Sonjoy Laskar

Hospitalization Epidemic in Patients With Heart Failure: Risk Factors, Risk Prediction, Knowledge Gaps, and Future Directions

Patients with heart failure (HF) are hospitalized over a million times annually in the United States. Hospitalization marks a fundamental change in the natural history of HF, leading to frequent subsequent rehospitalizations and a significantly higher mortality compared with nonhospitalized patients. Three-fourths of all HF hospitalizations are due to exacerbation of symptoms in patients with known HF. One-half of hospitalized HF patients experience readmission within 6 months. Preventing HF hospitalization and rehospitalization is important to improve patient outcomes and curb health care costs. To implement cost-effective strategies to contain the HF hospitalization epidemic, optimal schemes to identify high-risk individuals are needed. In this review, we describe the risk factors that have been associated with hospitalization risk in HF and the various multimarker risk prediction schemes developed to predict HF rehospitalization. We comment on areas that represent gaps in our knowledge or difficulties in interpretation of the current literature, representing opportunities for future research. We also discuss issues with using HF readmission rate as a quality indicator.

Utility of the Seattle Heart Failure Model in Patients With Advanced Heart Failure

OBJECTIVES The aim of this study was to validate the Seattle Heart Failure Model (SHFM) in patients with advanced heart failure (HF). BACKGROUND The SHFM was developed primarily from clinical trial databases and extrapolated the benefit of interventions from published data. METHODS We evaluated the discrimination and calibration of SHFM in 445 advanced HF patients (age 52 +/- 12 years, 68.5% male, 52.4% white, ejection fraction 18 +/- 8%) referred for cardiac transplantation. The primary end point was death (n = 92), urgent transplantation (n = 14), or left ventricular assist device (LVAD) implantation (n = 3); a secondary analysis was performed on mortality alone. RESULTS Patients were receiving optimal therapy (angiotensin-II modulation 92.8%, beta-blockers 91.5%, aldosterone antagonists 46.3%), and 71.0% had an implantable device (defibrillator 30.4%, biventricular pacemaker 3.4%, combined 37.3%). During a median follow-up of 21 months, 109 patients (24.5%) had an event. Although discrimination was adequate (c-statistic >0.7), the SHFM overall underestimated absolute risk (observed vs. predicted event rate: 11.0% vs. 9.2%, 21.0% vs. 16.6%, and 27.9% vs. 22.8% at 1, 2, and 3 years, respectively). Risk underprediction was more prominent in patients with an implantable device. The SHFM had different calibration properties in white versus black patients, leading to net underestimation of absolute risk in blacks. Race-specific recalibration improved the accuracy of predictions. When analysis was restricted to mortality, the SHFM exhibited better performance. CONCLUSIONS In patients with advanced HF, the SHFM offers adequate discrimination, but absolute risk is underestimated, especially in blacks and in patients with devices. This is more prominent when including transplantation and LVAD implantation as an end point.

Incremental value of renal function in risk prediction with the Seattle Heart Failure Model

BACKGROUND Impaired renal function portends poor heart failure (HF) outcomes. The Seattle Heart Failure Score (SHFS), a multimarker risk assessment tool, however does not incorporate renal function. In this study, we assessed the incremental value of renal function over the SHFS in patients with advanced HF on contemporary optimal treatment. METHODS Blood urea nitrogen (BUN), serum creatinine (sCr), BUN/sCr ratio, and estimated glomerular filtration rate were assessed in survival models with SHFS as the base model among 443 patients with HF (52 +/- 12 years, male 68.5%, white 52.4%, ejection fraction 0.18 +/- 0.08). Incremental value of renal function was assessed by changes in the likelihood ratio chi(2) and the area under the receiver operating characteristic curves for 1-, 2-, and 3-year event prediction. RESULTS During a median follow-up of 21 months, 108 (24.5%) of 443 patients had an event (death [n = 92], urgent transplantation [n = 13], or ventricular assist device implantation [n = 3]). All renal parameters individually were associated with outcome (BUN, P < .001; sCr, P < .001; BUN/sCr ratio, P = .006; and estimated glomerular filtration rate, P = .006); however, only BUN was an independent predictor of events in multivariable analyses. Addition of BUN improved the predictive ability of SHFS (Deltalikelihood ratio chi(2) 5.03, P = .025); however, the increase in the area under the receiver operating characteristic curve was marginal (year 1, 0.786 to 0.791; year 2, 0.732 to 0.741; year 3, 0.745 to 0.754; all P > .2). CONCLUSION Among the various renal function parameters, BUN had the strongest association with outcomes in patients with advanced HF. However, the incremental value of renal function over the SHFS for risk determination was marginal.

