Development and prospective validation of a clinical index to predict survival in ambulatory patients referred for cardiac transplant evaluation

Exercise and heart failure: an update

The present update is dedicated to the evolution of the interaction between heart failure (HF) and exercise and how the scientific community has handled it. Indeed, on the one hand, HF is a leading cause of morbidity and mortality with a stable prevalence from 1998 onward varying between 6.3% and 13.3%. On the other hand, exercise is seen as a diagnostic and prognostic tool as well as a therapeutic intervention in chronic HF. More precisely, the knowledge, the clinical application, and the research interest on the mutual interactions between exercise and HF have different phases in disease progression: Before HF onset (past): exercise provides protective benefit in preventing HF (primary prevention). With HF present: exercise improvement with training provides benefits in HF (secondary prevention). The prediction of future in HF patients: exercise impairment, as a leading characteristic of HF, is used as a prognostic factor.

Personalized survival predictions via Trees of Predictors: An application to cardiac transplantation

Background

Risk prediction is crucial in many areas of medical practice, such as cardiac transplantation, but existing clinical risk-scoring methods have suboptimal performance. We develop a novel risk prediction algorithm and test its performance on the database of all patients who were registered for cardiac transplantation in the United States during 1985-2015.

Methods and findings

We develop a new, interpretable, methodology (ToPs: Trees of Predictors) built on the principle that specific predictive (survival) models should be used for specific clusters within the patient population. ToPs discovers these specific clusters and the specific predictive model that performs best for each cluster. In comparison with existing clinical risk scoring methods and state-of-the-art machine learning methods, our method provides significant improvements in survival predictions, both post- and pre-cardiac transplantation. For instance: in terms of 3-month survival post-transplantation, our method achieves AUC of 0.660; the best clinical risk scoring method (RSS) achieves 0.587. In terms of 3-year survival/mortality predictions post-transplantation (in comparison to RSS), holding specificity at 80.0%, our algorithm correctly predicts survival for 2,442 (14.0%) more patients (of 17,441 who actually survived); holding sensitivity at 80.0%, our algorithm correctly predicts mortality for 694 (13.0%) more patients (of 5,339 who did not survive). ToPs achieves similar improvements for other time horizons and for predictions pre-transplantation. ToPs discovers the most relevant features (covariates), uses available features to best advantage, and can adapt to changes in clinical practice.

Conclusions

We show that, in comparison with existing clinical risk-scoring methods and other machine learning methods, ToPs significantly improves survival predictions both post- and pre-cardiac transplantation. ToPs provides a more accurate, personalized approach to survival prediction that can benefit patients, clinicians, and policymakers in making clinical decisions and setting clinical policy. Because survival prediction is widely used in clinical decision-making across diseases and clinical specialties, the implications of our methods are far-reaching.

Performance of existing risk scores around heart transplantation: validation study in a 4-year cohort

Several risk scores exist to help identify best candidate recipients for heart transplantation (HTx). This study describes the performance of five heart failure risk scores and two post-HTx mortality risk scores in a French single-centre cohort. All patients listed for HTx through a 4-year period were included. Waiting-list risk scores [Heart Failure Survival Score (HFSS), Seattle Heart Failure Model (SHFM), Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC), Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF) and Get With The Guidelines-Heart Failure (GWTG-HF)] and post-HTx scores Index for Mortality Prediction After Cardiac Transplantation (IMPACT and CARRS) were computed. Main outcomes were 1-year mortality on waiting list and after HTx. Performance was assessed using receiver operator characteristic (ROC), calibration and goodness-of-fit analyses. The cohort included 414 patients. Waiting-list mortality was 14.0%, and post-HTx mortality was 16.3% at 1-year follow-up. Heart failure risk scores had adequate discrimination regarding waiting-list mortality (ROC AUC for HFSS = 0.68, SHFM = 0.74, OPTIMIZE-HF = 0.72, MAGGIC = 0.70 and GWTG = 0.77; all P-values <0.05). On the contrary, post-HTx risk scores did not discriminate post-HTx mortality (AUC for IMPACT = 0.58, and CARRS = 0.48, both P-values >0.50). Subgroup analysis on patients undergoing HTx after ventricular assistance device (VAD) implantation (i.e. bridge-to-transplantation) (n = 36) showed an IMPACT AUC = 0.72 (P < 0.001). In this single-centre cohort, existing heart failure risk scores were adequate to predict waiting-list mortality. Post-HTx mortality risk scores were not, except in the VAD subgroup.

Defining Ambulatory Advanced Heart Failure: MedaMACS and Beyond

PURPOSE OF REVIEW

Extended survival with LVADs has generated interest in implantation for ambulatory patients with advanced heart failure (HF) prior to dependence on inotropes, though we remain limited in our ability to define and advance indications in this less sick advanced HF population.

RECENT FINDINGS

The MedaMACS and ROADMAP studies have informed prognosis and decision-making for ambulatory patients with advanced HF. Sicker INTERMACS profiles are consistently associated with high risk of death or rescue LVAD. Appropriately selected patients in profile 4 should be considered for LVADs based on their high mortality and poor quality of life. These studies also shed light on discordant perceptions of HF disease severity between patients and their physicians. For ambulatory patients with HF not at imminent risk of death, shared decision-making about LVAD requires measured and individualized consideration of risk and benefit beyond survival. Future studies, including the ongoing REVIVAL study, should provide additional prognostic information in this patient population and should aid patients, caregivers, and physicians as they contemplate complex decisions regarding LVAD therapy.

A Decision Support System for the Treatment of Patients with Ventricular Assist Device Support

Background: Heart failure (HF) is affecting millions of people every year and it is characterized by impaired ventricular performance, exercise intolerance and shortened life expectancy. Despite significant advancements in drug therapy, mortality of the disease remains excessively high, as heart transplant remains the gold standard treatment for end-stage HF when no contraindications subsist. Traditionally, implanted Ventricular Assist Devices (VADs) have been employed in order to provide circulatory support to patients who cannot survive the waiting time to transplantation, reducing the workload imposed on the heart. In many cases that process could recover its contractility performance.

Objectives: The SensorART platform focuses on the management and remote treatment of patients suffering from HF. It provides an inter-operable, extendable and VAD-independent solution, which incorporates various hardware and software components in a holistic approach, in order to improve the quality of the patients’ treatment and the workflow of the specialists. This paper focuses on the description and analysis of Specialist’s Decision Support System (SDSS), an innovative component of the SensorART platform.

