Effect of Torsemide Versus Furosemide on Symptoms and Quality of Life Among Patients Hospitalized for Heart Failure: The TRANSFORM-HF Randomized Clinical Trial.

BACKGROUND: Loop diuretics are a primary therapy for the symptomatic treatment of heart failure (HF), but whether torsemide improves patient symptoms and quality of life better than furosemide remains unknown. As prespecified secondary end points, the TRANSFORM-HF trial (Torsemide Comparison With Furosemide for Management of Heart Failure) compared the effect of torsemide versus furosemide on patient-reported outcomes among patients with HF. METHODS: TRANSFORM-HF was an open-label, pragmatic, randomized trial of 2859 patients hospitalized for HF (regardless of ejection fraction) across 60 hospitals in the United States. Patients were randomly assigned in a 1:1 ratio to a loop diuretic strategy of torsemide or furosemide with investigator-selected dosage. This report examined effects on prespecified secondary end points, which included Kansas City Cardiomyopathy Questionnaire Clinical Summary Score (KCCQ-CSS; assessed as adjusted mean difference in change from baseline; range, 0-100 with 100 indicating best health status; clinically important difference, ≥5 points) and Patient Health Questionnaire-2 (range, 0-6; score ≥3 supporting evaluation for depression) over 12 months. RESULTS: Baseline data were available for 2787 (97.5%) patients for KCCQ-CSS and 2624 (91.8%) patients for Patient Health Questionnaire-2. Median (interquartile range) baseline KCCQ-CSS was 42 (27-60) in the torsemide group and 40 (24-59) in the furosemide group. At 12 months, there was no significant difference between torsemide and furosemide in change from baseline in KCCQ-CSS (adjusted mean difference, 0.06 [95% CI, -2.26 to 2.37]; P=0.96) or the proportion of patients with Patient Health Questionnaire-2 score ≥3 (15.1% versus 13.2%: P=0.34). Results for KCCQ-CSS were similar at 1 month (adjusted mean difference, 1.36 [95% CI, -0.64 to 3.36]; P=0.18) and 6-month follow-up (adjusted mean difference, -0.37 [95% CI, -2.52 to 1.78]; P=0.73), and across subgroups by ejection fraction phenotype, New York Heart Association class at randomization, and loop diuretic agent before hospitalization. Irrespective of baseline KCCQ-CSS tertile, there was no significant difference between torsemide and furosemide on change in KCCQ-CSS, all-cause mortality, or all-cause hospitalization. CONCLUSIONS: Among patients discharged after hospitalization for HF, a strategy of torsemide compared with furosemide did not improve symptoms or quality of life over 12 months. The effects of torsemide and furosemide on patient-reported outcomes were similar regardless of ejection fraction, previous loop diuretic use, and baseline health status. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT03296813.

Medical Therapy Before, During and After Hospitalization in Medicare Beneficiaries With Heart Failure and Diabetes: Get With The Guidelines - Heart Failure Registry.

BACKGROUND: Patients hospitalized with heart failure (HF) and diabetes mellitus (DM) are at risk for worsening clinical status. Little is known about the frequency of therapeutic changes during hospitalization. We characterized the use of medical therapies before, during and after hospitalization in patients with HF and DM. METHODS: We identified Medicare beneficiaries in Get With The Guidelines-Heart Failure (GWTG-HF) hospitalized between July 2014 and September 2019 with Part D prescription coverage. We evaluated trends in the use of 7 classes of antihyperglycemic therapies (metformin, sulfonylureas, GLP-1RA, SGLT2-inhibitors, DPP-4 inhibitors, thiazolidinediones, and insulins) and 4 classes of HF therapies (evidence-based ß-blockers, ACEi or ARB, MRA, and ARNI). Medication fills were assessed at 6 and 3 months before hospitalization, at hospital discharge and at 3 months post-discharge. RESULTS: Among 35,165 Medicare beneficiaries, the median age was 77 years, 54% were women, and 76% were white; 11,660 (33%) had HFrEF (LVEF ≤ 40%), 3700 (11%) had HFmrEF (LVEF 41%-49%), and 19,805 (56%) had HFpEF (LVEF ≥ 50%). Overall, insulin was the most commonly prescribed antihyperglycemic after HF hospitalization (n = 12,919, 37%), followed by metformin (n = 7460, 21%) and sulfonylureas (n = 7030, 20%). GLP-1RA (n = 700, 2.0%) and SGLT2i (n = 287, 1.0%) use was low and did not improve over time. In patients with HFrEF, evidence-based beta-blocker, RASi, MRA, and ARNI fills during the 6 months preceding HF hospitalization were 63%, 62%, 19%, and 4%, respectively. Fills initially declined prior to hospitalization, but then rose from 3 months before hospitalization to discharge (beta-blocker: 56%-82%; RASi: 51%-57%, MRA: 15%-28%, ARNI: 3%-6%, triple therapy: 8%-20%; P < 0.01 for all). Prescription rates 3 months after hospitalization were similar to those at hospital discharge. CONCLUSIONS: In-hospital optimization of medical therapy in patients with HF and DM is common in participating hospitals of a large US quality improvement registry.

