High Risk of Stroke in Patients With Worsening Heart Failure, Reduced Ejection Fraction, Coronary Heart Disease and Sinus Rhythm: Risk Prediction Score Analysis From the COMMANDER-HF Trial.

BACKGROUND: Patients with heart failure with reduced ejection fraction (HFrEF) and sinus rhythm have a heightened risk of stroke. Whether anticoagulation benefits these patients is uncertain. In this post hoc analysis of the A Study to Assess the Effectiveness and Safety of Rivaroxaban in Reducing the Risk of Death, Myocardial Infarction, or Stroke in Participants with Heart Failure and Coronary Artery Disease Following an Episode of Decompensated Heart Failure (COMMANDER-HF) trial we evaluated how a previously validated risk model consisting of 3 variables (history of prior stroke, insulin-treated diabetes, and N-terminal pro-B-type natriuretic peptide level) would perform, compared with plasma d-dimer, for stroke prediction and estimation of the benefit of low-dose rivaroxaban. METHODS AND RESULTS: Stroke risk and treatment effect were computed across risk score and plasma d-dimer tertiles. Risk score was available in 58% of the COMMANDER-HF population (n = 2928). Over a median follow-up of 512 days (range 342-747 days), 60 patients experienced a stroke (14.6 per 1000 patient-years). The risk model did not identify patients at higher risk of stroke and showed a low overall prognostic performance (C-index = 0.53). The effect of rivaroxaban on stroke was homogeneous across risk score tertiles (P-interaction = .67). Among patients in whom the risk score was estimated, d-dimer was available in 2343 (80%). d-dimer had an acceptable discrimination performance for stroke prediction (C-index = 0.66) and higher plasma d-dimer concentrations were associated with higher rates of stroke (ie, tertile 3 vs tertile 1, hazard ratio 3.65, 95% confidence interval 1.59-8.39, P = .002). Treatment with low-dose rivaroxaban reduced the incidence of stroke in patients at highest risk by d-dimer levels (ie, >515 ng/mL, hazard ratio 0.42, 95% confidence interval 0.18-0.95, P-interaction = .074), without any safety concerns. CONCLUSIONS: In our analysis, plasma d-dimer concentrations performed better than a previously described 3-variable risk score for stroke prediction in patients with heart failure with reduced ejection fraction, a recent clinical worsening and sinus rhythm as enrolled in the COMMANDER-HF trial. In these patients, a raised plasma d-dimer concentration identified patients who might benefit most from rivaroxaban.

Real-World Eligibility and Cost-Effectiveness Analysis of Empagliflozin for Heart Failure in Korea.

BACKGROUND: The US Food and Drug Administration (FDA) and European Medicines Agency (EMA) approved empagliflozin for reducing cardiovascular mortality and heart failure (HF) hospitalization in patients with both HF with reduced ejection fraction (HFrEF) and HF with preserved ejection fraction (HFpEF). However, limited data are available on the generalizability of empagliflozin to clinical practice. Therefore, we evaluated real-world eligibility and potential cost-effectiveness based on a nationwide prospective HF registry. METHODS: A total of 3,108 HFrEF and 2,070 HFpEF patients from the Korean Acute Heart Failure (KorAHF) registry were analyzed. Eligibility was estimated by inclusion and exclusion criteria of EMPagliflozin outcomE tRial in Patients With chrOnic heaRt Failure With Reduced Ejection Fraction (EMPEROR-Reduced) and EMPagliflozin outcomE tRial in Patients With chrOnic heaRt Failure With Preserved Ejection Fraction (EMPEROR-Preserved) trials and by FDA & EMA label criteria. The cost-utility analysis was done using a Markov model to project the lifetime medical cost and quality-adjusted life year (QALY). RESULTS: Among the KorAHF patients, 91.4% met FDA & EMA label criteria, while 44.7% met the clinical trial criteria. The incremental cost-effectiveness ratio of empagliflozin was calculated at US$6,764 per QALY in the overall population, which is far below a threshold of US$18,182 per QALY. The cost-effectiveness benefit was more evident in patients with HFrEF (US$5,012 per QALY) than HFpEF (US$8,971 per QALY). CONCLUSION: There is a large discrepancy in real-world eligibility for empagliflozin between FDA & EMA labels and clinical trial criteria. Empagliflozin is cost-effective in HF patients regardless of ejection fraction in South Korea health care setting. The efficacy and safety of empagliflozin in real-world HF patients should be further investigated for a broader range of clinical applications. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01389843.

Determinants of Guideline-Directed Medical Therapy Implementation During Heart Failure Hospitalization.

