrEF patients (Black = 509 and White = 501) with 852 having ancestry quantification (>80% Yoruba African Ancestry = 381 and <5% Yoruba African Ancestry = 471). GUIDE-IT had 810 HFrEF patients (Black = 322 and White = 488). There was no significant difference in the association of RAASi exposure with heart failure hospitalization by race (meta-analysis P value for race*RAASi exposure interaction = .49; Black patients hazard ratio [HR, 95% confidence interval] for RAASi exposure = 0.89 [0.64-1.23)], P = .47; White patients = 1.20 [0.83-1.75], P = .34). Results were similar when analyzed by ancestry (P value for ancestry*RAASi exposure interaction = 0.57; >80% Yoruba African Ancestry = 0.93 [0.51-1.69], P = .80; <5% Yoruba African Ancestry = 1.29 [0.57-2.92], P = .54).

In contrast to a previous meta-analysis, this more contemporary analysis of 2 HFrEF patient datasets demonstrates the absence of a racial disparity in RAASi-associated reductions in heart failure hospitalizations. The difference in this racial disparity over time may be due to improvements in background heart failure therapies, racial differences in health care usage, and the use of more advanced statistical approaches.

Heart failure (HF) remains a leading cause of mortality, responsible for 13% of all deaths worldwide. The prognosis for patients with HF is poor, with only a 50% survival rate within 5 years. A major challenge of ischaemia-driven HF is the loss of cardiomyocytes, compounded by the minimal regenerative capacity of the adult heart. To date, replacement of irreversibly damaged heart muscle can only be achieved by complete heart transplantation. In the past 20 years, cell therapy has emerged and evolved as a promising avenue for cardiac repair and regeneration. During this time, cell therapy for HF has encountered substantial barriers in both preclinical studies and clinical trials but the field continues to progress and evolve from lessons learned from such research. In this Review, we provide an overview of ongoing trials of cell-based and cell product-based therapies for the treatment of HF. Findings from these trials will facilitate the clinical translation of cardiac regenerative and reparative therapies not only by evaluating the safety and efficacy of specific cell-based therapeutics but also by establishing the feasibility of novel or underexplored treatment protocols such as repeated intravenous dosing, personalized patient selection based on pharmacogenomics, systemic versus intramural cell delivery, and epicardial engraftment of engineered tissue products.

Heart failure is a leading cause of hospitalization worldwide, and congestion is the predominant cause of heart failure symptoms and hospitalization. The primary therapy used to treat and prevent congestion has historically been loop diuretics. However, many patients are discharged from hospital with residual congestion, which is associated with persistent heart failure symptoms, adverse outcomes and hospital readmission. Multiple medical strategies and devices have been and are being investigated with the aim of improving decongestion and subsequent heart failure outcomes. Numerous questions exist about the design of clinical trials to test emerging medical and device therapies, including the magnitude of benefit on congestive, kidney and post-discharge outcomes relative to conventional decongestion practices, and how best to implement novel therapies. In this Review, we discuss emerging medical and device strategies targeting congestion in patients with heart failure.

Mounting evidence has established metabolic dysfunction-associated steatotic liver disease (MASLD) as an independent risk factor for heart failure (HF), particularly HFpEF. In this narrative review we explore the impact of MASLD on cardiovascular structure and function. We summarize findings from multiple cohort studies demonstrating that MASLD is associated with distinct patterns of adverse cardiac remodeling, including increased left ventricular concentricity and impaired diastolic function. These subclinical changes in cardiac structure and function often precede overt HF development and appear to occur in the context of multiple interconnected pathways involving metabolic dysfunction, systemic inflammation, adipose tissue dysregulation, vascular dysfunction, and altered hepatic hemodynamics. Early identification of cardiac structural and functional abnormalities through systematic screening may enable timely intervention in this high-risk population. Lifestyle modifications remain foundational, but achieving and maintaining significant weight loss is challenging. Recent clinical trials have shown promising results with cardiometabolic agents, particularly glucagon-like protein 1 receptor agonists, which demonstrate significant weight loss and hepatic and cardiovascular benefits. Despite these advances, key knowledge gaps remain regarding optimal screening strategies, mechanisms linking MASLD to HF, and targeted therapeutic approaches. Addressing these gaps will be essential for developing effective prevention and treatment strategies in this high-risk population.