Estimated Glomerular Filtration Rate Slope as an Endpoint in Cardiovascular Trials.

PURPOSE OF REVIEW: End stage kidney disease can be a slow process and it may be challenging to achieve required follow-up for sufficient events. Therefore, a surrogate kidney endpoint, such as estimated glomerular filtration rate (eGFR) slope maybe attractive to assess the kidney in cardiovascular trials, especially heart failure (HF). RECENT FINDINGS: eGFR slope can generate informative results in a shorter follow-up period, has decreased risk of type-2 error, and is less sensitive to eGFR shifts compared with other surrogate kidney endpoints (eGFR decline≥40% or doubling creatinine). However, eGFR slope has its limitations with acute effects, heterogeneity in slope calculation/reporting, and deviations from linearity. eGFR slope is a kidney endpoint which may be well-suited for HF trials. Cross-collaborated guideline recommendations are needed to optimize the use of eGFR slope as a kidney endpoint in patients with HF.

Endpoint adjudication in cardiovascular clinical trials.

Endpoint adjudication (EA) is a common feature of contemporary randomized controlled trials (RCTs) in cardiovascular medicine. Endpoint adjudication refers to a process wherein a group of expert reviewers, known as the clinical endpoint committee (CEC), verify potential endpoints identified by site investigators. Events that are determined by the CEC to meet pre-specified trial definitions are then utilized for analysis. The rationale behind the use of EA is that it may lessen the potential misclassification of clinical events, thereby reducing statistical noise and bias. However, it has been questioned whether this is universally true, especially given that EA significantly increases the time, effort, and resources required to conduct a trial. Herein, we compare the summary estimates obtained using adjudicated vs. non-adjudicated site designated endpoints in major cardiovascular RCTs in which both were reported. Based on these data, we lay out a framework to determine which trials may warrant EA and where it may be redundant. The value of EA is likely greater when cardiovascular trials have nuanced primary endpoints, endpoint definitions that align poorly with practice, sub-optimal data completeness, greater operator variability, and lack of blinding. EA may not be needed if the primary endpoint is all-cause death or all-cause hospitalization. In contrast, EA is likely merited for more nuanced endpoints such as myocardial infarction, bleeding, worsening heart failure as an outpatient, unstable angina, or transient ischaemic attack. A risk-based approach to adjudication can potentially allow compromise between costs and accuracy. This would involve adjudication of a small proportion of events, with further adjudication done if inconsistencies are detected.

Leveraging electronic health records to streamline the conduct of cardiovascular clinical trials.

Conventional randomized controlled trials (RCTs) can be expensive, time intensive, and complex to conduct. Trial recruitment, participation, and data collection can burden participants and research personnel. In the past two decades, there have been rapid technological advances and an exponential growth in digitized healthcare data. Embedding RCTs, including cardiovascular outcome trials, into electronic health record systems or registries may streamline screening, consent, randomization, follow-up visits, and outcome adjudication. Moreover, wearable sensors (i.e. health and fitness trackers) provide an opportunity to collect data on cardiovascular health and risk factors in unprecedented detail and scale, while growing internet connectivity supports the collection of patient-reported outcomes. There is a pressing need to develop robust mechanisms that facilitate data capture from diverse databases and guidance to standardize data definitions. Importantly, the data collection infrastructure should be reusable to support multiple cardiovascular RCTs over time. Systems, processes, and policies will need to have sufficient flexibility to allow interoperability between different sources of data acquisition. Clinical research guidelines, ethics oversight, and regulatory requirements also need to evolve. This review highlights recent progress towards the use of routinely generated data to conduct RCTs and discusses potential solutions for ongoing barriers. There is a particular focus on methods to utilize routinely generated data for trials while complying with regional data protection laws. The discussion is supported with examples of cardiovascular outcome trials that have successfully leveraged the electronic health record, web-enabled devices or administrative databases to conduct randomized trials.

Transthyretin amyloid cardiomyopathy among patients hospitalized for heart failure and performance of an adapted wild-type ATTR-CM machine learning model: Findings from GWTG-HF.

