Esther Vorovich

Heart Failure With Recovered Ejection Fraction Clinical Description, Biomarkers, and Outcomes

Background— We hypothesized that patients with heart failure (HF) who recover left ventricular function (HF-Recovered) have a distinct clinical phenotype, biology, and prognosis compared with patients with HF with reduced ejection fraction (HF-REF) and those with HF with preserved ejection fraction (HF-PEF). Methods and Results— The Penn Heart Failure Study (PHFS) is a prospective cohort of 1821 chronic HF patients recruited from tertiary HF clinics. Participants were divided into 3 categories based on echocardiograms: HF-REF if EF was <50%, HF-PEF if EF was consistently ≥50%, and HF-Recovered if EF on enrollment in PHFS was ≥50% but prior EF was <50%. A significant portion of HF-Recovered patients had an abnormal biomarker profile at baseline, including 44% with detectable troponin I, although in comparison, median levels of brain natriuretic factor, soluble fms-like tyrosine kinase receptor-1, troponin I, and creatinine were greater in HF-REF and HF-PEF patients. In unadjusted Cox models over a maximum follow-up of 8.9 years, the hazard ratio for death, transplantation, or ventricular assist device placement in HF-REF patients was 4.1 (95% confidence interval, 2.4–6.8; P <0.001) and in HF-PEF patients was 2.3 (95% confidence interval, 1.2–4.5; P =0.013) compared with HF-Recovered patients. The unadjusted hazard ratio for cardiac hospitalization in HF-REF patients was 2.0 (95% confidence interval, 1.5–2.7; P <0.001) and in HF-PEF patients was 1.3 (95% confidence interval, 0.90–2.0; P =0.15) compared with HF-Recovered patients. Results were similar in adjusted models. Conclusions— HF-Recovered is associated with a better biomarker profile and event-free survival than HF-REF and HF-PEF. However, these patients still have abnormalities in biomarkers and experience a significant number of HF hospitalizations, suggesting persistent HF risk. # CLINICAL PERSPECTIVE {#article-title-32}Background— We hypothesized that patients with heart failure (HF) who recover left ventricular function (HF-Recovered) have a distinct clinical phenotype, biology, and prognosis compared with patients with HF with reduced ejection fraction (HF-REF) and those with HF with preserved ejection fraction (HF-PEF). Methods and Results— The Penn Heart Failure Study (PHFS) is a prospective cohort of 1821 chronic HF patients recruited from tertiary HF clinics. Participants were divided into 3 categories based on echocardiograms: HF-REF if EF was <50%, HF-PEF if EF was consistently ≥50%, and HF-Recovered if EF on enrollment in PHFS was ≥50% but prior EF was <50%. A significant portion of HF-Recovered patients had an abnormal biomarker profile at baseline, including 44% with detectable troponin I, although in comparison, median levels of brain natriuretic factor, soluble fms-like tyrosine kinase receptor-1, troponin I, and creatinine were greater in HF-REF and HF-PEF patients. In unadjusted Cox models over a maximum follow-up of 8.9 years, the hazard ratio for death, transplantation, or ventricular assist device placement in HF-REF patients was 4.1 (95% confidence interval, 2.4–6.8; P<0.001) and in HF-PEF patients was 2.3 (95% confidence interval, 1.2–4.5; P=0.013) compared with HF-Recovered patients. The unadjusted hazard ratio for cardiac hospitalization in HF-REF patients was 2.0 (95% confidence interval, 1.5–2.7; P<0.001) and in HF-PEF patients was 1.3 (95% confidence interval, 0.90–2.0; P=0.15) compared with HF-Recovered patients. Results were similar in adjusted models. Conclusions— HF-Recovered is associated with a better biomarker profile and event-free survival than HF-REF and HF-PEF. However, these patients still have abnormalities in biomarkers and experience a significant number of HF hospitalizations, suggesting persistent HF risk.