Methods: The SDSS is a Web-based tool that assists specialists on designing the therapy plan for their patients before and after VAD implantation, analyzing patients’ data, extracting new knowledge, and making informative decisions.

Results: SDSS offers support to medical and VAD experts through the different phases of VAD therapy, incorporating several tools covering all related fields; Statistics, Association Rules, Monitoring, Treatment, Weaning, Speed and Suction Detection.

Conclusions: SDSS and its modules have been tested in a number of patients and the results are encouraging.

Current indications for transplantation: stratification of severe heart failure and shared decision-making

Heart failure (HF) is a complex clinical syndrome that results from structural or functional cardiovascular disorders causing a mismatch between demand and supply of oxygenated blood and consecutive failure of the body's organs. For those patients with stage D HF, advanced therapies, such as mechanical circulatory support (MCS) or heart transplantation (HTx), are potentially life-saving options. The role of risk stratification of patients with stage D HF in a value-based healthcare framework is to predict which subset might benefit from advanced HF (AdHF) therapies, to improve outcomes related to the individual patient including mortality, morbidity and patient experience as well as to optimize health care delivery system outcomes such as cost-effectiveness. Risk stratification and subsequent outcome prediction as well as therapeutic recommendation-making need to be based on the comparative survival benefit rationale. A robust model needs to (I) have the power to discriminate (i.e., to correctly risk stratify patients); (II) calibrate (i.e., to show agreement between the predicted and observed risk); (III) to be applicable to the general population; and (IV) provide good external validation. The Seattle Heart Failure Model (SHFM) and the Heart Failure Survival Score (HFSS) are two of the most widely utilized scores. However, outcomes for patients with HF are highly variable which make clinical predictions challenging. Despite our clinical expertise and current prediction tools, the best short- and long-term survival for the individual patient, particularly the sickest patient, is not easy to identify because among the most severely ill, elderly and frail patients, most preoperative prediction tools have the tendency to be imprecise in estimating risk. They should be used as a guide in a clinical encounter grounded in a culture of shared decision-making, with the expert healthcare professional team as consultants and the patient as an empowered decision-maker in a trustful safe therapeutic relationship.

Reviewing the use of ventricular assist devices in the elderly: where do we stand today?

INTRODUCTION

Implantation of left ventricular assist devices (LVADS) in older patients appears to be an attractive option in the wake of donor shortage and increasing incidence and prevalence of end stage heart failure. Since the inception of the artificial heart program half a century ago tremendous progress in research and development has led to utilization of more sophisticated devices. VADs have therefore emerged as a successful therapy for extending life with meaningful quality. Areas covered: This review will address the use of LVADS as a bridge to transplantation, destination therapy and comparison of LVAD therapy with alternate list heart transplantation in the elderly population. Expert commentary: Age >70 years is an important aspect when assessing LVAD risk, but other characteristics appear to be better predictors of LVAD survival. Elevated pre-operative creatinine, bilirubin and ischemic etiology predispose to a higher risk of mortality. Creatinine has been shown to be a very powerful predictor in post LVAD survival. Based on the existing literature, the authors suggest an algorithm which could be useful when evaluating patients for LVAD implantation.

Association between preoperative peripheral blood mononuclear cell gene expression profiles, early postoperative organ function recovery potential and long-term survival in advanced heart failure patients undergoing mechanical circulatory support

BACKGROUND

Multiorgan dysfunction syndrome contributes to adverse outcomes in advanced heart failure (AdHF) patients after mechanical circulatory support (MCS) implantation and is associated with aberrant leukocyte activity. We tested the hypothesis that preoperative peripheral blood mononuclear cell (PBMC) gene expression profiles (GEP) can predict early postoperative improvement or non-improvement in patients undergoing MCS implantation. We believe this information may be useful in developing prognostic biomarkers.

METHODS & DESIGN

We conducted a study with 29 patients undergoing MCS-surgery in a tertiary academic medical center from 2012 to 2014. PBMC samples were collected one day before surgery (day -1). Clinical data was collected on day -1 and day 8 postoperatively. Patients were classified by Sequential Organ Failure Assessment score and Model of End-stage Liver Disease Except INR score (measured eight days after surgery): Group I = improving (both scores improved from day -1 to day 8, n = 17) and Group II = not improving (either one or both scores did not improve from day -1 to day 8, n = 12). RNA-sequencing was performed on purified mRNA and analyzed using Next Generation Sequencing Strand. Differentially expressed genes (DEGs) were identified by Mann-Whitney test with Benjamini-Hochberg correction. Preoperative DEGs were used to construct a support vector machine algorithm to predict Group I vs. Group II membership.

RESULTS

Out of 28 MCS-surgery patients alive 8 days postoperatively, one-year survival was 88% in Group I and 27% in Group II. We identified 28 preoperative DEGs between Group I and II, with an average 93% prediction accuracy. Out of 105 DEGs identified preoperatively between year 1 survivors and non-survivors, 12 genes overlapped with the 28 predictive genes.

CONCLUSIONS

In AdHF patients following MCS implantation, preoperative PBMC-GEP predicts early changes in organ function scores and correlates with long-term outcomes. Therefore, gene expression lends itself to outcome prediction and warrants further studies in larger longitudinal cohorts.

Exercise testing in heart failure: a contemporary discussion in an era of novel diagnostic techniques and biomarkers

PURPOSE OF REVIEW

The purpose of this review is to highlight recent advances in the field of exercise testing for patients with heart failure.

RECENT FINDINGS

The importance of assessment of cardiorespiratory fitness (CRF) and exercise testing in heart failure is highlighted in the consensus recommendation of the American Heart Association. Contemporary studies have validated the independent and incremental strength of CRF metrics in patients with heart failure and coronary artery disease. The use of respiratory gas analysis and imaging or hemodynamics during physical exercise is feasible and results in high prognostic utility across the continuum of heart failure. Understanding how CRF metrics complement existing and novel biomarkers and risk scores is an emerging subject of scientific inquiry.

SUMMARY

In the current era of personalized medicine, integrating CRF, imaging and circulating biomarkers will allow us to further develop individualized strategies for improving outcome in patients with heart failure.

