Factors Associated With Outcome in Heart Failure With Preserved Ejection Fraction

Systematic review and meta-analysis to predict mortality in heart failure with preserved ejection fraction: Development and validation of the HF-DANAS score

AIMS

The morbidity and mortality of heart failure with preserved ejection fraction (HFpEF) continue to increase with the accelerating global aging process. During the past decade, the pathophysiology, diagnostic methods, and prognostic prediction of HFpEF have been revolutionized, resulting in new and effective management strategies. Dynamic prognostic assessment facilitates systematic clinical management of patients, and the aim of this study was to investigate the risk factors for mortality in patients with HFpEF and to develop a risk prediction assessment model.

METHODS AND REULTS

Data for the derivation cohort were obtained from three databases, PubMed, Embase, and Cochrane. The validation cohort was obtained from the Chinese Heart Failure Center database. The β-coefficient was calculated based on the risk ratio (RR) and 95% confidence intervals (CI) corresponding to each risk factor to construct a mortality risk assessment model. A total of 30 studies were included in the meta-analysis: 22 prospective cohort studies and 8 retrospective cohort studies, including 34 196 HFpEF patients. Seven predictors of all-cause mortality in HFpEF patients were derived. Considering the need for feasibility in clinical practice, we performed subgroup and sensitivity analyses and determined the following cutoff values: age > 75 years (RR: 2.07, 95% CI: 1.83-2.35; P < 0.001), male sex (RR: 1.36, 95% CI: 1.17-1.59; P < 0.001), DM (RR: 1.23, 95% CI: 1.11-1.36; P < 0.001), anaemia (RR: 1.53, 95% CI: 1.41-1.67; P < 0.001), albumin concentration < 3.2 g/dL (RR: 1.29, 95% CI: 1.14-1.47; P < 0.001), AF (RR: 1.27, 95% CI: 1.12-1.43; P < 0.001), and NYHA class III/IV (RR: 1.63, 95% CI: 1.43-1.87; P < 0.001). The area under the receiver operating characteristic (ROC) curve (AUC) for this model was 71.3% (95% CI: 0.696-0.736), with an optimal cut-off value of 10.75. The sensitivity and specificity were 0.778 and 0.566, respectively. According to this risk score, we divided patients into three risk classes (low, moderate, and high risk), the numbers of patients who died by the end of the 1-year follow-up were 23 (1.87%), 82 (5.62%), and 382 (15.52%) in these three groups, and the 5-year mortality rates were 9.82%, 20.68%, and 43.28%, respectively.

CONCLUSIONS

This study developed an HF-DANAS scoring system for the HFpEF mortality risk containing seven predictors, providing clinicians with a simple assessment tool that can help improve clinical management.

The Prognostic Role of the Neutrophil-to-Lymphocytes Ratio in the Most Frequent Cardiovascular Diseases: An Update

Given the continuous changes in the world, with an increasing trend of unhealthy lifestyles, metabolic comorbidities, and increased susceptibility to cardiovascular diseases (CVDs), researchers change their attention to improve not only the therapeutic platform but also current CVD predictive and prognostic tools to improve disease outcomes. As CVD is characterized by an inflammatory paradigm involving, to some degree, the innate and adaptative immune systems, the neutrophil-to-lymphocyte ratio (NLR) emerged as a potential low-cost, rapidly available, and reliable inflammatory marker, with substantial recent evidence showing its potential utility in clinical practice. Thus, in this literature review, we will present an up-to-date discussion of the prognostic role of NLR in the most frequent CVDs, such as acute and chronic coronary disease, atherosclerotic disease, heart failure, cardiac valvopathies, and cardiac arrhythmias with predilection to atrial fibrillation.

Echocardiographic predictors of cardiovascular outcome in heart failure with preserved ejection fraction

AIMS

The optimal echocardiographic predictors of cardiovascular outcome in heart failure (HF) with preserved ejection fraction (HFpEF) are unknown. We aimed to identify independent echocardiographic predictors of cardiovascular outcome in patients with HFpEF.

METHODS AND RESULTS

Systematic literature search of three electronic databases was conducted from date of inception until November 2022. Hazard ratios (HRs) and their 95% confidence intervals (CIs) for echocardiographic variables from multivariate prediction models for the composite primary endpoint of cardiovascular death and HF hospitalization were pooled using a random effects meta-analysis. Specific subgroup analyses were conducted for studies that enrolled patients with acute versus chronic HF, and for those studies that included E/e', pulmonary artery systolic pressure (PASP), renal function, natriuretic peptides and diuretic use in multivariate models. Forty-six studies totalling 20 056 patients with HFpEF were included. Three echocardiographic parameters emerged as independent predictors in all subgroup analyses: decreased left ventricular (LV) global longitudinal strain (HR 1.24, 95% CI 1.10-1.39 per 5% decrease), decreased left atrial (LA) reservoir strain (HR 1.30, 95% CI 1.13-1.1.50 per 5% decrease) and lower tricuspid annular plane systolic excursion (TAPSE) to PASP ratio (HR 1.17, 95% CI 1.07-1.25 per 0.1 unit decrease). Other independent echocardiographic predictors of the primary endpoint were a higher E/e', moderate to severe tricuspid regurgitation, LV mass index and LA ejection fraction, although these variables were less robust.

CONCLUSIONS

Impaired LV global longitudinal strain, lower LA reservoir strain and lower TAPSE/PASP ratio predict cardiovascular death and HF hospitalization in HFpEF and are independent of filling pressures, clinical characteristics and natriuretic peptides. These echocardiographic parameters reflect key functional changes in HFpEF, and should be incorporated in future prospective risk prediction models.

Age-stratified profiles and outcomes of patients with heart failure with preserved ejection fraction

AIMS

This study aimed to elucidate age-stratified clinical profiles and outcomes in patients with heart failure (HF) with preserved left ventricular ejection fraction (LVEF) (HFpEF).

METHODS AND RESULTS

The Chronic Heart Failure Registry and Analysis in the Tohoku District-2 (CHART-2) Study included 2824 consecutive HFpEF patients with LVEF ≥ 50% (mean age 69.0 ± 12.3 years; 67.7% male) with a median follow-up of 9.8 years. We stratified them into five age groups: ≤54 (N = 349, 12.4%), 55-64 (N = 529, 18.7%), 65-74 (N = 891, 31.6%), 75-84 (N = 853, 30.2%), and ≥85 years (N = 202, 7.2%), and we categorized these age groups into younger (≤64 years) and older (≥65 years) groups. We compared the clinical profiles and outcomes of HFpEF patients across age groups. Younger HFpEF groups exhibited a male predominance, elevated body mass index (BMI), and poorly controlled diabetes (haemoglobin A1c > 7.0%). Older HFpEF groups were more likely to be female with multiple comorbidities, including coronary artery disease, hypertension, renal impairment, and atrial fibrillation. The positive association between elevated BMI and HFpEF was more pronounced with lower classes of age from ≥85 to ≤54 years, especially in males. With higher classes of age from ≤54 to ≥85 years, mortality rates increased, and HF death became proportionally more prevalent (Ptrend < 0.001), whereas sudden cardiac death (SCD) exhibited the opposite trend (Ptrend = 0.002). Poorly controlled diabetes emerged as the only predictor of SCD in the younger groups (adjusted hazard ratio 4.26; 95% confidence interval 1.45-12.5; P = 0.008). Multiple comorbidities were significantly associated with an increased risk of HF-related mortality in the older groups.

CONCLUSIONS

Younger HFpEF patients (≤64 years) exhibit a male predominance, elevated BMI, and poorly controlled diabetes, highlighting the importance of glycaemic control in reducing SCD risk. Older HFpEF patients (≥65 years) are more likely to be female, with multiple comorbidities linked to an increased risk of HF-related mortality. These findings underscore the need for physicians to recognize age-related, distinct HFpEF phenotypes for personalized patient management.

Prognostic models for patients suffering a heart failure with a preserved ejection fraction: a systematic review

The purpose of this study was to systematically review the development, performance, and applicability of prognostic models developed for predicting poor events in patients with heart failure with preserved ejection fraction (HFpEF). Databases including Embase, PubMed, Web of Science Core Collection, the Cochrane Library, China National Knowledge Infrastructure, Wan Fang, Wei Pu, and China Biological Medicine were queried from their respective dates of inception to 1 June 2023, to examine multivariate models for prognostic prediction in HFpEF. Both forward and backward citations of all studies were included in our analysis. Two researchers individually used the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS) checklist to extract data and assess the quality of the models using the Predictive Mode Bias Risk Assessment Tool (PROBAST). Among the 6897 studies screened, 16 studies derived and/or validated a total of 39 prognostic models. The sample size ranges for model development, internal validation, and external validation are 119 to 5988, 152 to 1000, and 30 to 5957, respectively. The most frequently employed modelling technique was Cox proportional hazards regression. Six studies (37.50%) conducted internal validation of models; bootstrap and k-fold cross-validation were the commonly used methods for internal validation of models. Ten of these models (25.64%) were validated externally, with reported the c-statistic in the external validation set ranging from 0.70 to 0.96, while the remaining models await external validation. The MEDIA echo score and I-PRESERVE-sudden cardiac death prediction mode have been externally validated using multiple cohorts, and the results consistently show good predictive performance. The most frequently used predictors identified among the models were age, n-terminal pro-brain natriuretic peptide, ejection fraction, albumin, and hospital stay in the last 5 months owing to heart failure. All study predictor domains and outcome domains were at low risk of bias, high or unclear risk of bias of all prognostic models due to underreporting in the area of analysis. All studies did not evaluate the clinical utility of the prognostic models. Predictive models for predicting prognostic outcomes in patients with HFpEF showed good discriminatory ability but their utility and generalization remain uncertain due to the risk of bias, differences in predictors between models, and the lack of clinical application studies. Future studies should improve the methodological quality of model development and conduct external validation of models.

Low-density lipoprotein cholesterol, erythrocyte, and platelet in heart failure with preserved ejection fraction

AIMS

Low-density lipoprotein cholesterol (LDL-C), anaemia and low platelets have been associated with worse clinical outcomes in heart failure patients. We investigated the relationship between the combination of these three components and clinical outcome in patients with heart failure with preserved ejection fraction (HFpEF).

