Prognostic Models Derived in PARADIGM-HF and Validated in ATMOSPHERE and the Swedish Heart Failure Registry to Predict Mortality and Morbidity in Chronic Heart Failure

International Society for Heart and Lung Transplantation Guidelines for the Evaluation and Care of Cardiac Transplant Candidates-2024

The "International Society for Heart and Lung Transplantation Guidelines for the Evaluation and Care of Cardiac Transplant Candidates-2024" updates and replaces the "Listing Criteria for Heart Transplantation: International Society for Heart and Lung Transplantation Guidelines for the Care of Cardiac Transplant Candidates-2006" and the "2016 International Society for Heart Lung Transplantation Listing Criteria for Heart Transplantation: A 10-year Update." The document aims to provide tools to help integrate the numerous variables involved in evaluating patients for transplantation, emphasizing updating the collaborative treatment while waiting for a transplant. There have been significant practice-changing developments in the care of heart transplant recipients since the publication of the International Society for Heart and Lung Transplantation (ISHLT) guidelines in 2006 and the 10-year update in 2016. The changes pertain to 3 aspects of heart transplantation: (1) patient selection criteria, (2) care of selected patient populations, and (3) durable mechanical support. To address these issues, 3 task forces were assembled. Each task force was cochaired by a pediatric heart transplant physician with the specific mandate to highlight issues unique to the pediatric heart transplant population and ensure their adequate representation. This guideline was harmonized with other ISHLT guidelines published through November 2023. The 2024 ISHLT guidelines for the evaluation and care of cardiac transplant candidates provide recommendations based on contemporary scientific evidence and patient management flow diagrams. The American College of Cardiology and American Heart Association modular knowledge chunk format has been implemented, allowing guideline information to be grouped into discrete packages (or modules) of information on a disease-specific topic or management issue. Aiming to improve the quality of care for heart transplant candidates, the recommendations present an evidence-based approach.

AI hybrid survival assessment for advanced heart failure patients with renal dysfunction

Renal dysfunction (RD) often characterizes the worse course of patients with advanced heart failure (AHF). Many prognosis assessments are hindered by researcher biases, redundant predictors, and lack of clinical applicability. In this study, we enroll 1736 AHF/RD patients, including data from Henan Province Clinical Research Center for Cardiovascular Diseases (which encompasses 11 hospital subcenters), and Beth Israel Deaconess Medical Center. We developed an AI hybrid modeling framework, assembling 12 learners with different feature selection paradigms to expand modeling schemes. The optimized strategy is identified from 132 potential schemes to establish an explainable survival assessment system: AIHFLevel. The conditional inference survival tree determines a probability threshold for prognostic stratification. The evaluation confirmed the system's robustness in discrimination, calibration, generalization, and clinical implications. AIHFLevel outperforms existing models, clinical features, and biomarkers. We also launch an open and user-friendly website www.hf-ai-survival.com , empowering healthcare professionals with enhanced tools for continuous risk monitoring and precise risk profiling.

Cardiovascular disease healthcare trajectories: descriptions, similarities, mortality rates of heart failure in France

AIMS

The primary objectives of this study were to analyse the nationwide healthcare trajectories of heart failure (HF) patients in France, 2 years after their first hospitalization, and to measure sequence similarities. Secondary objectives were to identify the association between trajectories and the risk of mortality.

METHODS AND RESULTS

A retrospective, observational study was conducted using data extracted from the Echantillon Généraliste des Bénéficiaires database, covering the period from 1 January 2008 to 31 December 2018. Follow-up concluded upon death or at the end of the study. We developed a methodology specific to healthcare data by extracting frequent healthcare trajectories and measuring their similarity for use in a survival machine learning analysis. In total, 11 488 HF patients were included and followed up for an average of 2.9 ± 1.3 years. The mean age of the patients was 78.0 ± 13.2 years. The first-year mortality rate was 31.7% and increased to 78.8% at 5 years. Fifty per cent of patients experienced re-hospitalization for reasons related to cardiovascular diseases. We identified 1707 hospitalization sequences, and 21 sequences were associated with survival, while 15 sequences were linked to mortality. In all our models, age and gender emerged as the most significant predictors of mortality (permutation feature importance: 0.099 ± 0.00078 and 0.0087 ± 0.00018, respectively; weights could be interpreted in relative terms). Specifically, the age at initial hospitalization for HF was positively associated with mortality. Gender (male: 49.5%) was associated with poorer prognoses. Healthcare trajectories, including non-surgical device treatments, valve replacements, and atrial fibrillation ablation, were associated with a better prognosis (permutation feature importance: 0.0047 ± 0.00011, 0.0014 ± 0.000073, and 0.00095 ± 0.000097, respectively), except in cases where these invasive treatments preceded or followed hospitalization for cardiac decompensation. The predominant negative prognosis sequences were mostly those that included HF-related hospitalizations before or after other-related hospitalizations (permutation feature importance: 0.0007 ± 0.000091 and 0.00011 ± 0.000045, respectively).

CONCLUSIONS

We highlight the value of healthcare trajectories on frequent hospitalization sequences, mortality, and prognosis and indicate the necessary prognostic value of HF re-hospitalization. Our work may be an essential tool for better identification of at-risk patients in order to increase and improve personalized care in the future.

Deep learning for predicting rehospitalization in acute heart failure: Model foundation and external validation

AIMS

Assessing the risk for HF rehospitalization is important for managing and treating patients with HF. To address this need, various risk prediction models have been developed. However, none of them used deep learning methods with real-world data. This study aimed to develop a deep learning-based prediction model for HF rehospitalization within 30, 90, and 365 days after acute HF (AHF) discharge.

METHODS AND RESULTS

We analysed the data of patients admitted due to AHF between January 2014 and January 2019 in a tertiary hospital. In performing deep learning-based predictive algorithms for HF rehospitalization, we use hyperbolic tangent activation layers followed by recurrent layers with gated recurrent units. To assess the readmission prediction, we used the AUC, precision, recall, specificity, and F1 measure. We applied the Shapley value to identify which features contributed to HF readmission. Twenty-two prognostic features exhibiting statistically significant associations with HF rehospitalization were identified, consisting of 6 time-independent and 16 time-dependent features. The AUC value shows moderate discrimination for predicting readmission within 30, 90, and 365 days of follow-up (FU) (AUC:0.63, 0.74, and 0.76, respectively). The features during the FU have a relatively higher contribution to HF rehospitalization than features from other time points.

CONCLUSIONS

Our deep learning-based model using real-world data could provide valid predictions of HF rehospitalization in 1 year follow-up. It can be easily utilized to guide appropriate interventions or care strategies for patients with HF. The closed monitoring and blood test in daily clinics are important for assessing the risk of HF rehospitalization.

Development and internal validation of a clinical prediction model to predict independence in daily living at discharge for patients with heart failure: analysis using a Japanese national inpatient database real-world dataset

PURPOSE

To develop a clinical prediction model (CPM) to predict independence in activities of daily living (ADLs) in patients with heart failure.

SUBJECTS AND METHODS

We collected the data of the individuals who were admitted and rehabilitated for heart failure from January 2017 to June 2022 from Japan's Diagnosis Procedure Combination database. We assessed the subjects' ADLs at discharge using the Barthel Index and classified them into independence, partial-independence, and total-dependence groups based on their ADLs at discharge. Two CPMs (an independence model and a partial-independence model) were developed by a binomial logistic regression analysis. The predictors included subject characteristics, treatment, and post-hospitalization disease onset. The CPMs' accuracy was validated by the area under the curve (AUC). Internal validation was performed using the bootstrap method. The final CPM is presented in a nomogram.

RESULTS

We included 96,753 patients whose ADLs could be traced at discharge. The independence model had a 0.73 mean AUC and a 1.0 slope at bootstrapping. We thus developed a simplified model using nomograms, which also showed adequate predictive accuracy in the independence model. The partial-independence model had a 0.65 AUC and inadequate predictive accuracy.

CONCLUSIONS

The independence model of ADLs in patients with heart failure is a useful CPM.

Prediction of recurrent heart failure hospitalizations and mortality using the echocardiographic Killip score

AIM

Examine the performance of a simple echocardiographic "Killip score" (eKillip) in predicting heart failure (HF) hospitalizations and mortality after index event of decompensated HF hospitalization.

METHODS

HF patients hospitalized at our facility between 03/2019-03/2021 who underwent an echocardiography during their index admission were included in this retrospective analysis. The cohort was divided into 4 classes of eKillip according to: stroke volume index (SVI) < 35ml/m2 > and E/E' ratio < 15 > . An eKillip Class I was defined as SVI ≥ 35ml/m2 and E/E' ≤ 15 and was used as reference.

RESULTS

Included 751 patients, median age 78.1 (IQR 69.3-86) years, 59% men, left ventricular ejection fraction 45 (IQR 30-60)%, brain natriuretic peptide levels 634 (IQR 331-1222)pg/ml. Compared with eKillip Class I, a graded increase in the combined endpoint of 30-day mortality and rehospitalizations rates was noted: (Class II: HR 1.77, CI 0.95-3.33, p = 0.07; Class III: HR 1.94, CI 1.05-3.6, p = 0.034; Class IV: HR 2.9, CI 1.64-5.13, p < 0.001 respectively), which overall persisted after correction for clinical (Class II: HR 1.682, CI 0.9-3.15, p = 0.105; Class III: HR 2.104, CI 1.13-3.9, p = 0.019; Class IV: HR 2.74, CI 1.54-4.85, p = 0.001 respectively) or echocardiographic parameters (Class II: HR 1.92, CI 1.02-3.63, p = 0.045; Class III: HR 1.54, CI 0.81-2.95, p = 0.189; Class IV: HR 2.04, CI 1.1-3.76, p = 0.023 respectively). Specifically, the eKillip Class IV group comprised one-third of the patient population and persistently showed increased risk of 30-day HF hospitalizations or mortality following multivariate analysis.

CONCLUSION

A simple echocardiographic score can assist identifying high-risk decompensated HF patients for recurrent hospitalizations and mortality.

S2I2N0-3 score predicts short- and long-term mortality and morbidity in HFrEF: a post-hoc analysis of the GUIDE-IT trial

AIMS

This study investigated the S2I2N0-3 score, a simple tool comprising stroke history, insulin-treated diabetes, and N-terminal pro-brain natriuretic peptide, for forecasting mortality and morbidity in heart failure (HF) with reduced ejection fraction (HFrEF).

