Usefulness of peak exercise oxygen consumption and the heart failure survival score to predict survival in patients >65 years of age with heart failure

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.

Heart failure with mid-range or mildly reduced ejection fraction

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

Global Longitudinal Strain Predicts Poor Functional Capacity in Patients with Systolic Heart Failure

Background

Left ventricular global longitudinal strain value (GLS) can predict functional capacity in patients with preserved left ventricular ejection fraction (LVEF) heart failure (HF) and to assess prognosis in reduced LVEF HF.

Objetive

Correlate GLS with parameters of Cardiopulmonary Exercise Test (CPET) and to assess if they could predict systolic HF patients that are more appropriated to be referred to heart transplantation according to CPET criteria.

Methods

Systolic HF patients with LVEF < 45%, NYHA functional class II and III, underwent prospectively CPET and echocardiography with strain analysis. LVEF and GLS were correlated with the following CPET variables: maxVO₂, VE/VCO₂ slope, heart rate reduction during the first minute of recovery (HRR) and time needed to reduce maxVO₂ in 50% after physical exercise (T_1/2VO₂). ROC curve analysis of GLS to predict VO₂ < 14 mL/kg/min and VE/VCO₂ slope > 35 (heart transplantation’s criteria) was performed.

Results

Twenty six patients were selected (age, 47 ± 12 years, 58% men, mean LVEF = 28 ± 8%). LVEF correlated only with maxVO₂ and T_1/2VO₂. GLS correlated to all CPET variables (maxVO₂: r = 0.671, p = 0.001; VE/VCO₂ slope: r = -0.513, p = 0.007; HRR: r = 0.466, p = 0.016, and T_1/2VO₂: r = -0.696, p = 0.001). GLS area under the ROC curve to predict heart transplantation’s criteria was 0.88 (sensitivity 75%, specificity 83%) for a cut-off value of -5.7%, p = 0.03.

Conclusion

GLS was significantly associated with all functional CPET parameters. It could classify HF patients according to the functional capacity and may stratify which patients have a poor prognosis and therefore to deserve more differentiated treatment, such as heart transplantation.

An Appraisal of Biomarker-Based Risk-Scoring Models in Chronic Heart Failure: Which One Is Best?

PURPOSE OF REVIEW

While prediction models incorporating biomarkers are used in heart failure, these have shown wide-ranging discrimination and calibration. This review will discuss externally validated biomarker-based risk models in chronic heart failure patients assessing their quality and relevance to clinical practice.

RECENT FINDINGS

Biomarkers may help in determining prognosis in chronic heart failure patients as they reflect early pathologic processes, even before symptoms or worsening disease. We present the characteristics and describe the performance of 10 externally validated prediction models including at least one biomarker among their predictive factors. Very few models report adequate discrimination and calibration. Some studies evaluated the additional predictive value of adding a biomarker to a model. However, these have not been routinely assessed in subsequent validation studies. New and existing prediction models should include biomarkers, which improve model performance. Ongoing research is needed to assess the performance of models in contemporary patients.

Critical Appraisal of Multivariable Prognostic Scores in Heart Failure: Development, Validation and Clinical Utility

Optimal management of heart failure requires accurate risk assessment. Many prognostic risk models have been proposed for patient with chronic and acute heart failure. Methodological critical issues are the data source, the outcome of interest, the choice of variables entering the model, the validation of the model in external population. Up to now, the proposed risk models can be a useful tool to help physician in the clinical decision-making. The availability of big data and of new methods of analysis may lead to developing new models in the future.

Predicting Risk in Patients Hospitalized for Acute Decompensated Heart Failure and Preserved Ejection Fraction: The Atherosclerosis Risk in Communities Study Heart Failure Community Surveillance

BACKGROUND

Risk-prediction models specifically for hospitalized heart failure with preserved ejection fraction are lacking.

METHODS AND RESULTS

We analyzed data from the ARIC (Atherosclerosis Risk in Communities) Study Heart Failure Community Surveillance to create and validate a risk score predicting mortality in patients ≥55 years of age admitted with acute decompensated heart failure with preserved ejection fraction (ejection fraction ≥50%). A modified version of the risk-prediction model for acute heart failure developed from patients in the EFFECT (Enhanced Feedback for Effective Cardiac Treatment) study was used as a composite predictor of 28-day and 1-year mortalities and evaluated together with other potential predictors in a stepwise logistic regression. The derivation sample consisted of 1852 hospitalizations from 2005 to 2011 (mean age, 77 years; 65% women; 74% white). Risk scores were created from the identified predictors and validated in hospitalizations from 2012 to 2013 (n=821). Mortality in the derivation and validation sample was 11% and 8% at 28 days and 34% and 31% at 1 year. The modified EFFECT score, including age, systolic blood pressure, blood urea nitrogen, sodium, cerebrovascular disease, chronic obstructive pulmonary disease, and hemoglobin, was a powerful predictor of mortality. Another important predictor for both 28-day and 1-year mortalities was hypoxia. The risk scores were well calibrated and had good discrimination in the derivation sample (area under the curve: 0.76 for 28-day and 0.72 for 1-year mortalities) and validation sample (area under the curve: 0.73 and 0.71, respectively).