METHODS AND RESULTS

We examined the data of 1021 patients with HFpEF hospitalized with acute decompensated heart failure (HF) from the PURSUIT-HFpEF registry, a prospective, multicenter observational study. The enrolled patients were classified into four groups by an LEP (LDL-C, Erythrocyte, and Platelet) score of 0 to 3 points, with 1 point each for LDL-C, erythrocyte and platelet values less than the cut-off values as calculated by receiver operating characteristic curve analysis. The endpoint, a composite of all-cause death and HF readmission, was evaluated among the four groups. Median follow-up duration was 579 [300, 978] days. Risk of the composite endpoint significantly differed among the four groups (P < 0.001). Kaplan-Meier analysis showed that the groups with an LEP score of 2 had higher risk of the composite endpoint than those with an LEP score of 0 or 1 (P < 0.001, and P = 0.013, respectively), while those with an LEP score of 3 had higher risk than those with an LEP score of 0, 1 or 2 (P < 0.001, P < 0.001 and P = 0.020, respectively). Cox proportional hazards analysis showed that an LEP score of 3 was significantly associated with the composite endpoint (P = 0.030). Kaplan-Meier analysis showed that risk of the composite of all-cause death and HF readmission was significantly higher in low LDL values (less than the cut-off values as calculated by receiver operating characteristic curve analysis) patients with statin use than in those without statin use (log rank P = 0.002).

CONCLUSIONS

LEP score, which comprehensively reflects extra-cardiac co-morbidities, is significantly associated with clinical outcomes in HFpEF patients.

The impact of atrial fibrillation on clinical outcomes in heart failure with mid-range and preserved ejection fraction patients

BACKGROUND

The combined effect of left ventricular ejection fraction (LVEF) and atrial fibrillation (AF) on clinical outcomes in heart failure (HF) remains complex.

OBJECTIVE

In this post hoc analysis of the TOPCAT trial, we aimed to evaluate the impact of AF on clinical outcomes in patients with HF stratified by LVEF range.

METHODS

A total of 3442 patients were included, stratified into 3 groups according to LVEF range-HF with mid-range ejection fraction (HFmrEF), LVEF of 45%-50% (n = 823); HF with preserved ejection fraction (HFpEF), LVEF of 51%-60% (n = 1682); and HF with normal ejection fraction (HFnEF), LVEF >60% (n = 937)-and subdivided according to the presence of AF at enrollment. Cox regression analysis was used to define independent associations between AF and clinical outcomes.

RESULTS

AF was prevalent in 38.6% in HFmrEF, 34.6% in HFpEF, and 33.7% in HFnEF (P = .07). AF was associated with worse primary outcome in each subgroup and with HF hospitalizations and worse cardiovascular mortality in HFpEF and HFnEF. The hazard ratio for the primary outcome in those with AF compared with sinus rhythm (SR) was 1.11 (1.01-1.22; P = .03) in HFmrEF, 1.20 (1.11-1.29; P < .001) in HFpEF, and 1.16 (1.05-1.28; P = .004) in HFnEF. When LVEF was treated as a continuous variable, there was a linear negative association between LVEF and the effect of AF vs SR for the primary end point and HF hospitalizations and a linear positive association for cardiovascular mortality.

CONCLUSION

Compared with SR, AF was independently associated with worse outcomes across all LVEF ranges.

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.

Development and validation of a diagnostic nomogram in pulmonary hypertension due to left heart disease

BACKGROUND

Pulmonary hypertension (pH) due to left heart disease (pH-LHD) is the most common form of pH in clinical practice.

OBJECTIVES

The purpose of the study is to develop a diagnostic nomogram predictive model combining conventional noninvasive examination and detection indicators.

METHODS

Our study retrospectively included 361 patients with left heart disease (LHD) who underwent right heart catheterization between 2013 and 2020. All patients were randomly divided into a training cohort (253, 70 %) and a validation cohort (108, 30 %). pH was defined as resting mean pulmonary arterial pressure (mPAP) ≥25 mmHg measured by RHC examination. Data dimension reduction and feature selection were used by Lasso regression model. The nomogram was constructed based on multivariable logistic regression.

RESULTS

A total of 175 patients with LHD were diagnosed with pH during their hospitalization, representing 48.5 % of the cohort. The mean age of the overall group was 55.6 years, with 76.7 % being male patients. Excessive resting heart rate, elevated New York Heart Association functional class, increased red blood cell distribution width, right ventricular end-diastolic diameter, and pulmonary artery systolic pressure measured by echocardiography were independently associated with the prevalence of pH-LHD. The inclusion of these 5 variables in the nomogram showed good discrimination (AUC = 0.866 [95 % CI, 0.820-0.911]) and optimal calibration (Hosmer-Lemeshow test, P = 0.791) for the validation cohort.

CONCLUSIONS

The noninvasive nomogram of pH-LHD developed in this study has excellent diagnostic value and clinical applicability, and can more accurately evaluate the presence risk of pH in patients with LHD.

The two different profiles in heart failure with preserved ejection fraction and type 2 diabetes mellitus: ischemic and diabetic

OBJECTIVE

Two profiles of patients with heart failure with preserved ejection fraction (HFpEF) and type 2 diabetes mellitus (T2DM) can be discerned: those with ischemic and those with diabetic cardiomyopathy (DMC). We aim to analyze clinical differences and prognosis between patients of these two profiles.

MATERIAL AND METHODS

This cohort study analyzes data from the Spanish Heart Failure Registry, a multicenter, prospective registry that enrolled patients admitted for decompensated heart failure and followed them for one year. Three groups were created according to the presence of T2DM and heart disease depending on the etiology (ischemic when coronary artery disease was present, or DMC when no coronary, valvular, or congenital heart disease; no hypertension; nor infiltrative cardiovascular disease observed on an endomyocardial biopsy). The groups and outcomes were compared.

RESULTS

A total of 466 patients were analyzed. Group 1 (n = 210) included patients with ischemic etiology and T2DM. Group 2 (n = 112) included patients with DMC etiology and T2DM. Group 3 (n = 144), a control group, included patients with ischemic etiology and without T2DM. Group 1 had more hypertension and dyslipidemia; group 2 had more atrial fibrillation (AF) and higher body mass index; group 3 had more chronic kidney disease and were older. In the regression analysis, group 3 had a better prognosis than group 1 (reference group) for cardiovascular mortality and HF readmissions (HR 0.44;95%CI 0.2-1; p = .049).

CONCLUSIONS

Patients with T2DM and HFpEF, who had the poorest prognosis, were of two different profiles: either ischemic or DMC etiology. The first had a higher burden of cardiovascular disease and inflammation whereas the second had a higher prevalence of obesity and AF. The first had a slightly poorer prognosis than the second, though this finding was not significant.

A novel polygenic risk score improves prognostic prediction of heart failure with preserved ejection fraction in the Chinese Han population

AIMS

Mortality risk assessment in patients with heart failure (HF) with preserved ejection fraction (HFpEF) presents a major challenge. We sought to construct a polygenic risk score (PRS) to accurately predict the mortality risk of HFpEF.

METHODS AND RESULTS

We first carried out a microarray analysis of 50 HFpEF patients who died and 50 matched controls who survived during 1-year follow-up for candidate gene selection. The HF-PRS was developed using the independent common (MAF > 0.05) genetic variants that showed significant associations with 1-year all-cause death (P < 0.05) in 1442 HFpEF patients. Internal cross-validation and subgroup analyses were performed to evaluate the discrimination ability of the HF-PRS. In 209 genes identified by microarray analysis, 69 independent variants (r < 0.1) were selected to develop the HF-PRS model. This model yielded the best discrimination capability for 1-year all-cause mortality with an area under the curve (AUC) of 0.852 (95% CI 0.827-0.877), which outperformed the clinical risk score consisting of 10 significant traditional risk factors for 1-year all-cause mortality (AUC 0.696, 95% CI 0.658-0.734, P = 4 × 10-11), with net reclassification improvement (NRI) of 0.741 (95% CI 0.605-0.877; P < 0.001) and integrated discrimination improvement (IDI) of 0.181 (95% CI 0.145-0.218; P < 0.001). Individuals in the medium and the highest tertile of the HF-PRS had nearly a five-fold (HR = 5.3, 95% CI 2.4-11.9; P = 5.6 × 10-5) and 30-fold (HR = 29.8, 95% CI 14.0-63.5; P = 1.4 × 10-18) increased risk of mortality compared to those in the lowest tertile, respectively. The discrimination ability of the HF-PRS was excellent in cross validation and throughout the subgroups regardless of comorbidities, gender, and patients with or without a history of heart failure.

CONCLUSION

The HF-PRS comprising 69 genetic variants provided an improvement of prognostic power over the contemporary risk scores and NT-proBNP in HFpEF patients.

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.

Diabetes leading to heart failure and heart failure leading to diabetes: epidemiological and clinical evidence

Type 2 diabetes mellitus (T2DM) is a risk factor that plays a major role in the onset of heart failure (HF) both directly, by impairing cardiac function, and indirectly, through associated diseases such as hypertension, coronary disease, renal dysfunction, obesity, and other metabolic disorders. In a population of HF patients, the presence of T2DM ranged from 20 to 40%, according to the population studied, risk factor characteristics, geographic area, and age, and it is associated with a worse prognosis. Finally, patients with HF, when compared with those without HF, show an increased risk for the onset of T2DM due to several mechanisms that predispose the HF patient to insulin resistance. Despite the epidemiological data confirmed the relationship between T2DM and HF, the exact prevalence of HF in T2DM comes from interventional trials rather than from observational registries aimed to prospectively evaluate the risk of HF occurrence in T2DM population. This review is focused on the vicious cycle linking HF and T2DM, from epidemiological data to prognostic implications.

One-year readmissions for circulatory diseases and in-hospital mortality after an index episode of heart failure in elderly patients. A nationwide data from public hospitals in Spain between 2016 and 2018

INTRODUCTION

Heart failure (HF) is one of the leading causes of hospitalization and death in elderly patients. However, there is limited evidence on readmission and mortality 1-year after discharge for HF.

METHODS

Retrospective analysis of the Minimum Basic Data Set, including HF episodes, discharged from Spanish hospitals between 2016 and 2018 in ≥ 75 years. We calculated: (a) the rate of readmissions due to circulatory system diseases (CSD) 365 days after index episode; (b) in-hospital mortality in readmissions; and (c) predictors of mortality and readmission.