METHODS AND RESULTS

Analysing 890 GUIDE-IT HFrEF trial participants, we stratified them by baseline S2I2N0-3 risk score into three risk groups. We examined the score's association with five adverse outcomes over short (90 days) and extended periods (median follow-up of 15 months) using Cox and competing risk models. Our analysis revealed significant positive associations between the S2I2N0-3 strata and adverse outcomes. When analysed as a continuous variable, each point increment of the S2I2N0-3 score was associated with a higher risk of short- and long-term cardiovascular death [short term: hazard ratio (HR) 1.43, 95% confidence interval (CI) 1.03-1.98; long term: HR 1.18, 95% CI 1.02-1.38], all-cause death (HR 1.52, 95% CI 1.12-2.07; HR 1.18, 95% CI 1.03-1.36), HF hospitalization (HR 1.39, 95% CI 1.20-1.62; HR 1.18, 95% CI 1.06-1.31), any hospitalization (HR 1.19, 95% CI 1.06-1.34; HR 1.09, 95% CI 1.00-1.19), and the composite outcome of cardiovascular death and HF hospitalization (HR 1.39, 95% CI 1.21-1.60; HR 1.17, 95% CI 1.06-1.30). The S2I2N0-3 demonstrated reliable prognostic value, with C-indices ranging from 0.619 to 0.753 across outcomes and time points. When compared with the Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) score using Z-statistics, net reclassification index, and integrated discrimination improvement, the S2I2N0-3 showed comparable predictive power for all outcomes during both short- and long-term follow-ups.

CONCLUSIONS

The S2I2N0-3 risk score had modest predictive values for both short- and long-term clinical outcomes in HFrEF patients, offering equivalent performance to the established MAGGIC score.

Prognostic Models for Mortality and Morbidity in Heart Failure With Preserved Ejection Fraction

Importance

Accurate risk prediction of morbidity and mortality in patients with heart failure with preserved ejection fraction (HFpEF) may help clinicians risk stratify and inform care decisions.

Objective

To develop and validate a novel prediction model for clinical outcomes in patients with HFpEF using routinely collected variables and to compare it with a biomarker-driven approach.

Design, Setting, and Participants

Data were used from the Dapagliflozin Evaluation to Improve the Lives of Patients With Preserved Ejection Fraction Heart Failure (DELIVER) trial to derive the prediction model, and data from the Angiotensin Receptor Neprilysin Inhibition in Heart Failure With Preserved Ejection Fraction (PARAGON-HF) and the Irbesartan in Heart Failure With Preserved Ejection Fraction Study (I-PRESERVE) trials were used to validate it. The outcomes were the composite of HF hospitalization (HFH) or cardiovascular death, cardiovascular death, and all-cause death. A total of 30 baseline candidate variables were selected in a stepwise fashion using multivariable analyses to create the models. Data were analyzed from January 2023 to June 2023.

Exposures

Models to estimate the 1-year and 2-year risk of cardiovascular death or hospitalization for heart failure, cardiovascular death, and all-cause death.

Results

Data from 6263 individuals in the DELIVER trial were used to derive the prediction model and data from 4796 individuals in the PARAGON-HF trial and 4128 individuals in the I-PRESERVE trial were used to validate it. The final prediction model for the composite outcome included 11 variables: N-terminal pro-brain natriuretic peptide (NT-proBNP) level, HFH within the past 6 months, creatinine level, diabetes, geographic region, HF duration, treatment with a sodium-glucose cotransporter 2 inhibitor, chronic obstructive pulmonary disease, transient ischemic attack/stroke, any previous HFH, and heart rate. This model showed good discrimination (C statistic at 1 year, 0.73; 95% CI, 0.71-0.75) in both validation cohorts (C statistic at 1 year, 0.71; 95% CI, 0.69-0.74 in PARAGON-HF and 0.75; 95% CI, 0.73-0.78 in I-PRESERVE) and calibration. The model showed similar discrimination to a biomarker-driven model including high-sensitivity cardiac troponin T and significantly better discrimination than the Meta-Analysis Global Group in Chronic (MAGGIC) risk score (C statistic at 1 year, 0.60; 95% CI, 0.58-0.63; delta C statistic, 0.13; 95% CI, 0.10-0.15; P < .001) and NT-proBNP level alone (C statistic at 1 year, 0.66; 95% CI, 0.64-0.68; delta C statistic, 0.07; 95% CI, 0.05-0.08; P < .001). Models derived for the prediction of all-cause and cardiovascular death also performed well. An online calculator was created to allow calculation of an individual's risk.

Conclusions and Relevance

In this prognostic study, a robust prediction model for clinical outcomes in HFpEF was developed and validated using routinely collected variables. The model performed better than NT-proBNP level alone. The model may help clinicians to identify high-risk patients and guide treatment decisions in HFpEF.

Bioinformatics analysis and identification of potential key genes and pathways in the pathogenesis of nonischemic cardiomyopathy

Nonischemic cardiomyopathy (NICM) is a major cause of advanced heart failure, and the morbidity and mortality associated with NICM are serious medical problems. However, the etiology of NICM is complex and the related mechanisms involved in its pathogenesis remain unclear. The microarray datasets GSE1869 and GSE9128 retrieved from the Gene Expression Omnibus database were used to identify differentially expressed genes (DEGs) between NICM and normal samples. The co-expressed genes were identified using Venn diagrams. Kyoto Encyclopedia of Genes and Genomes pathway analyses and gene ontology enrichment were used to clarify biological functions and signaling pathways. Analysis of protein-protein interaction networks using Search Tool for the Retrieval of Interacting Genes/Proteins online to define the hub genes associated with NICM pathogenesis. A total of 297 DEGs were identified from GSE1869, 261 of which were upregulated genes and 36 were downregulated genes. A total of 360 DEGs were identified from GSE9128, 243 of which were upregulated genes and 117 were downregulated genes. In the 2 datasets, the screening identified 36 co-expressed DEGs. Kyoto Encyclopedia of Genes and Genomes pathway and gene ontology analysis showed that DEGs were mainly enriched in pantothenate and CoA biosynthesis, beta-alanine metabolism, kinetochore, G-protein beta/gamma-subunit complex, and other related pathways. The PPI network analysis revealed that DUSP6, EGR1, ZEB2, and XPO1 are the 4 hub genes of interest in the 2 datasets. Bioinformatics analysis of hub genes and key signaling pathways is an effective way to elucidate the mechanisms involved in the development of NICM. The results will facilitate further studies on the pathogenesis and therapeutic targets of NICM.

A novel score to predict left ventricular recovery in peripartum cardiomyopathy derived from the ESC EORP Peripartum Cardiomyopathy Registry

BACKGROUND AND AIMS

There are no established clinical tools to predict left ventricular (LV) recovery in women with peripartum cardiomyopathy (PPCM). Using data from women enrolled in the ESC EORP PPCM Registry, the aim was to derive a prognostic model to predict LV recovery at 6 months and develop the 'ESC EORP PPCM Recovery Score'-a tool for clinicians to estimate the probability of LV recovery.

METHODS

From 2012 to 2018, 752 women from 51 countries were enrolled. Eligibility included (i) a peripartum state, (ii) signs or symptoms of heart failure, (iii) LV ejection fraction (LVEF) ≤ 45%, and (iv) exclusion of alternative causes of heart failure. The model was derived using data from participants in the Registry and internally validated using bootstrap methods. The outcome was LV recovery (LVEF ≥50%) at six months. An integer score was created.

RESULTS

Overall, 465 women had a 6-month echocardiogram. LV recovery occurred in 216 (46.5%). The final model included baseline LVEF, baseline LV end diastolic diameter, human development index (a summary measure of a country's social and economic development), duration of symptoms, QRS duration and pre-eclampsia. The model was well-calibrated and had good discriminatory ability (C-statistic 0.79, 95% confidence interval [CI] 0.74-0.83). The model was internally validated (optimism-corrected C-statistic 0.78, 95% CI 0.73-0.82).

CONCLUSIONS

A model which accurately predicts LV recovery at 6 months in women with PPCM was derived. The corresponding ESC EORP PPCM Recovery Score can be easily applied in clinical practice to predict the probability of LV recovery for an individual in order to guide tailored counselling and treatment.

The Validity of Patient-Reported Outcome Measures of Quality of Life in Palliative Care: A Systematic Review

Importance: A recent systematic review and meta-analysis found that palliative care was not associated with improvement in quality of life (QOL) in terminal noncancer illness. Among potential reasons for a null effect, it is unclear if patient-reported outcome measures (PROMs) measuring QOL were derived or validated among populations with advanced life-limiting illness (ALLI). Objective: To systematically review the derivation and validation of QOL PROMs from a recent meta-analysis of randomized controlled trials (RCT) of palliative care interventions in people with terminal noncancer illness. Evidence Review: EMBASE, MEDLINE, and PsycINFO were searched from inception to January 8, 2023 for primary validation studies of QOL PROMs in populations with ALLI, defined as adults with a progressive terminal condition and an estimated median survival of less than or equal to one year. The primary outcome was the proportion of PROMs that were derived or validated in ≥1 ALLI population. Findings: Twenty-one unique studies of derivation (n = 13) and validation (n = 11, 3 studies evaluated both) provided data on 9657 participants (mean age 63 years, 50% female) across 15 unique QOL PROMs and subscales. Among studies of validation, 9 were in people with cancer (n = 2289, n = 5 PROMs), 1 in neurodegenerative disease (n = 23, n = 1 PROM), and 1 with mixed diseases (n = 248, n = 1 PROM). Across 15 QOL PROMs and subscales, 47% (n = 7) were derived or validated in an ALLI population. The majority of these seven PROMs were exclusively derived or validated among people with cancer (57%, n = 4). QOL PROMs such as Quality of Life at End of Life, EuroQoL-5 Dimension 5-level, and 36-item Short Form Survey demonstrated validity in more than one terminal noncancer illness. Conclusions: Most QOL PROMs that measured the effect of palliative care on QOL in RCTs were neither derived nor validated in an ALLI population. These findings raise questions about the inferences that palliative care does not improve QOL among people with terminal noncancer illness.

Prognostic Impact of Reduced Left Ventricular Ejection Fraction After Endovascular Therapy for Lower Extremities

BACKGROUND

The mechanism underlying a poor prognosis in patients with lower-extremity artery disease (LEAD) with heart failure is unknown. We examined the prognostic impact of the left ventricular ejection fraction (LVEF) in patients with LEAD who underwent endovascular therapy (EVT).Methods and Results: From August 2014 to August 2016, 2,180 patients with LEAD (mean age, 73.2 years; male, 71.9%) underwent EVT and were stratified into low-LVEF (LVEF <40%; n=234, 10.7%) and not-low LVEF groups. In the low- vs. not-low LVEF groups, there was a higher prevalence of heart failure (i.e., history of heart failure hospitalization or New York Heart Association functional class III or IV symptoms) (44.0% vs. 8.3%, respectively), diabetes mellitus, chronic kidney disease, below-the-knee lesion, critical limb ischemia, and incidence of major cardiovascular and cerebrovascular events (MACCEs) and major adverse limb events (MALEs) (P<0.001, all). Low LVEF independently predicted MACCEs (hazard ratio: 2.23, 95% confidence interval: 1.63-3.03; P<0.001) and MALEs (hazard ratio: 1.85, 95% confidence interval: 1.15-2.96; P=0.011), regardless of heart failure (P value for interaction: MACCEs: 0.27; MALEs: 0.52).