CONCLUSIONS

Mortality after acute decompensation in patients with heart failure with preserved ejection fraction is high, with one third of patients dying within a year. A prediction tool may allow for greater discrimination of the highest risk patients.

CLINICAL TRIAL REGISTRATION

URL: https://www.clinicaltrials.gov. Unique identifier: NCT00005131.

Evaluation of a Heart Transplant Candidate

PURPOSE OF REVIEW

Heart transplantation is the best option for irreversible and critically advanced heart failure. However, limited donor pool, the risk of rejection, infection, and right ventricular dysfunction in short-term post-transplant period, as well as, the development of coronary allograft vasculopathy and malignancy in the long-term post-transplant period limits the utility of heart transplantation for all comers with advanced heart failure. Therefore, selection of appropriate candidates is very important for the best short and long-term prognosis. In this article, we discuss the principles of selection of candidates and compare to the recently updated International Society for Heart and Lung Transplantation (ISHLT) listing criteria with the goal of updating current clinical practice.

RECENT FINDINGS

We found that while most of the recommendations in the new listing criteria are continuous with the previous criteria, updated recommendations are made on the risk stratification models in choosing transplantation candidates. Recommendation on hepatic dysfunction is not directly included in the updated ISHLT listing criteria; however, adoption of the Model for End-stage Liver Disease (MELD) score and modified MELD scores in the evaluation of risk are suggested in recent studies. In conclusion, evaluation of patient selection for heart transplantation should be comprehensive and individualized with respect to indications and the risk of comorbidities of candidates. With the advancement of mechanical circulatory support (MCS), the selection of heart transplantation candidate is continuously evolving and widened. MCS as bridge to candidacy should be considered when the candidate has potentially reversible risk factors for transplantation.

Skeletal Muscle Changes in Chronic Cardiac Disease and Failure

Peak exercise performance in healthy man is limited not only by pulmonary or skeletal muscle function but also by cardiac function. Thus, abnormalities in cardiac function will have a major impact on exercise performance. Many cardiac diseases affect exercise performance and indeed for some cardiac conditions such as atherosclerotic heart disease, exercise testing is frequently used not only to measure functional capacity but also to make a diagnosis of heart disease, evaluate the efficacy of treatment, and predict prognosis. Early in the course of cardiac diseases, exercise performance will be minimally affected but with disease progression impairment in exercise capacity will become apparent. Ejection fraction, that is, the percent of blood volume ejected with each cardiac cycle is often used as a measure of cardiac performance but frequently there is a dissociation between the ejection fraction and exercise capacity in patients with heart disease. How abnormalities in cardiac function impacts the muscles, vasculature, and lungs to impact exercise performance will here be reviewed. The focus of this work will be on patients with systolic heart failure as the incidence and prevalence of heart failure is reaching epidemic proportions and heart failure is the end result of many other chronic cardiac diseases. The prognostic role of exercise and benefits of exercise training will also be discussed.

Gender aspects in clinical presentation and prognostication of chronic heart failure according to NT-proBNP and the Heart Failure Survival Score

AIMS

We performed a prospective multi-center study to assess gender-specific differences in the predictive value of the measured level of NT-proBNP and the calculated Heart Failure Survival Score (HFSS).

METHODS

Baseline characteristics and follow-up data up to 5 years from 2,019 men and 530 women diagnosed with chronic heart failure (CHF) due to ischemic heart disease or dilated cardiomyopathy were prospectively compared. Death from any cause constituted the endpoint of the study. NT-proBNP was measured and HFSS calculated according to standard methods. Survival of men and women according to level of NT-proBNP and HFSS was analyzed in logistic regression models.

RESULTS

Median NT-proBNP level in men was 1,394 ng/l (IQR 516-3,406 ng/l) and 1,168 ng/l (IQR 444-2,830 ng/l) in women (p = n.s.). Median HFSS value was 8.4 (IQR 7.7-9.1) and 8.5 (8.0-9.1) in men and women, respectively. NT-proBNP levels and HFSS score correlated well with survival rates in both genders (p for interaction = 0.22 for NT-proBNP and 0.93 for HFSS). The all-cause death rates were similar in men and women.

CONCLUSION

Despite a number of gender-specific differences in CHF and the general predominance of men measured levels of NT-proBNP and HFSS score can be utilized for risk stratification with similar informative value in men and women.