Heart failure (HF) remains a leading global cause of cardiovascular deaths, with its prevalence expected to rise in the upcoming decade. Measuring the heart ejection fraction (EF) is crucial for diagnosing and monitoring HF. Although echocardiography is the gold standard for EF measurement, it is often inaccessible in remote areas due to its cost and complexity. In contrast, electrocardiography (ECG) is more readily available and affordable, and emerging research suggests a possible link between ECG signals and EF. In this work, we explore the potential of 12-lead ECG signals to estimate EF using various machine learning (ML) and deep learning (DL) models. While recent studies have considered the use of ML or DL for estimating EF, these algorithms are often trained and tested on urban-based populations. However, demographics like those in rural Appalachia, where disease prevalence is extremely high, have been overlooked, potentially due to the unavailability of large volumes of data. Moreover, there have been concerning reports regarding the fairness of AI predictions across different populations, making it crucial to understand the performance of AI models across diverse demographics before their widespread application. To address this, our study focuses on analyzing AI models for EF estimation in the rural Appalachian population. We utilized a 12-lead ECG dataset of 55,500 patients from WVU Medicine hospitals in West Virginia and employed a wide array of AI algorithms, ranging from Random Forest to modern deep learning-based methods like Transformers, to estimate EF. We also considered different thresholds for analyzing these AI algorithms and examined the impact of single and multi-lead ECG signals, and conducted model interpretability analysis. Overall, our comprehensive analysis demonstrated that deep learning-based algorithms achieved the highest performance, with an AUROC of around 0.86 for EF estimation from 12-lead ECG signals. Additionally, we found that while individual ECG leads were insufficient for accurate EF estimation, specific lead combinations significantly improved classification performance.

Background/Objectives: Although nursing complexity and health literacy (HL) are critical determinants of patient outcomes, their combined impact on mortality, hospital re-admissions, and emergency department (ED) visits remains poorly understood. This study aims to measure nursing complexity and HL in hospitalized patients, examine their interaction, and analyze their impacts on mortality, hospital re-admissions, and ED visits over a one-year follow-up period. Methods: Adult patients from two hospital centers were enrolled, excluding those with stays under two days or cognitive impairments. Data were collected at baseline to assess nursing complexity (measured according to the number of nursing diagnoses assigned to patients within 24 h from hospital admission) and HL (assessed using the Single-Item Literacy Screener, SILS). Patients were followed during a 12-month follow-up period to track mortality, hospital re-admissions, and ED visits. Latent class analysis classified patients into distinct nursing complexity and HL profiles. Survival analyses and Cox proportional hazard models were used to evaluate the relationships between variables. Results: At baseline, among the 2667 enrolled patients, 55.9% were classified as having high nursing complexity, and 32% had inadequate HL. High nursing complexity was associated with lower HL (r = 0.384; p < 0.001). During follow-up, 387 patients (14.5%) were lost. Of the remaining sample, mortality occurred in 8.3% of the patients, hospital re-admissions in 27.2%, and ED visits in 16.8%. Nursing complexity was significantly associated with higher mortality (HR: 1.84, adjusted HR: 1.81), but not with hospital re-admissions or ED visits. The patients with inadequate HL (32%) had increased risks of mortality (HR: 11.21, adjusted HR: 7.75), hospital re-admissions (HR: 3.61, adjusted HR: 3.58), and ED visits (HR: 20.78, adjusted HR: 14.45). The patients with both high nursing complexity and inadequate HL had the highest mortality risk and the lowest 12-month survival rate (75%; 95% CI: 71.1-79.1%; p < 0.001). Conclusions: This study demonstrates that both high nursing complexity and inadequate HL independently and jointly contribute to adverse patient outcomes. Interventions targeting HL and supporting patients with high nursing complexity could reduce risks, enhance care, and improve patient survival. While these findings underscore the critical role of both factors in patient outcomes, the limitations include this study's single-country setting and reliance on a single-item HL measure. Future research should validate these findings in broader healthcare contexts and integrate multidimensional HL assessments for a more comprehensive evaluation.