Echocardiography and Risk Prediction in Advanced Heart Failure: Incremental Value Over Clinical Markers

BACKGROUND Incremental value of echocardiography over clinical parameters for outcome prediction in advanced heart failure (HF) is not well established. METHODS AND RESULTS We evaluated 223 patients with advanced HF receiving optimal therapy (91.9% angiotensin-converting enzyme inhibitor/angiotensin receptor blocker, 92.8% beta-blockers, 71.8% biventricular pacemaker, and/or defibrillator use). The Seattle Heart Failure Model (SHFM) was used as the reference clinical risk prediction scheme. The incremental value of echocardiographic parameters for event prediction (death or urgent heart transplantation) was measured by the improvement in fit and discrimination achieved by addition of standard echocardiographic parameters to the SHFM. After a median follow-up of 2.4 years, there were 38 (17.0%) events (35 deaths; 3 urgent transplants). The SHFM had likelihood ratio (LR) chi(2) 32.0 and C statistic 0.756 for event prediction. Left ventricular end-systolic volume, stroke volume, and severe tricuspid regurgitation were independent echocardiographic predictors of events. The addition of these parameters to SHFM improved LR chi(2) to 72.0 and C statistic to 0.866 (P < .001 and P=.019, respectively). Reclassifying the SHFM-predicted risk with use of the echocardiography-added model resulted in improved prognostic separation. CONCLUSIONS Addition of standard echocardiographic variables to the SHFM results in significant improvement in risk prediction for patients with advanced HF.

Usefulness of Cardiac Index and Peak Exercise Oxygen Consumption for Determining Priority for Cardiac Transplantation

Decisions regarding cardiac transplantation listing are difficult in patients with heart failure who have relatively discordant peak exercise oxygen consumption (Vo(2)) and cardiac index (CI) values. One hundred five patients with heart failure who underwent cardiopulmonary exercise testing and right-sided cardiac catheterization for transplantation evaluation were studied. Patients were divided into 4 groups on the basis of peak Vo(2) and CI: group 1, Vo(2) > or = 12 ml/min/kg, CI > or = 1.8 L/min/m(2) (n = 30); group 2, Vo(2) > or = 12 ml/min/kg, CI <1.8, L/min/m(2) (n = 27); group 3, Vo(2) <12 ml/min/kg, CI > or = 1.8 L/min/m(2) (n = 25); and group 4, Vo(2) <12 ml/min/kg, CI <1.8 L/min/m(2) (n = 23). Groups were compared for event-free (death or ventricular assist device) survival. The overall CI was 1.9 + or - 0.4 L/min/m(2) and peak Vo(2) was 12.4 + or - 2.8 ml/min/kg; values in the 4 groups were as follows: group 1, peak Vo(2) 14.7 + or - 2.1 ml/min/kg, CI 2.2 + or - 0.3 L/min/m(2); group 2, peak VO(2) 14.2 + or - 1.3 ml/min/kg, CI 1.5 + or - 0.2 L/min/m(2); group 3, peak Vo(2) 10.2 + or - 1.3 ml/min/kg, CI 2.1 + or - 0.3 L/min/m(2); and group 4, peak Vo(2) 9.7 + or - 2.0 ml/min/kg, CI 1.6 + or - 0.2 L/min/m(2). After a median follow-up period of 3.7 years, 28 patients (26.0%) had events. Event-free survival was 96%, 95%, 96%, and 79% for 6 months (p = 0.04); 88%, 81%, 90%, and 73% for 12 months (p = 0.09); 88%, 73%, 85%, and 65% for 18 months (p = 0.11); and 83%, 73%, 79%, and 53% for 24 months (p = 0.06) for groups 1 to 4, respectively. Median survival was 5.1, 3.0, 3.9, and 2.6 years, respectively, in groups 1 to 4 (p = 0.052). In conclusion, almost half the patients had relatively discordant peak Vo(2) and CI measurements. Patients with lower peak Vo(2) values but relatively preserved CI values had survival comparable to post-transplantation survival, whereas those with low CI but preserved Vo(2) had a lower survival rate. These results suggest that the former group may be safely monitored on medical therapy, whereas the latter may benefit from early listing.

