Search

Steatotic liver disease (SLD) is a worldwide public health problem, causing considerable morbidity and mortality. Patients with SLD are at increased risk for major adverse cardiovascular (CV) events, type 2 diabetes mellitus and chronic kidney disease. Conversely, patients with cardiometabolic conditions have a high prevalence of SLD. In addition to epidemiological evidence linking many of these conditions, there is evidence of shared pathophysiological processes. In December 2022, a unique multi‐stakeholder, multi‐specialty meeting, called MOSAIC (Metabolic multi Organ Science Accelerating Innovation in Clinical Trials) was convened to foster collaboration across metabolic, hepatology, nephrology and CV disorders. One of the goals of the meeting was to consider approaches to drug development that would speed regulatory approval of treatments for multiple disorders by combining liver and cardiorenal endpoints within a single study. Non‐invasive tests, including biomarkers and imaging, are needed in hepatic and cardiorenal trials. They can be used as trial endpoints, to enrich trial populations, to diagnose and risk stratify patients and to assess treatment efficacy and safety. Although they are used in proof of concept and phase 2 trials, they are often not acceptable for regulatory approval of therapies. The challenge is defining the optimal combination of biomarkers, imaging and morbidity/mortality outcomes and ensuring that they are included in future trials while minimizing the burden on patients, trialists and trial sponsors. This paper provides an overview of some of the wide array of CV, liver and kidney measurements that were discussed at the MOSAIC meeting. [ABSTRACT FROM AUTHOR]

Purpose of Review: To review ongoing and planned clinical trials of weight loss among individuals with or at high risk of heart failure. Recent Findings: Intentional weight loss via semaglutide among persons with heart failure and preserved ejection fraction and obesity significantly improves weight loss and health status as assessed by the KCCQ-CSS score and is associated with improvements in 6-min walk test. Summary: Ongoing and planned trials will explore the role of intentional weight loss with treatments such as semaglutide or tirzepatide for individuals with heart failure across the entire ejection fraction spectrum. [ABSTRACT FROM AUTHOR]

Summary: Obesity is a worsening public health epidemic that remains challenging to manage. Obesity substantially increases the risk of cardiovascular diseases and presents a significant financial burden on the healthcare system. Digital health interventions, specifically telemedicine, may offer an attractive and viable solution for managing obesity. During the COVID‐19 pandemic, the need for a safer alternative to in‐person visits led to the increased popularity of telemedicine. Multiple studies have tested the efficacy of telemedicine modalities, including digital coaching via videoconferencing sessions, e‐health monitoring using wearable devices, and asynchronous forms of communication such as online chatrooms with counselors. In this review, we discuss the available evidence for telemedicine interventions in managing obesity, review current challenges and barriers to using telemedicine, and outline future directions to optimize the management of patients with obesity using telemedicine. [ABSTRACT FROM AUTHOR]

Highly bioavailable inorganic phosphate (Pi) is present in large quantities in the typical Western diet and represents a large fraction of total phosphate intake. Dietary Pi excess induces exercise intolerance and skeletal muscle mitochondrial dysfunction in normal mice. However, the relevance of this to humans remains unknown. The study was conducted on 13 individuals without a history of cardiopulmonary disease (46% female, 15% Black participants) enrolled in the pilot-phase of the Dallas Heart and Mind Study. Total dietary phosphate was estimated from 24-h dietary recall (ASA24). Muscle ATP synthesis was measured at rest, and phosphocreatinine (PCr) dynamics was measured during plantar flexion exercise using 7-T 31P magnetic resonance (MR) spectroscopy in the calf muscle. Correlation was assessed between dietary phosphate intake normalized to total caloric intake, resting ATP synthesis, and PCr depletion during exercise. Higher dietary phosphate intake was associated with lower resting ATP synthesis (r = –0.62, P = 0.03), and with higher levels of PCr depletion during plantar flexion exercise relative to the resting period (r = –0.72; P = 0.004). These associations remain significant after adjustment for age and estimated glomerular filtration rate (both P < 0.05). High dietary phosphate intake was also associated with lower serum Klotho levels, and Klotho levels are in turn associated with PCr depletion and higher ADP accumulation post exercise. Our study suggests that higher dietary phosphate is associated with reduced skeletal muscle mitochondrial function at rest and exercise in humans providing new insight into potential mechanisms linking the Western diet to impaired energy metabolism. NEW & NOTEWORTHY: This is the first translational research study directly demonstrating the adverse effects of dietary phosphate on muscle energy metabolism in humans. Importantly, our data show that dietary phosphate is associated with impaired muscle ATP synthesis at rest and during exercise, independent of age and renal function. This is a new biologic paradigm with significant clinical dietary implications. [ABSTRACT FROM AUTHOR]