Development of prognostic tools in pulmonary arterial hypertension: Lessons from modern day registries

Pulmonary arterial hypertension (PAH) is characterised by increased pressure in the pulmonary arteries leading to right-sided ventricular failure, and death. Identification of factors that affect patient survival is important to improve patient management and outcomes. The first registry to evaluate survival and develop a prognostic model was the National Institutes of Health (NIH) registry in 1981. Importantly this prognostic model is based on data collected prior to availability of PAH-targeted therapies and does not reflect survival rates for treated patients. Since the 1980s, however, four modern registries of PAH now exist which compensate for the NIH equations shortcomings and include the French National registry, Pulmonary Hypertension Connection registry, the Mayo registry, and the Registry to Evaluate Early and Long-Term PAH Disease Management (REVEAL). The similarities and difference in these registries are highlighted in this review and although similar in many respects, the four registries vary in patient population, including the numbers of newly and previously diagnosed patients, as well as the era of observation, period of survival, and timing of assessment of potential predictive factors. Despite this, the predictive factors identified in each registry and described in detail within the body of this manuscript share surprising homology in that disease aetiology, patient gender and factors reflective of right heart failure are integral in depicting survival. Future modifications of modern prognostic equations should be an ongoing goal of the PAH community in order to provide increased accuracy with identification of novel risk factors and prediction of disease course.

Role of Depression and Social Isolation at Time of Waitlisting for Survival 8 Years After Heart Transplantation

Background

We evaluated depression and social isolation assessed at time of waitlisting as predictors of survival in heart transplant (HTx) recipients.

Methods and Results

Between 2005 and 2006, 318 adult HTx candidates were enrolled in the Waiting for a New Heart Study, and 164 received transplantation. Patients were followed until February 2013. Psychosocial characteristics were assessed by questionnaires. Eurotransplant provided medical data at waitlisting, transplantation dates, and donor characteristics; hospitals reported medical data at HTx and date of death after HTx. During a median follow‐up of 70 months (<1–93 months post‐HTx), 56 (38%) of 148 transplanted patients with complete data died. Depression scores were unrelated to social isolation, and neither correlated with disease severity. Higher depression scores increased the risk of dying (hazard ratio=1.07, 95% confidence interval, 1.01, 1.15, P=0.032), which was moderated by social isolation scores (significant interaction term; hazard ratio = 0.985, 95% confidence interval, 0.973, 0.998; P=0.022). These findings were maintained in multivariate models controlling for covariates (P values 0.020–0.039). Actuarial 1‐year/5‐year survival was best for patients with low depression who were not socially isolated at waitlisting (86% after 1 year, 79% after 5 years). Survival of those who were either depressed, or socially isolated or both, was lower, especially 5 years posttransplant (56%, 60%, and 62%, respectively).

Conclusions

Low depression in conjunction with social integration at time of waitlisting is related to enhanced chances for survival after HTx. Both factors should be considered for inclusion in standardized assessments and interventions for HTx candidates.

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.

A one-year mortality clinical prediction rule for patients with heart failure

AIMS

To create and validate a clinical prediction rule which is easy to manage, reproducible and that allows classifying patients admitted for heart failure according to their one-year mortality risk.

METHODS

A prospective cohort study carried out with 2565 consecutive patients admitted with heart failure in 13 hospitals in Spain. The derivation cohort was made up of 1283 patients and 1282 formed the validation cohort. In the derivation cohort, we carried out a multivariate logistic model to predict one-year mortality. The performance of the derived predictive risk score was externally validated in the validation cohort, and internally validated by K-fold cross-validation. The risk score was categorized into four risk levels.

RESULTS

The mean age was 77.2years, 49.7% were female and there were 611 (23.8%) deaths in the follow-up period. The variables included in the predictive model were: age≥75, systolic blood pressure<135, New York Heart Association class III-IV, heart valve disease, dementia, prior hospitalization, haemoglobin<13, sodium<136, urea≥86, length of stay≥14 and Physical dimension of Minnesota Living with Heart Failure questionnaire. The AUC for the risk score were 0.73 and 0.70 in the derivation and validation cohorts, respectively, and 0.73 in the K-fold cross-validation. The percentage of mortality ranged from 8.08% in the low-risk to 58.20% in the high-risk groups (p<0.0001; AUC, 0.72).

CONCLUSIONS

This model based on routinely available data, for admitted patients and with a follow-up at one year is a simple and easy-to-use tool for improving management of patients with heart failure.

Multiparametric prognostic scores in chronic heart failure with reduced ejection fraction: a long-term comparison

AIMS

Risk stratification in heart failure (HF) is crucial for clinical and therapeutic management. A multiparametric approach is the best method to stratify prognosis. In 2012, the Metabolic Exercise test data combined with Cardiac and Kidney Indexes (MECKI) score was proposed to assess the risk of cardiovascular mortality and urgent heart transplantation. The aim of the present study was to compare the prognostic accuracy of MECKI score to that of HF Survival Score (HFSS) and Seattle HF Model (SHFM) in a large, multicentre cohort of HF patients with reduced ejection fraction.

METHODS AND RESULTS

We collected data on 6112 HF patients and compared the prognostic accuracy of MECKI score, HFSS, and SHFM at 2- and 4-year follow-up for the combined endpoint of cardiovascular death, urgent cardiac transplantation, or ventricular assist device implantation. Patients were followed up for a median of 3.67 years, and 931 cardiovascular deaths, 160 urgent heart transplantations, and 12 ventricular assist device implantations were recorded. At 2-year follow-up, the prognostic accuracy of MECKI score was significantly superior [area under the curve (AUC) 0.781] to that of SHFM (AUC 0.739) and HFSS (AUC 0.723), and this relationship was also confirmed at 4 years (AUC 0.764, 0.725, and 0.720, respectively).

CONCLUSION

In this cohort, the prognostic accuracy of the MECKI score was superior to that of HFSS and SHFM at 2- and 4-year follow-up in HF patients in stable clinical condition. The MECKI score may be useful to improve resource allocation and patient outcome, but prospective evaluation is needed.