Matrix Metalloproteinases, Tissue Inhibitors of Metalloproteinases, and Heart Failure Outcomes

Heart failure (HF) prevalence continues to increase and is associated with a high mortality, morbidity, and cost burden for the society. [1, 2] The most common cause of HF in the United States is coronary artery disease. [3] Left ventricular (LV) dysfunction, irrespective of the cause of heart failure (HF), leads to perturbed wall stress resulting in remodeling and HF progression. Matrix metalloproteinases (MMP) are a family of proteolytic enzymes that are involved in the protein degradation in the extracellular matrix and play an important role in remodeling. [4, 5] Multiple classes of MMPs have been identified in human myocardium.[5, 6] Certain MMPs, specifically MMP-2, MMP-3, and MMP-9 have been shown to have high expression in the left ventricle. [7, 8] Tissue inhibitors of metalloproteinases (TIMPS) are low-molecular-weight molecules that bind to MMPs forming MMP-TIMP complexes that exhibit an inhibitory control on MMPs. Several studies have delineated the relationship between MMPs and TIMPs, and that the changes in the MMP/TIMP ratio correlate with left ventricular hypertrophy and dilation. [9, 10] Loss of inhibitory control of TIMP on MMP correlates with progression of left ventricular remodeling via increased MMP activity, extra-cellular matrix proteolysis, and myocardial remodeling changes. [11] There have been conflicting reports on MMPs and TIMPs levels association with HF outcomes. [12-17] These studies have generally not assessed the multiple members of the MMP and TIMP family simultaneously and have assessed varying HF outcomes. In this study, we sought to assess the association between multiple MMPs and TIMPs with clinical outcomes, health status, and exercise capacity among HF patients. We examined the association of baseline serum levels of MMP 1, 2, and 9 and TIMP 1, 2, 3, and 4 with outcomes among 147 outpatients with HF from 1/2008 to 7/2009 enrolled in the Atlanta Cardiomyopathy Consortium, a prospective cohort study enrolling HF patients from three university-affiliated teaching hospitals. All patients undergo detailed history surveys, electrocardiogram, six minute walk test, standardized questionnaires, and collection of blood and urine samples. Every six months, the patients are contacted to assess outcomes including medication changes, procedures, new diagnoses, and hospitalizations. Mortality data are collected through medical record review, information obtained from family members, and Social Security Death Index query. Hospitalization data are obtained from regular electronic health records review, all outpatient notes from any specialty encounter for any reported admission to an outside hospital, and direct patient inquiry during follow-up. Levels of MMPs and TIMPs were measured by Fluorokine MAP Human MMP and TIMP kits with a coefficient of variation < 10% for intra-assay and <15% for inter-assay testing. Clinical outcome was defined as a composite of death, cardiac transplantation, or left ventricular assist device placement or HF hospitalizations. Exercise capacity was determined using the six minute walk test. [18] Health status was assessed with the Kansas City Cardiomyopathy Questionnaire (KCCQ), a 23-item tool with scales that measure multiple aspects of health status in HF patients including clinical symptoms, self-efficacy, physical limitation, social limitation and quality of life. [19] A difference of five points on the KCCQ scale scores is considered clinically important. [20] Correlations between biomarkers, ejection fraction, and exercise capacity were assessed with Pearson correlation. Outcomes were described with Kaplan–Meier estimates and compared with the log-rank statistic between groups. The association of biomarkers with outcomes was examined with Cox proportional hazards models. Patients were divided into two groups based on linearity of strongest associated biomarker with outcomes. Other continuous non time dependent variables in these groups were compared with t-test. Multivariable Cox proportional hazards analysis was then performed adjusting for independent predictors of outcomes in univariate analysis (p-value <0.20). Statistical analysis was done using software from SAS Institute Inc., Cary, Version 9.2 