CONCLUSIONS

Low LVEF, but not symptomatic heart failure, increased the incidence of MACCEs and MALEs. Intensive cardiac dysfunction management may improve LEAD prognosis after EVT.

Incremental prognostic value of functional impairment assessed by 6-min walking test for the prediction of mortality in heart failure

Natriuretic peptides (NP) are recognized as the most powerful predictors of adverse outcomes in heart failure (HF). We hypothesized that a measure of functional limitation, as assessed by 6-min walking test (6MWT), would improve the accuracy of a prognostic model incorporating a NP. This was a multicenter observational retrospective study. We studied the prognostic value of severe functional impairment (SFI), defined as the inability to perform a 6MWT or a distance walked during a 6MWT < 300 m, in 1696 patients with HF admitted to cardiac rehabilitation. The primary outcome was 1-year all-cause mortality. After adjusting for the baseline multivariable risk model-including age, sex, systolic blood pressure, anemia, renal dysfunction, sodium level, and NT-proBNP-or for the MAGGIC score, SFI had an odds ratio of 2.58 (95% CI 1.72-3.88; p < 0.001) and 3.12 (95% CI 2.16-4.52; p < 0.001), respectively. Adding SFI to the baseline risk model or the MAGGIC score yielded a significant improvement in discrimination and risk classification. Our data suggest that a simple, 6MWT-derived measure of SFI is a strong predictor of death and provide incremental prognostic information over well-established risk markers in HF, including NP, and the MAGGIC score.

Heart failure registries - Future directions

Heart failure (HF) is a growing, global public health issue. Despite advances in HF care, many challenges remain and HF outcomes are poor. Some of the major reasons for this are the lack of understanding and treatment for certain HF sub-types as well as the lack of implementation of treatment in areas where effective treatment exists. HF registries provide the opportunity to transform clinical research and patient care. Recently the registry-based randomized clinical trial has emerged as a pragmatic and inexpensive alternative to the gold standard in clinical trial design, the randomized controlled trial. Registries may also provide platforms for strategy trials, implementation trials, and screening. Using examples from the Swedish Heart Failure Registry and others, the present review provides insights into how registry-based research can address many of the unmet needs in HF.

Empagliflozin improves cardiac function in rats with chronic heart failure

The objective of this study is to examine the effect of empagliflozin on cardiac function in rats with chronic heart failure and the possible mechanism. Forty 6-week-old male SD rats were randomly divided into the control group, empagliflozin treatment group, and sham-operated group. SD rats in the control group and empagliflozin treatment group were subjected to ligation of the anterior descending coronary artery to induce an acute myocardial infarction model. SD rats in the sham-operated group were only subjected to threading of the anterior descending branch of the coronary artery without ligation. On the second day after surgery, the control group and sham operation group were given physiological saline by gavage, while the empagliflozin treatment group was given empagliflozin (30 mg/kg/day) by gavage. Sixteen weeks later, cardiac function, intracellular reactive oxygen species (ROS) levels, mitochondrial membrane potential (MMP), serum brain natriuretic peptide, hypersensitive C-reactive protein (hs-CRP), iNOS expression levels, and myocardial morphological changes were observed. Compared with that in the control group, heart function in the empagliflozin-treated group was significantly improved, MMP was increased, intracellular ROS levels were decreased, and NT-proBNP and hs-CRP were significantly reduced, and HE staining showed that the cell oedema was less than that in the control group, tissue arrangement was more orderly, and iNOS expression was inhibited. Empagliflozin can improve cardiac function in rats with chronic heart failure, and the mechanism may involve inhibiting inflammation, reducing myocardial oxidative stress, and improving myocardial fibrosis.

Bayesian inference for a principal stratum estimand on recurrent events truncated by death

Recurrent events are often important endpoints in randomized clinical trials. For example, the number of recurrent disease-related hospitalizations may be considered as a clinically meaningful endpoint in cardiovascular studies. In some settings, the recurrent event process may be terminated by an event such as death, which makes it more challenging to define and estimate a causal treatment effect on recurrent event endpoints. In this paper, we focus on the principal stratum estimand, where the treatment effect of interest on recurrent events is defined among subjects who would be alive regardless of the assigned treatment. For the estimation of the principal stratum effect in randomized clinical trials, we propose a Bayesian approach based on a joint model of the recurrent event and death processes with a frailty term accounting for within-subject correlation. We also present Bayesian posterior predictive check procedures for assessing the model fit. The proposed approaches are demonstrated in the randomized Phase III chronic heart failure trial PARAGON-HF (NCT01920711).

Bone quality, mineral density, and fractures in heart failure

BACKGROUND

The trabecular bone score (TBS) indirectly estimates bone quality and predicts low-impact fractures independently of bone mineral density (BMD). However, there is still a paucity of data linking bone and heart diseases, mainly with gaps in the TBS analysis.

METHODS

In this cross-sectional study, we evaluated TBS, BMD, and fractures in patients with heart failure with reduced ejection fraction (HFrEF) and in sex-, BMI- and age-matched controls, and we assessed the fracture probability using the FRAX tool, considering active search for fractures by vertebral fracture assessment (VFA) and the adjustment for the TBS.

RESULTS

TBS values were 1.296 ± 0.14 in 85 patients (43.5% women; age 65 ± 13 years) and 1.320 ± 0.11 in 142 controls (P = 0.07), being reduced (< 1.31) in 51.8% and 46.1% of them, respectively (P = 0.12). TBS was lower in patients than in the controls when BMD was normal (P = 0.04) and when the BMI was 15-37 kg/m2 (P = 0.03). Age (odds ratio [OR] 1.05; P = 0.026), albumin (OR 0.12; P = 0.046), statin use (OR 0.27; P = 0.03), and energy intake (OR 1.03; P = 0.014) were associated with reduced TBS. Fractures on VFA occurred in 42.4% of the patients, and VFA and TBS adjustment increased the fracture risk by 16%-23%.

CONCLUSION

Patients with HFrEF had poor bone quality, with a better discriminating impact of the TBS assessment when BMD was normal, and BMI was suitable for densitometric analysis. Variables related to the prognosis, severity, and treatment of HFrEF were associated with reduced TBS. VFA and TBS adjustment increased fracture risk.

The prediction model of the short-term outcome in elderly heart failure patients

This study was designed to investigate the effect of the comprehensive geriatric assessment on the short-term prognosis of the elderly heart failure patients (EHFP), analyze the relevant risk factors, and construct an effective risk prediction model. According to the selection and exclusion criteria, 617 patients were filtered from 800 patients from the cadre ward database of the first Hospital of Jilin University. The EHFP were randomly divided into the model group (432 cases) and the validation group (185 cases). A retrospective study on the general clinical data of patients in the model group was conducted to analyze the risk factors associated with the short-term outcomes of EHFP. Based on the risk factors, the risk prediction model was established and validated through the validation group. In the model group, the following independent risk factors were identified for the short-term outcomes in EHFP in the light of univariate logistic and cox regression analysis: female (β = 0.989, OR = 1.277, 95% CI: 1.090-1.847, P = 0.024), age (65-75 years, β = 0.654, OR = 2.320, 95% CI: 1.135-3.136, P = 0.012; 75-85 years, β = 1.123, OR = 3.159, 95% CI: 1.532-5.189, P = 0.001; age > 85 years old, β = 1.513, OR = 4.895, 95% CI: 1.866-979, P = 0.001), frailty (β = 1.015, OR = 2.761, 95% CI: 1.097-6.945, P = 0.031), malnutrition (β = 1.271, OR = 3.560, 95% CI: 1.122-11.325, P = 0.002), and EF≦40% (β = 1.250, OR = 3.498, 95% CI: 1.898-6.447, P = 0.001). The simple risk prediction score was set up in line with the five risk factors, including range (1-7), the area under ROC curve (0.771, 95% CI: 0.723-0.819), and H-L test (P = 0.393), so patients were divided into the low-risk group (1-3) and the high-risk group (4-8). As a result, the number of EHFP in the high-risk group was significantly much more than that in the low-risk group (70.1% versus 29.9%, P < 0.001). Besides, the area under ROC curve (0.758, 95% CI: 0.682-0.835) and H-L test (P = 0.669) of the validation group indicated that this model could be a promising prediction model for the short-term outcomes of EHFP. Female, age, frailty, malnutrition, and EF ≦ 40% are independent risk factors for short-term outcomes of EHFP. The risk prediction model based on the five risk factors provided compelling clinic predictive value for the short-term prognosis of EHFP.

Personalized lifetime prediction of survival and treatment benefit in patients with heart failure with reduced ejection fraction: The LIFE-HF model

AIMS

Although trials have proven the group-level effectiveness of various therapies for heart failure with reduced ejection fraction (HFrEF), important differences in absolute effectiveness exist between individuals. We developed and validated the LIFEtime-perspective for Heart Failure (LIFE-HF) model for the prediction of individual (lifetime) risk and treatment benefit in patients with HFrEF.

METHODS AND RESULTS

Cox proportional hazards functions with age as the time scale were developed in the PARADIGM-HF and ATMOSPHERE trials (n = 15 415). Outcomes were cardiovascular death, heart failure (HF) hospitalization or cardiovascular death, and non-cardiovascular mortality. Predictors were age, sex, New York Heart Association class, prior HF hospitalization, diabetes mellitus, extracardiac vascular disease, systolic blood pressure, left ventricular ejection fraction, N-terminal pro-B-type natriuretic peptide, and glomerular filtration rate. The functions were combined in life-tables to predict individual overall and HF hospitalization-free survival. External validation was performed in the SwedeHF registry, ASIAN-HF registry, and DAPA-HF trial (n = 51 286). Calibration of 2- to 10-year risk was adequate, and c-statistics were 0.65-0.74. An interactive tool was developed combining the model with hazard ratios from trials to allow estimation of an individual's (lifetime) risk and treatment benefit in clinical practice. Applying the tool to the development cohort, combined treatment with a mineralocorticoid receptor antagonist, sodium-glucose cotransporter 2 inhibitor, and angiotensin receptor-neprilysin inhibitor was estimated to afford a median of 2.5 (interquartile range [IQR] 1.7-3.7) and 3.7 (IQR 2.4-5.5) additional years of overall and HF hospitalization-free survival, respectively.