Prognostic value of selected echocardiographic, impedance cardiographic, and hemodynamic parameters determined during right heart catheterization in patients qualified for heart transplantation

The aim of the study was to verify prognostic value of selected echocardiographic (UKG), impedance cardiography (ICG), and right heart catheterization (RHC) parameters in systolic heart failure (HF). UKG, ICG, and RHC were performed in 46 patients with chronic HF with ejection fraction <35%. During a 1-year follow-up, composite endpoint (death or hospitalization due to HF exacerbation) was achieved by 23 (50.0%) patients. Analysis of receiver operating characteristic (ROC) curves identified UKG parameters: inferior vena cava diameter on inspiration (IVCinsp) >13 mm [area under curve (AUC), 0.791], right atrial (RA) >5.2 cm (AUC 0.710) and ventricular dimension (RVD) >3.5 cm (AUC 0.717), tricuspid annular plane systolic excursion (TAPSE) <17 mm (AUC 0.682), and its velocity (S'RV) <6.07 cm/s (AUC 0.716) as unfavorable prognostic factors. RHC parameters: low values of cardiac index (CI < 2.1 L/min; AUC 0.846) and high pulmonary capillary wedge pressure (PCWP > 24 mmHg; AUC 0.773) turned out to be the most accurate single predictors of worse outcome. Prognostic value of non-invasive parameters was improved due to the use of their composite measures: IVC% × TAPSE (<430%/mm; AUC 0.826), RVSP/TAPSE (>2.4 mmHg/mm; AUC 0.800), IVC% × SBP (>2097% mmHg; AUC 0.826), and RA × IVCinsp/S'RV (>11.8 cm s; AUC 0.839). In conclusion, composite measures based on non-invasive parameters, such as IVC%/TAPSE, RVSP/TAPSE and RA × IVCinsp/S'RV, may provide equally accurate prognosis as the invasive examination. PCWP and CI determined during RHC were the best individual predictors of the composite endpoint. In addition, echocardiographic parameters: RVD, RA, IVC, TAPSE, and S'RV are accurate predictors of the unfavorable outcome.

Cardiac Resynchronization Therapy in Older Adults with Heart Failure

Heart failure is a disease of poor prognosis marked by frequent hospitalizations, premature death, and impaired quality of life. Despite advances in medical therapy for patients with heart failure and reduced ejection fraction, mortality and hospitalizations with advanced disease are still increased and the quality of life continues to be poor in this population. The advent of cardiac resynchronization therapy has led to a significant improvement in both survival and symptom management in patients with heart failure and reduced ejection fraction. Its beneficial effects in the elderly population, however, are not well-defined.

Changing our Approach to Stage D Heart Failure

Despite the tremendous progress made in the management of heart failure (HF), many patients reach advanced stages. This paper aims to present a practical approach to the stage D HF patient who is no longer responding to optimal medical therapy. We discuss all available therapies for this patient population. We also offer some important caveats with regard to identification, risk stratification, evaluation and treatment including early patient referral to a center with an advanced HF program. Given the changing landscape of heart transplantation and an impending change in the allocation system, we also intend to engage a discussion on the need for a paradigm shift towards left ventricular assist device therapy in this population.

Sex Differences in Mortality Based on United Network for Organ Sharing Status While Awaiting Heart Transplantation

BACKGROUND

There are sex differences in mortality while awaiting heart transplantation, and the reason remains unclear.

METHODS AND RESULTS

We included all adults in the Scientific Registry of Transplant Recipients placed on the heart transplant active waitlist from 2004 to 2015. The primary end point was all-cause mortality. Multivariable Cox proportional hazards models were performed to evaluate survival by United Network for Organ Sharing (UNOS) status at the time of listing. Random survival forest was used to identify sex interactions for the competing risk of death and transplantation. There were 33 069 patients (25% women) awaiting heart transplantation. This cohort included 7681 UNOS status 1A (26% women), 13 027 UNOS status 1B (25% women), and 12 361 UNOS status 2 (26% women). During a median follow-up of 4.3 months, 1351 women and 4052 men died. After adjusting for >20 risk factors, female sex was associated with a significant risk of death among UNOS status 1A (adjusted hazard ratio, 1.14; 95% confidence interval, 1.01-1.29) and UNOS status 1B (adjusted hazard ratio, 1.17; 95% confidence interval, 1.05-1.30). In contrast, female sex was significantly protective for time to death among UNOS status 2 (adjusted hazard ratio, 0.85; 95% confidence interval, 0.76-0.95). Sex differences in probability of transplantation were present for every UNOS status, and >20 sex interactions were identified for mortality and transplantation.

CONCLUSIONS

When stratified by initial UNOS status, women had a higher mortality than men as UNOS status 1 and a lower mortality as UNOS status 2. With >20 sex interactions for mortality and transplantation, further evaluation is warranted to form a more equitable allocation system.

Comparative Analysis of Four Scores to Stratify Patients With Heart Failure and Reduced Ejection Fraction

There are several prognostic risk scores available for patients with heart failure with reduced ejection fraction (HFrEF) that can aid in the decision of listing candidates for heart transplant (HTx). A direct comparison between these scores has not been performed. Therefore, our objective was to evaluate the calibration and discriminative power of 4 contemporary HF scores. A retrospective analysis of 259 patients with HFrEF who underwent cardiopulmonary exercise test was conducted. The Heart Failure Survival Score (HFSS), Seattle Heart Failure Model (SHFM), Meta-analysis Global Group in Chronic Heart Failure (MAGGIC), and Metabolic Exercise Cardiac Kidney Index (MECKI) were compared. During the first year, 7 deaths occurred (6 cardiovascular) and 25 patients were submitted to HTx (8 urgent). Over a 2-year period, 14 deaths occurred (10 cardiovascular) and 34 patients received an HTx (8 urgent). Calibration analysis showed that SHFM and HFSS tended to underestimate event occurrence, whereas MAGGIC and MECKI tended to overestimate risk, especially in the highest risk subgroups. Interestingly, MECKI score at 1 year was well calibrated (expected similar to observed events). Overall, the MECKI score consistently showed better discrimination ability for all studied end points (areas under the curve between 0.8 and 0.9). In conclusion, along with HFSS and SHFM, the MECKI score can also be used to aid treatment decisions, such as HTx listing with the advantage of being very well calibrated at 1-year intervals, which might allow us to avoid the pitfalls of under/overestimation of risk.

Long-term management of end-stage heart failure

End-stage heart failure manifests as severe and often relentless symptoms that define the clinical syndrome of heart failure, namely congestion and hypoperfusion. These patients suffer from dyspnea, fatigue, abdominal discomfort, and ultimately cardiac cachexia. Renal and hepatic dysfunction frequently further complicates the process. Recurrent hospitalizations, cardiac arrhythmias, and intolerance to standard heart failure therapies are common as the disease progresses. Management focuses on controlling symptoms, correcting precipitants, avoiding triggers, and maximizing therapies with demonstrable survival benefit. Among appropriate candidates, advanced therapies such as orthotopic heart transplant (OHT) can significantly extend survival and improve the quality of life. Left ventricular assist devices have been used with increasing frequency as a bridge to OHT or as a destination therapy in appropriately selected candidates where they have a demonstrable mortality benefit over medical therapy. Importantly, a multidisciplinary patient-centered approach is crucial when considering these advanced therapies.