Aim: Left ventricular (LV) global longitudinal strain (GLS) may detect subtle abnormalities in myocardial contractility among individuals with normal LV ejection fraction (LVEF). However, the prognostic implications of GLS among healthy, community‐dwelling adults is not well‐established. Methods and results: Overall, 2234 community‐dwelling adults (56% women, 47% Black) with LVEF ≥50% without a history of cardiovascular disease (CVD) from the Dallas Heart Study who underwent cardiac magnetic resonance (CMR) with GLS assessed by feature tracking CMR (FT‐CMR) were included. The association of GLS with the risk of incident major adverse cardiovascular events (MACE; composite of incident myocardial infarction, incident heart failure [HF], hospitalization for atrial fibrillation, coronary revascularization, and all‐cause death), and incident HF or death were assessed with adjusted Cox proportional hazards models. A total of 309 participants (13.8%) had MACE during a median follow‐up duration of 17 years. Participants with the worst GLS (Q4) were more likely male and of the Black race with a history of tobacco use and diabetes with lower LVEF, higher LV end‐diastolic volume, and higher LV mass index. Cumulative incidence of MACE was higher among participants with worse (Q4 vs. Q1) GLS (20.4% vs. 9.0%). In multivariable‐adjusted Cox models that included clinical characteristics, cardiac biomarkers and baseline LVEF, worse GLS (Q4 vs. Q1) was associated with a significantly higher risk of MACE (hazard ratio [HR] 1.55, 95% confidence interval [CI] 1.07–2.24, p = 0.02) and incident HF or death (HR 1.57, 95% CI 1.03–2.38, p = 0.04). Conclusions: Impaired LV GLS assessed by FT‐CMR among adults free of cardiovascular disease is associated with a higher risk of incident MACE and incident HF or death independent of cardiovascular risk factors, cardiac biomarkers and LVEF. [ABSTRACT FROM AUTHOR]

The oblique random survival forest (RSF) is an ensemble supervised learning method for right-censored outcomes. Trees in the oblique RSF are grown using linear combinations of predictors, whereas in the standard RSF, a single predictor is used. Oblique RSF ensembles have high prediction accuracy, but assessing many linear combinations of predictors induces high computational overhead. In addition, few methods have been developed for estimation of variable importance (VI) with oblique RSFs. We introduce a method to increase computational efficiency of the oblique RSF and a method to estimate VI with the oblique RSF. Our computational approach uses Newton-Raphson scoring in each non-leaf node, We estimate VI by negating each coefficient used for a given predictor in linear combinations, and then computing the reduction in out-of-bag accuracy. In benchmarking experiments, we find our implementation of the oblique RSF is hundreds of times faster, with equivalent prediction accuracy, compared to existing software for oblique RSFs. We find in simulation studies that "negation VI" discriminates between relevant and irrelevant numeric predictors more accurately than permutation VI, Shapley VI, and a technique to measure VI using analysis of variance. All oblique RSF methods in the current study are available in the aorsf R package, and additional are available online. [ABSTRACT FROM AUTHOR]

This article discusses the results of a post-hoc analysis of the VERTIS CV trial, which examined the effects of the medication ertugliflozin on the risk of hospitalization for heart failure (HHF) in patients with type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease. The study found that ertugliflozin significantly reduced the risk of first HHF in the overall cohort of participants. However, the treatment effect was more pronounced in individuals with a pre-trial ejection fraction (EF) of less than 45% and attenuated in those with an EF greater than 60%. These findings contribute to the understanding of the efficacy of SGLT2 inhibitors in reducing the risk of HHF across different EF ranges. [Extracted from the article]

Background Multidomain lifestyle interventions may slow aging as captured by deficit accumulation frailty indices; however, it is unknown whether benefits extend beyond intervention delivery. Methods We developed a deficit accumulation frailty index (FI-E) to span the 10 years that the Action for Health in Diabetes (Look AHEAD) randomized controlled clinical trial delivered interventions (a multidomain lifestyle intervention focused on caloric restriction, increased physical activity, and diet compared to a control condition) and to extend across an additional 8 years post-delivery. The study cohort included 5 145 individuals, aged 45–76 years at enrollment, who had type 2 diabetes and either obesity or overweight. Results Overall, FI-E scores were relatively lower among lifestyle participants throughout follow-up, averaging 0.0130 [95% confidence interval: 0.0104, 0.0156] (p <.001) less across the 18 years. During Years 1–8, the mean relative difference between control and lifestyle participants' FI-E scores was 0.0139 [0.0115, 0.0163], approximately 10% of the baseline level. During Years 9–18, this average difference was 0.0107 [0.0066, 0.0148]. Benefits were comparable for individuals grouped by baseline age and body mass index and sex but were not evident for those entering the trial with a history of cardiovascular disease. Conclusions Multidomain lifestyle intervention may slow biological aging long term, as captured by an FI-E. Clinical Trials Registration Number: NCT00017953 [ABSTRACT FROM AUTHOR]