Despite the availability of disease-modifying therapies, scalable strategies for heart failure (HF) risk stratification remain elusive. Portable devices capable of recording single-lead electrocardiograms (ECGs) may enable large-scale community-based risk assessment.

To evaluate whether an artificial intelligence (AI) algorithm can predict HF risk from noisy single-lead ECGs.

A retrospective cohort study of individuals without HF at baseline was conducted among individuals with conventionally obtained outpatient ECGs in the integrated Yale New Haven Health System (YNHHS) and prospective population-based cohorts of the UK Biobank (UKB) and the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Data analysis was performed from September 2023 to February 2025.

AI-ECG-defined risk of left ventricular systolic dysfunction (LVSD).

Among individuals with ECGs, lead I ECGs were isolated and a noise-adapted AI-ECG model (to simulate ECG signals from wearable devices) trained to identify LVSD was deployed. The association of the model probability with new-onset HF, defined as the first HF hospitalization, was evaluated. The discrimination of AI-ECG was compared against 2 risk scores for new-onset HF (Pooled Cohort Equations to Prevent Heart Failure [PCP-HF] and Predicting Risk of Cardiovascular Disease Events [PREVENT] equations) using the Harrel C statistic, integrated discrimination improvement, and net reclassification improvement.

There were 192 667 YNHHS patients (median [IQR] age, 56 [41-69] years; 111 181 women [57.7%]), 42 141 UKB participants (median [IQR] age, 65 [59-71] years; 21 795 women [51.7%]), and 13 454 ELSA-Brasil participants (median [IQR] age, 51 [45-58] years; 7348 women [54.6%]) with baseline ECGs. A total of 3697 (1.9%) developed HF in YNHHS over a median (IQR) of 4.6 (2.8-6.6) years, 46 (0.1%) in UKB over a median (IQR) of 3.1 (2.1-4.5) years, and 31 (0.2%) in ELSA-Brasil over a median (IQR) of 4.2 (3.7-4.5) years. A positive AI-ECG screening result for LVSD was associated with a 3- to 7-fold higher risk for HF, and each 0.1 increment in the model probability was associated with a 27% to 65% higher hazard across cohorts, independent of age, sex, comorbidities, and competing risk of death. AI-ECG's discrimination for new-onset HF was 0.723 (95% CI, 0.694-0.752) in YNHHS, 0.736 (95% CI, 0.606-0.867) in UKB, and 0.828 (95% CI, 0.692-0.964) in ELSA-Brasil. Across cohorts, incorporating AI-ECG predictions alongside PCP-HF and PREVENT equations was associated with a higher Harrel C statistic (difference in addition to PCP-HF, 0.080-0.107; difference in addition to PREVENT, 0.069-0.094). AI-ECG had an integrated discrimination improvement of 0.091 to 0.205 vs PCP-HF and 0.068 to 0.192 vs PREVENT; it had a net reclassification improvement of 18.2% to 47.2% vs PCP-HF and 11.8% to 47.5% vs PREVENT.

Across multinational cohorts, a noise-adapted AI-ECG model estimated HF risk using lead I ECGs, suggesting a potential HF risk-stratification strategy requiring prospective study using wearable and portable ECG devices.

The impact of acute heart failure following acute ischemic stroke on short-term cardiovascular outcomes remains unclear. This study investigated the association between acute heart failure and cardiovascular outcomes within 90 days after acute ischemic stroke.