Access to Heart Transplantation: A Proper Analysis of the Competing Risks of Death and Transplantation Is Required to Optimize Graft Allocation

Supplemental digital content is available in the text.

Background

Heart allocation systems are usually urgency-based, offering grafts to candidates at high risk of waitlist mortality. In the context of a revision of the heart allocation rules, we determined observed predictors of 1-year waitlist mortality in France, considering the competing risk of transplantation, to determine which candidate subgroups are favored or disadvantaged by the current allocation system.

Methods

Patients registered on the French heart waitlist between 2010 and 2013 were included. Cox cause-specific hazards and Fine and Gray subdistribution hazards were used to determine candidate characteristics associated with waitlist mortality and access to transplantation.

Results

Of the 2053 candidates, 7 variables were associated with 1-year waitlist mortality by the Fine and Gray method including 4 candidate characteristics related to heart failure severity (hospitalization at listing, serum natriuretic peptide level, systolic pulmonary artery pressure, and glomerular filtration rate) and 3 characteristics not associated with heart failure severity but with lower access to transplantation (blood type, age, and body mass index). Observed waitlist mortality for candidates on mechanical circulatory support was like that of others.

Conclusions

The heart allocation system strongly modifies the risk of pretransplant mortality related to heart failure severity. An in-depth competing risk analysis is therefore a more appropriate method to evaluate graft allocation systems. This knowledge should help to prioritize candidates in the context of a limited donor pool.

Multistate Model to Predict Heart Failure Hospitalizations and All-Cause Mortality in Outpatients With Heart Failure With Reduced Ejection Fraction: Model Derivation and External Validation

BACKGROUND

Outpatients with heart failure (HF) who are at high risk for HF hospitalization and death may benefit from early identification. We sought to develop and externally validate a model to predict both HF hospitalization and mortality that accounts for the semicompeting nature of the 2 outcomes and captures the risk associated with the transition from the stable outpatient state to the post-HF hospitalization state.

METHODS AND RESULTS

A multistate model to predict HF hospitalization and all-cause mortality was derived using data (n=3834) from the HEAAL study (Heart Failure Endpoint evaluation of Angiotensin II Antagonist Losartan), a multinational randomized trial in symptomatic patients with reduced left ventricular ejection fraction. Twelve easily and reliably obtainable demographic and clinical predictors were prespecified for model inclusion. Model performance was assessed in the SCD-HeFT cohort (Sudden Cardiac Death in Heart Failure Trial; n=2521). At 1 year, the probability of being alive without HF hospitalization was 94% for a typical patient in the lowest risk quintile and 77% for a typical patient in the highest risk quintile and this variability in risk continued through 7 years of follow-up. The model c-index was 0.72 in the derivation cohort, 0.66 in the validation cohort, and 0.69 in the implantable cardiac defibrillator arm of the validation cohort. There was excellent calibration across quintiles of predicted risk.

CONCLUSIONS

Our findings illustrate the advantages of a multistate modeling approach, providing estimates of HF hospitalization and death in the same model, comparison of predictors for the different outcomes and demonstrating the different trajectories of patients based on baseline characteristics and intermediary events.

CLINICAL TRIAL REGISTRATION

URL: http://www.clinicaltrials.gov. Unique identifiers: NCT00000609 and NCT00090259.

A Review of Prognostic Tools in Heart Failure

A minority of patients with end-stage disease are referred to palliative medicine for consultation in advanced heart failure. Educating stakeholders, including primary care, cardiology, and critical care of the benefits of hospice and palliative medicine for patients with poor prognosis, may increase appropriately timed referrals and improve quality of life for these patients. This article reviews multiple tools useful in prognostication in the setting of advanced heart failure.

Performance of AHEAD Score in an Asian Cohort of Acute Heart Failure With Either Preserved or Reduced Left Ventricular Systolic Function

Background

AHEAD (A: atrial fibrillation; H: hemoglobin; E: elderly; A: abnormal renal parameters; D: diabetes mellitus) score has been related to clinical outcomes of acute heart failure. However, the prognostic value of the AHEAD score in acute heart failure patients with either reduced or preserved left ventricular ejection fraction (HFrEF and HFpEF) remain to be elucidated.

Methods and Results

The study population consisted of 2143 patients (age 77±12 years, 68% men, 38% HFrEF) hospitalized primarily for acute heart failure with a median follow‐up of 23.75 months. The performance of the AHEAD score (atrial fibrillation, hemoglobin <13 mg/dL for men and 12 mg/dL for women, age >70 years, creatinine >130 μmol/L, and diabetes mellitus) was evaluated by Cox's regression analysis for predicting cardiovascular and all‐cause mortality. The mean AHEAD scores were 2.7±1.2 in the total study population, 2.6±1.3 in the HFrEF group, and 2.7±1.1 in the HFpEF group. After accounting for sex, sodium, uric acid, and medications, the AHEAD score remained significantly associated with all‐cause and cardiovascular mortality (hazard ratio and 95% CI: 1.49, 1.38–1.60 and 1.48, 1.33–1.64), respectively. The associations of AHEAD score with mortality remained significant in the subgroups of HFrEF (1.63, 1.47–1.82) and HFpEF (1.34, 1.22–1.48). Moreover, when we calculated a new AHEAD‐U score by considering uric acid (>8.6 mg/dL) in addition to the AHEAD score, the net reclassification was improved by 19.7% and 20.1% for predicting all‐cause and cardiovascular mortality, respectively.

Conclusions

The AHEAD score was useful in predicting long‐term mortality in the Asian acute heart failure cohort with either HFrEF or HFpEF. The new AHEAD‐U score may further improve risk stratification.