Comparison of matrix metalloproteinase 9 and brain natriuretic peptide as clinical biomarkers in chronic heart failure

BACKGROUND Matrix metalloproteinase 9 (MMP-9) may serve as a biomarker of ventricular remodeling in selected populations, but few studies have assessed its performance in clinical practice. We tested MMP-9 as a biomarker of remodeling and predictor of outcomes in a systolic heart failure cohort derived from clinical practice and compared its performance to brain natriuretic peptide (BNP). METHODS Plasma MMP-9 and BNP levels were measured in 395 outpatients with systolic heart failure who participated in the Penn Heart Failure Study. We tested for (1) cross-sectional associations between biomarker levels, left ventricular end-diastolic dimension index (LVEDDI), and ejection fraction (EF), and (2) associations between baseline biomarker levels and risk of subsequent cardiac hospitalization or death over 3 years of follow-up. RESULTS Matrix metalloproteinase 9 had no significant correlation with LVEDDI (rho = 0.04, P = not significant) or EF (rho = -0.06, P = not significant), whereas BNP showed highly significant correlations (LVEDDI: rho = -0.27, P < .0001; EF: rho = -0.35, P < .0001). In multivariate linear regression models, MMP-9 again showed no significant associations with LVEDDI (P = .6) or EF (P = .14), whereas BNP showed strong independent associations (LVEDDI: P < .001; EF: P = .002). Kaplan-Meier analyses showed no difference in hospital-free survival by baseline MMP-9 tertile (P = .7), whereas higher BNP tertile predicted worse survival (P < .0001). In multivariate Cox models, baseline MMP-9 level did not predict risk of adverse outcome (hazard ratio for log increase 0.98, P = .9), whereas BNP was a significant independent predictor (hazard ratio for log increase 1.15, P = .02). CONCLUSION Compared to BNP, MMP-9 is a poor clinical biomarker of remodeling and outcome in patients with systolic heart failure derived from clinical practice.

Biomarker predictors of cardiac hospitalization in chronic heart failure: a recurrent event analysis

BACKGROUND Identification of heart failure (HF) patients at risk for hospitalization may improve care and reduce costs. We evaluated 9 biomarkers as predictors of cardiac hospitalization in chronic HF. METHODS AND RESULTS In a multicenter cohort of 1,512 chronic HF outpatients, we assessed the association between 9 biomarkers and cardiac hospitalization with the use of a recurrent events approach. Over a median follow-up of 4 years, 843 participants experienced ≥ 1 hospitalizations (total 2,178 hospitalizations). B-type natriuretic peptide (BNP) and troponin I (TnI) exhibited the strongest associations with risk of hospitalization (hazard ratio [HR] 3.8 [95% confidence interval (CI) 2.9-4.9] and HR 3.3 [95% CI 2.8-3.9]; 3rd vs 1st tertiles). Soluble Fms-like tyrosine kinase receptor 1 (sFlt-1) exhibited the next strongest association (HR 2.8 [95% CI 2.4-3.4]), followed by soluble Toll-like receptor 2 (HR 2.3 [95% CI 2.0-2.8]) and creatinine (HR 1.9 [95% CI 1.6-2.4]). Within ischemic/nonischemic subgroups, BNP and TnI remained most strongly associated. Except for creatinine, HRs for all biomarkers studied were smaller within the ischemic subgroup, suggesting greater importance of cardiorenal interactions in decompensation of ischemic HF. CONCLUSION Although BNP and TnI exhibited the strongest associations with hospitalization, etiology-dependent associations for the remaining biomarkers suggest etiology-specific mechanisms for HF exacerbation. sFlt-1 exhibited a strong association with cardiac hospitalization, highlighting its potential role as a biomarker of HF morbidity.

Clinical InvestigationCongestive Heart FailureComparison of matrix metalloproteinase 9 and brain natriuretic peptide as clinical biomarkers in chronic heart failure