We retrospectively analyzed 1658 patients with acute ischemic stroke. In-hospital heart failure was defined as heart failure diagnosed on admission or within seven days of hospitalization. The primary outcome was a composite of major adverse cardiovascular events within 90 days of acute ischemic stroke. Secondary outcomes included a composite of fatal or nonfatal heart failure and all-cause mortality. Logistic regression analyses were used to identify predictors of these outcomes. Eighty-two patients with acute ischemic stroke (4.9 %) developed acute heart failure. Major adverse cardiovascular events occurred in 120 patients (7 %) within 90 days. In-hospital heart failure was an independent predictor of major adverse cardiovascular events (odds ratio [OR] 2.25, 95 % confidence interval [CI] 1.11-4.53, p = 0.023) and fatal or nonfatal heart failure (OR 4.72, 95 % CI 1.96-11.35, p = 0.001) within 90 days. However, it was not a significant predictor of all-cause mortality (OR 1.90, 95 % CI 0.94-3.84, p = 0.075).

In-hospital heart failure was a significant predictor of major adverse cardiovascular events and fatal or nonfatal heart failure within 90 days after acute ischemic stroke.

Improved patient monitoring and management after heart failure (HF) hospitalizations are needed to reduce readmissions significantly.

The aim of this study was to investigate the association between monitoring data and readmissions.

PREEMPT-HF (PRecision Event Monitoring for PatienTs with Heart Failure using HeartLogic) was a global, observational, single-arm study enrolling adult HF patients remotely monitored with HeartLogic-capable implantable cardioverter-defibrillator and cardiac resynchronization therapy devices. Patients and clinicians were blinded to the index and alerts. Participants were followed for 12 months for site reporting of events.

A total of 2,155 patients were enrolled at 103 sites and were monitored remotely (39% implantable cardioverter-defibrillators and 61% cardiac resynchronization therapy-defibrillators). There were 243 hospitalizations for HF, of which 156 (64%) were index hospitalizations. There were 25 (28%) unplanned all-cause readmissions in the 30 days after discharge and 45 (46%) all-cause readmissions within 90 days. Alert sensitivity for outpatient visits and hospitalizations for HF was 78.3%, and the false-positive rate was 1.18/year. The HeartLogic index was higher before index hospitalizations for HF when followed by HF or readmission for all causes. Index hospitalizations for HF were also more likely to be followed by readmission for HF in 90 days if the patient was in an alert state (vs out-of-alert state) 1 or 2 weeks before or 2 weeks after the index admission.

HeartLogic index trends were significantly different for patients who were readmitted for HF. These trends suggest that individuals at risk for readmission have had a more sustained worsening and/or insufficient intervention during the initial hospitalization for HF. (PRecision Event Monitoring for PatienTs with Heart Failure using HeartLogic [PREEMPT-HF]; NCT03579641).

Heart failure is a global disease with significant morbidity. Heart transplant (HT) can be a lifesaving therapy for select patients with end-stage heart failure. In 2020, over 7000 HTs were performed globally; 90% of HTs were performed in the United States and Western Europe, with only 10% throughout the rest of the world. In this article, we offer an overview of the global landscape of HT, exploring challenges and prospects worldwide. We review HT practices, rates and post-HT outcomes, underscoring the differences between countries within each region. We review limitations hindering HT expansion, such as sociocultural factors, as seen in Japan and Israel; health care funding, in countries like India and South Africa; socioeconomic disparities in access, like the United States; and shortage in organ supply, as seen in China and Saudi Arabia. This review underscores the need to address limitations and highlights opportunities to enhance global HT accessibility, especially in lower- and middle-income countries.

Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome with various causes and a pathophysiology that leads to diverse spectrum of phenotypes. In contrast to a wide range of established treatments for heart failure with reduced ejection fraction (HFrEF), effective medical treatment options for HFpEF are relatively limited with excessively high residual risk of morbidity and mortality. Device-based therapies have emerged as a promising strategy to improve outcomes in patients with HFpEF. Herein, we present data on devices in HFpEF targeting various unique mechanisms including structural inventions, autonomic modulation, and electrophysiologic modulation as well as remote monitoring devices. While early studies of these therapeutic devices have not definitively demonstrated clinical benefits in HFpEF, growing evidence suggests potential benefits in select patient populations for some of these emerging technologies.