RESULTS

We included 178,523 patients (59.2% women) aged 85.1 ± 5.5 years. The most frequent comorbidities were arrhythmias (56.0%) and renal failure (39.5%). During the follow-up, 48,932 patients (27.4%) had at least one readmission for CSD and a crude rate of 40.2%, the most frequent one HF (52.8%). The median between the date of readmission and discharge from the last admission was 70 days [IQI 24; 171] for the first readmission. The most relevant predictors of the number of readmissions were valvular heart disease and myocardial ischemia. During the readmissions, 26,757 patients (79.1%) died, representing a cumulative in-hospital mortality of 47,945 (26.9%). The factors in the index episode predictors of mortality during readmissions were cardio-respiratory failure and stroke. The number of readmissions was a risk factor for in-hospital mortality (OR 1.13; 95% CI 1.11-1.14).

CONCLUSIONS

The readmission rate for CSD 1-year after the index episode of HF in patients ≥ 75 years was 28.4%. The cumulative in-hospital mortality rate during the readmissions was 26.9%, and the number of rehospitalizations was identified as one of the main predictors of mortality.

Validation of the MEDIA echo score for the prognosis of heart failure with preserved ejection fraction

There is currently no widely used prognostic score in heart failure (HF) with preserved ejection fraction (HFpEF). The MEDIA echo score, including four variables (pulmonary arterial systolic pressure > 40 mmHg, inferior vena cava collapsibility index < 50%, average E/e' > 9, and lateral mitral annular s' < 7 cm/s), has been proposed as a useful risk stratification tool. This study aimed at further validating the MEDIA echo score in both hospitalised and ambulatory HFpEF patients. The MEDIA echo score ranges from 0 to 4 (each criterion scores 1 point). The associations between MEDIA echo score and cardiovascular outcomes were assessed in two independent HFpEF cohorts, namely patients hospitalised for worsening HFpEF (N = 242, mean age 78 ± 11), and stable ambulatory HFpEF patients (N = 76, mean age 65 ± 8). Using multivariable Cox models, in the worsening HFpEF cohort, patients with a MEDIA echo score of 3-4 displayed a significant increased risk of death (HR 2.10, 95%CI 1.02-4.33, P = 0.043, score 0-1 as reference). In the ambulatory HFpEF cohort, patients with a MEDIA echo score of 2 had a significantly higher risk of death or HF hospitalisation (HR 3.44, 95%CI 1.27-9.30, P = 0.015, score 0 as reference), driven by HF hospitalisation; in that cohort, adding the MEDIA echo score to the clinical model significantly improved reclassification for the combined endpoint (integrated discrimination improvement 6.2%, P = 0.006). The MEDIA echo score significantly predicted the outcome of HFpEF patients in both hospital and ambulatory settings; its use may help refine routine risk stratification on top of well-established prognosticators in stable HFpEF patients.

Unveiling Human Proteome Signatures of Heart Failure with Preserved Ejection Fraction

Heart failure with preserved ejection fraction (HFpEF) is a highly prevalent but still poorly understood clinical entity. Its current pathophysiological understanding supports a critical role of comorbidities and their chronic effect on cardiac function and structure. Importantly, despite the replication of some HFpEF phenotypic features, to this day, experimental models have failed to bring new effective therapies to the clinical setting. Thus, the direct investigation of HFpEF human myocardial samples may unveil key, and possibly human-specific, pathophysiological mechanisms. This study employed quantitative proteomic analysis by advanced mass spectrometry (SWATH-MS) to investigate signaling pathways and pathophysiological mechanisms in HFpEF. Protein-expression profiles were analyzed in human left ventricular myocardial samples of HFpEF patients and compared with a mixed control group. Functional analysis revealed several proteins that correlate with HFpEF, including those associated with mitochondrial dysfunction, oxidative stress, and inflammation. Despite the known disease heterogeneity, proteomic profiles could indicate a reduced mitochondrial oxidative phosphorylation and fatty-acid oxidation capacity in HFpEF patients with diabetes. The proteomic characterization described in this work provides new insights. Furthermore, it fosters further questions related to HFpEF cellular pathophysiology, paving the way for additional studies focused on developing novel therapies and diagnosis strategies for HFpEF patients.

Interpretable machine learning for 28-day all-cause in-hospital mortality prediction in critically ill patients with heart failure combined with hypertension: A retrospective cohort study based on medical information mart for intensive care database-IV and eICU databases

Background

Heart failure (HF) combined with hypertension is an extremely important cause of in-hospital mortality, especially for the intensive care unit (ICU) patients. However, under intense working pressure, the medical staff are easily overwhelmed by the large number of clinical signals generated in the ICU, which may lead to treatment delay, sub-optimal care, or even wrong clinical decisions. Individual risk stratification is an essential strategy for managing ICU patients with HF combined with hypertension. Artificial intelligence, especially machine learning (ML), can develop superior models to predict the prognosis of these patients. This study aimed to develop a machine learning method to predict the 28-day mortality for ICU patients with HF combined with hypertension.

Methods

We enrolled all critically ill patients with HF combined with hypertension in the Medical Information Mart for IntensiveCare Database-IV (MIMIC-IV, v.1.4) and the eICU Collaborative Research Database (eICU-CRD) from 2008 to 2019. Subsequently, MIMIC-IV was divided into training cohort and testing cohort in an 8:2 ratio, and eICU-CRD was designated as the external validation cohort. The least absolute shrinkage and selection operator (LASSO) Cox regression with internal tenfold cross-validation was used for data dimension reduction and identifying the most valuable predictive features for 28-day mortality. Based on its accuracy and area under the curve (AUC), the best model in the validation cohort was selected. In addition, we utilized the Shapley Additive Explanations (SHAP) method to highlight the importance of model features, analyze the impact of individual features on model output, and visualize an individual’s Shapley values.

Results

A total of 3,458 and 6582 patients with HF combined with hypertension in MIMIC-IV and eICU-CRD were included. The patients, including 1,756 males, had a median (Q1, Q3) age of 75 (65, 84) years. After selection, 22 out of a total of 58 clinical parameters were extracted to develop the machine-learning models. Among four constructed models, the Neural Networks (NN) model performed the best predictive performance with an AUC of 0.764 and 0.674 in the test cohort and external validation cohort, respectively. In addition, a simplified model including seven variables was built based on NN, which also had good predictive performance (AUC: 0.741). Feature importance analysis showed that age, mechanical ventilation (MECHVENT), chloride, bun, anion gap, paraplegia, rdw (RDW), hyperlipidemia, peripheral capillary oxygen saturation (SpO₂), respiratory rate, cerebrovascular disease, heart rate, white blood cell (WBC), international normalized ratio (INR), mean corpuscular hemoglobin concentration (MCHC), glucose, AIDS, mean corpuscular volume (MCV), N-terminal pro-brain natriuretic peptide (Npro. BNP), calcium, renal replacement therapy (RRT), and partial thromboplastin time (PTT) were the top 22 features of the NN model with the greatest impact. Finally, after hyperparameter optimization, SHAP plots were employed to make the NN-based model interpretable with an analytical description of how the constructed model visualizes the prediction of death.

Conclusion

We developed a predictive model to predict the 28-day mortality for ICU patients with HF combined with hypertension, which proved superior to the traditional logistic regression analysis. The SHAP method enables machine learning models to be more interpretable, thereby helping clinicians to better understand the reasoning behind the outcome and assess in-hospital outcomes for critically ill patients.

Biomarker-driven prognostic models in chronic heart failure with preserved ejection fraction: the EMPEROR-Preserved trial

AIMS

Biomarker-driven prognostic models incorporating N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-sensitivity cardiac troponin T (hs-cTnT) in heart failure (HF) with preserved ejection fraction (HFpEF) are lacking. We aimed to generate a biomarker-driven prognostic tool for patients with chronic HFpEF enrolled in EMPEROR-Preserved.

METHODS AND RESULTS

Multivariable Cox regression models were created for (i) the primary composite outcome of HF hospitalization or cardiovascular death, (ii) all-cause death, (iii) cardiovascular death, and (iv) HF hospitalization. PARAGON-HF was used as a validation cohort. NT-proBNP and hs-cTnT were the dominant predictors of the primary outcome, and in addition, a shorter time since last hospitalization, New York Heart Association (NYHA) class III or IV, history of chronic obstructive pulmonary disease (COPD), insulin-treated diabetes, low haemoglobin, and a longer time since HF diagnosis were key predictors (eight variables, all p < 0.001). The consequent primary outcome risk score discriminated well (c-statistic = 0.75) with patients in the top 10th of risk having an event rate >22× higher than those in the bottom 10th. A model for HF hospitalization alone had even better discrimination (c = 0.79). Empagliflozin reduced the risk of cardiovascular death or hospitalization for HF in patients across all risk levels. NT-proBNP and hs-cTnT were also the dominant predictors of all-cause and cardiovascular mortality followed by history of COPD, low albumin, older age, left ventricular ejection fraction ≥50%, NYHA class III or IV and insulin-treated diabetes (eight variables, all p < 0.001). The mortality risk model had similar discrimination for all-cause and cardiovascular mortality (c-statistic = 0.72 for both). External validation provided c-statistics of 0.71, 0.71, 0.72, and 0.72 for the primary outcome, HF hospitalization alone, all-cause death, and cardiovascular death, respectively.

CONCLUSIONS

The combination of NT-proBNP and hs-cTnT along with a few readily available clinical variables provides effective risk discrimination both for morbidity and mortality in patients with HFpEF. A predictive tool-kit facilitates the ready implementation of these risk models in routine clinical practice.

Predictors and Outcomes of Heart Failure With Preserved Ejection Fraction in Patients With a Left Ventricular Ejection Fraction Above or Below 60

Background Although potential therapeutic candidates for heart failure with preserved ejection fraction (HFpEF) are emerging, it is still unclear whether they will be effective in patients with left ventricular ejection fraction (LVEF) of 60% or higher. Our aim was to identify the clinical characteristics of these patients with HFpEF by comparing them to patients with LVEF below 60%. Methods and Results From a multicenter, prospective, observational cohort (PURSUIT-HFpEF [Prospective Multicenter Obsevational Study of Patients with Heart Failure with Preserved Ejection Fraction]), we investigated 812 consecutive patients (median age, 83 years; 57% women), including 316 with 50% ≤ LVEF <60% and 496 with 60% ≤ LVEF, and compared the clinical backgrounds of the 2 groups and their prognoses for cardiac mortality or HF readmission. Two hundred four adverse outcomes occurred at a median of 366 days. Multivariable Cox regression tests adjusted for age, sex, heart rate, atrial fibrillation, estimated glomerular filtration rate, N-terminal pro-B-type natriuretic peptide, and prior heart failure hospitalization revealed that systolic blood pressure (hazard ratio [HR], 0.925 [95% CI, 0.862-0.992]; P=0.028), high-density lipoprotein to C-reactive protein ratio (HR, 0.975 [95% CI, 0.944-0.995]; P=0.007), and left ventricular end-diastolic volume index (HR, 0.870 [95% CI, 0.759-0.997]; P=0.037) were uniquely associated with outcomes among patients with 50% ≤ LVEF <60%, whereas only the ratio of peak early mitral inflow velocity to velocity of mitral annulus early diastolic motion e'(HR, 1.034 [95% CI, 1.003-1.062]; P=0.034) was associated with outcomes among patients with 60% ≤ LVEF. Conclusions Prognostic factors show distinct differences between patients with HFpEF with 50% ≤ LVEF <60% and with 60% ≤ LVEF. These findings suggest that the 2 groups have different inherent pathophysiology. Registration URL: https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000024414; Unique identifier: UMIN000021831 PURSUIT-HFpEF.