NC, USA. Table 1 shows baseline characteristics. Mean age of patients was 57.1±11.9 years, 67% were male; and 58% were white. Patients were on optimal medical therapy. Mean ejection fraction was 24.6±10.9 % and mean BNP level was 510±720 pg/ml. During follow-up of 23.1±6.7 months, 49 patients (33%) experienced clinical outcome (22 death or transplant or LVAD placement and 27 HF hospitalizations). Among the biomarkers, there were several inter-correlations; MMP-2 and TIMP-2 had the strongest correlation (r= 0.77, p=<.0001) (Table 2). Table 1 Study population baseline characteristics. Table 2 Correlation among biomarkers of collagen turnover In univariate Cox regression analysis TIMP-2 was the strongest predictor of the outcome among the biomarkers of collagen turnover (hazard ratio [HR] 1.019, 95% confidence interval [CI] 1.007, 1.032 for each 1 pg/ml increase) (Table 3). Univariate predictors of events included, ejection fraction (HR 0.96, CI 0.931-0.989), BNP (HR1.001 CI 1.00 - 1.001) and creatinine (HR 1.27 CI 1.15-1.4). Age, Gender and race were not significant predictors of adverse events. History of smoking (43% vs. 26%, p=.001) and sleep apnea (63% vs. 26%, p=.03) were significant predictors of outcomes whereas diabetes had a strong trend (42.8% VS. 19.5%, P 0.08). TIMP-2 levels were dichotomized at fourth quartile (133.82 pg/ml) based on linearity of events (1st quartile= 133.82, event rate 59.5%). TIMP-2 was negatively correlated to ejection fraction (r = -0.26, p=0.002) and six minute walk test (r= -0.19, P=0.03); and positively with BNP (r=0.20, p=0.03). The group with value >133.82 pg/ml had significant lower ejection fraction (19.3% vs. 26.3%, p< 0.001), less distance covered during the six minute walk test (335 meters vs. 382 meters, p<0.016) and lower KCCQ physical limitation score (61.6 vs. 71.6, p<0.024). Overall KCCQ scores were not different (67.5 vs. 62.2, p = 0.19) In Cox regression model controlling for age, race, gender, ejection fraction, smoking, sleep apnea, diabetes, depression, BNP, creatinine, and baseline therapy, TIMP-2 level >133.82 was an independent predictor of outcomes (HR 2.89 95% CI 1.09 , 7.7) Figure 1. Figure 1 Kaplan-Meier survival curve of the two groups divide at TIMP-2 >133.82 pg/ml Prior studies have shown the prognostic utility of MMP-1[12] ,MMP-2[13] , and TIMP-1 [14] in HF. MMP-1 is shown to correlate with functional capacity [12] [15], neuroharmonal activation[16], and BNP levels [17]. However, these and other studies have shown conflicting results. [12] [15] [13] [14] [21]. Our study is unique since we compared several MMPs and TIMPs for multiple outcomes. We found that highest TIMP-2 quartile has thrice the event rate when compared with the lowest quartile. We also found that TIMP-2 negatively correlate with Physical Limitation Score. The important question raised from our data is that what makes TIMP-2 the best predictor among the biomarkers of collagen turnover. It is generally accepted that MMPs are harmful and TIMPs are beneficial for extracellular matrix and lower TIMP levels could be detrimental in HF. The review by Brew and Nagase points to several independent effects of TIMP-2 including anti-angiogenicity [22]. We can only hypothesize that maybe this is what we are observing in our data. Myocardial remodeling is the central culprit in the progression of chronic systolic HF [23] and therapies that inhibit myocardial remodeling [24, 25], such as angiotensin-converting enzyme inhibitors, β-blockers and aldosterone antagonists help ameliorate clinical outcomes including HF hospitalization and death[26]. Whether TIMP-2 levels have the potential of accurately guide therapy and help optimize this management needs study. Our limitation was that our study was an observational cohort study with a smaller sample size. Also, we do not have the data on changes in biomarker levels over time. We conclude that elevated serumlevels of TIMP-2 levels correlate with MMP-2, BNP, creatinine levels, ejection fraction, quality of life indices and functional capacity; and were strongly and independently associated with adverse outcomes in this cohort of outpatients with primarily systolic HF. Further experimental studies are needed to explore the utility of TIMP-2 to help guide management and therapy in heart failure patients.