CONCLUSION

The LIFE-HF model enables estimation of lifelong overall and HF hospitalization-free survival, and (lifetime) treatment benefit for individual patients with HFrEF. It could serve as a tool to improve the management of HFrEF by facilitating personalized medicine and shared decision-making.

Development and validation of a multivariate model for predicting heart failure hospitalization and mortality in patients receiving maintenance hemodialysis

BACKGROUND

Heart failure (HF) in patients undergoing maintenance hemodialysis (MHD) increases their hospitalization rates, mortality, and economic burden significantly. We aimed to develop and validate a predictive model utilizing contemporary deep phenotyping for individual risk assessment of all-cause mortality or HF hospitalization in patients on MHD.

MATERIALS AND METHODS

A retrospective review was conducted from January 2017 to October 2022, including 348 patients receiving MHD from four centers. The variables were adjusted by Cox regression analysis, and the clinical prediction model was constructed and verified.

RESULTS

The median follow-up durations were 14 months (interquartile range [IQR] 9-21) for the modeling set and 14 months (9-20) for the validation set. The composite outcome occurred in 72 (29.63%) of 243 patients in the modeling set and 39 (37.14%) of 105 patients in the validation set. The model predictors included age, albumin, history of cerebral hemorrhage, use of angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers/"sacubitril/valsartan", left ventricular ejection fraction, urea reduction ratio, N-terminal prohormone of brain natriuretic peptide, and right atrial size. The C-index was 0.834 (95% CI 0.784-0.883) for the modeling set and 0.853 (0.798, 0.908) for the validation set. The model exhibited excellent calibration across the complete risk profile, and the decision curve analysis (DCA) suggested its ability to maximize patient benefits.

CONCLUSION

The developed prediction model offered an accurate and personalized assessment of HF hospitalization risk and all-cause mortality in patients with MHD. It can be employed to identify high-risk patients and guide treatment and follow-up.

Heart failure diagnosis in the general community - Who, how and when? A clinical consensus statement of the Heart Failure Association (HFA) of the European Society of Cardiology (ESC)

A significant proportion of patients experience delays in the diagnosis of heart failure due to the non-specific signs and symptoms of the syndrome. Diagnostic tools such as measurement of natriuretic peptide concentrations are fundamentally important when screening for heart failure, yet are frequently under-utilized. This clinical consensus statement provides a diagnostic framework for general practitioners and non-cardiology community-based physicians to recognize, investigate and risk-stratify patients presenting in the community with possible heart failure.

Incremental prognostic value of biomarkers in PARADIGM-HF

AIMS

It is uncertain how much candidate biomarkers improve risk prediction when added to comprehensive models including routinely collected clinical and laboratory variables in heart failure.

METHODS AND RESULTS

Aldosterone, cystatin C, high-sensitivity troponin T (hs-TnT), galectin-3, growth differentiation factor-15 (GDF-15), kidney injury molecule-1, matrix metalloproteinase-2 and -9, soluble suppression of tumourigenicity-2, tissue inhibitor of metalloproteinase-1 (TIMP-1) and urinary albumin to creatinine ratio were measured in 1559 of PARADIGM-HF participants. We tested whether these biomarkers, individually or collectively, improved the performance of the PREDICT-HF prognostic model, which includes clinical, routine laboratory, and natriuretic peptide data, for the primary endpoint and cardiovascular and all-cause mortality. The mean age of participants was 67.3 ± 9.9 years, 1254 (80.4%) were men and 1103 (71%) were in New York Heart Association class II. During a mean follow-up of 30.7 months, 300 patients experienced the primary outcome and 197 died. Added individually, only four biomarkers were independently associated with all outcomes: hs-TnT, GDF-15, cystatin C and TIMP-1. When all biomarkers were added simultaneously to the PREDICT-HF models, only hs-TnT remained an independent predictor of all three endpoints. GDF-15 also remained predictive of the primary endpoint; TIMP-1 was the only other predictor of both cardiovascular and all-cause mortality. Individually or in combination, these biomarkers did not lead to significant improvements in discrimination or reclassification.

CONCLUSIONS

None of the biomarkers studied individually or collectively led to a meaningful improvement in the prediction of outcomes over what is provided by clinical, routine laboratory, and natriuretic peptide variables.

Association of Carbohydrate Antigen 125 on the Response to Dapagliflozin in Patients With Heart Failure

BACKGROUND

Elevated circulating carbohydrate antigen 125 (CA125) is a marker of congestion and a predictor of outcomes in acute heart failure (HF). Less is known about CA125 in chronic ambulatory HF with reduced ejection fraction.

OBJECTIVES

This study examined the association between baseline CA125 (and changes in CA125) and outcomes in patients with HF with reduced ejection fraction in the DAPA-HF (Dapagliflozin and Prevention of Adverse Outcomes in Heart Failure; NCT03036124) trial and its relationship with the effect of dapagliflozin.

METHODS

The primary outcome was a composite of a first episode of worsening HF or cardiovascular death. CA125 was measured at baseline and 12 months following randomization.

RESULTS

Median baseline CA125 was 13.04 U/mL (IQR: 8.78-21.13 U/mL) in 3,123 of 4,774 patients with available data. Compared with CA125 ≤35 U/mL (upper limit of normal), patients with CA125 >35 U/mL were at a higher risk of the primary outcome (adjusted HR: 1.59; 95% CI: 1.29-1.96). The adjusted risks of the primary outcome relative to quartile 1 (Q1) (≤8.78 U/mL) were as follow: Q2, 8.79-13.04 U/mL (HR: 0.94; 95% CI: 0.71-1.24); Q3, 13.05-21.13 U/mL (HR: 1.22; 95% CI: 0.94-1.59); Q4, ≥21.14 U/mL (HR: 1.63; 95% CI: 1.28-2.09). The beneficial effect of dapagliflozin compared with placebo on the primary outcome was consistent whether CA125 was analyzed in quartiles (interaction P = 0.13) or as a continuous variable (interaction P = 0.75). The placebo-corrected relative change in CA125 at 12 months was -5.2% (95% CI: -10.6% to 0.5%; P = 0.07).

CONCLUSIONS

In DAPA-HF, elevated CA125 levels were an independent predictor of the risk of worsening HF or cardiovascular death. Dapagliflozin reduced the risk of worsening HF or cardiovascular death regardless of baseline CA125.

Prognostic Role of Metabolic Exercise Testing in Heart Failure

Heart failure is a clinical syndrome with significant heterogeneity in presentation and severity. Serial risk-stratification and prognostication can guide management decisions, particularly in advanced heart failure, when progression toward advanced therapies or end-of-life care is warranted. Each currently utilized prognostic marker carries its own set of challenges in acquisition, reproducibility, accuracy, and significance. Left ventricular ejection fraction is foundational for heart failure syndrome classification after clinical diagnosis and remains the primary parameter for inclusion in most clinical trials; however, it does not consistently correlate with symptoms and functional capacity, which are also independently prognostic in this patient population. Utilizing the left ventricular ejection fraction as the sole basis of prognostication provides an incomplete characterization of this condition and is prone to misguide medical decision-making when used in isolation. In this review article, we survey and exposit the important role of metabolic exercise testing across the heart failure spectrum, as a complementary diagnostic and prognostic modality. Metabolic exercise testing, also known as cardiopulmonary exercise testing, provides a comprehensive evaluation of the multisystem (i.e., neurological, respiratory, circulatory, and musculoskeletal) response to exercise performance. These differential responses can help identify the predominant contributors to exercise intolerance and exercise symptoms. Additionally, the aerobic exercise capacity (i.e., oxygen consumption during exercise) is directly correlated with overall life expectancy and prognosis in many disease states. Specifically in heart failure patients, metabolic exercise testing provides an accurate, objective, and reproducible assessment of the overall circulatory sufficiency and circulatory reserve during physical stress, being able to isolate the concurrent chronotropic and stroke volume responses for a reliable depiction of the circulatory flow rate in real time.

A Prognostic Model Based on Clinical Biomarkers for Heart Failure in Adult Patients Following Allogeneic Hematopoietic Stem Cell Transplantation

Heart failure (HF) is an uncommon but serious cardiovascular complication after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Unfortunately, knowledge about early mortality prognostic factors in patients with HF after allo-HSCT is limited, and an easy-to-use prognostic model is not available. This study aimed to develop and validate a clinical-biomarker prognostic model capable of predicting HF mortality following allo-HSCT that uses a combination of variables readily available in clinical practice. To investigate this issue, we conducted a retrospective analysis at our center with 154 HF patients who underwent allo-HSCT between 2008 and 2021. The patients were separated according to the time of transplantation, with 100 patients composing the derivation cohort and the other 54 patients composing the external validation cohort. We first calculated the univariable association for each variable with 2-month mortality in the derivation cohort. We then included the variables with a P value <.1 in univariate analysis as candidate predictors in the multivariate analysis using a backward stepwise logistic regression model. Variables remaining in the final model were identified as independent prognostic factors. To predict the prognosis of HF, a scoring system was established, and scores were assigned to the prognostic factors based on the regression coefficient. Finally, 4 strongly significant independent prognostic factors for 2-month mortality from HF were identified using multivariable logistic regression methods with stepwise variable selection: pulmonary infection (P = .005), grade III to IV acute graft-versus-host disease (severe aGVHD; P = .033), lactate dehydrogenase (LDH) >426 U/L (P = .049), and brain natriuretic peptide (BNP) >1799 pg/mL (P = .026). A risk grading model termed the BLIPS score (for BNP, LDH, cardiac troponin I, pulmonary infection, and severe aGVHD) was constructed according to the regression coefficients. The validated internal C-statistic was .870 (95% confidence interval [CI], .798 to .942), and the external C-statistic was .882 (95% CI, .791-.973). According to the calibration plots, the model-predicted probability correlated well with the actual observed frequencies. The clinical use of the prognostic model, according to decision curve analysis, could benefit HF patients. The BLIPS model in our study can serve to identify HF patients at higher risk for mortality early, which might aid designing timely targeted therapies and eventually improving patients' survival and prognosis.

IGFBP-7 and Outcomes in Heart Failure With Reduced Ejection Fraction: Findings From DAPA-HF

BACKGROUND

Insulin-like growth factor-binding protein-7 (IGFBP-7) has been proposed as a potential prognostic biomarker in heart failure (HF), but the association between elevation in IGFBP-7 and HF outcomes in ambulant patients with heart failure with reduced ejection fraction (HFrEF) is unknown.

OBJECTIVES

The authors addressed this question in a post hoc analysis of the DAPA-HF (Dapagliflozin and Prevention of Adverse Outcomes in Heart Failure) trial.