BACKGROUND: An 11-factor random forest model has been developed among ambulatory heart failure (HF) patients for identifying potential wild-type amyloidogenic TTR cardiomyopathy (wtATTR-CM). The model has not been evaluated in a large sample of patients hospitalized for HF. METHODS: This study included Medicare beneficiaries aged ≥65 years hospitalized for HF in the Get With The Guidelines-HF® Registry from 2008-2019. Patients with and without a diagnosis of ATTR-CM were compared, as defined by inpatient and outpatient claims data within 6 months pre- or post-index hospitalization. Within a cohort matched 1:1 by age and sex, univariable logistic regression was used to evaluate relationships between ATTR-CM and each of the 11 factors of the established model. Discrimination and calibration of the 11-factor model were assessed. RESULTS: Among 205,545 patients (median age 81 years) hospitalized for HF across 608 hospitals, 627 patients (0.31%) had a diagnosis code for ATTR-CM. Univariable analysis within the 1:1 matched cohort of each of the 11-factors in the ATTR-CM model found pericardial effusion, carpal tunnel syndrome, lumbar spinal stenosis, and elevated serum enzymes (e.g., troponin elevation) to be strongly associated with ATTR-CM. The 11-factor model showed modest discrimination (c-statistic 0.65) and good calibration within the matched cohort. CONCLUSIONS: Among US patients hospitalized for HF, the number of patients with ATTR-CM defined by diagnosis codes on an inpatient/outpatient claim within 6 months of admission was low. Most factors within the prior 11-factor model were associated with greater odds of ATTR-CM diagnosis. In this population, the ATTR-CM model demonstrated modest discrimination.

Comparison of 30-day Readmission Rates and Inpatient Cardiac Procedures for Weekday Versus Weekend Hospital Admissions for Heart Failure.

BACKGROUND: Whether the timing of hospital presentation impacts care delivery and clinical outcomes for patients hospitalized for heart failure (HF) remains a matter of debate. In this study, we examined all-cause and HF-specific 30-day readmission rates for patients who were admitted for HF on a weekend vs admitted for HF on a weekday. METHODS AND RESULTS: We conducted a retrospective analysis using the 2010-2019 Nationwide Readmission Database to compare 30-day readmission rates among patients who were admitted for HF on a weekday (Monday to Friday) vs patients who were admitted for HF on a weekend (Saturday or Sunday). We also compared in-hospital cardiac procedures and temporal trends in 30-day readmission by day of index hospital admission. Among 8,270,717 index HF hospitalizations, 6,302,775 were admitted on a weekday and 1,967,942 admitted on a weekend. For weekday and weekend admissions, the 30-day all-cause readmission rates were 19.8% vs 20.3%, and HF-specific readmission rates were 8.1% vs 8.4%, respectively. Weekend admissions were independently associated with higher risk of all-cause (adjusted odds ratio [aOR] 1.04, 95% confidence interval [CI] 1.03-1.05, P < .001) and HF-specific readmission (aOR 1.04, 95% CI 1.03-1.05, P < .001). Weekend HF admissions were less likely to undergo echocardiography (aOR 0.95, 95% CI 0.94-0.96, P < .001), right heart catheterization (aOR 0.80, 95% CI 0.79-0.81, P < .001), electrical cardioversion (aOR 0.90, 95% CI 0.88-0.93, P < .001), or receive temporary mechanical support devices (aOR 0.84, 95% CI 0.79-0.89, P < .001). The mean length of stay was shorter for weekend HF admissions (5.1 days vs 5.4 days, P < .001). Between 2010 and 2019, 30-day all-cause (18.5% to 18.2%, trend P < .001) and HF-specific (8.4% to 8.3%, trend P < .001) readmission rates decreased among weekday HF admissions. Among weekend HF admissions, the HF-specific 30-day readmission rate decreased (8.8% to 8.7%, trend P < .001), but the all-cause 30-day readmission rate remained stable (trend P = .280). CONCLUSIONS: Among patients hospitalized for HF, weekend admissions were independently associated with excess risk of 30-day all-cause and HF-specific readmission and a lower likelihood of undergoing in-hospital cardiovascular testing and procedures. The 30-day all-cause readmission rate has decreased modestly over time among patients admitted on weekdays, but has remained stable among patients admitted on weekends.

Managing Heart Failure in Patients on Dialysis: State-of-the-Art Review.

Heart failure (HF) and end-stage kidney disease (ESKD) frequently coexist; 1 comorbidity worsens the prognosis of the other. HF is responsible for almost half the deaths of patients on dialysis. Despite patients' with ESKD composing an extremely high-risk population, they have been largely excluded from landmark clinical trials of HF, and there is, thus, a paucity of data regarding the management of HF in patients on dialysis, and most of the available evidence is observational. Likewise, in clinical practice, guideline-directed medical therapy for HF is often down-titrated or discontinued in patients with ESKD who are undergoing dialysis; this is due to concerns about safety and tolerability. In this state-of-the-art review, we discuss the available evidence for each of the foundational HF therapies in ESKD, review current challenges and barriers to managing patients with HF on dialysis, and outline future directions to optimize the management of HF in these high-risk patients.

Inconsistent Outcome Reporting in Heart Failure Randomized Controlled Trials.