Although lipoprotein(a) [Lp(a)] level elevation is associated with new-onset heart failure (HF), it is unclear if elevated Lp(a) levels predict cardiovascular events in patients with chronic HF. Thus, we examined the association between Lp(a) levels and adverse cardiovascular outcomes in patients with HF.

A total of 1088 patients with HF undergoing cardiac catheterization at Emory-affiliated hospitals from 2004 to 2022 were divided into low (<30 mg/dL), intermediate (30-49 mg/dL), and high (≥50 mg/dL) Lp(a) groups. The primary outcome was the composite of cardiovascular death and HF hospitalization. Outcomes were assessed by Lp(a) group with competing risk modeling accounting for noncardiovascular death after adjustment for demographics, traditional cardiovascular risk factors, ejection fraction, ischemic HF etiology, and N-terminal prohormone of brain natriuretic peptide. Sensitivity analyses were performed to explore for heterogeneity of effect. The median age was 67 years, 34% were women, 18% were Black, 74% had ischemic HF, and 60% had an ejection fraction of ≤40%. During a median follow-up time of 4.3 years, 474 composite events (44%) occurred. When compared with participants with Lp(a) <30 mg/dL after multivariable adjustment, those with Lp(a) 30-49 mg/dL (subdistribution hazard ratio [sHR] 1.35, 95% confidence interval 1.04-1.76, P = .025) and Lp(a) ≥50 mg/dL (sHR 1.38, 95% confidence interval 1.11-1.72, P = .004) had a significantly higher risk of cardiovascular death or HF hospitalization. This relationship seemed to diminish over time and was nominally stronger in those with ischemic versus nonischemic HF (Pinteraction = .06), but did not meet significance after adjustment for multiple hypothesis testing.

In patients with HF, Lp(a) ≥30 mg/dL independently predicts the risk of cardiovascular death or HF hospitalization.

Background: The purpose of the study is to investigate a possible predictive value of irisin for improved left ventricular (LV) ejection fraction (EF) in discharged patients with known heart failure with reduced ejection fraction (HFrEF). Methods: We included in the study 313 patients who were discharged with HFrEF (at admission, LVEF ≤ 40%) and monitored for 3 months. HF with improved LVEF (HFimpEF) was characterized as a >40% increase in LVEF on transthoracic B-mode echocardiography within 3 months of follow-up. Circulating biomarkers including NT-proBNP and irisin were detected at baseline and after 3 months of observation. By the third month, 117 (37.4%) patients had HFimpEF, whereas 196 individuals were categorized as having persistent HFrEF. Results: We found that HFimpEF was related to lower LV end-diastolic dimensions and concentrations of NT-proBNP and higher left atrial volume index (LAVI) and irisin concentrations than those with persistent HFrEF. The most balanced cut-offs of irisin and NT-proBNP concentrations (improved LVEF versus non-improved LVEF) were 10.8 ng/mL and 1540 pmol/L, respectively. Multivariate regression analysis showed that atrial fibrillation (odds ratio [OR] = 0.95; p = 0.010), LAVI < 39 mL/m2 (OR = 1.23; p = 0.001), irisin levels ≥ 10.8 ng/mL (OR = 1.73; p = 0.001), and NT-proBNP < 1540 pmol/mL (OR = 1.47; p = 0.001) independently predicted HFimpEF. The discriminative ability of irisin ≥ 10.8 ng/mL was better than NT-proBNP < 1540 pmol/mL; the predictive ability of irisin alone was not improved by the combined model (irisin added to NT-proBNP). Conclusions: serum irisin ≥ 10.8 ng/mL predicted HFimpEF independently of natriuretic peptide in HFrEF patients.