METHODS

The primary outcome was a composite of cardiovascular death or a worsening HF event. The risk of adverse outcome was compared across tertiles of IGFBP-7 concentration by means of Cox proportional hazard models adjusted for N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-sensitivity troponin T (hsTnT). The efficacy of randomized treatment across IGFBP-7 tertiles was assessed. Change in IGFBP-7 at 12 months was compared with the use of geometric means.

RESULTS

A total of 3,158 patients had IGFBP-7 measured at baseline, and 2,493 had a repeated measure at 12 months. Patients in the highest tertile of IGFBP-7 had evidence of more advanced HFrEF. The adjusted HR for the primary endpoint in tertile 3, compared with tertile 1, was 1.48 (95% CI: 1.17-1.88). There was no modification of the benefit of dapagliflozin by baseline IGFBP-7 (P interaction = 0.34). Dapagliflozin did not change IGFBP-7 levels over 1 year (P = 0.34).

CONCLUSIONS

Higher IGFBP-7 in patients with HFrEF was associated with worse clinical profile and an increased risk of adverse clinical outcomes. IGFBP-7 provided prognostic information incremental to clinical variables, NT-proBNP, and hsTnT. The benefit of dapagliflozin was not modulated by IGFBP-7 level. (Study to Evaluate the Effect of Dapagliflozin on the Incidence of Worsening Heart Failure or Cardiovascular Death in Patients With Chronic Heart Failure [DAPA-HF]; NCT03036124).

A Novel Nomogram Integrated with Systemic Inflammation Markers and Traditional Prognostic Factors for Adverse Events' Prediction in Patients with Chronic Heart Failure in the Southwest of China

Objective

Inflammation contributes to the pathogenesis and progression of heart failure (HF). This study aimed to construct a nomogram based on systemic inflammatory markers and traditional prognostic factors to assess the risk of adverse outcomes (cardiovascular readmission and all-cause death) in patients with chronic heart failure (CHF).

Methods

Data were retrospectively collected from patients with HF admitted to the Department of Cardiovascular Medicine at the First Affiliated Hospital of Chongqing Medical University from January 2018 to April 2020, and each patient had complete follow-up information. The follow-up duration was from June 2018 to May 31, 2022. 550 patients were included and randomly assigned to the derivation and validation cohorts with a ratio of 7:3, and prognostic risk factors of CHF were identified by Cox regression analysis. The nomogram chart scoring model was constructed.

Results

The Cox multivariate regression analysis showed that traditional prognostic factors such as age (P=0.011), BMI (P=0.048), NYHA classification (P<0.001), creatinine (P<0.001), and systemic inflammatory markers including LMR (P=0.001), and PLR (P=0.015) were independent prognostic factors for CHF patients. Integrated with traditional and inflammatory prognostic factors, a nomogram was established, which yielded a C-index value of 0.739 (95% CI: 0.714-0.764) in the derivation cohort and 0.713 (95% CI: 0.668-0.758) in the validation cohort, respectively. The calibration curves exhibited good performance of the nomogram in predicting the adverse outcomes for patients with CHF. In subgroups (HFrEF, HFmrEF, and HFpEF groups), the systematic inflammatory markers-based nomograms proved to be effective prediction tools for patients' adverse overcomes, as well.

Conclusion

The nomogram combining systemic inflammatory markers and traditional risk factors has satisfactory predictive performance for adverse outcomes (mortality and readmission) in patients with CHF.

Risk of Mortality Prediction Involving Time-Varying Covariates for Patients with Heart Failure Using Deep Learning

Heart failure (HF) is challenging public medical and healthcare systems. This study aimed to develop and validate a novel deep learning-based prognostic model to predict the risk of all-cause mortality for patients with HF. We also compared the performance of the proposed model with those of classical deep learning- and traditional statistical-based models. The present study enrolled 730 patients with HF hospitalized at Toho University Ohashi Medical Center between April 2016 and March 2020. A recurrent neural network-based model (RNNSurv) involving time-varying covariates was developed and validated. The proposed RNNSurv showed better prediction performance than those of a deep feed-forward neural network-based model (referred as "DeepSurv") and a multivariate Cox proportional hazard model in view of discrimination (C-index: 0.839 vs. 0.755 vs. 0.762, respectively), calibration (better fit with a 45-degree line), and ability of risk stratification, especially identifying patients with high risk of mortality. The proposed RNNSurv demonstrated an improved prediction performance in consideration of temporal information from time-varying covariates that could assist clinical decision-making. Additionally, this study found that significant risk and protective factors of mortality were specific to risk levels, highlighting the demand for an individual-specific clinical strategy instead of a uniform one for all patients.

Oxidative stress markers-driven prognostic model to predict post-discharge mortality in heart failure with reduced ejection fraction

Background

Current predictive models based on biomarkers reflective of different pathways of heart failure with reduced ejection fraction (HFrEF) pathogenesis constitute a useful tool for predicting death risk among HFrEF patients. The purpose of the study was to develop a new predictive model for post-discharge mortality risk among HFrEF patients, based on a combination of clinical patients’ characteristics, N-terminal pro-B-type Natriuretic peptide (NT-proBNP) and oxidative stress markers as a potentially valuable tool for routine clinical practice.

Methods

116 patients with stable HFrEF were recruited in a prospective single-center study. Plasma levels of NT-proBNP and oxidative stress markers [superoxide dismutase (SOD), glutathione peroxidase (GPX), uric acid (UA), total bilirubin (TB), gamma-glutamyl transferase (GGT) and total antioxidant capacity (TAC)] were measured in the stable predischarge condition. Generalized linear model (GLM), random forest and extreme gradient boosting models were developed to predict post-discharge mortality risk using clinical and laboratory data. Through comprehensive evaluation, the most performant model was selected.

Results

During a median follow-up of 525 days (7–930), 33 (28%) patients died. Among the three created models, the GLM presented the best performance for post-discharge death prediction in HFrEF. The predictors included in the GLM model were age, female sex, beta blockers, NT-proBNP, left ventricular ejection fraction (LVEF), TAC levels, admission systolic blood pressure (SBP), angiotensin-converting enzyme inhibitors/angiotensin receptor II blockers (ACEI/ARBs) and UA levels. Our model had a good discriminatory power for post-discharge mortality [The area under the curve (AUC) = 74.5%]. Based on the retained model, an online calculator was developed to allow the identification of patients with heightened post-discharge death risk.

Conclusion

In conclusion, we created a new and simple tool that may allow the identification of patients at heightened post-discharge mortality risk and could assist the treatment decision-making.

Update on the Practical Role of Echocardiography in Selection, Implantation, and Management of Patients Requiring Left Ventricular Assist Device Therapy

PURPOSE OF REVIEW

Echocardiography is a valuable tool for management of patients with a left ventricular assist device (LVAD). We present an updated review on the practical applications of the role of echocardiography for pre- and postoperative evaluation of patients selected.

RECENT FINDINGS

The LVAD is a temporary or permanent option for patients with advanced heart failure who are unresponsive to other therapy. Use of the device has its own risks, and implantation remains a complex procedure. Transthoracic and transesophageal echocardiography are useful tools for patient evaluation and monitoring both peri- and postoperatively, as we previously presented. Assessment of left and right ventricular function, complications such as thrombus formation or intracardiac shunting, and valvular disease are all important in this assessment. This also aids in predicting postoperative complications. Placement of the device is confirmed intraoperatively, and subsequent ramp studies are used to determine optimal device settings. Right ventricular (RV) failure is the most common postoperative complication and preoperative evaluation of its function is crucial. Studies suggest that tricuspid annular plane systolic excursion, RV fractional area change, and RV global longitudinal strain are strong predictors of RV failure; LV ejection fraction, size, and end-diastolic diameter are also important markers. Aortic regurgitation and mitral stenosis must always be corrected prior to LVAD placement. However, direct visualization before and after implantation, especially to rule out potential contraindications such as thrombi, cannot be overemphasized. Ramp studies remain an integral part of device optimization and may result in greater myocardial recovery than previously realized.

Mortality Risk Assessment in Peripheral Arterial Disease-The Burden of Cardiovascular Risk Factors over the Years: A Single Center's Experience

Atherosclerosis is the basis of the cardiovascular continuum in peripheral artery disease (PAD) patients. Limiting functional decline and increasing quality of life are the main objectives for these patients. We conducted a prospective cohort study on 101 patients with PAD admitted to a single center in Northeast Romania. We used an index score to evaluate the 10-year mortality risk assessment and based on the scores we divided the patients into two groups: a low and low-intermediate risk mortality group (49 cases, 48.5%) and a high-intermediate and high-risk mortality group (52 cases, 51.5%). We analyzed demographics, comorbidities, clinical and paraclinical parameters and we aimed to identify the parameters associated with an unfavorable prognosis. Patients in the high-intermediate and high-risk mortality group were associated more with cardiovascular risk factors. Hypertension (p = 0.046), dyslipidemia (p < 0.001), diabetes mellitus (p < 0.001), and tobacco use (p = 0.018) were statistically significant factors. Lipid profile (low-density lipoprotein cholesterol, p = 0.005) and fasting blood glucose (p = 0.013) had higher mean serum values in the high-intermediate and high-risk mortality group, with a positive correlation between them and the ankle-brachial index value (p = 0.003). A multidisciplinary assessment and, especially, correction of associated cardiovascular risk factors prevent complications, and thus, improve the prognosis in the medium and long term.

Liver tests and outcomes in heart failure with reduced ejection fraction: findings from DAPA-HF

AIMS

Reflecting both increased venous pressure and reduced cardiac output, abnormal liver tests are common in patients with severe heart failure and are associated with adverse clinical outcomes. We aimed to investigate the prognostic significance of abnormal liver tests in ambulatory patients with heart failure with reduced ejection fraction (HFrEF), explore any treatment interaction between bilirubin and sodium-glucose cotransporter 2 (SGLT2) inhibitors and examine change in liver tests with SGLT2 inhibitor treatment.

METHODS AND RESULTS

We explored these objectives in the Dapagliflozin And Prevention of Adverse outcomes in Heart Failure (DAPA-HF) trial, with focus on bilirubin. We calculated the incidence of cardiovascular death or worsening heart failure by bilirubin tertile. Secondary cardiovascular outcomes were examined, along with the change in liver tests at the end-of-study visit. Baseline bilirubin was available in 4720 patients (99.5%). Participants in the highest bilirubin tertile (T3) have more severe HFrEF (lower left ventricular ejection fraction, higher N-terminal pro-B-type natriuretic peptide [NT-proBNP] and worse New York Heart Association class), had a greater burden of atrial fibrillation but less diabetes. Higher bilirubin (T3 vs. T1) was associated with worse outcomes even after adjustment for other predictive variables, including NT-proBNP and troponin T (adjusted hazard ratio for the primary outcome 1.73 [95% confidence interval 1.37-2.17], p < 0.001; and 1.52 [1.12-2.07], p = 0.01 for cardiovascular death). Baseline bilirubin did not modify the benefits of dapagliflozin. During follow-up, dapagliflozin had no effect on liver tests.