Aims: Heart failure with reduced ejection fraction (HFrEF) is treatable but guideline‐directed medical therapy (GDMT) may not be affordable or accessible to people living with the disease. Methods and results: In this cross‐sectional survey, we investigated the price, affordability, and accessibility of four pivotal classes of HFrEF GDMT: angiotensin‐converting enzyme inhibitors (ACEi), angiotensin receptor blockers (ARB) or angiotensin‐neprilysin inhibitors (ARNI); beta‐blockers; mineralocorticoid receptor antagonists (MRA); and sodium glucose co‐transporter 2 inhibitors (SGLT2i). We sampled online or community pharmacies in 10 countries across a range of World Bank income groups, assessing mean 30 day retail prescription prices, affordability relative to gross national income per capita per month, and accessibility. We reported median price ratios relative to the International Reference Standard. We performed a literature review to evaluate accessibility to GDMT classes through publicly funded drug programmes in each country. HFrEF GDMT prices, both absolute and relative to the international reference, were highest in the United States and lowest in Pakistan and Bangladesh. The most expensive drug was the ARNI, sacubitril/valsartan, with a mean (standard deviation, SD) 30 day price ranging from $11.06 (0.81) in Pakistan to $611.50 (3.54) in United States. The least expensive drug was the MRA, spironolactone, with a mean (SD) 30 day price ranging from $0.18 (0.00) in Pakistan to $12.32 (0.00) in England. Affordability (SD) of quadruple therapy—ARNI, beta‐blockers, MRA, and SGLT2i—was best in high‐income and worst in low‐income countries, ranging from 1.49 (0.00)% of gross national income per capita per month in England to 232.47 (31.47)% in Uganda. Publicly funded drug programmes offset costs for eligible patients, but ARNI and SGLT2i were inaccessible through these programmes in low‐ and middle‐income countries. Price, affordability, and access were substantially improved in all countries by substituting ARNI for ACEi/ARB. Conclusions: There was marked variation between countries in the retail price of HFrEF GDMT. Despite higher prices in high‐income countries, GDMT was more accessible and affordable than in low‐ and middle‐income countries. Publicly funded drug programmes in lower income countries increased affordability but limited access to newer HFrEF GDMT classes. Pharmaco‐disparities must be addressed to improve HFrEF outcomes globally. [ABSTRACT FROM AUTHOR]

For decades, heart failure with preserved ejection fraction (HFpEF) proved an elusive entity to treat. Sodium-glucose cotransporter 2 (SGLT2) inhibitors have recently been shown to reduce the composite of heart failure hospitalization or cardiovascular death in patients with HFpEF in the landmark DELIVER and EMPEROR-Preserved trials. While improvements in blood sugar, blood pressure, and attenuation of kidney disease progression all may play some role, preclinical and translational research have identified additional mechanisms of these agents. The SGLT2 inhibitors have intriguingly been shown to induce a nutrient-deprivation and hypoxic-like transcriptional paradigm, with increased ketosis, erythropoietin, and autophagic flux in addition to altering iron homeostasis, which may contribute to improved cardiac energetics and function. These agents also reduce epicardial adipose tissue and alter adipokine signalling, which may play a role in the reductions in inflammation and oxidative stress observed with SGLT2 inhibition. Emerging evidence also indicates that these drugs impact cardiomyocyte ionic homeostasis although whether this is through indirect mechanisms or via direct, off-target effects on other ion channels has yet to be clearly characterized. Finally, SGLT2 inhibitors have been shown to reduce myofilament stiffness as well as extracellular matrix remodelling/fibrosis in the heart, improving diastolic function. The SGLT2 inhibitors have established themselves as robust, disease-modifying therapies and as recent trial results are incorporated into clinical guidelines, will likely become foundational in the therapy of HFpEF. [ABSTRACT FROM AUTHOR]

A study published in the European Journal of Heart Failure examined the association between a diabetes-specific heart failure risk score (WATCH-DM) and the presence of subclinical cardiomyopathy in individuals with diabetes. The study included 150 adults with diabetes and found that those with high WATCH-DM scores had a significantly greater prevalence of diabetic cardiomyopathy (DbCM) compared to those with low scores. The study suggests that the WATCH-DM risk score may be a useful tool for identifying individuals with diabetes who are at high risk of developing heart failure. However, the study has limitations, such as a small sample size and the inability to establish causality. The study was supported by a research grant and the authors have disclosed potential conflicts of interest. [Extracted from the article]