Prevalence and Prognostic Significance of Polyvascular Disease in Patients Hospitalized With Acute Decompensated Heart Failure: The ARIC Study

BACKGROUND

Polyvascular disease is associated with increased mortality rates and decreased quality of life. Whether its prevalence or associated outcomes differ for patients hospitalized with heart failure with reduced vs preserved ejection fraction (HFrEF vs HFpEF, respectively) is uncertain.

METHODS

The Atherosclerosis Risk in Communities (ARIC) study conducted hospital surveillance of acute decompensated heart failure (ADHF) from 2005-2014. Polyvascular disease (coexisting disease in ≥ 2 arterial beds) was identified based on the finding of prevalent coronary artery disease, peripheral artery disease or cerebrovascular disease. Mortality risks associated with polyvascular disease were analyzed separately for HFpEF and HFrEF, with adjustment for potential confounders. All analyses were weighted by the inverse of the sampling probability.

RESULTS

Of 24,937 weighted (5460 unweighted) hospitalizations due to ADHF (52% female, 32% Black, mean age 75 years), polyvascular disease was prevalent in 22% with HFrEF and in 17% with HFpEF. One-year mortality risks increased sequentially with 0, 1 and ≥ 2 arterial bed involvement, both for patients with HFrEF (29%-32%-38%; P trend = 0.0006) and for those with HFpEF (26%-32%-37%; P trend < 0.0001). After adjustments, polyvascular disease was associated with a 26% higher mortality hazard for patients with HFrEF (HR = 1.26; 95% CI: 1.07-1.50) and a 29% higher hazard for patients with HFpEF (HR = 1.29; 95% CI: 1.03-1.62), with no interaction by HF type (P interaction = 0.9).

CONCLUSION

Patients hospitalized with ADHF and coexisting polyvascular disease have an increased risk of death, irrespective of HF type. Clinical attention should be directed toward polyvascular disease, with implementation of secondary prevention strategies to improve the prognosis of this high-risk population.

SUMMARY

Polyvascular disease is known to be associated with myocardial infarction, stroke or cardiovascular death and is a major risk factor for decreased quality of life. This study sought to evaluate the relationship between polyvascular disease and mortality in patients hospitalized with acute decompensated heart failure (ADHF), and to understand whether the associations differ based on ejection fraction. Patients hospitalized with ADHF and coexisting polyvascular disease had an increased risk of death, irrespective of heart failure type, implying the need for increased clinical attention directed toward polyvascular disease, along with implementation of secondary prevention strategies to improve prognosis.

TWEET

Patients hospitalized with acute HF and coexisting polyvascular disease face an increased risk of death, irrespective of HF type.

A nomogram to predict the in-hospital mortality of patients with congestive heart failure and chronic kidney disease

AIMS

Patients with congestive heart failure (CHF) may also suffer from chronic kidney disease (CKD), and the two conditions may interact to increase the risk of death. The purpose of this study was to investigate the risk factors contributing to in-hospital mortality in patients with CHF and CKD and to develop a nomogram to predict the risk of in-hospital mortality.

METHODS AND RESULTS

This retrospective study used data from the Marketplace for Medical Information in Intensive Care (MIMIC-IV, version 1.0). Patients diagnosed with CHF and CKD in MIMIC-IV were included in this study. The least absolute shrinkage and selection operator (LASSO) logistic regression is used to select risk variables for the nomogram model, and bootstrap is used for internal validation. Simplified Acute Physiology Score II (SAPS II) and Logistic Organ Dysfunction Score (LODS) were compared with the nomogram model by the area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA). A total of 4638 adult patients with CHF and CKD were included in the final cohort; of them, 707 (15.2%) died and 3931 (84.8%) survived during hospitalization. Our final model included the following 13 variables: age, acute kidney injury, myocardial infarction, anaemia, heart rate ≥ 100 b.p.m., systolic blood pressure ≥ 130 mmHg, anion gap (AG) ≥ 20 mEq/L, sodium ≥ 145 mEq/L, red blood cell distribution width (RDW) ≥ 15.5%, white blood cell count ≥ 10 K/μL, continuous renal replacement therapy (CRRT), angiotensin-converting enzyme inhibitors/angiotensin receptor blockers, and beta-blocker. The corrected C-statistic of the nomogram was 0.767, and the calibration curve indicating good concordance between the predicted and observed values. The nomogram demonstrated good accuracy for predicting the in-hospital mortality with an AUC of 0.771 (95% CI: 0.752-0.790), while the AUC for SAPS II and LODS was 0.747 (95% CI: 0.726-0.767) and 0.752 (95% CI: 0.730-0.773), respectively. DCA found that when the threshold probability was 0.05 to 0.41, the nomogram model could provide a greater net benefit than SAPS II.

CONCLUSIONS

In this retrospective cohort analysis of patients with CHF and CKD, we identified 13 independent variables associated with in-hospital mortality using LASSO logistic regression. RDW, AG, and CRRT were reported to play a significant role in in-hospital mortality among patients with CHF and CKD for the first time. Based on a simplified model including 13 variables, a nomogram was drawn to predict the risk of in-hospital mortality. In comparison with SAPS II and LODS, the nomogram model performed well.

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.

Role of confirmed and potential predictors of an unfavorable outcome in heart failure in everyday clinical practice

Heart failure (HF) is the only cardiovascular disease with an ever increasing incidence. HF, through reduced functional capacity, frequent exacerbations of disease, and repeated hospitalizations, results in poorer quality of life, decreased work productivity, and significantly increased costs of the public health system. The main challenge in the treatment of HF is the availability of reliable prognostic models that would allow patients and doctors to develop realistic expectations about the prognosis and to choose the appropriate therapy and monitoring method. At this moment, there is a lack of universal parameters or scales on the basis of which we could easily capture the moment of deterioration of HF patients' condition. Hence, it is crucial to identify such factors which at the same time will be widely available, cheap, and easy to use. We can find many studies showing different predictors of unfavorable outcome in HF patients: thorough assessment with echocardiography imaging, exercise testing (e.g., 6-min walk test, cardiopulmonary exercise testing), and biomarkers (e.g., N-terminal pro-brain type natriuretic peptide, high-sensitivity troponin T, galectin-3, high-sensitivity C-reactive protein). Some of them are very promising, but more research is needed to create a specific panel on the basis of which we will be able to assess HF patients. At this moment despite identification of many markers of adverse outcomes, clinical decision-making in HF is still predominantly based on a few basic parameters, such as the presence of HF symptoms (NYHA class), left ventricular ejection fraction, and QRS complex duration and morphology.

Predictors of thirty-day readmission in nonagenarians presenting with acute heart failure with preserved ejection fraction: a nationwide analysis

BACKGROUD

Acute heart failure with preserved ejection fraction (HFpEF) is a common but poorly studied cause of hospital admissions among nonagenarians. This study aimed to evaluate predictors of thirty-day readmission, in-hospital mortality, length of stay, and hospital charges in nonagenarians hospitalized with acute HFpEF.

METHODS

Patients hospitalized between January 2016 and December 2018 with a primary diagnosis of diastolic heart failure were identified using ICD-10 within the Nationwide Readmission Database. We excluded patients who died in index admission, and discharged in December each year to allow thirty-day follow-up. Univariate regression was performed on each variable. Variables with P-value < 0.2 were included in the multivariate regression model.

RESULTS

From a total of 45,393 index admissions, 43,646 patients (96.2%) survived to discharge. A total of 7,437 patients (15.6%) had a thirty-day readmission. Mean cost of readmission was 43,265 United States dollars (USD) per patient. Significant predictors of thirty-day readmission were chronic kidney disease stage III or higher [adjusted odds ratio (aOR) = 1.20, 95% CI: 1.07-1.34,P = 0.002] and diabetes mellitus (aOR = 1.18, 95% CI: 1.07-1.29,P = 0.001). Meanwhile, female (aOR = 0.90, 95% CI: 0.82-0.99,P = 0.028) and palliative care encounter (aOR = 0.27, 95% CI: 0.21-0.34,P < 0.001) were associated with lower odds of readmission. Cardiac arrhythmia (aOR = 1.46, 95% CI: 1.11-1.93, P = 0.007) and aortic stenosis (aOR = 1.36, 95% CI: 1.05-1.76,P = 0.020) were amongst predictors of in-hospital mortality.

CONCLUSIONS

In nonagenarians hospitalized with acute HFpEF, thirty-day readmission is common and costly. Chronic comorbidities predict poor outcomes. Further strategies need to be developed to improve the quality of care and prevent the poor outcome in nonagenarians.

Under-Enrollment of Obese Heart Failure with Preserved Ejection Fraction Patients in Major HFpEF Clinical Trials

BACKGROUND

Therapy for heart failure with preserved ejection fraction (HFpEF) remains an unmet need with lack of consensus definition of HFpEF for inclusion into clinical trials. We evaluated for whether hemodynamically characterized patients from a HFpEF referral center met inclusion criteria for 4 major HFpEF trials.

METHODS

Patients were assessed for theoretical inclusion into four major clinical trials (I-PRESERVE, RELAX, TOPCAT, and PARAGON-HF). Clinical, echocardiographic, hemodynamic characteristics, and cardiovascular outcomes were compared between patients who met inclusion criteria versus those who did not for each trial.