CONCLUSION

Bilirubin concentration was an independent predictor of worse outcomes but did not modify the benefits of dapagliflozin in HFrEF. Dapagliflozin was not associated with change in liver tests.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov NCT03036124.

Neutrophil-to-Lymphocyte Ratio and Outcomes in Patients Admitted for Acute Heart Failure (As Seen in the BLAST-AHF, Pre-RELAX-AHF, and RELAX-AHF Studies)

Previous studies have suggested that the neutrophil-to-lymphocyte ratio (NLR) is a novel yet readily evaluable inflammatory biomarker that may be useful for determining cardiovascular prognosis during acute episodes. The study investigated the role of NLR in predicting cardiovascular (CV) outcomes in patients with acute heart failure (HF). Individual patient data from the BLAST-AHF (phase 2b study of the biased ligand of the angiotensin 2 type 1 receptor, TRV027), Pre-RELAX-AHF (phase 2b study of recombinant human relaxin-2, serelaxin), and RELAX-AHF (phase 3 study of serelaxin) randomized, placebo-controlled studies for patients with acute HF were pooled for analysis. Dyspnea visual analog scale area under the curve through day 5, worsening HF through day 5, 30-day all-cause mortality, 60-day HF/renal failure rehospitalizations or CV death, 180-day all-cause mortality, and 180-day CV death were assessed. There were several differences in the baseline characteristics of the patients divided by NLR tertile, with patients in the higher NLR having worse clinical characteristics. NLR was an independent predictor of 30-day all-cause mortality (adjusted hazard ratio [HR] per log₂ NLR increment: 1.66 [1.22 to 2.25], p = 0.001), 60-day HF/renal failure rehospitalizations or CV death: 1.33 [1.12 to 1.57], p = 0.001), 180-day all-cause mortality (adjusted HR 1.27 [1.08 to 1.50], p = 0.003), and 180-day CV death (adjusted HR 1.24 [1.04 to 1.49], p = 0.018). NLR, a readily available inflammatory biomarker, was associated with independent risk for short- and long-term adverse outcomes in acute HF, surpassing traditional markers, such as natriuretic peptides.

Utility of PREDICT-HF score in high-risk Asian heart failure patients receiving sacubitril/valsartan

Objective

The aim of this study was to investigate the application of sacubitril/valsartan in clinical practice and the utility of PREDICT-HF score for outcome prediction in Asian heart failure patients with difference risk profiles.

Methods

The TAROT-HF study was a multicenter, single-arm, observational study. Totally 1,187 outpatients with HFrEF treated with sacubitril/valsartan were enrolled and categorized by: (1) high-risk group with ≥1 of the following three risk factors: old age (≥80 years), low baseline systolic blood pressure (<100 mmHg), and renal impairment (eGFR <30 ml/min/1.73 m²), and (2) standard-risk group, those who did not have any risk factors. Clinical outcomes were assessed using the PREDICT-HF risk model.

Results

A total of 305 (25.7%) patients matched the criteria for the high-risk group. The event rates of cardiovascular death or first unplanned heart failure hospitalization (HFH) among the overall population, high-risk, and standard-risk groups were 13.7, 24.9, and 10.8 events per 100 patient-years, respectively. The C statistics for the PREDICT-HF model in the overall cohort and high-risk group for cardiovascular death or first unplanned HFH at 2 years were 0.73 (95% CI 0.70–0.76) and 0.71 (95% CI 0.65–0.76), respectively. The permanent discontinuation rate among the high-risk patients was significantly higher than that among the standard-risk patients (8.3 vs. 2.5 per 100 patient-years, p < 0.001).

Conclusions

Real-world outcomes of the TAROT-HF study demonstrated that the PREDICT-HF model performed well in Asian HFrEF patients. Three easily detected clinical profiles of age, renal function, and systolic BP could help to identify patients at risk before initiating sacubitril/valsartan.

Development and validation of a decision support tool for the diagnosis of acute heart failure: systematic review, meta-analysis, and modelling study

OBJECTIVES

To evaluate the diagnostic performance of N-terminal pro-B-type natriuretic peptide (NT-proBNP) thresholds for acute heart failure and to develop and validate a decision support tool that combines NT-proBNP concentrations with clinical characteristics.

DESIGN

Individual patient level data meta-analysis and modelling study.

SETTING

Fourteen studies from 13 countries, including randomised controlled trials and prospective observational studies.

PARTICIPANTS

Individual patient level data for 10 369 patients with suspected acute heart failure were pooled for the meta-analysis to evaluate NT-proBNP thresholds. A decision support tool (Collaboration for the Diagnosis and Evaluation of Heart Failure (CoDE-HF)) that combines NT-proBNP with clinical variables to report the probability of acute heart failure for an individual patient was developed and validated.

MAIN OUTCOME MEASURE

Adjudicated diagnosis of acute heart failure.

RESULTS

Overall, 43.9% (4549/10 369) of patients had an adjudicated diagnosis of acute heart failure (73.3% (2286/3119) and 29.0% (1802/6208) in those with and without previous heart failure, respectively). The negative predictive value of the guideline recommended rule-out threshold of 300 pg/mL was 94.6% (95% confidence interval 91.9% to 96.4%); despite use of age specific rule-in thresholds, the positive predictive value varied at 61.0% (55.3% to 66.4%), 73.5% (62.3% to 82.3%), and 80.2% (70.9% to 87.1%), in patients aged <50 years, 50-75 years, and >75 years, respectively. Performance varied in most subgroups, particularly patients with obesity, renal impairment, or previous heart failure. CoDE-HF was well calibrated, with excellent discrimination in patients with and without previous heart failure (area under the receiver operator curve 0.846 (0.830 to 0.862) and 0.925 (0.919 to 0.932) and Brier scores of 0.130 and 0.099, respectively). In patients without previous heart failure, the diagnostic performance was consistent across all subgroups, with 40.3% (2502/6208) identified at low probability (negative predictive value of 98.6%, 97.8% to 99.1%) and 28.0% (1737/6208) at high probability (positive predictive value of 75.0%, 65.7% to 82.5%) of having acute heart failure.

CONCLUSIONS

In an international, collaborative evaluation of the diagnostic performance of NT-proBNP, guideline recommended thresholds to diagnose acute heart failure varied substantially in important patient subgroups. The CoDE-HF decision support tool incorporating NT-proBNP as a continuous measure and other clinical variables provides a more consistent, accurate, and individualised approach.

STUDY REGISTRATION

PROSPERO CRD42019159407.

2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines

AIM

The "2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure" replaces the "2013 ACCF/AHA Guideline for the Management of Heart Failure" and the "2017 ACC/AHA/HFSA Focused Update of the 2013 ACCF/AHA Guideline for the Management of Heart Failure." The 2022 guideline is intended to provide patient-centric recommendations for clinicians to prevent, diagnose, and manage patients with heart failure.

METHODS

A comprehensive literature search was conducted from May 2020 to December 2020, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from MEDLINE (PubMed), EMBASE, the Cochrane Collaboration, the Agency for Healthcare Research and Quality, and other relevant databases. Additional relevant clinical trials and research studies, published through September 2021, were also considered. This guideline was harmonized with other American Heart Association/American College of Cardiology guidelines published through December 2021. Structure: Heart failure remains a leading cause of morbidity and mortality globally. The 2022 heart failure guideline provides recommendations based on contemporary evidence for the treatment of these patients. The recommendations present an evidence-based approach to managing patients with heart failure, with the intent to improve quality of care and align with patients' interests. Many recommendations from the earlier heart failure guidelines have been updated with new evidence, and new recommendations have been created when supported by published data. Value statements are provided for certain treatments with high-quality published economic analyses.

2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure

AIM

The "2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure" replaces the "2013 ACCF/AHA Guideline for the Management of Heart Failure" and the "2017 ACC/AHA/HFSA Focused Update of the 2013 ACCF/AHA Guideline for the Management of Heart Failure." The 2022 guideline is intended to provide patient-centric recommendations for clinicians to prevent, diagnose, and manage patients with heart failure.

METHODS

A comprehensive literature search was conducted from May 2020 to December 2020, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from MEDLINE (PubMed), EMBASE, the Cochrane Collaboration, the Agency for Healthcare Research and Quality, and other relevant databases. Additional relevant clinical trials and research studies, published through September 2021, were also considered. This guideline was harmonized with other American Heart Association/American College of Cardiology guidelines published through December 2021.

STRUCTURE

Heart failure remains a leading cause of morbidity and mortality globally. The 2022 heart failure guideline provides recommendations based on contemporary evidence for the treatment of these patients. The recommendations present an evidence-based approach to managing patients with heart failure, with the intent to improve quality of care and align with patients' interests. Many recommendations from the earlier heart failure guidelines have been updated with new evidence, and new recommendations have been created when supported by published data. Value statements are provided for certain treatments with high-quality published economic analyses.

Effect of Dapagliflozin, Compared With Placebo, According to Baseline Risk in DAPA-HF

OBJECTIVES

The authors sought to examine the effect of dapagliflozin across the spectrum of risk in patients enrolled in DAPA-HF.

BACKGROUND

In the DAPA-HF (Dapagliflozin And Prevention of Adverse-outcomes in Heart Failure) trial, the sodium-glucose cotransporter 2 inhibitor dapagliflozin decreased the risk of worsening HF events and cardiovascular death in patients with HF and reduced ejection fraction.

METHODS

The MAGGIC (Meta-analysis Global Group in Chronic Heart Failure) and the PARADIGM-HF (Prospective comparison of ARNI with ACEI to Determine Impact on Global Mortality and morbidity in Heart Failure) PREDICT-HF (Risk of Events and Death in the Contemporary Treatment of Heart Failure) risk models were used to categorize patients according to risk score quintiles. The authors analyzed rates of the primary composite outcome of a worsening HF event or cardiovascular death, its components, and all-cause mortality according to risk quintile and whether risk modified the effect of dapagliflozin.

RESULTS

The MAGGIC score was available for 4,740 of 4,744 patients in DAPA-HF (median score 22 [IQR: 18-25]). A1-point increase was associated with an 8.2% (95% CI: 6.9%-9.4%) higher relative risk of the primary endpoint (P < 0.001). The benefit of dapagliflozin over placebo for the primary endpoint was similar across the spectrum of MAGGIC risk score (interaction P = 0.71). Applying the overall relative risk reduction (26%) with dapagliflozin added to standard therapy resulted in 7 fewer patients in the highest MAGGIC risk quintile experiencing a primary outcome, compared with 2 in the lowest quintile, per 100 person-years of treatment. The findings with PREDICT-HF were similar, although this model led to better risk discrimination.