This article discusses the complexity of exercise intolerance in heart failure with preserved ejection fraction (HFpEF). Exercise intolerance is a common symptom of HFpEF and is associated with a poor quality of life and increased risk of adverse outcomes. The article highlights a study that characterizes the haemodynamic profiles of HFpEF patients and identifies four clinically defined phenogroups: cardiometabolic, left atrial myopathy, pulmonary vascular disease, and vascular stiffening. The study findings reveal distinct exercise haemodynamic impairments across these phenogroups and provide insights into the physiologic basis of disease progression. The article suggests that personalized treatment approaches based on these phenogroups may improve exercise capacity and quality of life for HFpEF patients. [Extracted from the article]

This article discusses the challenges in diagnosing heart failure with preserved ejection fraction (HFpEF) and the potential of artificial intelligence (AI) and natural language processing (NLP) to improve diagnosis. HFpEF is difficult to diagnose and often underdiagnosed, leading to missed opportunities for treatment and management. The study by Wu et al. applied NLP to a database of patients with a clinical diagnosis of heart failure and found a significant disparity in the diagnosis rates of HFpEF. NLP can aid clinicians in identifying high-risk patients and prompt further investigation for accurate diagnosis and personalized treatment. The incorporation of AI and NLP into HFpEF detection shows promise for enhancing diagnosis, monitoring disease progression, and tailoring treatment regimens. However, further research, validation, and ethical considerations are needed for the full integration of AI and NLP into clinical practice. [Extracted from the article]

Aims: Sex differences in long‐term outcomes following hospitalization for heart failure (HF) across ejection fraction (EF) subtypes are not well described. In this study, we evaluated the risk of mortality and rehospitalization among males and females across the spectrum of EF over 5 years of follow‐up following an index HF hospitalization event. Methods and results: Patients hospitalized with HF between 1 January 2006 and 31 December 2014 from the American Heart Association's Get With The Guidelines‐Heart Failure registry with available 5‐year follow‐up using Medicare Part A claims data were included. The association between sex and risk of mortality and readmission over a 5‐year follow‐up period for each HF subtype (HF with reduced EF [HFrEF, EF ≤40%], HF with mildly reduced EF [HFmrEF, EF 41–49%], and HF with preserved EF [HFpEF, EF >50%]) was assessed using adjusted Cox models. The effect modification by the HF subtype for the association between sex and outcomes was assessed by including multiplicative interaction terms in the models. A total of 155 670 patients (median age: 81 years, 53.4% female) were included. Over 5‐year follow‐up, males and females had comparably poor survival post‐discharge; however, females (vs. males) had greater years of survival lost to HF compared with the median age‐ and sex‐matched US population (HFpEF: 17.0 vs. 14.6 years; HFrEF: 17.3 vs. 15.1 years; HFmrEF: 17.7 vs. 14.6 years for age group 65‐69 years). In adjusted analysis, females (vs. males) had a lower risk of 5‐year mortality (adjusted hazard ratio [aHR] 0.89, 95% confidence interval [CI] 0.87–0.90, p < 0.0001), and the risk difference was most pronounced among patients with HFrEF (aHR 0.87, 95% CI 0.85–0.89; pinteraction[sex*HF subtype] = 0.04). Females (vs. males) had a higher adjusted risk of HF readmission over 5‐year follow‐up (aHR 1.06, 95% CI 1.04–1.08, p < 0.0001), with the risk difference most pronounced among patients with HFpEF (aHR 1.11, 95% CI 1.07–1.14; pinteraction[sex*HF subtype] = 0.001). Conclusions: While females (vs. males) had lower adjusted mortality, females experienced a significantly greater loss in survival time than the median age‐ and sex‐matched US population and had a greater risk of rehospitalization over 5 years following HF hospitalization. [ABSTRACT FROM AUTHOR]

Heart failure (HF) is a heterogeneous syndrome affecting more than 60 million individuals globally. Despite recent advancements in understanding of the pathophysiology of HF, many issues remain including residual risk despite therapy, understanding the pathophysiology and phenotypes of patients with HF and preserved ejection fraction, and the challenges related to integrating a large amount of disparate information available for risk stratification and management of these patients. Risk prediction algorithms based on artificial intelligence (AI) may have superior predictive ability compared to traditional methods in certain instances. AI algorithms can play a pivotal role in the evolution of HF care by facilitating clinical decision making to overcome various challenges such as allocation of treatment to patients who are at highest risk or are more likely to benefit from therapies, prediction of adverse outcomes, and early identification of patients with subclinical disease or worsening HF. With the ability to integrate and synthesize large amounts of data with multidimensional interactions, AI algorithms can supply information with which physicians can improve their ability to make timely and better decisions. In this review, we provide an overview of the AI algorithms that have been developed for establishing early diagnosis of HF, phenotyping HF with preserved ejection fraction, and stratifying HF disease severity. This review also discusses the challenges in clinical deployment of AI algorithms in HF, and the potential path forward for developing future novel learning‐based algorithms to improve HF care. [ABSTRACT FROM AUTHOR]