RESULTS

Of 131 HFpEF patients, 23% of patients met enrollment criteria for I-PRESERVE, 38% for RELAX, 18% for TOPCAT, and 13% for PARAGON-HF. The top criteria that excluded patients included low natriuretic peptide level, obesity, uncontrolled hypertension, young age, and low hemoglobin. There was no difference in probability of HF hospitalization or death in patients included or excluded into each clinical trial.

CONCLUSION

In a cohort with hemodynamic evidence of HFpEF, a low proportion of patients met inclusion criteria for major HFpEF clinical trials, with no difference in outcomes in patients who did or did not meet inclusion criteria. Given the lack of proven therapies in HFpEF, consideration should be given to modifying criteria to represent contemporary HFpEF patients in future clinical trials.

N-terminal prohormone B-type natriuretic peptide variability acts as a predictor of poor prognosis in patients with cardiorenal syndrome type 2

This study aims to explore the effect of N-terminal pro-brain natriuretic peptide (NT-proBNP) variability (mean absolute difference of the log2 NT-proBNP level measured in hospital) on the prognosis of patients with cardiorenal syndrome (CRS) type 2. Patients with CRS type 2 were retrospectively included. The varied NT-proBNP indications were analyzed. They were NT-proBNP I(pre-treatment), NT-proBNP II(post-treatment), NT-proBNP II/I, ΔNT-proBNP, log2 (NT-proBNP) variability and mean log2 (NT-proBNP). A logistic regression model and survival curves (Kaplan–Meier analysis) were built to identify independent predictors associated with poor prognosis. The primary outcomes were major adverse renal and cardiac events. The secondary outcome was all-cause mortality. From 2012 to 2016, 136 patients were included in this study with 69 (50.7%) had high log2 (NT-proBNP) variability level. The optimal cutoff level for each NT-proBNP indication that predicts poor prognosis was calculated, and the area under curves ranged from 0.668 to 0.891 with different indications. Kaplan–Meier analysis revealed that there was significantly correlated with prevalence of primary outcomes and NT-proBNP variability. The hazard ratios (HRs) ranged from 1.67 to 6.61 with different indications. The multivariate regression analyses also identified the risk of the primary outcomes were associated with elevated NT-proBNP values, except NT-proBNP I. The odds ratio (ORs) ranged from 1.83 to 6.61 with different indications. When analyzing the relationship between NT-proBNP variability and all-cause mortality, the results were the same. NT-proBNP variability might serve as an independent predictor for poor prognosis and all-cause mortality in patients with CRS type 2.

The clinical and prognostic value of late Gadolinium enhancement imaging in heart failure with mid-range and preserved ejection fraction

Heart failure (HF) with mid-range or preserved ejection fraction (HFmrEF; HFpEF) is a heterogeneous disorder that could benefit from strategies to identify subpopulations at increased risk. We tested the hypothesis that HFmrEF and HFpEF patients with myocardial scars detected with late gadolinium enhancement (LGE) are at increased risk for all-cause mortality. Symptomatic HF patients with left ventricular ejection fraction (LVEF) > 40%, who underwent cardiac magnetic resonance (CMR) imaging were included. The presence of myocardial LGE lesions was visually assessed. T1 mapping was performed to calculate extracellular volume (ECV). Multivariable logistic regression analyses were used to determine associations between clinical characteristics and LGE. Cox regression analyses were used to assess the association between LGE and all-cause mortality. A total of 110 consecutive patients were included (mean age 71 ± 10 years, 49% women, median N-terminal brain natriuretic peptide (NT-proBNP) 1259 pg/ml). LGE lesions were detected in 37 (34%) patients. Previous myocardial infarction and increased LV mass index were strong and independent predictors for the presence of LGE (odds ratio 6.32, 95% confidence interval (CI) 2.07–19.31, p = 0.001 and 1.68 (1.03–2.73), p = 0.04, respectively). ECV was increased in patients with LGE lesions compared to those without (28.6 vs. 26.6%, p = 0.04). The presence of LGE lesions was associated with a fivefold increase in the incidence of all-cause mortality (hazards ratio 5.3, CI 1.5–18.1, p = 0.009), independent of age, sex, New York Heart Association (NYHA) functional class, NT-proBNP, LGE mass and LVEF. Myocardial scarring on CMR is associated with increased mortality in HF patients with LVEF > 40% and may aid in selecting a subpopulation at increased risk.

Risk Scores and Prediction Models in Chronic Heart Failure: A Comprehensive Review

BACKGROUND

Heart failure affects a substantial proportion of the adult population, with an estimated prevalence of 1-2% in developed countries. Over the previous decades, many prediction models have been introduced for this specific population in an attempt to better stratify and manage heart failure patients.

OBJECTIVE

The aim of this study is the systematic review of recent, relevant literature regarding risk scores or prediction models in ambulatory patients with an established diagnosis of chronic heart failure.

METHODS

We conducted a systematic search of the literature in PubMed and CENTRAL from their inception up till December 2019 for studies assessing the performance of risk scores and prediction models and original research studies. Grey literature was searched as well. This review is reported in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement.

RESULTS

We included 16 eligible studies in this systematic review. Major heart failure risk scores derived from large heart failure populations were among the included studies. Due to significant heterogeneity regarding the main endpoints, a direct comparison of the included prediction scores was inevitable. The majority referred to patients with heart failure with reduced ejection fraction, while only two out of 16 prediction scores have been developed exclusively for heart failure patients with preserved ejection fraction. Ischemic heart disease was the most common aetiology of heart failure in the included studies. Finally, more than half of the prediction scores have not been externally validated.

CONCLUSION

Prediction models aiming at heart failure patients with a preserved or mid-range ejection fraction are lacking. Prediction scores incorporating recent advances in pharmacotherapy should be developed in the future.

High Neutrophil to Lymphocyte Ratio and Its Gene Signatures Correlate With Diastolic Dysfunction in Heart Failure With Preserved Ejection Fraction

Aims: To evaluate the interrelation between neutrophil to lymphocyte ratio (NLR) coupled with gene signatures, inflammation, and diastolic dysfunction in patients with heart failure (HF) with preserved ejection fraction (HFpEF). Methods: The clinical profile of 172 patients with HFpEF (EF ≥ 50%) and 173 non-HF control individuals was analyzed retrospectively. The association between NLR and HFpEF and the predictive performance of NLR for HFpEF were assessed by the binary logistic regression analysis and the receiver operating characteristic curve (ROC). Multivariate linear regression models further examined the associations between NLR and high-sensitivity C-reactive protein (hs-CRP), N-terminal prohormone of brain natriuretic peptide (NT-proBNP), and average septal-lateral E/e', respectively. The freshly isolated neutrophils from 30 HFpEF patients and 42 non-HF controls were subjected to transcriptomic profiling. The biomarkers related to neutrophil activation and inflammation were detected in serum samples. Results: The HFpEF patients in Southeast China were lean and had comorbidity burden and worse cardiac structure/function. Compared with non-HF control individuals, HFpEF patients had a rise in NLR. NLR displayed an independent association with HFpEF [adjusted odds ratio, 2.351; 95% CI, 1.464-3.776; p < 0.001] and it predicted HFpEF with the area under the ROC 0.796 (95% CI, 0.748-0.845, p < 0.001). The positive associations between NLR and hs-CRP, NT-proBNP, and mitral E/e' were found in HFpEF patients. Moreover, patients had significantly elevated serum levels of neutrophil elastase and inflammatory biomarkers, both of which correlated with the mitral E/e' ratio. Finally, multiple molecules that drive neutrophil degranulation and inflammation, such as S100A8/A9/A12 and PADI4, were transcriptionally up-regulated in neutrophils of HFpEF patients. Conclusions: The high NLR coupled with transcriptional activation of neutrophils correlates with systemic inflammation and functional impairment in HFpEF patients, which may suggest a causative role of neutrophils in the pathogenesis of the disease.

Distinctive prognostic factor of heart failure with preserved ejection fraction stratified with admission blood pressure

Aims

The prognostic importance of admission systolic blood pressure (SBP) in heart failure with preserved ejection fraction (HFpEF) is elusive. We aimed to clarify the pathophysiological differences between patients categorized with admission SBP among HFpEF patients.

Methods and results

We studied 1008 inpatients from PURSUIT‐HFpEF, a multicentre prospective observational registry. We classified patients as having elevated (>140 mmHg), preserved (90–140 mmHg), or low (<90 mmHg) admission SBP. Most cases had elevated (n = 584) or preserved (n = 420) SBP; the four cases with low SBP were excluded. Univariable Cox regression testing revealed that preserved SBP patients had a higher risk of a composite of cardiac death and heart failure re‐hospitalization [hazard ratio (HR) 1.48, 95% confidence interval (CI) 1.14–1.92, P = 0.0035] than elevated SBP patients. In multivariable Cox regression models, while prior heart failure hospitalization (HR 1.36, 95% CI 1.01–2.84, P = 0.0453), atrial fibrillation (HR 1.82, 95% CI 1.10–2.99, P = 0.0209), and N‐terminal pro‐B‐type natriuretic peptide (HR 1.94, 95% CI 1.10–3.43, P = 0.0229) at discharge were significantly associated with adverse outcomes in elevated SBP patients, N‐terminal pro‐B‐type natriuretic peptide (HR 2.06, 95% CI 1.04–4.07, P = 0.0373) and right ventricular‐pulmonary artery uncoupling reflected by the tricuspid annular plane systolic excursion/pulmonary artery systolic pressure ratio (HR 0.19, 95% CI 0.05–0.65, P = 0.0075) at discharge were significant prognostic factors in preserved SBP patients.

Conclusions

Patients with preserved admission SBP had significant higher risks for adverse outcomes than those with elevated SBP in HFpEF. Tricuspid annular plane systolic excursion/pulmonary artery systolic pressure was the distinctive prognostic factor between the two groups.

Resting heart rate and real-life treatment modalities in outpatients with left ventricular systolic dysfunction study: A multicenter, prospective, observational, and national registry

OBJECTIVE

Heart rate (HR) reduction is associated with improved outcomes in heart failure (HF). This multicenter, prospective, observational, and national registry aimed to evaluate resting HR and the impacts of HR-related medications in real-life clinical practice in patients with HF.

METHODS

The Resting HR and Real-Life Treatment Modalities in Outpatients with Left Ventricular Systolic Dysfunction (REALITY HF) study enrolled 1054 patients with HF and left ventricular ejection fraction (LVEF) of <40% from 16 centers. Clinical characteristics, HR, and medications were noted (enrollment phase). A total of 487 patients with sinus rhythm and HR of ≥70 bpm were included in a further 4-month follow-up (FU) program (V0). Changes in HR and medications were reevaluated at 1-month (V1) and 4-month (V2) FU visits. The Kansas City Cardiomyopathy Questionnaire (KCCQ) was used to assess the quality of life (QoL) of 320 patients in a 4-month FU program.