Comparison of Multivariate Risk Estimation Models to Predict Prognosis in Patients With Implantable Cardioverter Defibrillators With or Without Cardiac Resynchronization Therapy

Several multivariate risk score models were developed to predict prognosis of patients with heart failure (HF). We compared 3 models with regard to prediction of mortality in patients with HF who received an implantable defibrillator (ICD) or a cardiac resynchronization therapy defibrillator (CRT-D), as primary prevention of sudden death. The study cohort consisted of 823 patients (ICD = 410; CRT-D = 413). The evaluated models were the Seattle Heart Failure Model (SHFM), the Multicenter Automatic Defibrillator Implantation Trial II (MADIT II) score, and an adjusted Charlson Comorbidity Index (aCCI). End point was the performance of the models to predict all-cause mortality at 5 years. This was determined by c-statistics, for both subgroups. Multivariate analysis was used to analyze the relations between the risk score models, their individual components and mortality, and its applicability to the entire population. Cumulative mortality was 4.9% at 1 year and 21.1% at 5 years. Discriminatory power for 5-year mortality was highest for the SHFM (0.73; p <0.001) compared with the MADIT II score and the aCCI for the entire population. SHFM performed better than the MADIT II score for CRT-D group. In the entire population, the SHFM and the aCCI were significant predictors of mortality in multivariate analysis (hazard ratio 1.90, 95% confidence interval 1.49 to 2.43 vs hazard ratio 1.11, 95% confidence interval 1.01 to 1.22). The strongest individual components were age, HF, impaired renal function, and cancer, whereas CRT-D use was no predictor. In conclusion, the SHFM has the best discriminatory power for 5-year mortality in patients with HF with an ICD or CRT-D. The aCCI and MADIT II scores are less powerful but viable alternatives.

Palliative Care Training in Cardiology Fellowship: A National Survey of the Fellows

Objectives:

To address perspectives of cardiology fellows on the current state of palliative education and palliative and hospice resource utilization within their fellowship experiences.

Methods:

We conducted an online national survey of cardiology fellows during the 2015 to 2016 academic year. Survey questions aimed to assess perceived importance of palliative care education, level of palliative care education during fellowship, and the structure of palliative care support at respondent institutions. Responses were collected anonymously. A total of 519 programs, including subspecialty programs, were contacted.

Results:

We received 365 responses, a number that represents roughly 14% of all cardiology fellows nationwide during the 2015 to 2016 academic year. Fellows reported discordance in the quality of education between general cardiology and palliative care principles as it relates to care of the patient approaching the end of life. Fellows infrequently received explicit training nor were observed or mentored in delivering end-of-life discussions. Respondents reported an underutilization of palliative care and hospice resources during fellowship training and also a perception that attending faculty were not routinely addressing goals of care.

Conclusions:

Our survey results highlight a need for enhanced palliative care and end-of-life training experiences for cardiology fellows and also suggest underutilization of hospice and palliative care resources for patients with advanced cardiac diseases. These findings create a platform for future work that might: (1) confirm this training deficit, (2) lead to exploration of educational models that could reconcile this deficit, and (3) potentially help improve palliative care support for patients and families facing advanced heart disease.

Advanced Heart Failure: Prevalence, Natural History, and Prognosis

Heart failure is a complex clinical syndrome. The natural history of this syndrome is progressive. Advanced heart failure is present when a patient has signs and symptoms of heart failure that are refractory to therapy. Patients with the most advanced disease and worst prognosis can be identified using iterative, integrated clinical assessment of symptom burden, effort intolerance, and cardiac dysfunction. Recognizing the transition to advanced heart failure is necessary for referral to an advanced heart disease program. Advanced heart disease specialists can tailor medical therapies, perform risk stratification, and evaluate candidacy for mechanical support, transplantation, or end-of-life palliative treatment options.

Thirty years of heart transplantation at the University Medical Centre Utrecht

Purpose

To analyse patient demographics, indications, survival and donor characteristics for heart transplantation (HTx) during the past 30 years at the University Medical Centre Utrecht (UMCU).

Methods

Data have been prospectively collected for all patients who underwent HTx at the UMCU from 1985 until 2015. Patients who were included underwent orthotopic HTx at an age >14 years.

Results

In total, 489 hearts have been transplanted since 1985; 120 patients (25%) had left ventricular assist device (LVAD) implantation prior to HTx. A shift from ischaemic heart disease to dilated cardiomyopathy has been seen as the leading indication for HTx since the year 2000. Median age at HTx was 49 years (range 16–68). Median waiting time and donor age have also increased from 40 to 513 days and from 27 to 44 years respectively (range 11–65). Donor cause of death is now primarily stroke, in contrast to head and brain injury in earlier years. Estimated median survival is 15.4 years (95% confidence interval 14.2–16.6) There is better survival throughout these years.

Conclusion

Over the past 30 years, patient and donor demographics and underlying diseases have shifted substantially. Furthermore, the increase in waiting time due to lack of available donor hearts has led to a rise in the use of LVADs as bridge to transplant. Importantly, an improvement in survival rates is found over time which could be explained by better immunosuppressive therapy and improvements in follow-up care.

Validity of the Seattle Heart Failure Model for prognosis in a population at low coronary heart disease risk

AIM

Validation of the Seattle Heart Failure Model (SHFM) for predicting the risk of death in a population different than the derivation cohort.

METHODS

In a retrospective analysis of a cohort of chronic heart failure patients with left ventricular systolic dysfunction, consecutively referred between 2000 and 2011, we computed the score, according to characteristics at referral. We compared the observed risk of death with that predicted by the model, using receiver operating characteristic (ROC) curves to assess discrimination and a goodness-of-fit test for the comparison of predicted and observed risks.

RESULTS

In 565 patients, 68.5% were men, the median age was 70 years, 46.0% had ischemic cause, 89.7% moderate-severe left ventricular systolic dysfunction and 61.2% New York Heart Association class II. The risk of death increased progressively with the model's score, with an area under the ROC curve between 0.69 and 0.72 when considering different follow-up periods. The model underestimated the risk of death (observed vs. predicted: 12.2 vs. 10.4%, P < 0.001; 28.1 vs. 25.1%, P < 0.001; and 43.4 vs. 35.7%, P < 0.001 at 1, 3 and 5 years, respectively). Accurate predictions, with nonsignificant differences between observed and predicted risks in a goodness-of-fit test, were obtained after recalibration.

CONCLUSION

In this study, the SHFM substantially underestimated the absolute risk of death in ambulatory chronic heart failure patients, mostly nonischemic and elderly. After adjustment for sample-specific circumstances, the recalibrated model demonstrated to be credible in clinical practice and may provide useful information to physicians.

The Change in Body Weight During Hospitalization Predicts Mortality in Patients With Acute Decompensated Heart Failure

Background

In our experience, the change in body weight (BW) during hospitalization varies greatly in patients with acute decompensated heart failure (HF). Since the clinical significance of a change in BW is not clear, we investigated whether a change in BW could predict mortality.