Their findings illuminate the potential of these models to improve the early identification of patients at risk of developing HF, particularly stage B HF, which could lead to early intervention strategies and, ultimately, improved patient outcomes. B This article refers to 'Prediction models for heart failure in the community: A systematic review and meta-analysis' by R Nadarajah I et al i ., published in this issue on pages 1724-1738. b Heart failure (HF) is a complex clinical syndrome that represents a significant and growing public health concern worldwide.[1] With an aging population and increasing prevalence of risk factors such as hypertension, diabetes, and obesity, the incidence of HF is only expected to increase. [Extracted from the article]

Aims Ketone bodies (KB) are an important alternative metabolic fuel source for the myocardium. Experimental and human investigations suggest that KB may have protective effects in patients with heart failure. This study aimed to examine the association between KB and cardiovascular outcomes and mortality in an ethnically diverse population free from cardiovascular disease (CVD). Methods and results This analysis included 6796 participants (mean age 62 ± 10 years, 53% women) from the Multi-Ethnic Study of Atherosclerosis. Total KB was measured by nuclear magnetic resonance spectroscopy. Multivariable-adjusted Cox proportional hazard models were used to examine the association of total KB with cardiovascular outcomes. At a mean follow-up of 13.6 years, after adjusting for traditional CVD risk factors, increasing total KB was associated with a higher rate of hard CVD, defined as a composite of myocardial infarction, resuscitated cardiac arrest, stroke, and cardiovascular death, and all CVD (additionally included adjudicated angina) [hazard ratio, HR (95% confidence interval, CI): 1.54 (1.12–2.12) and 1.37 (1.04–1.80) per 10-fold increase in total KB, respectively]. Participants also experienced an 87% (95% CI: 1.17–2.97) increased rate of CVD mortality and an 81% (1.45–2.23) increased rate of all-cause mortality per 10-fold increase in total KB. Moreover, a higher rate of incident heart failure was observed with increasing total KB [1.68 (1.07–2.65), per 10-fold increase in total KB]. Conclusion The study found that elevated endogenous KB in a healthy community-based population is associated with a higher rate of CVD and mortality. Ketone bodies could serve as a potential biomarker for cardiovascular risk assessment. [ABSTRACT FROM AUTHOR]

Natriuretic peptides, brain (B‐type) natriuretic peptide (BNP) and N‐terminal prohormone of brain natriuretic peptide (NT‐proBNP) are globally and most often used for the diagnosis of heart failure (HF). In addition, they can have an important complementary role in the risk stratification of its prognosis. Since the development of angiotensin receptor–neprilysin inhibitors (ARNIs), the use of natriuretic peptides as therapeutic agents has grown in importance. The present document is the result of the Trilateral Cooperation Project among the Heart Failure Association of the European Society of Cardiology, the Heart Failure Society of America and the Japanese Heart Failure Society. It represents an expert consensus that aims to provide a comprehensive, up‐to‐date perspective on natriuretic peptides in the diagnosis and management of HF, with a focus on the following main issues: (1) history and basic research: discovery, production and cardiovascular protection; (2) diagnostic and prognostic biomarkers: acute HF, chronic HF, inclusion/endpoint in clinical trials, and natriuretic peptide‐guided therapy; (3) therapeutic use: nesiritide (BNP), carperitide (ANP) and ARNIs; and (4) gaps in knowledge and future directions. [ABSTRACT FROM AUTHOR]

Background: Housing instability is a key social determinant of health and has been linked to adverse short- and long-term health. Eviction reflects a severe form of housing instability and disproportionately affects minority and women residents in the USA; however, its relationship with mortality has not previously been described. Objective: To evaluate the independent association of county-level eviction rates with all-cause mortality in the USA after adjustment for county demographic, socioeconomic, and health-related characteristics. Design: Cross-sectional. Participants: Six hundred eighty-six US counties with available 2016 county-level eviction and mortality data. Exposure: 2016 US county-level eviction rate. Outcome: 2016 US county-level age-adjusted all-cause mortality. Key Results: Among 686 counties (66.1 million residents, 50.5% [49.7–51.2] women, 2% [0.5–11.1] Black race) with available eviction and mortality data in 2016, we observed a significant and graded relationship between county-level eviction rate and all-cause mortality. Counties in the highest eviction tertile demonstrated a greater proportion of residents of Black race and women and a higher prevalence of poverty and comorbid health conditions. After adjustment for county-level sociodemographic traits and prevalent comorbid health conditions, age-adjusted all-cause mortality was highest among counties in the highest eviction tertile (Tertile 3 vs 1 (per 100,000 people) 33.57: 95% CI: 10.5–56.6 p=.004). Consistent results were observed in continuous analysis of eviction, with all-cause mortality increasing by 9.32 deaths per 100,000 people (4.77, 13.89, p<.0001) for every 1% increase in eviction rates. Significant interaction in the relationship between eviction and all-cause mortality was observed by the proportion of Black and women residents. Conclusions: In this cross-sectional analysis, county-level eviction rates were significantly associated with all-cause mortality with the strongest effects observed among counties with the highest proportion of Black and women residents. State and federal protections from evictions may help to reduce the health consequences of housing instability and address disparities in health outcomes. [ABSTRACT FROM AUTHOR]

Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous entity with complex pathophysiology and manifestations. Phenomapping is the process of applying statistical learning techniques to patient data to identify distinct subgroups based on patterns in the data. Phenomapping has emerged as a technique with potential to improve the understanding of different HFpEF phenotypes. Phenomapping efforts have been increasing in HFpEF over the past several years using a variety of data sources, clinical variables, and statistical techniques. This review summarizes methodologies and key takeaways from these studies, including consistent discriminating factors and conserved HFpEF phenotypes. We argue that phenomapping results to date have had limited implications for clinical care and clinical trials, given that the phenotypes, as currently described, are not reliably identified in each study population and may have significant overlap. We review the inherent limitations of aggregating and utilizing phenomapping results. Lastly, we discuss potential future directions, including using phenomapping to optimize the likelihood of clinical trial success or to drive discovery in mechanisms of the disease process of HFpEF. [ABSTRACT FROM AUTHOR]

Background Individuals with diabetes have a high frailty burden and increased risk of heart failure (HF). In this study, we evaluated the association of baseline and longitudinal changes in frailty with risk of HF and its subtypes: HF with preserved ejection fraction (HFpEF), and HF with reduced ejection fraction (HFrEF). Methods Participants (age: 45–76 years) of the Look AHEAD trial without prevalent HF were included. The frailty index (FI) was used to assess frailty burden using a 35-variable deficit model. The association between baseline and longitudinal changes (1- and 4-year follow-up) in FI with risk of overall HF, HFpEF (ejection fraction [EF] ≥ 50%), and HFrEF (EF < 50%) independent of other risk factors and cardiorespiratory fitness was assessed using adjusted Cox models. Results The study included 5 100 participants with type 2 diabetes mellitus, of which 257 developed HF. In adjusted analysis, higher frailty burden was significantly associated with a greater risk of overall HF. Among HF subtypes, higher baseline FI was significantly associated with risk of HFpEF (hazard ratio [HR] [95% CI] per 1- SD higher FI: 1.37 [1.15–1.63]) but not HFrEF (HR [95% CI]: 1.19 [0.96–1.46]) after adjustment for potential confounders, including traditional HF risk factors. Among participants with repeat measures of FI at 1- and 4-year follow-up, an increase in frailty burden was associated with a higher risk of HFpEF (HR [95% CI] per 1- SD increase in FI at 4 years: 1.78 [1.35–2.34]) but not HFrEF after adjustment for other confounders. Conclusions Among individuals with type 2 diabetes mellitus, higher baseline frailty and worsening frailty burden over time were independently associated with higher risk of HF, particularly HFpEF after adjustment for other confounders. [ABSTRACT FROM AUTHOR]

Aims: To evaluate the contribution of baseline and longitudinal changes in cardiometabolic health (CMH) towards heart failure (HF) risk among adults with type 2 diabetes (T2D). Methods and results: Participants of the Look AHEAD trial with T2D and without prevalent HF were included. Adjusted Cox models were used to create a CMH score incorporating target levels of parameters weighted based on relative risk for HF. The associations of baseline and changes in the CMH score with risk of overall HF, HF with preserved (HFpEF) and reduced ejection fraction (HFrEF) were assessed using Cox models. Among the 5080 participants, 257 incident HF events occurred over 12.4 years of follow‐up. The CMH score included 2 points each for target levels of waist circumference, glomerular filtration rate, urine albumin‐to‐creatinine ratio, and 1 point each for blood pressure and glycated haemoglobin at target. High baseline CMH score (6–8) was significantly associated with lower overall HF risk (adjusted hazard ratio [HR], ref = low score (0–3): 0.31, 95% confidence interval [CI] 0.21–0.47) with similar associations observed for HFpEF and HFrEF. Improvement in CMH was significantly associated with lower risk of overall HF (adjusted HR per 1‐unit increase in score at 4 years: 0.80, 95% CI 0.70–0.91). In the ACCORD validation cohort, the baseline CMH score performed well for predicting HF risk with adequate discrimination (C‐index 0.70), calibration (chi‐square 5.53, p = 0.70), and risk stratification (adjusted HR [high (6–8) vs. low score (0–3)]: 0.35, 95% CI 0.26–0.46). In the Look AHEAD subgroup with available biomarker data, incorporating N‐terminal pro‐B‐type natriuretic peptide to the baseline CMH score improved model discrimination (C‐index 0.79) and risk stratification (adjusted HR [high (8–10) vs. low score (0–4)]: 0.18, 95% CI 0.09–0.35). Conclusions: Achieving target levels of more CMH parameters at baseline and sustained improvements were associated with lower HF risk in T2D. [ABSTRACT FROM AUTHOR]