CONCLUSIONS

The benefits of dapagliflozin were consistent across the broad spectrum of baseline risk in DAPA-HF.

Discriminative Utility of Apelin-to-NT-Pro-Brain Natriuretic Peptide Ratio for Heart Failure with Preserved Ejection Fraction among Type 2 Diabetes Mellitus Patients

Background: Apelin is a regulatory vasoactive peptide, which plays a pivotal role in adverse cardiac remodeling and heart failure (HF) with reduced ejection fraction. The purpose of the study was to investigate whether serum levels of apelin is associated with HF with preserved election fraction (HFpEF) in patients with T2DM. Methods: The study retrospectively involved 101 T2DM patients aged 41 to 62 years (48 patients with HFpEF and 28 non-HFpEF patients). The healthy control group consisted of 25 individuals with matched age and sex. Data collection included demographic and anthropometric information, hemodynamic performances and biomarkers of the disease. Transthoracic B-mode echocardiography, Doppler and TDI were performed at baseline. Serum levels of N-terminal pro-brain natriuretic peptide (NT-proBNP) and apelin were measured by ELISA in all patients at the study entry. Results: Unadjusted multivariate logistic model yielded the only apelin to NT-proBNP ratio (OR = 1.44; p = 0.001), BMI > 34 кг/м2 (OR = 1.07; p = 0.036), NT-proBNP > 458 pmol/mL (OR = 1.17; p = 0.042), LAVI > 34 mL/m2 (OR = 1.06; p = 0.042) and E/e’ > 11 (OR = 1.04; p = 0.044) remained to be strong predictors for HFpEF. After obesity adjustment, multivariate logistic regression showed that the apelin to NT-proBNP ratio < 0.82 × 10−2 units remained sole independent predictor for HFpEF (OR = 1.44; 95% CI: 1.18–2.77; p = 0.001) HFpEF in T2DM patients. In conclusion, we found that apelin to NT-proBNP ratio < 0.82 × 10−2 units better predicted HFpEF in T2DM patients than apelin and NT-proBNP alone. This finding could open new approach for CV risk stratification of T2DM at higher risk of HF.

Heart failure with mid-range or mildly reduced ejection fraction

Left ventricular ejection fraction (EF) remains the major parameter for diagnosis, phenotyping, prognosis and treatment decisions in heart failure. The 2016 ESC heart failure guidelines introduced a third EF category for an EF of 40-49%, defined as heart failure with mid-range EF (HFmrEF). This category has been largely unexplored compared with heart failure with reduced EF (HFrEF; defined as EF <40% in this Review) and heart failure with preserved EF (HFpEF; defined as EF ≥50%). The prevalence of HFmrEF within the overall population of patients with HF is 10-25%. HFmrEF seems to be an intermediate clinical entity between HFrEF and HFpEF in some respects, but more similar to HFrEF in others, in particular with regard to the high prevalence of ischaemic heart disease in these patients. HFmrEF is milder than HFrEF, and the risk of cardiovascular events is lower in patients with HFmrEF or HFpEF than in those with HFrEF. By contrast, the risk of non-cardiovascular adverse events is similar or greater in patients with HFmrEF or HFpEF than in those with HFrEF. Evidence from post hoc and subgroup analyses of randomized clinical trials and a trial of an SGLT1-SGLT2 inhibitor suggests that drugs that are effective in patients with HFrEF might also be effective in patients with HFmrEF. Although the EF is a continuous measure with considerable variability, in this comprehensive Review we suggest that HFmrEF is a useful categorization of patients with HF and shares the most important clinical features with HFrEF, which supports the renaming of HFmrEF to HF with mildly reduced EF.

A Model for the Prediction of Mortality and Hospitalization in Chinese Heart Failure Patients

Background: Although many risk prediction models have been released internationally, the application of these models in the Chinese population still has some limitations.

Aims: The purpose of the study was to establish a heart failure (HF) prognosis model suitable for the Chinese population.

Methods: According to the inclusion criteria, we included patients with chronic heart failure (CHF) who were admitted to the Department of Cardiac Rehabilitation of Tongji Hospital from March 2007 to December 2018, recorded each patient's condition and followed up on the patient's re-admission and death. All data sets were randomly divided into derivation and validation cohorts in a ratio of 7/3. Least absolute shrinkage and selection operator regression and Cox regression were used to screen independent predictors; a nomogram chart scoring model was constructed and validated.

Results: A total of 547 patients were recruited in this cohort, and the median follow-up time was 519 days. The independent predictors screened out by the derivation cohort included age, atrial fibrillation (AF), percutaneous coronary intervention (PCI), diabetes mellitus (DM), peak oxygen uptake (peak VO₂), heart rate at the 8th minute after the cardiopulmonary exercise peaked (HR8min), C-reaction protein(CRP), and uric acid (UA). The C indexes values of the derivation and the validation cohorts were 0.69 and 0.62, respectively, and the calibration curves indicate that the model's predictions were in good agreement with the actual observations.

Conclusions: We have developed and validated a multiple Cox regression model to predict long-term mortality and readmission risk of Chinese patients with CHF.

Registration Number: ChicTR-TRC-00000235.

Head-to-head comparison of contemporary heart failure risk scores

AIMS

Several heart failure (HF) web-based risk scores are currently used in clinical practice. Currently, we lack head-to-head comparison of the accuracy of risk scores. This study aimed to assess correlation and mortality prediction performance of Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC-HF) risk score, which includes clinical variables + medications; Seattle Heart Failure Model (SHFM), which includes clinical variables + treatments + analytes; PARADIGM Risk of Events and Death in the Contemporary Treatment of Heart Failure (PREDICT-HF) and Barcelona Bio-Heart Failure (BCN-Bio-HF) risk calculator, which also include biomarkers, like N-terminal pro B-type natriuretic peptide (NT-proBNP).

METHODS AND RESULTS

A total of 1166 consecutive patients with HF from different aetiologies that had NT-proBNP measurement at first visit were included. Discrimination for all-cause mortality was compared by Harrell's C-statistic from 1 to 5 years, when possible. Calibration was assessed by calibration plots and Hosmer-Lemeshow test and global performance by Nagelkerke's R² . Correlation between scores was assessed by Spearman rank test. Correlation between the scores was relatively poor (rho value from 0.66 to 0.79). Discrimination analyses showed better results for 1-year mortality than for longer follow-up (SHFM 0.817, MAGGIC-HF 0.801, PREDICT-HF 0.799, BCN-Bio-HF 0.830). MAGGIC-HF showed the best calibration, BCN-Bio-HF overestimated risk while SHFM and PREDICT-HF underestimated it. BCN-Bio-HF provided the best discrimination and overall performance at every time-point.

CONCLUSIONS

None of the contemporary risk scores examined showed a clear superiority over the rest. BCN-Bio-HF calculator provided the best discrimination and overall performance with overestimation of risk. MAGGIC-HF showed the best calibration, and SHFM and PREDICT-HF tended to underestimate risk. Regular updating and recalibration of online web calculators seems necessary to improve their accuracy as HF management evolves at unprecedented pace.

Treatment with angiotensin receptor neprilysin inhibitor for Taiwan heart failure patients: Rationale and baseline characteristics of the TAROT-HF study

BACKGROUND

This study used a real-world database to investigate the prescription patterns of sacubitril/valsartan (Sac/Val) among Taiwanese patients with heart failure with reduced ejection fraction (HFrEF).

METHODS

The Treatment with Angiotensin Receptor neprilysin inhibitor fOr Taiwan Heart Failure patients (TAROT-HF) study is a principal investigator-initiated, multicenter, observational, retrospective study on Taiwanese HFrEF patients. A total of 1772 patients with HFrEF (mean age 62.5 years, 75.3% male, mean left ventricular ejection fraction [LVEF] 29.3%) who received Sac/Val at 10 hospitals between 2017 and 2018 were enrolled at the date of Sac/Val initiation. Among these patients, 585 (33%) initially received Sac/Val during acute decompensated heart failure (HF) hospitalization (TAROT-AHF arm), whereas 1187 (67%) initially received the same at the outpatient clinic (TAROT-CHF arm).

RESULTS

A total of 1343 (75.8%) patients received an initial dose of 50 mg twice daily or fewer, whereas 422 (23.8%) received the standard initiation dose (100 mg twice daily). During outpatient Sac/Val initiation, the mean dosages were significantly higher than that following hospitalization (117 ± 55 mg vs 109 ± 57 mg; p = 0.014). Multivariate analysis identified younger age, higher systolic blood pressure, higher LVEF, prior use of renin-angiotensin system inhibitors, use of ivabradine, and a history of diabetes mellitus as independent factors for initiating a standard Sac/Val dose. Over a follow-up period of 18 months, incidences of cardiovascular death or first unplanned HF hospitalization were 18.69 and 33.11 per 100-person years for the TAROT-CHF and TAROT-AHF arms, respectively.

CONCLUSION

The TAROT-HF study provided an opportunity to describe the clinical features of patients with HFrEF who received Sac/Val, assess the real-world utilization and efficacy of Sac/Val, and compare these patients with those included in prior registries.

Novel biomarker-driven prognostic models to predict morbidity and mortality in chronic heart failure: the EMPEROR-Reduced trial

Aims

The aim of this study was to generate a biomarker-driven prognostic tool for patients with chronic HFrEF. Circulating levels of N-terminal pro B-type natriuretic peptide (NT-proBNP) and high-sensitivity cardiac troponin T (hs-cTnT) each have a marked positive relationship with adverse outcomes in heart failure with reduced ejection fraction (HFrEF). A risk model incorporating biomarkers and clinical variables has not been validated in contemporary heart failure (HF) trials.

Methods and results

In EMPEROR-Reduced, 33 candidate variables were pre-selected. Multivariable Cox regression models were developed using stepwise selection for: (i) the primary composite outcome of HF hospitalization or cardiovascular death, (ii) all-cause death, and (iii) cardiovascular mortality. A total of 3730 patients were followed up for a median of 16 months, 823 (22%) patients had a primary outcome and 515 (14%) patients died, of whom 389 (10%) died from a cardiovascular cause. NT-proBNP and hs-cTnT were the dominant predictors of the primary outcome, and in addition, a shorter time since last HF hospitalization, longer time since HF diagnosis, lower systolic blood pressure, New York Heart Association (NYHA) Class III or IV, higher heart rate and peripheral oedema were key predictors (eight variables in total, all P < 0.001). The primary outcome risk score discriminated well (c-statistic = 0.73), with patients in the top 10th of risk having an event rate >9 times higher than those in the bottom 10th. Empagliflozin benefitted patients across risk levels for the primary outcome. NT-proBNP and hs-cTnT were also the dominant predictors of all-cause and cardiovascular mortality, followed by NYHA Class III or IV and ischaemic aetiology (four variables in total, all P < 0.001). The mortality risk model presented good event discrimination for all-cause and cardiovascular mortality (c-statistic = 0.69 for both). These simple models were externally validated in the BIOSTAT-CHF study, achieving similar c-statistics.

