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

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

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

The Degree of the Predischarge Pulmonary Congestion in Patients Hospitalized for Worsening Heart Failure Predicts Readmission and Mortality

BACKGROUND

Prediction of readmission and death after hospitalization for heart failure (HF) is an unmet need.

AIM

We evaluated the ability of clinical parameters, NT-proBNP level and noninvasive lung impedance (LI), to predict time to readmission (TTR) and time to death (TTD).

METHODS AND RESULTS

The present study is a post hoc analysis of the IMPEDANCE-HF extended trial comprising 290 patients with LVEF ≤45% and New York Heart Association functional class II-IV, randomized 1:1 to LI-guided or conventional therapy. Of all patients, 206 were admitted 766 times for HF during a follow-up of 57 ± 39 months. The normal LI (NLI), representing the "dry" lung status, was calculated for each patient at study entry. The current degree of pulmonary congestion (PC) compared with its dry status was represented by ΔLIR = ([measured LI/NLI] - 1) × 100%. Twenty-six parameters recorded during HF admission were used to predict TTR and TTD. To determine the parameter which mainly impacted TTR and TTD, variables were standardized, and effect size (ES) was calculated. Multivariate analysis by the Andersen-Gill model demonstrated that ΔLIRadmission (ES = 0.72), ΔLIRdischarge (ES = -3.14), group assignment (ES = 0.2), maximal troponin during HF admission (ES = 0.19), LVEF related to admission (ES = -0.22) and arterial hypertension (ES = 0.12) are independent predictors of TTR (p < 0.01, χ2 = 1,206). Analysis of ES showed that residual PC assessed by ∆LIRdischarge was the most prominent predictor of TTR. One percent improvement in predischarge PC, assessed by ∆LIRdischarge, was associated with a likelihood of TTR increase by 14% (hazard ratio [HR] 1.14, 95% confidence interval [CI] 1.13-1.15, p < 0.01) and TTD increase by 8% (HR 1.08, 95% CI 1.07-1.09, p < 0.01).

CONCLUSION

The degree of predischarge PC assessed by ∆LIR is the most dominant predictor of TTR and TTD.

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.

Mortality risk in dilated cardiomyopathy: the accuracy of heart failure prognostic models and dilated cardiomyopathy-tailored prognostic model

Aims

The aims of this paper were to investigate the analytical performance of the nine prognostic scales commonly used in heart failure (HF), in patients with dilated cardiomyopathy (DCM), and to develop a unique prognostic model tailored to DCM patients.

Methods and results

The hospital and outpatient records of 406 DCM patients were retrospectively analysed. The information on patient status was gathered after 48.2 ± 32.0 months. Tests were carried out to ascertain the prognostic accuracy in DCM using some of the most frequently applied HF prognostic scales (Barcelona Bio‐Heart Failure, Candesartan in Heart Failure‐Assessment of Reduction in Mortality and Morbidity, Studio della Streptochinasi nell'Infarto Miocardico‐Heart Failure, Eplerenone in Mild Patients Hospitalization and Survival Study in Heart Failure, Meta‐Analysis Global Group in Chronic Heart Failure, MUerte Subita en Insuficiencia Cardiaca, Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure, Seattle Heart Failure Model) and one dedicated to DCM, that of Miura et al. At follow‐up, 70 DCM patients (17.2%) died. Most analysed scores substantially overestimated the mortality risk, especially in survivors. The prognostic accuracy of the scales were suboptimal, varying between 60% and 80%, with the best performance from Barcelona Bio‐Heart Failure and Seattle Heart Failure Model for 1–5 year mortality [areas under the receiver operating curve 0.792–0.890 (95% confidence interval 0.725–0.918) and 0.764–0.808 (95% confidence interval 0.682–0.934), respectively].Based on our accumulated data, a self‐developed DCM prognostic model was constructed. The model consists of age, gender, body mass index, symptoms duration, New York Heart Association class, diabetes mellitus, prior stroke, abnormal liver function, dyslipidaemia, left bundle branch block, left ventricle end‐diastolic diameter, ejection fraction, N terminal pro brain natriuretic peptide, haemoglobin, estimated glomerular filtration rate, and pharmacological and resynchronisation therapy. This newly created prognostic model outperformed the analysed HF scales.

Conclusions

An analysis of various HF prognostic models found them to be suboptimal for DCM patients. A self‐developed DCM prognostic model showed improved performance over the nine other models studied. However, further validation of the prognostic model in different DCM populations is required.