BACKGROUND Matrix metalloproteinase 9 (MMP-9) may serve as a biomarker of ventricular remodeling in selected populations, but few studies have assessed its performance in clinical practice. We tested MMP-9 as a biomarker of remodeling and predictor of outcomes in a systolic heart failure cohort derived from clinical practice and compared its performance to brain natriuretic peptide (BNP). METHODS Plasma MMP-9 and BNP levels were measured in 395 outpatients with systolic heart failure who participated in the Penn Heart Failure Study. We tested for (1) cross-sectional associations between biomarker levels, left ventricular end-diastolic dimension index (LVEDDI), and ejection fraction (EF), and (2) associations between baseline biomarker levels and risk of subsequent cardiac hospitalization or death over 3 years of follow-up. RESULTS Matrix metalloproteinase 9 had no significant correlation with LVEDDI (rho = 0.04, P = not significant) or EF (rho = -0.06, P = not significant), whereas BNP showed highly significant correlations (LVEDDI: rho = -0.27, P < .0001; EF: rho = -0.35, P < .0001). In multivariate linear regression models, MMP-9 again showed no significant associations with LVEDDI (P = .6) or EF (P = .14), whereas BNP showed strong independent associations (LVEDDI: P < .001; EF: P = .002). Kaplan-Meier analyses showed no difference in hospital-free survival by baseline MMP-9 tertile (P = .7), whereas higher BNP tertile predicted worse survival (P < .0001). In multivariate Cox models, baseline MMP-9 level did not predict risk of adverse outcome (hazard ratio for log increase 0.98, P = .9), whereas BNP was a significant independent predictor (hazard ratio for log increase 1.15, P = .02). CONCLUSION Compared to BNP, MMP-9 is a poor clinical biomarker of remodeling and outcome in patients with systolic heart failure derived from clinical practice.

Right ventricular response to pulsatile load is associated with early right heart failure and mortality after left ventricular assist device

BACKGROUND Right ventricular (RV) adaptation to afterload is crucial for patients undergoing continuous-flow left ventricular assist device (cf-LVAD) implantation. We hypothesized that stratifying patients by RV pulsatile load, using pulmonary arterial compliance (PAC), and RV response to load, using the ratio of central venous to pulmonary capillary wedge pressure (CVP:PCWP), would identify patients at high risk for early right heart failure (RHF) and 6-month mortality after cf-LVAD. METHODS During the period from January 2008 to June 2014, we identified 151 patients at our center with complete hemodynamics prior to cf-LVAD. Pulsatile load was estimated using PAC indexed to body surface area (BSA), according to the formula: indexed PAC (PACi) = [SV / (PAsystolic - PAdiastolic)] / BSA, where SV is stroke volume and PA is pulmonary artery. Patients were divided into 4 hemodynamic groups by PACi and CVP:PCWP. RHF was defined as the need for unplanned RVAD, inotropic support ≥14 days or death due to RHF within 14 days. Risk factors for RHF and 6-month mortality were examined using logistic regression and Cox proportional hazards modeling. RESULTS Sixty-one patients (40.4%) developed RHF and 34 patients (22.5%) died within 6 months. Patients with RHF had lower PACi (0.92 vs 1.17 ml/mm Hg/m2, p = 0.008) and higher CVP:PCWP (0.48 vs 0.37, p = 0.001). Higher PACi was associated with reduced risk of RHF (adjusted odds ratio [adj-OR] 0.61, 95% confidence interval [CI] 0.39 to 0.94, p = 0.025) and low PACi with increased risk of 6-month mortality (adjusted hazard ratio [adj-HR] 3.18, 95% CI 1.40 to 7.25, p = 0.006). Compared to patients with low load (high PACi) and adequate right heart response to load (low CVP:PCWP), patients with low PACi and high CVP:PCWP had an increased risk of RHF (OR 4.74, 95% CI 1.23 to 18.24, p = 0.02) and 6-month mortality (HR 8.68, 95% CI 2.79 to 26.99, p < 0.001). CONCLUSIONS A hemodynamic profile combining RV pulsatile load and response to load identifies patients at high risk for RHF and 6-month mortality after cf-LVAD.

2017 ACC/AHA/HFSA/ISHLT/ACP Advanced Training Statement on Advanced Heart Failure and Transplant Cardiology (Revision of the ACCF/AHA/ACP/HFSA/ISHLT 2010 Clinical Competence Statement on Management of Patients With Advanced Heart Failure and Cardiac Transplant): A Report of the ACC Competency Management Committee

Eric S. Williams, MD, MACC, Chair Jonathan L. Halperin, MD, FACC, Co-Chair Jesse E. Adams III, MD, FACC James A. Arrighi, MD, FACC Eric H. Awtry, MD, FACC Eric R. Bates, MD, FACC John E. Brush Jr, MD, FACC Lori Daniels, MD, MAS, FACC Susan Fernandes, LPD, PA-C Rosario Freeman, MD, MS,