RESULTS

During enrollment, 794 patients (75.3%) were in sinus rhythm, in whom resting HR was 76.7±14 bpm, 69.1% had a resting HR of ≥70 bpm, 79.1% were receiving beta blocker (BB), and 6.1% were receiving ivabradine. Resting HR was lower in patients receiving BB (75.8±13 vs. 80.4±16 bpm; p=0.001); however, 65.8% of those still had a resting HR of ≥70 bpm. A significant association was found between elevated HR and worse New York Heart Association (NYHA) class, worse QoL, or lower LVEF. During the 4-month FU, adjustment of HR-lowering therapy was left to the physician's discretion. Resting HR significantly reduced from 83.6±12 (80) bpm at V0 to 78.6±13 (77) bpm at V1 (p=0.001) and further decreased to 73.0±11 (73) bpm at V2 (p=0.001). Patients achieving a resting HR of <70 bpm were 21.7% at V1 (p=0.001) and 39.9% at V2 (p=0.001). KCCQ significantly increased from 59.7±23 (62.7) at V0 to 73.1±18 (78.5) at V2 (p=0.001). In addition, patients with NYHA I increased from 22.2% at V0 to 29.2% at V1 and 39.4% at V2 (p=0.01).

CONCLUSION

In real-life clinical practice, elevated HR is highly prevalent in HF despite widely used BB therapy and is associated with worse clinical picture. Therapeutic interventions targeting HR significantly reduce HR, and HR lowering is associated with improved clinical outcomes.

Machine Learning-Driven Models to Predict Prognostic Outcomes in Patients Hospitalized With Heart Failure Using Electronic Health Records: Retrospective Study

Background

With the prevalence of cardiovascular diseases increasing worldwide, early prediction and accurate assessment of heart failure (HF) risk are crucial to meet the clinical demand.

Objective

Our study objective was to develop machine learning (ML) models based on real-world electronic health records to predict 1-year in-hospital mortality, use of positive inotropic agents, and 1-year all-cause readmission rate.

Methods

For this single-center study, we recruited patients with newly diagnosed HF hospitalized between December 2010 and August 2018 at the First Affiliated Hospital of Dalian Medical University (Liaoning Province, China). The models were constructed for a population set (90:10 split of data set into training and test sets) using 79 variables during the first hospitalization. Logistic regression, support vector machine, artificial neural network, random forest, and extreme gradient boosting models were investigated for outcome predictions.

Results

Of the 13,602 patients with HF enrolled in the study, 537 (3.95%) died within 1 year and 2779 patients (20.43%) had a history of use of positive inotropic agents. ML algorithms improved the performance of predictive models for 1-year in-hospital mortality (areas under the curve [AUCs] 0.92-1.00), use of positive inotropic medication (AUCs 0.85-0.96), and 1-year readmission rates (AUCs 0.63-0.96). A decision tree of mortality risk was created and stratified by single variables at levels of high-sensitivity cardiac troponin I (<0.068 μg/L), followed by percentage of lymphocytes (<14.688%) and neutrophil count (4.870×10⁹/L).

Conclusions

ML techniques based on a large scale of clinical variables can improve outcome predictions for patients with HF. The mortality decision tree may contribute to guiding better clinical risk assessment and decision making.

Risk Prediction in Patients With Heart Failure With Preserved Ejection Fraction Using Gene Expression Data and Machine Learning

Heart failure with preserved ejection fraction (HFpEF) has become a major health issue because of its high mortality, high heterogeneity, and poor prognosis. Using genomic data to classify patients into different risk groups is a promising method to facilitate the identification of high-risk groups for further precision treatment. Here, we applied six machine learning models, namely kernel partial least squares with the genetic algorithm (GA-KPLS), the least absolute shrinkage and selection operator (LASSO), random forest, ridge regression, support vector machine, and the conventional logistic regression model, to predict HFpEF risk and to identify subgroups at high risk of death based on gene expression data. The model performance was evaluated using various criteria. Our analysis was focused on 149 HFpEF patients from the Framingham Heart Study cohort who were classified into good-outcome and poor-outcome groups based on their 3-year survival outcome. The results showed that the GA-KPLS model exhibited the best performance in predicting patient risk. We further identified 116 differentially expressed genes (DEGs) between the two groups, thus providing novel therapeutic targets for HFpEF. Additionally, the DEGs were enriched in Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways related to HFpEF. The GA-KPLS-based HFpEF model is a powerful method for risk stratification of 3-year mortality in HFpEF patients.

Narrative review in the current role of angiotensin receptor-neprilysin inhibitors

Heart failure (HF) accounts for a tremendous burden on health care systems and the society. Since the landmark PARADIGM-HF trial, sacubitril/valsartan, the first in the class of angiotensin receptor neprilysin inhibitor (ARNI) showed superiority to enalapril in patients with HF with reduced ejection fraction (HFrEF). We performed a narrative literature review, hand-searched the reference lists of included articles and relevant reviews. Inhibition of neprilysin increases bradykinin, natriuretic peptides and adrenomedullin levels counteract the neurohormal activation that leads to sodium retention, vasoconstriction, and cardiac remodeling. In PARADIGM-HF the primary outcome of CV death or HF hospitalization was reduced 20% in the ARNI group (HR 0.80, P<0.001) similar to mortality due to cardiovascular cause (HR 0.80, P<0.001) in patients with HFrEF, rendering a number needed to treat of 21 patients. This effect was consistent across subgroups. The safety of starting ARNI inpatient once the acute decompensation of HF is stabilized was demonstrated in PIONEER-HF trial. With willingness-to-pay thresholds commonly acceptable in the United States, sacubitril/valsartan is likely to be cost effective, which might not be in other health systems. Although its safety has been reassured in some clinical trials, common side effects are hypotension, worsening kidney function, hyperkalemia and angioedema. In HFpEF (PARAGON-HF), sacubitril/valsartan showed decrease in the level of the cardiac biomarkers, with improve functional NYHA and decrease in hospitalizations, predominately in women and patients with borderline ejection fraction. Some ongoing studies aim to demonstrate the effects of ARNI in acute coronary syndrome, stable ischemic heart disease, advanced HF, mitral regurgitation, aortic impedance and pulmonary hypertension. In conclusion, sacubitril/valsartan has proven to be an effective addition to the HFrEF arsenal, with safety comparable to current standard of care. In HFpEF, it improves quality of life, particularly in women and in patients with borderline ejection fraction, with no effect on mortality.

A heart failure phenotype stratified model for predicting 1-year mortality in patients admitted with acute heart failure: results from an individual participant data meta-analysis of four prospective European cohorts

BACKGROUND

Prognostic models developed in general cohorts with a mixture of heart failure (HF) phenotypes, though more widely applicable, are also likely to yield larger prediction errors in settings where the HF phenotypes have substantially different baseline mortality rates or different predictor-outcome associations. This study sought to use individual participant data meta-analysis to develop an HF phenotype stratified model for predicting 1-year mortality in patients admitted with acute HF.

METHODS

Four prospective European cohorts were used to develop an HF phenotype stratified model. Cox model with two rounds of backward elimination was used to derive the prognostic index. Weibull model was used to obtain the baseline hazard functions. The internal-external cross-validation (IECV) approach was used to evaluate the generalizability of the developed model in terms of discrimination and calibration.

RESULTS

3577 acute HF patients were included, of which 2368 were classified as having HF with reduced ejection fraction (EF) (HFrEF; EF < 40%), 588 as having HF with midrange EF (HFmrEF; EF 40-49%), and 621 as having HF with preserved EF (HFpEF; EF ≥ 50%). A total of 11 readily available variables built up the prognostic index. For four of these predictor variables, namely systolic blood pressure, serum creatinine, myocardial infarction, and diabetes, the effect differed across the three HF phenotypes. With a weighted IECV-adjusted AUC of 0.79 (0.74-0.83) for HFrEF, 0.74 (0.70-0.79) for HFmrEF, and 0.74 (0.71-0.77) for HFpEF, the model showed excellent discrimination. Moreover, there was a good agreement between the average observed and predicted 1-year mortality risks, especially after recalibration of the baseline mortality risks.

CONCLUSIONS

Our HF phenotype stratified model showed excellent generalizability across four European cohorts and may provide a useful tool in HF phenotype-specific clinical decision-making.

The impact of chronic obstructive pulmonary disease on hospitalization and mortality in patients with heart failure

BACKGROUND

Several studies have suggested that chronic obstructive pulmonary disease (COPD) could be predictive of the prognosis in patients with heart failure (HF), but yield conflicting findings. Therefore, we conducted a meta-analysis to examine the impact of COPD on adverse outcomes in patients with HF.

METHODS

We systematically searched the databases of PubMed, EMBASE, Google Scholar, Cochrane library from inception to August 2020 for the relevant studies. Adjusted risk ratios (RRs) and confidence intervals (CIs) were collected and then pooled by the Review Manager version 5.30 software with a random-effects model.

RESULTS

A total of 18 studies (6 post hoc analyses of trials and 12 observational studies) were included in this meta-analysis. COPD was associated with an increased risk of all-cause mortality (hospitalized HF: RR 1.43, 95% CI: 1.20-1.70; chronic HF: RR 1.24, 95% CI: 1.16-1.33), but not cardiovascular mortality, in patients with hospitalized HF or chronic HF. In addition, COPD was associated with increased risks of all-cause hospitalization (RR 1.31, 95% CI: 1.21-1.42) and HF hospitalization (RR 1.31, 95% CI: 1.21-1.42) in the chronic HF patients.

CONCLUSIONS

COPD comorbidity could increase the risk of all-cause mortality of HF patients. Future research should confirm the findings on hospitalization because of the limited studies included for this outcome.

Developing and validating models to predict sudden death and pump failure death in patients with heart failure and preserved ejection fraction

BACKGROUND

Sudden death (SD) and pump failure death (PFD) are leading modes of death in heart failure and preserved ejection fraction (HFpEF). Risk stratification for mode-specific death may aid in patient enrichment for new device trials in HFpEF.