Conclusions

The combination of NT-proBNP and hs-cTnT with a small number of readily available clinical variables provides prognostic assessment for patients with HFrEF. This predictive tool kit can be easily implemented for routine clinical use.

Prognostic value of high-sensitivity cardiac troponin I in heart failure patients with mid-range and reduced ejection fraction

Background

The identification of high-risk heart failure (HF) patients makes it possible to intensify their treatment. Our aim was to determine the prognostic value of a newly developed, high-sensitivity troponin I assay (Atellica^®, Siemens Healthcare Diagnostics) for patients with HF with reduced ejection fraction (HFrEF; LVEF < 40%) and HF with mid-range EF (HFmrEF) (LVEF 40%–49%).

Methods and results

A total of 520 patients with HFrEF and HFmrEF were enrolled in this study. Two-year all-cause mortality, heart transplantation, and/or left ventricular assist device implantation were defined as the primary endpoints (EP). A logistic regression analysis was used for the identification of predictors and development of multivariable models. The EP occurred in 14% of the patients, and these patients had higher NT-proBNP (1,950 vs. 518 ng/l; p < 0.001) and hs-cTnI (34 vs. 17 ng/l, p < 0.001) levels. C-statistics demonstrated that the optimal cut-off value for the hs-cTnI level was 17 ng/l (AUC 0.658, p < 0.001). Described by the AUC, the discriminatory power of the multivariable model (NYHA > II, NT-proBNP, hs-cTnI and urea) was 0.823 (p < 0.001). Including heart failure hospitalization as the component of the combined secondary endpoint leads to a diminished predictive power of increased hs-cTnI.

Conclusion

hs-cTnI levels ≥ 17 ng/l represent an independent increased risk of an adverse prognosis for patients with HFrEF and HFmrEF. Determining a patient’s hs-cTnI level adds prognostic value to NT-proBNP and clinical parameters.

Extrapolating Long-term Event-Free and Overall Survival With Dapagliflozin in Patients With Heart Failure and Reduced Ejection Fraction: An Exploratory Analysis of a Phase 3 Randomized Clinical Trial

Importance

Sodium glucose cotransporter 2 inhibitors reduce morbidity and mortality in patients with heart failure and reduced ejection fraction (HFrEF). Clinicians may find estimates of the projected long-term benefits of sodium glucose cotransporter 2 inhibitors a helpful addition to clinical trial results when communicating the benefits of this class of drug to patients.

Objective

To estimate the projected long-term treatment effects of dapagliflozin in patients with HFrEF over the duration of a patient's lifetime.

Design, Setting, and Participants

Exploratory analysis was performed of Dapagliflozin and Prevention of Adverse Outcomes in Heart Failure (DAPA-HF), a phase 3 randomized, placebo-controlled clinical trial conducted at 410 sites in 20 countries. Patients with an ejection fraction less than or equal to 40% in New York Heart Association functional classification II to IV and elevated plasma levels of N-terminal pro B-type natriuretic peptide were enrolled between February 15, 2017, and August 17, 2018, with final follow-up on June 6, 2019. Mean (SD) duration of follow-up was 17.6 (5.2) months.

Interventions

Dapagliflozin, 10 mg, once daily vs placebo in addition to standard therapy.

Main Outcomes and Measures

The primary composite outcome was time to first hospitalization for heart failure, urgent heart failure visit requiring intravenous therapy, or cardiovascular death. The trial results were extrapolated to estimate the projected long-term treatment effects of dapagliflozin over the duration of a patient's lifetime for the primary outcome and the secondary outcome of death from any cause.

Results

A total of 4744 patients (1109 women [23.4%]; 3635 men [76.6%]) were randomized in DAPA-HF, with a mean (SD) age of 66.3 (10.9) years. The extrapolated mean event-free survival for an individual aged 65 years from a primary composite end point event was 6.2 years for placebo and 8.3 years for dapagliflozin, representing an event-free survival time gain of 2.1 years (95% CI, 0.8-3.3 years; P = .002). When considering death from any cause, mean extrapolated life expectancy for an individual aged 65 years was 9.1 years for placebo and 10.8 years for dapagliflozin, with a gain in survival of 1.7 years (95% CI, 0.1-3.3; P = .03) with dapagliflozin. Similar results were seen when extrapolated across the age range studied. In analyses of subgroups of patients in DAPA-HF, consistent benefits were seen with dapagliflozin on both event-free and overall survival.

Conclusions and Relevance

These findings indicate that dapagliflozin provides clinically meaningful gains in extrapolated event-free and overall survival. These findings may be helpful in communicating the benefits of this treatment to patients with HFrEF.

Trial Registration

ClinicalTrials.gov Identifier: NCT03036124.

Prognostic value of natriuretic peptides in heart failure: systematic review and meta-analysis

Risk models, informing optimal long-term medical management, seldom use natriuretic peptides (NP) in ascertaining the absolute risk of outcomes for HF patients. Individual studies evaluating the prognostic value of NPs in HF patients have reported varying effects, arriving at best estimates requires a systematic review. We systematically summarized the best evidence regarding the prognostic value of brain natriuretic peptide (BNP) and NT-proBNP in predicting mortality and hospitalizations in ambulatory heart failure (HF) patients. We searched bibliographic databases from 2005 to 2018 and included studies evaluating the association of BNP or NT-proBNP with mortality or hospitalization using multivariable Cox proportional hazard models. We pooled hazard ratios using random-effect models, explored heterogeneity using pre-specified subgroup analyses, and evaluated the certainty of evidence using the Grading of Recommendations and Development Evaluation framework. We identified 67 eligible studies reporting on 76,178 ambulatory HF patients with a median BNP of 407 pg/mL (261-574 pg/mL). Moderate to high-quality evidence showed that a 100-pg/mL increase in BNP was associated with a 14% increased hazard of mortality (HR 1.14, 95% CI 1.06-1.22); a 1-log-unit increase was associated with a 51% increased hazard of mortality (HR 1.51, 95% CI 1.41-1.61) and 48% increased hazard of mortality or hospitalization (HR 1.48, 95% CI 1.29-1.69). With moderate to high certainty, we observed a 14% independent relative increase in mortality, translating to a clinically meaningful increase in absolute risk even for low-risk patients. The observed associations may help in developing more accurate risk models that incorporate NPs and accurately prognosticate HF patients.

Clinical Outcome Predictions for the VerICiguaT Global Study in Subjects With Heart Failure With Reduced Ejection Fraction (VICTORIA) Trial

BACKGROUND

The prediction of outcomes in patients with heart failure (HF) may inform prognosis, clinical decisions regarding treatment selection, and new trial planning. The VerICiguaT Global Study in Subjects With Heart Failure With Reduced Ejection Fraction included high-risk patients with HF with reduced ejection fraction and a recent worsening HF event. The study participants had a high event rate despite the use of contemporary guideline-based therapies. To provide generalizable predictive data for a broad population with a recent worsening HF event, we focused on risk prognostication in the placebo group.

METHODS AND RESULTS

Data from 2524 participants randomized to placebo with chronic HF (New York Heart Association functional class II-IV) and an ejection fraction of less than 45% were studied and backward variable selection was used to create Cox proportional hazards models for clinical end points, selecting from 66 candidate predictors. Final model results were produced, accounting for missing data, and nonlinearities. Optimism-corrected c-indices were calculated using 200 bootstrap samples. Over a median follow-up of 10.4 months, the primary outcome of HF hospitalization or cardiovascular death occurred in 972 patients (38.5%). Independent predictors of increased risk for the primary end point included HF characteristics (longer HF duration and worse New York Heart Association functional class), medical history (prior myocardial infarction), and laboratory values (higher N-terminal pro-hormone B-type natriuretic peptide, bilirubin, urate; lower chloride and albumin). Optimism-corrected c-indices were 0.68 for the HF hospitalization/cardiovascular death model, 0.68 for HF hospitalization/all-cause death, 0.72 for cardiovascular death, and 0.73 for all-cause death.

CONCLUSIONS

Predictive models developed in a large diverse clinical trial with comprehensive clinical and laboratory baseline data-including novel measures-performed well in high-risk patients with HF who were receiving excellent guideline-based clinical care.

CLINICAL TRIAL REGISTRATION

Clinicaltrials.gov identifier, NCT02861534.Lay Summary: Patients with heart failure may benefit from tools that help clinicians to better understand a patient's risk for future events like hospitalization. Relatively few risk models have been created after the worsening of heart failure in a contemporary cohort. We provide insights on the risk factors for clinical events from a recent, large, global trial of patients with worsening heart failure to help clinicians better understand and communicate prognosis and select treatment options.

Association of Heart Failure With Outcomes Among Patients With Peripheral Artery Disease: Insights From EUCLID

Background Peripheral artery disease (PAD) and heart failure (HF) are each independently associated with poor outcomes. Risk factors associated with new-onset HF in patients with primary PAD are unknown. Furthermore, how the presence of HF is associated with outcomes in patients with PAD is unknown. Methods and Results This analysis examined risk relationships of HF on outcomes in patients with symptomatic PAD randomized to ticagrelor or clopidogrel as part of the EUCLID (Examining Use of Ticagrelor in Peripheral Arterial Disease) trial. Patients were stratified based on presence of HF at enrollment. Cox models were used to determine the association of HF with outcomes. A separate Cox model was used to identify risk factors associated with development of HF during follow-up. Patients with PAD and HF had over twice the rate of concomitant coronary artery disease as those without HF. Patients with PAD and HF had significantly increased risk of major adverse cardiovascular events (hazard ratio [HR], 1.31; 95% CI, 1.13-1.51) and all-cause mortality (HR, 1.39; 95% CI, 1.19-1.63). In patients with PAD, the presence of HF was associated with significantly less bleeding (HR, 0.65; 95% CI, 0.45-0.96). Characteristics associated with HF development included age ≥66 (HR, 1.29; 95% CI, 1.18-1.40 per 5 years), diabetes mellitus (HR, 1.85; 95% CI, 1.41-2.43), and weight (bidirectionally associated, ≥76 kg, HR, 0.77; 95% CI, 0.64-0.93; <76 kg, HR, 1.12; 95% CI, 1.07-1.16). Conclusions Patients with PAD and HF have a high rate of coronary artery disease with a high risk for major adverse cardiovascular events and death. These data support the possible need for aggressive treatment of (recurrent) atherosclerotic disease in PAD, especially patients with HF.