Aims: We aimed to investigate the impact of obstructive coronary artery disease (CAD) in patients with acute decompensated heart failure (ADHF), and examine potential differences in prognostic utility for heart failure with reduced (HFrEF) versus preserved ejection fraction (HFpEF). Methods and results: The Atherosclerosis Risk in Communities study conducted hospital surveillance of ADHF from 2005 to 2014. Obstructive CAD was defined as ≥50% or ≥75% stenosis, respectively, for the left main and other major epicardial arteries. Adjusted associations between obstructive CAD and 30‐, 60‐, and 90‐day mortality were analysed. A total of 934 (4146 weighted) patients admitted with ADHF (mean age 72 years, 46% women, 30% Black, 30% HFpEF) had available angiography (61% performed in hospital). Obstructive CAD was more prevalent with HFrEF than HFpEF, whether at the left main (15% vs. 11%), left anterior descending (LAD) (48% vs. 30%), left circumflex (37% vs. 32%), right coronary (42% vs. 32%), or multiple coronary arteries (45% vs. 33%). In‐hospital revascularization was performed in 25% and 22% of patients with HFrEF and HFpEF, respectively. Obstructive CAD was associated with higher adjusted mortality, particularly with left main or LAD involvement, and had a more pronounced association with 90‐day mortality in HFrEF (odds ratio [OR] 2.77; 95% confidence interval [CI] 1.53–5.02) than HFpEF (OR 0.94; 95% CI 0.36–2.41) (p‐interaction = 0.05). Conclusion: Patients hospitalized with ADHF and coexisting obstructive CAD have higher short‐term mortality, warranting the need for effective interventions and secondary prevention. [ABSTRACT FROM AUTHOR]

Introduction: Texas Health Resources (THR), a large, nonprofit health care system based in the Dallas‐Fort Worth area, has collaborated with the University of Texas Southwestern Medical Center (UTSW) to develop and operate a unique, integrated approach for Learning Health System (LHS) workforce development. This training model centers on academic health system faculty members conducting later‐stage translational research within a partnering regional care delivery organization. Methods: The THR Clinical Scholars Program engages early career UTSW faculty members to conduct studies that are likely to have an impact on care delivery at the health system level. Interested candidates submit formal applications to the program. A joint committee comprised of senior research faculty from UTSW and THR clinical leadership reviews proposals with a focus on the shared LHS needs of both institutions—developing high quality research output that can be applied to enhance care delivery. A key prioritization criterion for funding is the degree to which the research addresses a question relevant to THR as a high‐volume network with multiple channels for consumers to access care. The program emphasis is on supporting embedded research initiatives using health system data to generate knowledge that will improve the quality and efficiency of care for the patient populations served by the participant organizations. Results: We discuss specific strategic and tactical components of the THR Clinical Scholars Program including an overview of the academic affiliation agreement between the collaborating organizations, criteria for successful program applications, data sharing, and funding. We also share project summaries from selected clinical scholars as examples of the LHS research done in the program to date. Conclusion: This experience report provides an implementation framework for other academic health systems interested in adopting similar LHS workforce training models with community partners. [ABSTRACT FROM AUTHOR]