BACKGROUND: Randomized controlled trials (RCTs) may report outcomes different from those prespecified on trial-registration websites, protocols and statistical analysis plans (SAPs). This study sought to investigate the prevalence and characteristics of heart failure (HF) RCTs that report outcomes different from those prespecified. METHODS AND RESULTS: MEDLINE via PubMed was searched to include phase II-IV HF RCTs in 9 high-impact journals from 2010 to 2020. Outcomes reported in trial publications were compared with prespecified outcomes in protocols, registration websites and SAPs. We used the χ2 or Fisher exact test to analyze correlations between trial characteristics and inconsistencies. Among 216 trials, 32 inconsistencies were observed in 28 trials (13.0%). Among 32 inconsistencies, 2 (6.3%) pertained to omission of prespecified primary outcomes, 4 (12.5%) to omission of prespecified secondary outcomes, 2 (6.3%) to changing prespecified primary outcomes to secondary outcomes, and 2 (6.3%) to changing prespecified secondary outcomes to primary outcomes. Of the inconsistencies, 3 (9.4%) pertained to addition of new primary outcomes, 17 (53.1%) to addition of new secondary outcomes, and 2 (6.3%,) to changes in the timing of assessment of primary outcomes. The majority of the inconsistencies favored statistically significant findings; 78 (36.1%) were registered retrospectively. Single-center recruitment was associated with outcome inconsistencies (ß = -0.14; 95% CI, -0.22 - -0.01; P = 0.035). CONCLUSIONS: More than 1 in 10 trials reported outcomes inconsistent with those specified in trial registration websites, SAPs and protocols. An action plan is warranted to minimize selective reporting and improve transparency.

Effect of Torsemide vs Furosemide After Discharge on All-Cause Mortality in Patients Hospitalized With Heart Failure: The TRANSFORM-HF Randomized Clinical Trial.

Importance: Although furosemide is the most commonly used loop diuretic in patients with heart failure, some studies suggest a potential benefit for torsemide. Objective: To determine whether torsemide results in decreased mortality compared with furosemide among patients hospitalized for heart failure. Design, Setting, and Participants: TRANSFORM-HF was an open-label, pragmatic randomized trial that recruited 2859 participants hospitalized with heart failure (regardless of ejection fraction) at 60 hospitals in the United States. Recruitment occurred from June 2018 through March 2022, with follow-up through 30 months for death and 12 months for hospitalizations. The final date for follow-up data collection was July 2022. Interventions: Loop diuretic strategy of torsemide (n = 1431) or furosemide (n = 1428) with investigator-selected dosage. Main Outcomes and Measures: The primary outcome was all-cause mortality in a time-to-event analysis. There were 5 secondary outcomes with all-cause mortality or all-cause hospitalization and total hospitalizations assessed over 12 months being highest in the hierarchy. The prespecified primary hypothesis was that torsemide would reduce all-cause mortality by 20% compared with furosemide. Results: TRANSFORM-HF randomized 2859 participants with a median age of 65 years (IQR, 56-75), 36.9% were women, and 33.9% were Black. Over a median follow-up of 17.4 months, a total of 113 patients (53 [3.7%] in the torsemide group and 60 [4.2%] in the furosemide group) withdrew consent from the trial prior to completion. Death occurred in 373 of 1431 patients (26.1%) in the torsemide group and 374 of 1428 patients (26.2%) in the furosemide group (hazard ratio, 1.02 [95% CI, 0.89-1.18]). Over 12 months following randomization, all-cause mortality or all-cause hospitalization occurred in 677 patients (47.3%) in the torsemide group and 704 patients (49.3%) in the furosemide group (hazard ratio, 0.92 [95% CI, 0.83-1.02]). There were 940 total hospitalizations among 536 participants in the torsemide group and 987 total hospitalizations among 577 participants in the furosemide group (rate ratio, 0.94 [95% CI, 0.84-1.07]). Results were similar across prespecified subgroups, including among patients with reduced, mildly reduced, or preserved ejection fraction. Conclusions and Relevance: Among patients discharged after hospitalization for heart failure, torsemide compared with furosemide did not result in a significant difference in all-cause mortality over 12 months. However, interpretation of these findings is limited by loss to follow-up and participant crossover and nonadherence. Trial Registration: ClinicalTrials.gov Identifier: NCT03296813.

Contemporary outpatient management of patients with worsening heart failure with reduced ejection fraction: Rationale and design of the CHART-HF study.