METHODS

Models were derived in 4116 patients in the Irbesartan in Heart Failure with Preserved Ejection Fraction trial (I-Preserve), using competing risks regression analysis. A series of models were built in a stepwise manner, and were validated in the Candesartan in Heart failure: Assessment of Reduction in Mortality and morbidity (CHARM)-Preserved and Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist (TOPCAT) trials.

RESULTS

The clinical model for SD included older age, men, lower LVEF, higher heart rate, history of diabetes or myocardial infarction, and HF hospitalization within previous 6 months, all of which were associated with a higher SD risk. The clinical model predicting PFD included older age, men, lower LVEF or diastolic blood pressure, higher heart rate, and history of diabetes or atrial fibrillation, all for a higher PFD risk, and dyslipidaemia for a lower risk of PFD. In each model, the observed and predicted incidences were similar in each risk subgroup, suggesting good calibration. Model discrimination was good for SD and excellent for PFD with Harrell's C of 0.71 (95% CI 0.68-0.75) and 0.78 (95% CI 0.75-0.82), respectively. Both models were robust in external validation. Adding ECG and biochemical parameters, model performance improved little in the derivation cohort but decreased in validation. Including NT-proBNP substantially increased discrimination of the SD model, and simplified the PFD model with marginal increase in discrimination.

CONCLUSIONS

The clinical models can predict risks for SD and PFD separately with good discrimination and calibration in HFpEF and are robust in external validation. Adding NT-proBNP further improved model performance. These models may help to identify high-risk individuals for device intervention in future trials.

CLINICAL TRIAL REGISTRATION

I-Preserve: ClinicalTrials.gov NCT00095238; TOPCAT: ClinicalTrials.gov NCT00094302; CHARM-Preserved: ClinicalTrials.gov NCT00634712.

Resting Heart Rate as an Important Predictor of Mortality and Morbidity in Ambulatory Patients With Heart Failure: A Systematic Review and Meta-Analysis

BACKGROUND

Resting heart rate is a risk factor of adverse heart failure outcomes; however, studies have shown controversial results. This meta-analysis evaluates the association of resting heart rate with mortality and hospitalization and identifies factors influencing its effect.

METHODS AND RESULTS

We systematically searched electronic databases in February 2019 for studies published in 2005 or before that evaluated the resting heart rate as a primary predictor or covariate of multivariable models of mortality and/or hospitalization in adult ambulatory patients with heart failure. Random effects inverse variance meta-analyses were performed to calculate pooled hazard ratios. The Grading of Recommendations, Assessment, Development and Evaluation approach was used to assess evidence quality. Sixty-two studies on 163,445 patients proved eligible. Median population heart rate was 74 bpm (interquartile range 72-76 bpm). A 10-bpm increase was significantly associated with increased risk of all-cause mortality (hazard ratio 1.10, 95% confidence interval 1.08-1.13, high quality). Overall, subgroup analyses related to patient characteristics showed no changes to the effect estimate; however, there was a strongly positive interaction with age showing increasing risk of all-cause mortality per 10 bpm increase in heart rate.

CONCLUSIONS

High-quality evidence demonstrates increasing resting heart rate is a significant predictor of all-cause mortality in ambulatory patients with heart failure on optimal medical therapy, with consistent effect across most patient factors and an increased risk trending with older age.

Prognostic Importance of Right Ventricular-Vascular Uncoupling in Acute Decompensated Heart Failure With Preserved Ejection Fraction

Background:

Recent accumulating evidence reveals that the right ventricular (RV)-pulmonary artery (PA) uncoupling is associated with poor outcome in patients with heart failure (HF), RV dysfunction, and pulmonary hypertension. However, the prognostic utility of RV-PA uncoupling in HF with preserved ejection fraction (HFpEF) remains elusive. In this study, we aim to investigate the associations of RV-PA uncoupling with outcomes of HFpEF inpatients.

Methods:

We prospectively studied 655 patients, registered in PURSUIT-HFpEF (The Prospective Multicenter Obervational Study of Patients with Heart Failure with Preserved Ejection Fraction), a multicenter observational study of Japanese HFpEF inpatients. We assigned registered patients based on the determined value of tricuspid annular plane systolic excursion/pulmonary artery systolic pressure ratio that can predict primary outcome as an indicator of RV-PA uncoupling.

Results:

Univariable Cox regression testing revealed that RV-PA uncoupling was associated with the primary endpoint of all-cause death, HF rehospitalization, and cerebrovascular events (hazard ratio [HR] 1.77 [95% CI, 1.34–2.32], P <0.0001) and the secondary endpoints of all-cause death and HF rehospitalization (HR 2.75 [95% CI, 1.77–4.33], P <0.0001, HR 1.63 [95% CI, 1.18–2.26], P =0.0036, respectively). Multivariable analysis also showed that RV-PA uncoupling was significantly associated with primary endpoint and all-cause death independent of age, sex, atrial fibrillation, renal dysfunction, elevated E/e’, and elevated NT-proBNP (N-terminal pro-B-type natriuretic peptide) (HR 1.38 [95% CI, 1.01–1.88], P =0.0413, HR 1.85 [95% CI, 1.14–3.01], P =0.0129, respectively).

Conclusions:

Prospective study of a hospitalized cohort revealed that RV-PA uncoupling was independently associated with adverse outcomes in acute decompensated patients with HFpEF.

Registration:

URL: https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000024414 . Unique identifier: UMIN000021831.

Proteomic Evaluation of the Comorbidity-Inflammation Paradigm in Heart Failure With Preserved Ejection Fraction: Results From the PROMIS-HFpEF Study

BACKGROUND

A systemic proinflammatory state has been hypothesized to mediate the association between comorbidities and abnormal cardiac structure/function in heart failure with preserved ejection fraction (HFpEF). We conducted a proteomic analysis to investigate this paradigm.

METHODS

In 228 patients with HFpEF from the multicenter PROMIS-HFpEF study (Prevalence of Microvascular Dysfunction in Heart Failure With Preserved Ejection Fraction), 248 unique circulating proteins were quantified by a multiplex immunoassay (Olink) and used to recapitulate systemic inflammation. In a deductive approach, we performed principal component analysis to summarize 47 proteins known a priori to be involved in inflammation. In an inductive approach, we performed unbiased weighted coexpression network analyses of all 248 proteins to identify clusters of proteins that overrepresented inflammatory pathways. We defined comorbidity burden as the sum of 8 common HFpEF comorbidities. We used multivariable linear regression and statistical mediation analyses to determine whether and to what extent inflammation mediates the association of comorbidity burden with abnormal cardiac structure/function in HFpEF. We also externally validated our findings in an independent cohort of 117 HFpEF cases and 30 comorbidity controls without heart failure.

RESULTS

Comorbidity burden was associated with abnormal cardiac structure/function and with principal components/clusters of inflammation proteins. Systemic inflammation was also associated with increased mitral E velocity, E/e' ratio, and tricuspid regurgitation velocity; and worse right ventricular function (tricuspid annular plane systolic excursion and right ventricular free wall strain). Inflammation mediated the association between comorbidity burden and mitral E velocity (proportion mediated 19%-35%), E/e' ratio (18%-29%), tricuspid regurgitation velocity (27%-41%), and tricuspid annular plane systolic excursion (13%) (P<0.05 for all), but not right ventricular free wall strain. TNFR1 (tumor necrosis factor receptor 1), UPAR (urokinase plasminogen activator receptor), IGFBP7 (insulin-like growth factor binding protein 7), and GDF-15 (growth differentiation factor-15) were the top individual proteins that mediated the relationship between comorbidity burden and echocardiographic parameters. In the validation cohort, inflammation was upregulated in HFpEF cases versus controls, and the most prominent inflammation protein cluster identified in PROMIS-HFpEF was also present in HFpEF cases (but not controls) in the validation cohort.

CONCLUSIONS

Proteins involved in inflammation form a conserved network in HFpEF across 2 independent cohorts and may mediate the association between comorbidity burden and echocardiographic indicators of worse hemodynamics and right ventricular dysfunction. These findings support the comorbidity-inflammation paradigm in HFpEF.

Predicting High-Risk Patients and High-Risk Outcomes in Heart Failure

Identifying patients with heart failure at high risk for poor outcomes is important for patient care, resource allocation, and process improvement. Although numerous risk models exist to predict mortality, hospitalization, and patient-reported health status, they are infrequently used for several reasons, including modest performance, lack of evidence to support routine clinical use, and barriers to implementation. Artificial intelligence has the potential to enhance the performance of risk prediction models, but has its own limitations and remains unproved.

Atrial fibrillation in patients with heart failure with preserved ejection fraction

PURPOSE OF REVIEW

To review the shared pathology of atrial fibrillation and heart failure with preserved ejection fraction (HFpEF) and the prognostic, diagnostic, and treatment challenges incurred by the co-occurrence of these increasingly prevalent diseases.

RECENT FINDINGS

Multiple risk factors and mechanisms have been proposed as potentially linking atrial fibrillation and HFpEF, with systemic inflammation more recently being invoked. Nonvitamin K oral anticoagulants, left atrial appendage occlusion devices, and catheter ablation have emerged as alternative treatment options. Other novel pharmacological agents, such as neprilysin inhibitors, need to be studied further in this patient population.

SUMMARY

Atrial fibrillation and HFpEF commonly co-occur because of their shared risk factors and pathophysiology and incur increased morbidity and mortality relative to either condition alone. Although the presence of both diseases can often make each diagnosis difficult, it is important to do so early in the disease course as there are now a variety of treatment options aimed at improving symptoms and quality of life, slowing disease progression, and improving prognosis. However, more research needs to be performed on the role of catheter ablation in this population. Novel pharmacologic and procedural treatment options appear promising and may further improve the treatment options available to this growing population.

Associations of cardiovascular biomarkers and plasma albumin with exceptional survival to the highest ages

Supercentenarians (those aged ≥110 years) are approaching the current human longevity limit by preventing or surviving major illness. Identifying specific biomarkers conducive to exceptional survival might provide insights into counter-regulatory mechanisms against aging-related disease. Here, we report associations between cardiovascular disease-related biomarkers and survival to the highest ages using a unique dataset of 1,427 oldest individuals from three longitudinal cohort studies, including 36 supercentenarians, 572 semi-supercentenarians (105–109 years), 288 centenarians (100–104 years), and 531 very old people (85–99 years). During follow-up, 1,000 participants (70.1%) died. Overall, N-terminal pro-B-type natriuretic peptide (NT-proBNP), interleukin-6, cystatin C and cholinesterase are associated with all-cause mortality independent of traditional cardiovascular risk factors and plasma albumin. Of these, low NT-proBNP levels are statistically associated with a survival advantage to supercentenarian age. Only low albumin is associated with high mortality across age groups. These findings expand our knowledge on the biology of human longevity.