Aims: Sodium‐glucose cotransporter 2 (SGLT2) inhibitors have been shown to reduce the risk of hospitalization for heart failure (HHF) and composite kidney outcomes, but the mediators underlying these benefits are unknown. Materials and methods: Among participants from VERTIS CV, a trial of patients with type 2 diabetes mellitus and atherosclerotic cardiovascular disease randomized to ertugliflozin versus placebo, Cox proportional hazards regression models were used to evaluate the percentage mediation of ertugliflozin efficacy on the first HHF and kidney composite outcome in 26 potential mediators. Time‐dependent approaches were used to evaluate associations between early (change from baseline to the first post‐baseline measurement) and average (weighted average of change from baseline using all post‐baseline measurements) changes in covariates with clinical outcomes. Results: For the HHF analyses, early changes in four biomarkers (haemoglobin, haematocrit, serum albumin and urate) and average changes in seven biomarkers (early biomarkers + weight, chloride and serum protein) were identified as fulfilling the criteria as mediators of ertugliflozin effects on the risk of HHF. Similar results were observed for the composite kidney outcome, with early changes in four biomarkers (glycated haemoglobin, haemoglobin, haematocrit and urate), and average changes in five biomarkers [early biomarkers (not glycated haemoglobin) + weight, serum albumin] mediating the effects of ertugliflozin on the kidney outcome. Conclusions: In these analyses from the VERTIS CV trial, markers of volume status and haemoconcentration and/or haematopoiesis were the strongest mediators of the effect of ertugliflozin on reducing risk of HHF and composite kidney outcomes in the early and average change periods. ClinicalTrials.gov identifier: NCT01986881 [ABSTRACT FROM AUTHOR]

Background: Among individuals with atherosclerotic cardiovascular disease (ASCVD), type 2 diabetes mellitus (T2DM) is common and confers increased risk for morbidity and mortality. Differentiating risk is key to optimize efficiency of treatment selection. Our objective was to develop and validate a model to predict risk of major adverse cardiovascular events (MACE) comprising the first event of cardiovascular death, myocardial infarction (MI), or stroke for individuals with both T2DM and ASCVD. Methods: Using data from the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS), we used Cox proportional hazards models to predict MACE among participants with T2DM and ASCVD. All baseline covariates collected in the trial were considered for inclusion, although some were excluded immediately because of large missingness or collinearity. A full model was developed using stepwise selection in each of 25 imputed datasets, and comprised candidate variables selected in 20 of the 25 datasets. A parsimonious model with a maximum of 10 degrees of freedom was created using Cox models with least absolute shrinkage and selection operator (LASSO), where the adjusted R-square was used as criterion for selection. The model was then externally validated among a cohort of participants with similar criteria in the ACCORD (Action to Control Cardiovascular Risk in Diabetes) trial. Discrimination of both models was assessed using Harrell's C-index and model calibration by the Greenwood-Nam-D'Agostino statistic based on 4-year event rates. Results: Overall, 1491 (10.2%) of 14,671 participants in TECOS and 130 (9.3%) in the ACCORD validation cohort (n = 1404) had MACE over 3 years' median follow-up. The final model included 9 characteristics (prior stroke, age, chronic kidney disease, prior MI, sex, heart failure, insulin use, atrial fibrillation, and microvascular complications). The model had moderate discrimination in both the internal and external validation samples (C-index = 0.65 and 0.61, respectively). The model was well calibrated across the risk spectrum—from a cumulative MACE rate of 6% at 4 years in the lowest risk quintile to 26% in the highest risk quintile. Conclusion: Among patients with T2DM and prevalent ASCVD, this 9-factor risk model can quantify the risk of future ASCVD complications and inform decision making for treatments and intensity. [ABSTRACT FROM AUTHOR]

Aims Post-operative atrial fibrillation (POAF) is associated with stroke and mortality. It is unknown if POAF is associated with subsequent heart failure (HF) hospitalization. This study aims to examine the association between POAF and incident HF hospitalization among patients undergoing cardiac and non-cardiac surgeries. Methods and results A retrospective cohort study was conducted using all-payer administrative claims data that included all non-federal emergency department visits and acute care hospitalizations across 11 states in the USA. The study population included adults aged at least 18 years hospitalized for surgery without a prior diagnosis of HF. Cox proportional hazards regression models were used to examine the association between POAF and incident HF hospitalization after making adjustment for socio-demographics and comorbid conditions. Among 76 536 patients who underwent cardiac surgery, 14 365 (18.8%) developed incident POAF. In an adjusted Cox model, POAF was associated with incident HF hospitalization [hazard ratio (HR) 1.33; 95% confidence interval (CI) 1.25–1.41]. In a sensitivity analysis excluding HF within 1 year of surgery, POAF remained associated with incident HF hospitalization (HR 1.15; 95% CI 1.01–1.31). Among 2 929 854 patients who underwent non-cardiac surgery, 23 763 (0.8%) developed incident POAF. In an adjusted Cox model, POAF was again associated with incident HF hospitalization (HR 2.02; 95% CI 1.94–2.10), including in a sensitivity analysis excluding HF within 1 year of surgery (HR 1.49; 95% CI 1.38–1.61). Conclusions Post-operative atrial fibrillation is associated with incident HF hospitalization among patients without prior history of HF undergoing both cardiac and non-cardiac surgeries. These findings reinforce the adverse prognostic impact of POAF and suggest that POAF may be a marker for identifying patients with subclinical HF and those at elevated risk for HF. [ABSTRACT FROM AUTHOR]