BACKGROUND: Patients with heart failure with reduced ejection fraction (HFrEF) and worsening HF events (WHFE) represent a distinct subset of patients with a substantial comorbidity burden, greater potential for intolerance to medical therapy, and high risk of subsequent death, hospitalization and excessive healthcare costs. Although multiple therapies have been shown to be efficacious and safe in this high-risk population, there are limited real-world data regarding factors that impact clinical decision-making when initiating or modifying therapy. Likewise, prior analyses of US clinical practice support major gaps in medical therapy for HFrEF and few medication changes during longitudinal follow-up, yet granular data on reasons why clinicians do not initiate or up-titrate guideline-directed medication are lacking. METHODS: We designed the CHART-HF study, an observational study of approximately 1,500 patients comparing patients with and without WHFE (WHFE defined as receipt of intravenous diuretics in the inpatient, outpatient, or emergency department setting) who had an index outpatient visit in the US between 2017 and 2019. Patient-level data on clinical characteristics, clinical outcomes, and therapy will be collected from 2 data sources: a single integrated health system, and a national panel of cardiologists. Furthermore, clinician-reported rationale for treatment decisions and the factors prioritized with selection and optimization of therapies in real-world practice will be obtained. To characterize elements of clinician decision-making not documented in the medical record, the panel of cardiologists will review records of patients seen under their care to explicitly note their primary reason for initiating, discontinuing, and titrating medications specific medications, as well as the reason for not making changes to each medication during the outpatient visit. CONCLUSIONS: Results from CHART-HF have the potential to detail real-world US practice patterns regarding care of patients with HFrEF with versus without a recent WHFE, to examine clinician-reported reasons for use and non-use of guideline-directed medical therapy, and to characterize the magnitude and nature of clinical inertia toward evidence-based medication changes for HFrEF.

Titration of medical therapy and clinical outcomes among patients with heart failure with reduced ejection fraction: Findings from the HF-ACTION trial.

BACKGROUND: Clinical guidelines recommend titration of angiotensin converting enzyme inhibitors (ACEi) and beta-blockers among patients with heart failure with reduced ejection fraction (HFrEF) to maximally tolerated doses. Patient characteristics associated with dose titration and clinical outcomes subsequent to dose titration remain poorly characterized. METHODS: Among 1999 ambulatory patients with chronic HFrEF in the HF-ACTION trial, use and dosing of ACEi and evidence-based beta-blockers were examined at baseline and 6-month follow-up. Multivariable logistic regression models were used to assess factors associated with dose escalation (medication initation or dosing increase) or dose de-escalation (medication discontinuation or dosing decrease). Cox proportional hazard regression models were used to examine associations between dose trajectory group (stable target, stable sub-target, dose escalation, and dose de-escalation) and subsequent mortality and hospitalization outcomes. RESULTS: For both ACEi and beta-blockers, hospitalization for heart failure in the 6 months prior to enrollment (odds ratio [OR] 2.32 [95% confidence interval 1.58-3.42]) for ACEi; 1.42 [1.05-1.9] for beta-blockers) and higher systolic blood pressure (OR 1.01 [1.00-1.03] per 1 mmHg increase for ACEi; 1.01 [1.00-1.02] for beta-blockers) were associated with dose escalation. Hospitalization 6 months prior to enrollment for any cause (including HF or non-HF causes) was associated with dose de-escalation (OR 1.60 [1.14-2.25] for ACEi; 1.67 [1.20-2.33] for beta-blockers). After adjustment for patient characteristics, compared with stable target dosing, dose de-escalation of either medication was associated with greater all-cause mortality (adjusted hazard ratio [aHR] 1.64 [1.11-2.42] for ACEi; 1.62 [1.04-2.53] for beta-blockers). Compared with stable target dosing, both dose de-escalation (aHR 1.98 [1.36-2.87]) and stable sub-target dosing (aHR 1.49 [1.18-1.87]) of beta-blockers were associated with greater cardiovascular mortality or hospitalization for heart failure. CONCLUSIONS: Among outpatients with chronic HFrEF, patient characteristics including recent hospitalization status and blood pressure were associated with odds of subsequent escalation and de-escalation of ACEi and beta-blocker therapy. Compared with patients receiving guildeline-recommended target doses, dose de-escalation of either medication and sub-target dosing of beta-blockers were associated with greater morbidity and mortality over long-term follow-up.

Trends in hospitalizations for heart failure, acute myocardial infarction, and stroke in the United States from 2004 to 2018.

AIM: To determine the trends in hospitalizations for heart failure (HF), acute myocardial infarction (AMI), and stroke in the United States (US). METHOD AND RESULTS: A retrospective analysis of the National Inpatient Sample weighted data between January 1, 2004 and December 31, 2018 which included hospitalized adults ≥18 years with a primary discharge diagnosis of HF, AMI, or stroke using International Classification of Diseases-9/10 administrative codes. Main outcomes were hospitalization for HF, AMI, and stroke per 1000 United States adults, length of stay, and in-hospital mortality. There were 33.4 million hospitalizations for HF, AMI, and stroke, with most being for HF (48%). After the initial decline in HF hospitalizations (5.3 hospitalizations/1000 US adults in 2004 to 4 hospitalizations/1000 US adults in 2013, P < .001), there was a progressive increase in HF hospitalizations between 2013 and 2018 (4.0 hospitalizations/1000 US adults in 2013 to 4.9 hospitalizations/1000 US adults in 2018; P < .001). Hospitalization for AMI decreased (3.1 hospitalizations/1000 US adults in 2004 to 2.5 hospitalizations/1000 US adults in 2010, P < .001) and remained stable between 2010 and 2018. There was no significant change for hospitalization for stroke between 2004 and 2011 (2.3 hospitalizations/1000 US adults in 2004 vs 2.3 hospitalizations per 1000 US adults in 2011, P = .614); however, there was a small but significant increase in hospitalization for stroke after 2011 that reached 2.5 hospitalizations/1000 US adults in 2018. Adjusted length of stay and in-hospital mortality decreased for HF, AMI, and stroke hospitalizations. CONCLUSIONS: In contrast to the trend of AMI and stroke hospitalizations, a progressive increase in hospitalizations for HF has occurred since 2013. From 2004 to 2018, in-hospital mortality has decreased for HF, AMI, and stroke hospitalizations.