Utility of the Seattle Heart Failure Model in patients with cardiac resynchronization therapy and implantable cardioverter defibrillator referred for heart transplantation

BACKGROUND

The Seattle Heart Failure Model (SHFM) predicts survival in heart failure but may underestimate risk in severe heart failure, and the performance has not been evaluated explicitly in patients with cardiac resynchronization therapy (CRT) and/or implantable cardioverter defibrillator (ICD) referred for heart transplantation. We aimed to assess the utility of the SHFM by validation in patients with CRT and/or ICD referred for heart transplantation.

METHODS

We assessed the SHFM performance in 382 patients with CRT and/or ICD referred for heart transplantation. Outcome was survival free from urgent transplantation or left ventricular assist device. Model discrimination and calibration were assessed graphically and by formal tests.

RESULTS

During a mean follow-up of 2.3 years, 195 events occurred. One-, 2-, and 3-year observed event-free survival was 77%, 62%, and 52%, and the observed to predicted event-free survival ratio was 0.89, 0.80, and 0.76. Calibration plots demonstrated results deviating from the ideal calibration line at 1, 2, and 3 years. The SHFM score adequately assigned patients in discrete risk strata, according to Kaplan-Meier estimated survival. Time-dependent receiver operating characteristic curve analyses demonstrated good discrimination overall, which was slightly better for 1-year (area under the curve [AUC] 0.774) compared with 2-year (AUC 0.742) and 3-year (AUC 0.728) event-free survival.

CONCLUSIONS

The SHFM has good discrimination but underestimates risk of adverse outcomes in patients with CRT and/or ICD referred for heart transplantation. The SHFM may be used to assess relative risk and changes over time, but when assessing absolute percentage of event-free survival, the overestimation of event-free survival should be accounted for.

A meta-analysis of the prognostic significance of cardiopulmonary exercise testing in patients with heart failure

The objective of the study is to assess the role of cardiopulmonary exercise testing (CPX) variables, including peak oxygen consumption (VO(2)), which is the most recognized CPX variable, the minute ventilation/carbon dioxide production (VE/VCO(2)) slope, the oxygen uptake efficiency slope (OUES), and exercise oscillatory ventilation (EOV) in a current meta-analysis investigating the prognostic value of a broader list of CPX-derived variables for major adverse cardiovascular events in patients with HF. A search for relevant CPX articles was performed using standard meta-analysis methods. Of the initial 890 articles found, 30 met our inclusion criteria and were included in the final analysis. The total subject populations included were as follows: peak VO(2) (7,319), VE/VCO(2) slope (5,044), EOV (1,617), and OUES (584). Peak VO(2), the VE/VCO(2) slope and EOV were all highly significant prognostic markers (diagnostic odds ratios ≥ 4.10). The OUES also demonstrated promise as a prognostic marker (diagnostic odds ratio = 8.08) but only in a limited number of studies (n = 2). No other independent variables (including age, ejection fraction, and beta-blockade) had a significant effect on the meta-analysis results for peak VO(2) and the VE/VCO(2) slope. CPX is an important component in the prognostic assessment of patients with HF. The results of this meta-analysis strongly confirm this and support a multivariate approach to the application of CPX in this patient population.

A case for assessment of oscillatory breathing during cardiopulmonary exercise test in risk stratification of elderly patients with chronic heart failure

The prognostic value of exercise oscillatory breathing (EOB) during cardiopulmonary test (CPX) has been described in young chronic heart failure (HF) patients. We assessed the prognostic role of EOB vs other clinical and ventilatory parameters in elderly HF patients performing a maximal CPX.

METHODS AND RESULTS

We prospectively followed-up 370 HF outpatients ≥ 65 years after a symptom limited CPX. We tested the predictive value of clinical and ventilatory parameters for all-cause mortality and a composite of all-cause mortality and HF hospitalizations. Median age was 74 years, 51% had ischemic heart disease, 25% NYHA class III; ejection fraction was 41% [34-50]. Peak oxygen consumption (PVO(2)) was 11.9 [9.9-14] mL/kg/min, the slope of the regression line relating ventilation to CO(2) output, (VE/VCO(2) slope) was 33.9 [29.8-39.2]. EOB was found in 58% of patients. At follow-up, 84 patients died and overall 158, using a time-to-first event approach, met the composite end-point. Independent predictors of all-cause mortality were CPX EOB and the ratio of VE/VCO(2) slope to peak VO(2), hemoglobin, creatinine and body mass index. The area under the ROC curve (AUC) of the Cox multivariable model was 0.80 (95% CI 0.73 to 0.87). Independent predictors of the composite end-point were EOB, VE/VCO(2) slope, hemoglobin and HF admissions in the previous year (Model AUC 0.75) (95% CI 0.69 to 0.81).

CONCLUSIONS

Among elderly HF patients, EOB prevalence is higher than middle-aged cohorts. EOB and the ratio of VE/VCO(2) slope to peak VO(2) resulted the strongest ventilatory predictor of all-cause mortality, independent of ventricular function.