Efferocytosis and Outside-In Signaling by Cardiac Phagocytes. Links to Repair, Cellular Programming, and Intercellular Crosstalk in Heart

Phagocytic sensing and engulfment of dying cells and extracellular bodies initiate an intracellular signaling cascade within the phagocyte that can polarize cellular function and promote communication with neighboring non-phagocytes. Accumulating evidence links phagocytic signaling in the heart to cardiac development, adult myocardial homeostasis, and the resolution of cardiac inflammation of infectious, ischemic, and aging-associated etiology. Phagocytic clearance in the heart may be carried out by professional phagocytes, such as macrophages, and non-professional cells, including myofibrolasts and potentially epithelial cells. During cardiac development, phagocytosis initiates growth cues for early cardiac morphogenesis. In diseases of aging, including myocardial infarction, heightened levels of cell death require efficient phagocytic debridement to salvage further loss of terminally differentiated adult cardiomyocytes. Additional risk factors, including insulin resistance and other systemic risk factors, contribute to inefficient phagocytosis, altered phagocytic signaling, and delayed cardiac inflammation resolution. Under such conditions, inflammatory presentation of myocardial antigen may lead to autoimmunity and even possible rejection of transplanted heart allografts. Increased understanding of these basic mechanisms offers therapeutic opportunities.

2017 ACC/AHA/HFSA/ISHLT/ACP Advanced Training Statement on Advanced Heart Failure and Transplant Cardiology (Revision of the ACCF/AHA/ACP/HFSA/ISHLT 2010 Clinical Competence Statement on Management of Patients with Advanced Heart Failure and Cardiac Transplant): A Report of the ACC Competency Management Committee

Since the 1995 publication of its Core Cardiovascular Training Statement (COCATS),1 the American College of Cardiology (ACC) has played a central role in defining the knowledge, experiences, skills, and behaviors expected of all clinical cardiologists upon completion of training. Subsequent updates have incorporated major advances and revisions—both in content and structure—including, most recently, …

Response to Letter Regarding Article, “Heart Failure With Recovered Ejection Fraction: Clinical Description, Biomarkers, and Outcomes”

We thank Drs Psaty, Shah, and Gottdiener for their interest in our article. They expressed concern with our study methodology and, more specifically, our patient population. The Penn Heart Failure Study cohort was composed of patients who had heart failure for an average of 6 years before recruitment at 1 of 3 tertiary care centers.1 As the authors note, this delay in study enrollment selects for patients who survived early disease, but are sufficiently ill to require referral to a tertiary care center. This may introduce bias in the estimation of prognosis, and precludes analysis of …

Predicting Long Term Outcome in Patients Treated With Continuous Flow Left Ventricular Assist Device: The Penn—Columbia Risk Score

Background Predicting which patients are unlikely to benefit from continuous flow left ventricular assist device (LVAD) treatment is crucial for the identification of appropriate patients. Previously developed scoring systems are limited to past eras of device or restricted to specific devices. Our objective was to create a risk model for patients treated with continuous flow LVAD based on the preimplant variables. Methods and Results We performed a retrospective analysis of all patients implanted with a continuous flow LVAD between 2006 and 2014 at the University of Pennsylvania and included a total of 210 patients (male 78%; mean age, 56±15; mean follow‐up, 465±486 days). From all plausible preoperative covariates, we performed univariate Cox regression analysis for covariates affecting the odds of 1‐year survival following implantation (P<0.2). These variables were included in a multivariable model and dropped if significance rose above P=0.2. From this base model, we performed step‐wise forward and backward selection for other covariates that improved power by minimizing Akaike Information Criteria while maximizing the Harrell Concordance Index. We then used Kaplan–Meier curves, the log‐rank test, and Cox proportional hazard models to assess internal validity of the scoring system and its ability to stratify survival. A final optimized model was identified based on clinical and echocardiographic parameters preceding LVAD implantation. One‐year mortality was significantly higher in patients with higher risk scores (hazard ratio, 1.38; P=0.004). This hazard ratio represents the multiplied risk of death for every increase of 1 point in the risk score. The risk score was validated in a separate patient cohort of 260 patients at Columbia University, which confirmed the prognostic utility of this risk score (P=0.0237). Conclusion We present a novel risk score and its validation for prediction of long‐term survival in patients with current types of continuous flow LVAD support.