Machine learning to define phenotypes and outcomes of patients hospitalized for heart failure with preserved ejection fraction: Findings from ASCEND-HF.

BACKGROUND: Heart Failure with Preserved Ejection Fraction (HFpEF) is a heterogenous disease with few therapies proven to provide clinical benefit. Machine learning can characterize distinct phenotypes and compare outcomes among patients with HFpEF who are hospitalized for acute HF. METHODS: We applied hierarchical clustering using demographics, comorbidities, and clinical data on admission to identify distinct clusters in hospitalized HFpEF (ejection fraction >40%) in the ASCEND-HF trial. We separately applied a previously developed latent class analysis (LCA) clustering method and compared in-hospital and long-term outcomes across cluster groups. RESULTS: Of 7141 patients enrolled in the ASCEND-HF trial, 812 (11.4%) were hospitalized for HFpEF and met the criteria for complete case analysis. Hierarchical Cluster 1 included older women with atrial fibrillation (AF). Cluster 2 had elevated resting blood pressure. Cluster 3 had young men with obesity and diabetes. Cluster 4 had low resting blood pressure. Mortality at 180 days was lowest among Cluster 3 (KM event-rate 6.2 [95% CI: 3.5, 10.9]) and highest among Cluster 4 (18.8 [14.6, 24.0], P < .001). Twenty four-hour urine output was higher in Cluster 3 (2700 mL [1800, 3975]) than Cluster 4 (2100 mL [1400, 3055], P < .001). LCA also identified four clusters: A) older White or Asian women, B) younger men with few comorbidities, C) older individuals with AF and renal impairment, and D) patients with obesity and diabetes. Mortality at 180 days was lowest among LCA Cluster B (KM event-rate 5.5 [2.0, 10.3]) and highest among LCA Cluster C (26.3 [19.2, 35.4], P < .001). CONCLUSIONS: In patients hospitalized for HFpEF, cluster analysis demonstrated distinct phenotypes with differing clinical profiles and outcomes.

National trends and disparities in statin use for ischemic heart disease from 2006 to 2018: Insights from National Ambulatory Medical Care Survey.

BACKGROUND: Statins are a cornerstone guideline-directed medical therapy for secondary prevention of ischemic heart disease (IHD). However, recent temporal trends and disparities in statin utilization for IHD have not been well characterized. METHODS: This retrospective analysis included data from outpatient adult visits with IHD from the National Ambulatory Medical Care Survey (NAMCS) between January 2006 and December 2018. We examined the trends and predictors of statin utilization in outpatient adult visits with IHD. RESULTS: Between 2006 and 2018, we identified a total of 542,704,112 weighted adult ambulatory visits with IHD and of those 46.6% were using or prescribed statin. Middle age (50-74 years) (adjusted odds ratio [aOR] 1.65, 95% confidence interval [CI] 1.28-2.13 P < .001) and old age (≥75 years) (aOR = 1.66, CI 1.26-2.19, P < .001) compared to young age (18-49 years), and male sex (aOR = 1.35, CI 1.23-1.48, P < .001) were associated with greater likelihood of statin utilization, whereas visits with non-Hispanic (NH) Black patients (aOR = 0.75, CI 0.61-0.91, P = .005) and Hispanic patients (aOR = 0.74, CI 0.60-0.92, P = .006) were associated with decreased likelihood of statin utilization compared to NH White patient visits. Compared with private insurance, statin utilization was nominally lower in Medicare (aOR = 0.91, CI 0.80-1.02, P = .112), Medicaid (aOR = 0.78, CI 0.59-1.02, P = .072) and self-pay/no charge (aOR = 0.72, CI 0.48-1.09, P = .122) visits, however did not reach statistical significance. There was no significant uptake in statin utilization from 2006 (44.1%) to 2018 (46.2%) (P = .549). CONCLUSIONS: Substantial gaps remain in statin utilization for patients with IHD, with no significant improvement in use between 2006 and 2018. Persistent disparities in statin prescription remain, with the largest treatment gaps among younger patients, women, and racial/ethnic minorities (NH Blacks and Hispanics).

Prognostic Interplay Between COVID-19 and Heart Failure With Reduced Ejection Fraction.