Heart Failure With Reduced Ejection Fraction: A Review

IMPORTANCE

Worldwide, the burden of heart failure has increased to an estimated 23 million people, and approximately 50% of cases are HF with reduced ejection fraction (HFrEF).

OBSERVATIONS

Heart failure is a clinical syndrome characterized by dyspnea or exertional limitation due to impairment of ventricular filling or ejection of blood or both. HFrEF occurs when the left ventricular ejection fraction (LVEF) is 40% or less and is accompanied by progressive left ventricular dilatation and adverse cardiac remodeling. Assessment for heart failure begins with obtaining a medical history and physical examination. Also central to diagnosis are elevated natriuretic peptides above age- and context-specific thresholds and identification of left ventricular systolic dysfunction with LVEF of 40% or less as measured by echocardiography. Treatment strategies include the use of diuretics to relieve symptoms and application of an expanding armamentarium of disease-modifying drug and device therapies. Unless there are specific contraindications, patients with HFrEF should be treated with a β-blocker and one of an angiotensin receptor-neprilysin inhibitor, angiotensin-converting enzyme inhibitor, or angiotensin receptor blocker as foundational therapy, with addition of a mineralocorticoid receptor antagonist in patients with persistent symptoms. Ivabradine and hydralazine/isosorbide dinitrate also have a role in the care of certain patients with HFrEF. More recently, sodium-glucose cotransporter 2 (SGLT2) inhibitors have further improved disease outcomes, significantly reducing cardiovascular and all-cause mortality irrespective of diabetes status, and vericiguat, a soluble guanylate cyclase stimulator, reduces heart failure hospitalization in high-risk patients with HFrEF. Device therapies may be beneficial in specific subpopulations, such as cardiac resynchronization therapy in patients with interventricular dyssynchrony, transcatheter mitral valve repair in patients with severe secondary mitral regurgitation, and implantable cardiac defibrillators in patients with more severe left ventricular dysfunction particularly of ischemic etiology.

CONCLUSIONS AND RELEVANCE

HFrEF is a major public health concern with substantial morbidity and mortality. The management of HFrEF has seen significant scientific breakthrough in recent decades, and the ability to alter the natural history of the disease has never been better. Recent developments include SGLT2 inhibitors, vericiguat, and transcatheter mitral valve repair, all of which incrementally improve prognosis beyond foundational neurohormonal therapies. Disease morbidity and mortality remain high, with a 5-year survival rate of 25% after hospitalization for HFrEF.

Liver function and prognosis, and influence of sacubitril/valsartan in patients with heart failure with reduced ejection fraction

AIMS

The prevalence of liver function abnormalities is common in patients with heart failure (HF) with reduced ejection fraction (HFrEF). We assessed the impact of liver function on prognosis and the effect of sacubitril/valsartan on measures of liver function in patients with HFrEF.

METHODS AND RESULTS

The PARADIGM-HF trial was a randomized, double-blind, active treatment-controlled trial. We included 8232 HFrEF patients with available measures of liver function, including transaminases, alkaline phosphatase (ALP) and bilirubin; the primary endpoint was a composite of HF hospitalization and cardiovascular (CV) death. At screening, 11.6% of study patients had total bilirubin above the upper limit of normal (20.5 μmol/L) and 9.2% had ALP above the upper limit of normal (123 IU/L). Although ALP and albumin were associated with an increased risk of outcomes, among conventional test of liver function, total bilirubin was the strongest predictor for the primary endpoint [hazard ratio (HR) 1.10; 95% confidence interval (CI) 1.04-1.15; P < 0.001], HF hospitalization (HR 1.14; 95% CI 1.07-1.22; P < 0.001); CV death (HR 1.07; 95% CI 1.00-1.14; P = 0.040), and all-cause death (HR 1.08; 95% CI 1.02-1.14; P = 0.009). All conventional measures of liver function were significantly improved in the sacubitril/valsartan group compared with the enalapril group after randomization (between-group reduction: total bilirubin 2.4%, 95% CI 0.7-4.2%, P = 0.007; aspartate aminotransferase 7.9%, 95% CI 6.7-9.0%, P < 0.001; alanine aminotransferase 7.7%; 95% CI 6.2-9.3%, P < 0.001; ALP 5.4%, 95% CI 4.4-6.4%, P < 0.001).

CONCLUSION

Total bilirubin was a significant and independent predictor of CV death or HF hospitalization and all-cause mortality in patients with HFrEF enrolled in PARADIGM-HF. Sacubitril/valsartan improved measures of liver function compared with enalapril.