Background: Despite evidence that guideline-directed medical therapies (GDMTs) improve outcomes in patients with heart failure (HF) with reduced ejection fraction (HFrEF), implementation remains suboptimal. Objectives: The purpose of this study was to measure GDMT implementation during acute HFrEF hospitalization, evaluate the association between socioeconomic factors and GDMT implementation, and assess the association of GDMT utilization with subsequent clinical events. Methods: Retrospective determination of GDMT utilization using a modified optimal medical therapy (mOMT) score (which accounts for specific contraindications to drugs) during unplanned HF hospitalization of consecutive adult patients with new-onset or previously diagnosed HFrEF from 2017 to 2018. Outcomes included discharge mOMT score, association between socioeconomic factors and GDMT implementation (assessed using both the Mann-Whitney U test for binary variables and the Kruskall-Wallace for nonbinary variables), composite outcome 1-year all-cause mortality and 1-year HF readmission, and each component as a function of discharge mOMT score (assessed using univariate and multivariable Cox proportional hazards regression models). Results: Of 391 patients fulfilling entry criteria (of which 152 [38.9%] had new-onset HFrEF), only 49 (12.5%) had a perfect or near-perfect discharge mOMT score. Black patients and those experiencing homelessness had significantly lower discharge mOMT scores. Higher discharge mOMT score is associated with a lower rate of composite endpoint events, particularly in patients with new-onset HFrEF. Overall, a 0.1-increase in the mOMT score resulted in a 9.2% reduction in the composite endpoint. Conclusions: Suboptimal implementation of GDMT during HF hospitalization is widespread and is associated with a worse outcome. Black patients and patients experiencing homelessness were less likely to have GDMT optimized.

Incidence of Acute Rejection Compared With Endomyocardial Biopsy Complications for Heart Transplant Patients in the Contemporary Era.

BACKGROUND: The reference standard of detecting acute rejection (AR) in adult heart transplant (HTx) patients is an endomyocardial biopsy (EMB). The majority of EMBs are performed in asymptomatic patients. However, the incidence of treated AR compared with EMB complications has not been compared in the contemporary era (2010-current). METHODS: The authors retrospectively analyzed 2769 EMBs obtained in 326 consecutive HTx patients between August 2019 and August 2022. Variables included surveillance versus for-cause indication, recipient and donor characteristics, EMB procedural data and pathological grades, treatment for AR, and clinical outcomes. RESULTS: The overall EMB complications rate was 1.6%. EMBs performed within 1 mo after HTx compared with after 1 mo from HTx showed significantly increased complications (OR, 12.74, P < 0.001). The treated AR rate was 14.2% in the for-cause EMBs and 1.2% in the surveillance EMBs. We found the incidence of AR versus EMB complications was significantly lower in the surveillance compared with the for-cause EMB group (OR, 0.05, P < 0.001). We also found the incidence of EMB complications was higher than treated AR in surveillance EMBs. CONCLUSIONS: The yield of surveillance EMBs has declined in the contemporary era, with a higher incidence of EMB complications compared with detected AR. The risk of EMB complications was highest within 1 mo after HTx. Surveillance EMB protocols in the contemporary era may need to be reevaluated.

Performance of risk models to predict mortality risk for patients with heart failure: evaluation in an integrated health system.

BACKGROUND: Referral of patients with heart failure (HF) who are at high mortality risk for specialist evaluation is recommended. Yet, most tools for identifying such patients are difficult to implement in electronic health record (EHR) systems. OBJECTIVE: To assess the performance and ease of implementation of Machine learning Assessment of RisK and EaRly mortality in Heart Failure (MARKER-HF), a machine-learning model that uses structured data that is readily available in the EHR, and compare it with two commonly used risk scores: the Seattle Heart Failure Model (SHFM) and Meta-Analysis Global Group in Chronic (MAGGIC) Heart Failure Risk Score. DESIGN: Retrospective, cohort study. PARTICIPANTS: Data from 6764 adults with HF were abstracted from EHRs at a large integrated health system from 1/1/10 to 12/31/19. MAIN MEASURES: One-year survival from time of first cardiology or primary care visit was estimated using MARKER-HF, SHFM, and MAGGIC. Discrimination was measured by the area under the receiver operating curve (AUC). Calibration was assessed graphically. KEY RESULTS: Compared to MARKER-HF, both SHFM and MAGGIC required a considerably larger amount of data engineering and imputation to generate risk score estimates. MARKER-HF, SHFM, and MAGGIC exhibited similar discriminations with AUCs of 0.70 (0.69-0.73), 0.71 (0.69-0.72), and 0.71 (95% CI 0.70-0.73), respectively. All three scores showed good calibration across the full risk spectrum. CONCLUSIONS: These findings suggest that MARKER-HF, which uses readily available clinical and lab measurements in the EHR and required less imputation and data engineering than SHFM and MAGGIC, is an easier tool to identify high-risk patients in ambulatory clinics who could benefit from referral to a HF specialist.

Distinct Comorbidity Clusters in Patients With Acute Heart Failure: Data From RELAX-AHF-2.