BACKGROUND: COVID-19 may negatively impact the prognosis of patients with chronic HFrEF and vice versa. METHODS: This study included 2 parallel analyses of patients in the United States who were in the TriNetX health database and who underwent polymerase chain reaction testing for SARS-CoV-2 as an inpatient or outpatient between January and September of 2020. Analysis A included patients with positive tests for COVID-19 and compared patients with histories of worsening heart failure with reduced ejection fraction (HFrEF) (hospitalization due to heart failure (HF) or IV diuretic use during the prior 12 months), HFrEF without worsening, and no prior HF. Analysis B included patients with histories of HFrEF and compared patients with positive vs negative COVID-19 tests. Outcomes included mortality and worsening HF. In both analyses, prespecified subgroup analyses were stratified by inpatient vs outpatient settings of the COVID-19 tests. RESULTS: In Analysis A, of 99,052 patients with positive COVID-19 tests, 514 (0.5%) and 524 (0.5%) patients had histories of worsening HFrEF and HFrEF without worsening, respectively. After adjustment, compared to patients without HF, worsening HFrEF (risk ratio [RR] 1.42, 95% CI 1.10-1.83; P< 0.001) and HFrEF without worsening (RR 1.33, 95% CI 0.96-1.84; P= 0.06) were associated with higher 30-day mortality rates. Excess risk of mortality tended to be pronounced in patients initially diagnosed with COVID-19 as outpatients (P for interaction, 0.12 and 0.006, respectively). In Analysis B, of 14,838 patients with HFrEF tested for COVID-19, 1038 (7.0%) had positive tests. After adjustment, testing positive was associated with excess 30-day mortality risk (RR 1.67, 95% CI 1.38-2.02; P< 0.001) and worsening HF (RR 1.33, 95% CI 1.17-1.51; P< 0.001). Mortality risk was nominally more pronounced among patients presenting as outpatients (P for interaction 0.07). CONCLUSION: In this large cohort of patients tested for COVID-19, among patients testing positive, a history of HFrEF with or without worsening was associated with excess mortality rates, particularly among patients diagnosed with COVID-19 as outpatients. Among patients with established HFrEF, compared with testing negative, testing positive for COVID-19 was independently associated with higher risk of death and worsening HF.

Emergency Department Visits Versus Hospital Readmissions Among Patients Hospitalized for Heart Failure.

BACKGROUND: Worsening heart failure (HF) often requires hospitalization but in some cases may be managed in the outpatient or emergency department (ED) settings. The predictors and clinical significance of ED visits without admission vs hospitalization are unclear. METHODS: The ASCEND-HF trial included 2661 US patients hospitalized for HF with reduced or preserved ejection fraction. Clinical characteristics were compared between patients with a subsequent all-cause ED visit (with ED discharge) within 30 days vs all-cause readmission within 30 days. Factors associated with each type of care were assessed in multivariable models. Multivariable models landmarked at 30 days evaluated associations between each type of care and subsequent 150-day mortality. RESULTS: Through 30-day follow-up, 193 patients (7%) had ED discharge, 459 (17%) had readmission, and 2009 (76%) had neither urgent visit. Patients with ED discharge vs readmission were similar with respect to age, sex, systolic blood pressure, ejection fraction, and coronary artery disease, whereas ED discharge patients had a modestly lower creatinine (P < .01). Among patients with either event within 30 days, a higher creatinine and prior HF hospitalization were associated with a higher likelihood of readmission, as compared with ED discharge (P < .02). Landmarked at 30 days, rates of death during the subsequent 150 days were 21.0% for patients who were readmitted and 11.4% for patients discharged from the ED. Compared with patients who were readmitted, ED discharge was independently associated with lower 150-day mortality (adjusted hazard ratio 0.58, 95% confidence interval 0.36-0.92, P = .02). CONCLUSIONS: In this cohort of US patients hospitalized for HF, worse renal function and prior HF hospitalization were associated with a higher likelihood of early postdischarge readmission, as compared with ED discharge. Although subsequent mortality was high after discharge from the ED, this risk of mortality was significantly lower than patients who were readmitted to the hospital.

Patient-reported and Clinical Outcomes Among Patients Hospitalized for Heart Failure With Reduced Versus Preserved Ejection Fraction.