Methods

We retrospectively enrolled 130 patients (72 males; aged 68 ± 10 years) who were hospitalized due to acute decompensated HF and followed for 2 years after discharge. The change in the BW index during hospitalization (ΔBWI) was calculated as (BW at hospital admission minus BW at hospital discharge)/body surface area at hospital discharge.

Results

The patients were divided into quartiles according to ΔBWI, and the 2-year mortality rates in the quartiles with the lowest, second, third and highest ΔBWI were 18.8%, 12.1%, 3.1% and 9.1%, respectively. In a multivariate Cox proportional hazards analysis after adjusting for variables with a P value less than 0.05, ΔBWI was independently associated with 2-year mortality (P = 0.0002), and the quartile with the lowest ΔBWI had a higher relative risk (RR) for 2-year mortality than the quartile with the highest ΔBWI (RR: 7.46, 95% confidence interval: 1.03 - 53.99, P = 0.04).

Conclusion

In conclusion, ΔBWI was significantly associated with 2-year mortality after discharge, which indicates that ΔBWI might be a simple predictor of prognosis in acute decompensated HF.

Bendopnea and risk of adverse clinical outcomes in ambulatory patients with systolic heart failure

BACKGROUND

Recently, the symptom of bendopnea, that is, shortness of breath when bending forwards such as when putting on shoes, has been described in heart failure patients and found to be associated with higher ventricular filling pressures, particularly in the setting of low cardiac index. However, it is not known whether bendopnea is associated with clinical outcomes.

METHODS

In a prospective convenience sample of 179 patients followed in our heart failure disease management clinic, we determined the presence of bendopnea at the time of enrollment and ascertained clinical outcomes through 1 year of follow-up. We performed univariate and stepwise multivariable modeling to test the association of bendopnea with clinical outcomes.

RESULTS

Bendopnea was present in 32 of 179 (18%) subjects. At 1 year, those with versus without bendopnea were at increased risk of the composite endpoint of death, heart failure admission, inotrope initiation, left ventricular assist device implantation, or cardiac transplantation in univariate (hazard ratio [HR] 1.9, P < .05) but not multivariable (HR 1.9, P = .11) analysis. Bendopnea was more strongly associated with short-term outcomes including heart failure admission at 3 months in both univariate (HR 3.1, P < .004) and multivariable (HR 2.5, P = .04) analysis.

CONCLUSIONS

Bendopnea was associated with an increased risk of adverse outcomes in ambulatory patients with heart failure, particularly heart failure admission at 3 months.

Impact of Oral Treatment on Physical Function in Older Patients Hospitalized for Heart Failure: A Randomized Clinical Trial

Background

Frailty is a characteristic of older patients with heart failure, who undergo functional decline during hospitalization. At present, continuous intravenous infusion of diuretics is widely used for the treatment of hospitalized patients with heart failure. In this prospective, randomized, open-label controlled trial, we tested whether an early switch from continuous intravenous infusion therapy to oral treatment with diuretics prevents functional decline in patients hospitalized for heart failure.

Methods

A total of 59 patients hospitalized for heart failure were randomized to either continuous intravenous infusion (n = 30) or oral medication (n = 29) within 48 h of admission. The primary outcome was the Barthel index, a universally utilized scale to assess the functional status of patients in their activities of daily living, assessed at 10 days. Secondary outcomes included the number of daily steps counted using pedometers and average hospital costs.

Results

Barthel index scores were significantly higher in the oral medication group than in the intravenous group (78.1 ± 20.8 vs. 59.6 ± 34.2, P = 0.029). The number of daily steps was significantly higher in the oral treatment group relative to the intravenous group (P < 0.001), and the average hospital costs were similar between the randomized groups. Multivariate analysis revealed that oral medication was a significant independent predictor of Barthel index score at day 10, and the number of daily steps was significantly associated with the patient’s functional outcome.

Conclusions

This trial showed that, in patients hospitalized for heart failure, oral medication increased functional independence during hospitalization compared with sustained continuous intravenous infusion, most likely because the release from the infusion line enabled the patients to be more mobile. Notably, these beneficial effects were achieved without increasing hospital costs.

Reasons why patients suffering from chronic heart failure at very low risk for mortality die

BACKGROUND

A proper prognostic stratification is crucial for organizing an effective clinical management and treatment decision-making in patients with chronic heart failure (CHF). In this study, we selected and characterized a sub-group of CHF patients at very low risk for death aiming to assess predictors of death in subjects with an expected probability of 1-year mortality near to 5%.

METHODS

We used the Cardiac and Comorbid Conditions HF (3C-HF) Score to identify CHF patients with the best mid-term prognosis. We selected patients belonging to the lowest quartile of 3C-HF score (≤9 points).

RESULTS

We recruited 1777 consecutive CHF patients at 3 Italian Cardiology Units (age 76±10years, 43% female, 32% with preserved ejection fraction). Subjects belonging to the lowest quartile of 3C-HF score were 609. During a median follow-up of 21 [12-40] months, 48 of these patients (8%) died, and 561 (92%) survived. The variables that contributed to death prediction by Cox regression multivariate analysis were older age (HR 1.03[CI 1.00-1.07]; p=0.04), male gender (HR 2.93[CI 1.50-5.51]; p=0.002) and a higher degree of renal dysfunction (HR 0.96[CI 0.94-0.98]; p<0.001).

CONCLUSIONS

The prognostic stratification of CHF patients by 3C-HF score allows one to select patients at different outcome and to identify the factors associated with death in outliers with a very low mortality risk at mid-term follow-up. The reasons why these patients do not outlive the matching part of subjects who expectedly survive are related to a declined renal function and unmodifiable conditions including older age and male gender.

Predicting hospitalization and mortality in patients with heart failure: The BARDICHE-index

BACKGROUND

Prediction of events in chronic heart failure (CHF) patients is still difficult and available scores are often complex to calculate. Therefore, we developed and validated a simple-to-use, multidimensional prognostic index for such patients.