BACKGROUND: Multimorbidity frequently occurs in patients with acute heart failure (AHF). The co-occurrence of comorbidities often follows specific patterns. OBJECTIVES: This study investigated multimorbidity subtypes and their associations with clinical outcomes. METHODS: From the prospective RELAX-AHF-2 (Relaxin for the Treatment of Acute Heart Failure-2) trial, 6,545 patients (26% with HF with preserved ejection fraction, defined as LVEF ≥50%) were classified into multimorbidity groups using latent class analysis. The association between subgroups and clinical outcomes was examined. Validation of these findings was conducted in the RELAX-AHF trial, which comprised 1,161 patients. RESULTS: Five distinct multimorbidity groups emerged: 1) diabetes and chronic kidney disease (CKD) (often male, high prevalence of CKD and diabetes mellitus); 2) ischemic (ischemic HF); 3) elderly/atrial fibrillation (AF) (oldest, high prevalence of AF); 4) metabolic (obese, hypertensive, more often HF with preserved ejection fraction); and 5) young (fewest comorbidities). After adjusting for confounders, patients in the diabetes and CKD (HR: 1.80; 95% CI: 1.50-2.20), elderly/AF (HR: 1.42; 95% CI: 1.20-1.70), and metabolic (HR: 1.40; 95% CI: 1.20-1.80) groups had higher rates of the composite outcome than patients in the young group, primarily driven by differences in rehospitalization. Treatment allocation (placebo or serelaxin) modified these associations (Pinteraction <0.001). Serelaxin-treated patients in the young group were associated with a lower risk for all-cause mortality (HR: 0.59; 95% CI: 0.40-0.90). Similarly, patients from the RELAX-AHF trial clustered in 5 multimorbidity groups. The clinical characteristics and associations with outcomes could also be validated. CONCLUSIONS: Comorbidities naturally clustered into 5 mutually exclusive groups in RELAX-AHF-2, showing variations in clinical outcomes. These data emphasize that the specific combination of comorbidities can influence adverse outcomes and treatment responses in patients with AHF.

Eligibility and Cost-Utility Analysis of Dapagliflozin in Patients with Heart Failure Across the Whole Spectrum of Ejection Fraction in South Korea.

BACKGROUND: The DAPA-HF and DELIVER trials demonstrated the clinical benefits of dapagliflozin in heart failure (HF) patients across the entire ejection fraction (EF) spectrum. However, further investigation is needed for the real-world application of dapagliflozin in HF patients. This study examines the proportion of real-world HF patients eligible for dapagliflozin and evaluates the cost-effectiveness of adding dapagliflozin to current HF therapy. METHODS: Data from the nationwide prospective registry, the Korean Acute Heart Failure (KorAHF) registry, were used to determine dapagliflozin eligibility based on the enrollment criteria of the DAPA-HF/DELIVER trials. A cost-utility analysis was conducted using a Markov model to assess the cost-effectiveness of dapagliflozin by comparing it to the standard of care. RESULTS: Out of 5178 KorAHF patients, 48.7% met the enrollment criteria of the DAPA-HF/DELIVER trials, while 89.5% met the label criteria (US Food and Drug Administration, European Medicines Agency, and Korean Ministry of Food and Drug Safety). Eligibility was highest among HF patients with preserved EF (55.3% vs. HF with mildly reduced EF and HF with reduced EF 46.4%). Dapagliflozin proved to be cost-effective, with an incremental cost-effectiveness ratio (ICER) of 4557 US dollar (US$) per quality-adjusted life year, which falls below the US$18,182 willingness-to-pay threshold. The cost-effectiveness benefit was more pronounced in patients with a left ventricular EF (LVEF) ≤ 40% (ICER US$3279 for LVEF ≤ 40% vs. US$8383 for LVEF > 40%). CONCLUSIONS: Discrepancies in dapagliflozin eligibility were observed between real-world data and clinical trial results. The addition of dapagliflozin to HF therapy proved to be highly cost-effective across the entire EF spectrum.

Mortality Prediction in Patients With or Without Heart Failure Using a Machine Learning Model.

Background: Most risk prediction models are confined to specific medical conditions, thus limiting their application to general medical populations. Objectives: The MARKER-HF (Machine learning Assessment of RisK and EaRly mortality in Heart Failure) risk model was developed in heart failure (HF) patients. We assessed the ability of MARKER-HF to predict 1-year mortality in a large community-based hospital registry database including patients with and without HF. Methods: This study included 41,749 consecutive patients who underwent echocardiography in a tertiary referral hospital (4,640 patients with and 37,109 without HF). Patients without HF were further subdivided into those with (n = 22,946) and without cardiovascular disease (n = 14,163) and also into cohorts based on recent acute coronary syndrome or history of atrial fibrillation, chronic obstructive pulmonary disease, chronic kidney disease, diabetes mellitus, hypertension, or malignancy. Results: The median age of the 41,749 patients was 65 years, and 56.2% were male. The receiver operated area under the curves for MARKER-HF prediction of 1-year mortality of patients with HF was 0.729 (95% CI: 0.706-0.752) and for patients without HF was 0.770 (95% CI: 0.760-0.780). MARKER-HF prediction of mortality was consistent across subgroups with and without cardiovascular disease and in patients diagnosed with acute coronary syndrome, atrial fibrillation, chronic obstructive pulmonary disease, chronic kidney disease, diabetes mellitus, or hypertension. Patients with malignancy demonstrated higher mortality at a given MARKER-HF score than did patients in the other groups. Conclusions: MARKER-HF predicts mortality for patients with HF as well as for patients suffering from a variety of diseases.