BACKGROUND: Differences between patients hospitalized for heart failure with reduced ejection fraction (HFrEF) vs HF with preserved EF (HFpEF) are not well-characterized, particularly as pertains to in-hospital decongestion and longitudinal patient-reported outcomes. The objective of this analysis was to compare patient-reported and clinical outcomes between patients hospitalized with HFrEF vs HFpEF. METHODS AND RESULTS: The Acute Study of Clinical Effectiveness of Nesiritide in Decompensated Heart Failure (ASCEND-HF) trial enrolled 7141 patients hospitalized for HF with reduced or preserved EF. We assessed the association between an EF ≤ 40% vs an EF >40% with in-hospital decongestion, risk of rehospitalization and mortality, and quality of life as measured by the EuroQOL 5 Dimensions (EQ-5D). Among 5800 patients (81%) with complete EF data, 4782 (82%) had an EF ≤40% and 1018 (18%) had an EF >40%. Both groups demonstrated similar rates of decongestion by weight change and urine volume through 24 hours, a similar risk of 30-day mortality and HF rehospitalization, and a similar 180-day mortality. Patients with HFpEF had worse EQ-5D scores at hour 24 (median 0.76, [interquartile range (IQR) 0.51-0.84] vs 0.78 [IQR 0.57-0.84]; P = .01) that persisted through discharge (0.81 [IQR 0.69-0.86] vs 0.83 [IQR 0.71-1.00]; P < .001) and the 30-day follow-up (0.78 [IQR 0.60-0.85] vs 0.83 [IQR 0.71-1.00]; P < .001). After adjustment, these differences were attenuated and not statistically significant. CONCLUSIONS: In this large, multinational cohort of patients hospitalized for HF, patients with an EF ≤ 40% vs an EF >40% experienced similar in-hospital decongestion and postdischarge clinical outcomes. Patients with an EF >40% reported worse in-hospital and postdischarge patient-reported health status, but these measures were similar to HFrEF after accounting for other clinical factors.

Ascertaining Death Events in a Pragmatic Clinical Trial: Insights From the TRANSFORM-HF Trial.

BACKGROUND: Death ascertainment can be challenging for pragmatic clinical trials that limit site follow-up activities to usual clinical care. METHODS AND RESULTS: We used blinded aggregate data from the ongoing ToRsemide comparison with furoSemide FOR Management of Heart Failure (TRANSFORM-HF) pragmatic clinical trial in patients with heart failure to evaluate the agreement between centralized call center death event identification and the United States National Death Index (NDI). Of 2284 total patients randomized through April 12, 2021, 1480 were randomized in 2018-2019 and 804 in 2020-2021. The call center identified 416 total death events (177 in 2018-2019 and 239 in 2020-2021). The NDI 2018-2019 final file identified 178 death events, 165 of which were also identified by the call center. The study's inter-rater reliability metric (Cohen's kappa coefficient, 0.920; 95% confidence interval, 0.889-0.951) demonstrates a high level of agreement. The time between a death event and its identification was less for the call center (median, 47 days; interquartile range, 11-103 days) than for the NDI (median, 270 days; interquartile range, 186-391 days). CONCLUSIONS: There is substantial agreement between deaths identified by a centralized call center and the NDI. However, the time between a death event and its identification is significantly less for the call center.

Medical Therapy During Hospitalization for Heart Failure With Reduced Ejection Fraction: The VICTORIA Registry.

BACKGROUND: For patients hospitalized for heart failure with reduced ejection fraction (HFrEF), guidelines recommend optimization of medical therapy prior to discharge. The degree to which changes in medical therapy occur during hospitalizations for HFrEF in North American clinical practice is unclear. METHODS: The VICTORIA registry (Vericiguat Global Study in Subjects with Heart Failure with Reduced Ejection Fraction) enrolled patients hospitalized for worsening chronic HFrEF across 51 sites in the United States and Canada from February 2018-January 2019. In patients with complete medication data who were not receiving dialysis, use and dose of angiotensin-converting enzyme inhibitor (ACEI)/angiotensin II receptor blocker (ARB), angiotensin receptor neprilysin inhibitor (ARNI), beta-blocker, mineralocorticoid receptor antagonist (MRA), and sodium glucose cotransporter-2 inhibitors (SGLT2i) were assessed at admission and discharge. RESULTS: Of 1695 patients, the median (IQR) age was 69 (59-79) years, and 33% were women. Among eligible patients, 33%, 25% and 55% were not prescribed ACEI/ARB/ARNI, beta-blocker, and MRA at discharge, respectively; 99% were not prescribed SGLT2i. For each medication, > 50% of patients remained on stable subtarget doses or no medication during hospitalization. In-hospital rates of initiation/dose increase were 20% for ACEI/ARB, 4% for ARNI, 20% for beta-blocker, 22% for MRA, and < 1% for SGLT2i; corresponding rates of dose decrease/discontinuation were 11%, 2%, 9%, 5%, and < 1%, respectively. Overall, 17% and 28% of eligible patients were prescribed triple therapy prior to admission and at discharge, respectively. At both admission and discharge, 1% of patients were prescribed triple therapy at target doses. Across classes of medication, multiple factors were independently associated with higher likelihood of in-hospital initiation/dosing increase (eg, Canadian enrollment, white race, admission to intensive care units) and discontinuation/dosing decrease (eg, worse renal function, admission to intensive care units). CONCLUSIONS: In this contemporary North American registry of patients hospitalized for worsening chronic HFrEF, for each recommended medical therapy, the large majority of eligible patients remained on stable subtarget doses or without medication at admission and discharge. Although most patients had no alterations in medical therapy, hospitalization in Canada and multiple patient characteristics were associated with higher likelihood of favorable in-hospital medication changes.