Supercentenarians are approaching the current longevity limit by avoiding or surviving major illness, thus identifying biomarkers for exceptional survival might provide insights into the protection against disease of aging. Here, the authors show low NT-proBNP and high albumin in plasma are the biological correlates of survival to the highest ages.

Age-specific differences in non-cardiac comorbidities among elderly patients hospitalized with heart failure: a special focus on young-old, old-old, and oldest-old

Supplemental Digital Content is available in the text

Background

Despite the growing epidemic of heart failure (HF), there is limited data available to systematically compare non-cardiac comorbidities in the young-old, old-old, and oldest-old patients hospitalized for HF. The precise differences will add valuable information for better management of HF in elderly patients.

Methods

A total of 1053 patients aged 65 years or older hospitalized with HF were included in this study. Patients were compared among three age groups: (1) young-old: 65 to 74 years, (2) old-old: 75 to 84 years, and (3) oldest-old: ≥85 years. Clinical details of presentation, comorbidities, and prescribed medications were recorded.

Results

The mean age was 76.7 years and 12.7% were 85 years or older. Most elderly patients with HF (97.5%) had at least one of the non-cardiac comorbidities. The patterns of common non-cardiac comorbidities were different between the young-old and oldest-old group. The three most common non-cardiac comorbidities were anemia (53.6%), hyperlipidemia (45.9%), and diabetes (42.4%) in the young-old group, while anemia (73.1%), infection (58.2%), and chronic kidney disease (44.0%) in the oldest-old group. Polypharmacy was observed in 93.0% elderly patients with HF. Additionally, 29.2% patients were diagnosed with infection, and 67.0% patients were prescribed antibiotics. However, 60.4% patients were diagnosed with anemia with only 8.9% of them receiving iron repletion.

Conclusions

Non-cardiac comorbidities are nearly universal in three groups but obviously differ by age, and inappropriate medications are very common in elderly patients with HF. Further treatment strategies should be focused on providing optimal medications for age-specific non-cardiac conditions.

Clinical characteristics and long-term prognosis of ischemic and non-ischemic cardiomyopathy

Objectives

The different etiology of HF has different prognostic risk factors. Prognosis assessment of ICM and NICM has important clinical value. This study is aimed to explore the predicting factors for ICM and NICM.

Methods

1082 HFrEF patients were retrospectively enrolled from Jan. 01, 2016 to Dec. 31, 2017. On Jan. 31, 2019, 873 patients were enrolled for analysis excluding incomplete, unfollowed, and unexplained data. The patients were divided into ischemic and non-ischemic group. The differences in clinical characteristics and long-term prognosis between the two groups were analyzed, and multivariate Cox analysis was used to predict the respective all-cause mortality, SCD and rehospitalization of CHF.

Results

873 patients aged 64(53,73) were divided into two groups: ICM (403, 46.16%) and NICM. At the end, 203 died (111 in ICM, 54.68%), of whom 87 had SCD (53 in ICM, 60.92%) and 269 had rehospitalization for HF(134 in ICM, 49.81%). Independent risk factors affecting all-cause mortality in ICM: DM, previous hospitalization of HF, age, eGFR, LVEF; for SCD: PVB, eGFR, Hb, revascularization; for readmission of HF: low T3 syndrome, PVB, DM, previous hospitalization of HF, eGFR. Otherwise; factors affecting all-cause mortality in NICM: NYHA III-IV, paroxysmal AF/AFL, previous hospitalization of HF, β-blocker; for SCD: low T3 syndrome, PVB, nitrates, sodium, β-blocker; for rehospitalization of HF: paroxysmal AF/AFL, previous admission of HF, LVEF.

Conclusions

Both all-cause mortality and SCD in ICM is higher than that in NICM. Different etiologies of CHF have different risk factors affecting the prognosis.

Left ventricular contractile performance and heart failure in patients with left ventricular ejection fraction more than 40

Heart failure (HF) with mid-range left ventricular ejection fraction (LVEF) (HFmrEF) is considered a new category of HF and LVEF < 50%, which is the upper threshold of LVEF for HFmrEF, is thought to represent a mild decrease in LV contractile performance. We aimed to consider an LVEF threshold value to be taken as a surrogate for impairment of LV contractile performance, resulting in new-onset HF. We enrolled 398 patients with LVEF ≥ 40% that underwent cardiac catheterization. Using the LV pressure recording with a catheter-tipped micromanometer, we calculated the inertia force of late systolic aortic flow (IFLSAF), which was sensitive to the slight impairment in LV contractile performance. We evaluated the utility of the IFLSAF for predicting future cardiovascular death or hospitalization for HF. We performed a receiver operating characteristic (ROC) curve analysis to determine the best LVEF threshold value for distinguishing whether the LV maintained the IFLSAF. A multivariate Cox proportional-hazards model revealed that the loss of IFLSAF was significantly associated with the future adverse events (HR: 7.798, 95%CI 2.174–27.969, p = 0.002). According to the ROC curve analysis, an LVEF ≥ 58% indicated that the LV could maintain the IFLSAF. We concluded that the loss of IFLSAF, which could reflect even slight impairment in LV contractile performance, was a reliable indicator for new-onset HF in patients with LVEF ≥ 40%. LVEF ≥ 58% could be taken as a surrogate for the IFLSAF maintenance; this threshold could be useful for risk stratification of new-onset HF in patients with preserved LVEF.

Changes in Myocardial Microstructure and Mechanics With Progressive Left Ventricular Pressure Overload

This study assessed the regional changes in myocardial geometry, microstructure, mechanical behavior, and properties that occur in response to progressive left ventricular pressure overload (LVPO) in a large animal model. Using an index of local biomechanical function at early onset of LVPO allowed for prediction of the magnitude of left ventricular chamber stiffness (Kc) and left atrial area at LVPO late timepoints. Our study found that LV myocardial collagen content alone was insufficient to identify mechanisms for LV myocardial stiffness with progression to heart failure with preserved ejection fraction (HFpEF). Serial assessment of regional biomechanical function might hold value in monitoring the natural history and progression of HFpEF, which would allow evaluation of novel therapeutic approaches.

A novel nomogram to predict all-cause readmission or death risk in Chinese elderly patients with heart failure

Aims

Elderly patients with heart failure (HF) are associated with frequent all‐cause readmission or death. The present study sought to develop an accurate and easy‐to‐use model to predict all‐cause readmission or death risk in Chinese elderly patients with HF.

Methods and results

This was a prospective cohort study in patients with HF aged 65 or older. Demographic, co‐morbidity, laboratory, and medication data were collected. A Cox regression model was used to identify factors for the prediction of readmission or death at 30 days and 1 year. A nomogram was developed with bootstrap validation. Of the included 854 patients, the cumulative all‐cause readmission and mortality rates were 10.5% and 11.6% at 30 days and 34.9% and 19.7% at 1 year, respectively. The independent risk factors associated with both 30 day and 1 year readmission or death were older age, stroke, diastolic blood pressure < 60 mmHg, body mass index ≤ 18.5 kg/m², lower estimated glomerular filtration rate, and BNP > 400 pg/mL (all P < 0.05). Anaemia, abnormal neutrophils, and admission without angiotensin‐converting enzyme inhibitors/angiotensin receptor blockers were the specific independent risk factors of 30 day all‐cause readmission or death (all P < 0.05), whereas serum sodium ≤ 140 mmol/L and admission without beta‐blockers were the specific independent risk factors of 1 year all‐cause readmission or death (all P < 0.05). The C‐index of the 30 day and 1 year diagnosis prediction model was 0.778 [95% confidence interval (CI) 0.693–0.862] and 0.738 (95% CI 0.640–0.836), respectively.

Conclusions

We developed accurate and easy‐to‐use nomograms to predict all‐cause readmission or death in Chinese elderly patients with HF. The nomograms will assist in reducing the all‐cause readmission and mortality rates.

Effects of the dual sodium-glucose linked transporter inhibitor, licogliflozin vs placebo or empagliflozin in patients with type 2 diabetes and heart failure

Aims

Explore the efficacy, safety and tolerability of the dual sodium–glucose cotransporter (SGLT) 1 and 2 inhibitor, licogliflozin in patients with type‐2 diabetes mellitus (T2DM) and heart failure.

Methods

This multicentre, parallel‐group phase IIA study randomized 125 patients with T2DM and heart failure (New York Heart Association II–IV; plasma N‐terminal pro b‐type natriuretic peptide [NT‐proBNP] >300 pg/mL) to licogliflozin (2.5 mg, 10 mg, 50 mg) taken at bedtime, empagliflozin (25 mg) or placebo (44 patients completed the study). The primary endpoint was change from baseline in NT‐proBNP after 12 weeks. Secondary endpoints included change from baseline in glycated haemoglobin, fasting plasma glucose, weight, blood pressure, fasting lipid profile, high‐sensitivity c‐reactive protein, and safety and tolerability.

Results

Licogliflozin 10 mg for 12 weeks significantly reduced NT‐proBNP vs placebo (Geometric mean ratio 0.56 [95% confidence interval: 0.33, 0.95], P = .033). A trend was observed with 50 mg licogliflozin (0.64 [95% confidence interval: 0.40, 1.03], P = .064), with no difference between licogliflozin and empagliflozin. The largest numerical decreases in glycated haemoglobin were with licogliflozin 50 mg (−0.58 ± 0.34%) and empagliflozin (−0.44 ± 1.18%) vs placebo (−0.04 ± 0.91%). The reduction in body weight was similar with licogliflozin 50 mg (−2.15 ± 2.40 kg) and empagliflozin (−2.25 ± 1.89 kg). A numerical reduction in systolic blood pressure was seen with licogliflozin 50 mg (−9.54 ± 16.88 mmHg) and empagliflozin (−6.98 ± 15.03 mmHg) vs placebo (−2.85 ± 11.97 mmHg). Adverse events (AEs) were mild, including hypotension (6.5%), hypoglycaemia (8.1%) and inadequate diabetes control (1.6%). The incidence of diarrhoea (4.9%) was lower than previously reported.

Conclusion

The reduction in NT‐proBNP with licogliflozin suggests a potential benefit of SGLT1 and 2 inhibition in patients with T2DM and heart failure.