METHODS

A theoretical model was developed based on known prognostic factors of CHF that are easily obtainable: Body mass index (B), Age (A), Resting systolic blood pressure (R), Dyspnea (D), N-termInal pro brain natriuretic peptide (NT-proBNP) (I), Cockroft-Gault equation to estimate glomerular filtration rate (C), resting Heart rate (H), and Exercise performance using the 6-min walk test (E) (the BARDICHE-index). Scores were given for all components and added, the sum ranging from 1 (lowest value) to 25 points (maximal value), with estimated risk being highest in patients with highest scores. Scores were categorized into three groups: a low (≤8 points); medium (9-16 points), or high (>16 points) BARDICHE-score. The model was validated in a data set of 1811 patients from two prospective CHF-cohorts (median follow-up 887days). The primary outcome was 5-year all-cause survival. Secondary outcomes were 5-year survival without all-cause hospitalization and 5-year survival without CHF-related hospitalization.

RESULTS

There were significant differences between BARDICHE-risk groups for mortality (hazard ratio=3.63 per BARDICHE-group, 95%-CI 3.10-4.25), mortality or all-cause hospitalization (HR=2.00 per BARDICHE-group, 95%-CI 1.83-2.19), and mortality or CHF-related hospitalization (HR=3.43 per BARDICHE-group, 95%-CI 3.01-3.92; all P<10-50). Outcome was predicted independently of left ventricular ejection fraction (LVEF) and gender.

CONCLUSIONS

The BARDICHE-index is a simple multidimensional prognostic tool for patients with CHF, independently of LVEF.

Changes in Left Ventricular Ejection Fraction Predict Survival and Hospitalization in Heart Failure With Reduced Ejection Fraction

BACKGROUND

Left ventricular remodeling, as commonly measured by left ventricular ejection fraction (LVEF), is associated with clinical outcomes. Although change in LVEF over time should reflect response to therapy and clinical course, serial measurement of LVEF is inconsistently performed in observational settings, and the incremental prognostic value of change in LVEF has not been well characterized.

METHODS AND RESULTS

The β-Blocker Evaluation of Survival Trial measured LVEF by radionuclide ventriculography at baseline and at 3 and 12 months after randomization. We built a series of multivariable models with 16 clinical parameters plus change in LVEF for predicting 4 major clinical end points, including the trial's primary end point of all-cause mortality. Among 2484 patients with at least 1 follow-up LVEF, change in LVEF was the second most significant predictor (behind baseline creatinine) of all-cause mortality (adjusted hazard ratio for improvement in LVEF by ≥5 U responder versus nonresponder [95% confidence intervals] for all-cause mortality=0.62 [0.52-0.73]). Other end points, including heart failure hospitalization or the composite of all-cause mortality and heart failure hospitalization, yielded similar results. LVEF change ≥5 U was associated with a modest increase in discrimination when added to traditional predictors and was predictive of outcomes in both the bucindolol and placebo treatment groups. LVEF change as a predictor of outcomes was affected by sex and race, with evidence that LVEF improvement is associated with less survival benefit in African Americans and women.

CONCLUSIONS

Serial evaluation for LVEF change predicts both survival and heart failure hospitalization and provides a dynamic/real-time measure of prognosis in heart failure with reduced LVEF.

CLINICAL TRIAL REGISTRATION

URL: http://www.clinicaltrials.gov. Unique identifier: NCT00000560.

Variables Measured During Cardiopulmonary Exercise Testing as Predictors of Mortality in Chronic Systolic Heart Failure

BACKGROUND

Data from a cardiopulmonary exercise (CPX) test are used to determine prognosis in patients with chronic heart failure (HF). However, few published studies have simultaneously compared the relative prognostic strength of multiple CPX variables.

OBJECTIVES

The study sought to describe the strength of the association among variables measured during a CPX test and all-cause mortality in patients with HF with reduced ejection fraction (HFrEF), including the influence of sex and patient effort, as measured by respiratory exchange ratio (RER).

METHODS

Among patients (n = 2,100, 29% women) enrolled in the HF-ACTION (HF-A Controlled Trial Investigating Outcomes of exercise traiNing) trial, 10 CPX test variables measured at baseline (e.g., peak oxygen uptake [Vo2], exercise duration, percent predicted peak Vo2 [%ppVo2], ventilatory efficiency) were examined.

RESULTS

Over a median follow-up of 32 months, there were 357 deaths. All CPX variables, except RER, were related to all-cause mortality (all p < 0.0001). Both %ppVo2 and exercise duration were equally able to predict (Wald chi-square: ∼141) and discriminate (c-index: 0.69) mortality. Peak Vo2 (ml·kg(-1)·min(-1)) was the strongest predictor of mortality among men (Wald chi-square: 129) and exercise duration among women (Wald chi-square: 41). Multivariable analyses showed that %ppVo2, exercise duration, and peak Vo2 (ml·kg(-1)·min(-1)) were similarly able to predict and discriminate mortality. In men, a 10% 1-year mortality rate corresponded to a peak Vo2 of 10.9 ml·kg(-1)·min(-1) versus 5.3 ml·kg(-1)·min(-1) in women.

CONCLUSIONS

Peak Vo2, exercise duration, and % ppVo2 carried the strongest ability to predict and discriminate the likelihood of death in patients with HFrEF. The prognosis associated with a given peak Vo2 differed by sex. (Exercise Training Program to Improve Clinical Outcomes in Individuals With Congestive Heart Failure; NCT00047437).

Simple Clinical Criteria to Determine the Prognosis of Heart Failure

Objective: To determine whether easily obtained clinical parameters serve as predictors of survival in patients with congestive heart failure. Several scoring systems to predict heart failure survival have been developed; however, many of these deal principally with transplant recipients or do not account for a patient’s response to therapy.

Methods: A total of 680 patients with an ejection fraction of less than 40% were included in the analysis. Baseline assessments were performed and treatment regimens were identified; patients were then followed for up to 5 years. Univariate and multivariate Cox regression models were used to determine clinically important predictors of survival. Kaplan-Meier survival functions for patients with and without the prognostic variable were constructed and mortality was calculated at 1 year and 5 years.

Results: Ejection fraction improvement at 6 months, diabetes mellitus, age, serum creatinine, and blood urea nitrogen (BUN) were significant predictors for survival in the univariate model. Ejection fraction improvement, age, and BUN were significant predictors in the multivariate model. These findings were used to construct a model for predicting patient mortality. Improved ejection fraction (>15 ejection fraction units) gave a 1-year mortality of 2% and a 5-year mortality of 11%. Mortality rates according to patient age and BUN levels were also calculated.

Conclusion: Ejection fraction improvement was the most important predictor for survival in patients with systolic dysfunction; monitoring ejection fraction changes through repeat echocardiograms has important prognostic value. In patients without ejection fraction improvement, age and renal function are important survival determinants.