Rapid onset and resolution of cardiogenic shock in a patient with pheochromocytoma.

A pheochromocytoma is a rare catecholamine-secreting tumor that can be familial or arise sporadically. Its typical presenting features include symptoms of headache, palpitations, and diaphoresis occurring in paroxysms. The classic presenting sign is episodic hypertension, although only in 59% of cases, have evidence of hypertension at diagnosis. There have been a few case reports of patients with pheochromocytoma presenting with cardiogenic shock but none with both cardiogenic shock and ventricular tachycardia. Additionally, we are not aware of any case reports of such a rapid decline and then improvement in ejection fraction (EF) as demonstrated in this case. We report the unusual presentation of a patient who developed cardiogenic shock within seconds during the course of a single transthoracic echocardiogram (TTE) only to recover minutes later without intervention.

ADHERENCE, PREDICTORS OF ADHERENCE AND OUTCOMES ASSOCIATED WITH SELF-CARE RECOMMENDATIONS AMONG HEART FAILURE PATIENTS

Abstract Category: 24. Myocardial Function/Heart Failure—Clinical Nonpharmacological TreatmentSession-Poster Board Number: 1160-25Authors: Catherine Norton, Vasiliki Georgiopoulou, Andreas Kalogeropoulos, Lucy Fike, Grigorios Giamouzis, Sonjoy Laskar, Robert Cole, Andrew Smith, Wilson W.H. Tang, Sandra Dunbar, Javed Butler, Emory University School of Medicine, Atlanta, GA, Cleveland Clinic Foundation, Cleveland, OH Background: Cumulative adherence with self-care recommendations and association with outcomes is not well described in heart failure (HF) patients.Methods: We used self-report to evaluate adherence to eight HF self-care recommendations (exercise, medications, alcohol and smoking habits, diet, weight and symptom monitoring) among 286 patients with HF (age, 56±11.6 years; 34.3% female; 46.2% black). Adherence was defined as optimal (overall ≥80%) or ideal (≥80% adherence to each recommendation). Outcomes included death or transplant or ventricular assist device placement; rates of emergency department visits, hospitalizations, and length of stay; health status using the Kansas City Cardiomyopathy Questionnaire.Results: Mean follow-up was 525±295 days. Adherence to individual recommendations ranged from 89% for medication to 26% for exercise. Optimal adherence was reported by 34% of patients whereas only 11% indicated ideal adherence. Education was the only sociodemographic variable associated with adherence (odds ratio [OR] 1.15; 95% confidence interval [CI] 1.05-1.25 for optimal; and OR 1.15; 95% CI 1.02-1.30 for ideal adherence per year of education). Patients with optimal or ideal adherence had better clinical outcomes (Table); however, only ideal adherence was associated with better quality of life.Conclusions: In this HF cohort, better adherence with self-care recommendations was associated with improved clinical outcomes. However, adherence was suboptimal for most patients. Optimal AdherenceDeath/Left Ventricular Assist Device/Transplant, % 8.0 9.2 0.73All cause hospitalizations, per 1000 patient-days 2.8 2.0 0.07HF hospitalizations, per 1000 patient-days 1.2 0.9 0.12Emergency department visits, per 1000 patient-days 1.3 0.8 0.02Hospital length of stay, per 1000 patient-days 13.8 8.8 0.06Hospital length of stay - HF only, per 1000 patient-days 8.5 5.5 0.13Kansas City Cardiomyopathy Questionnaire Overall Summary Score 65.2±23.2 67.9±24.3 0.37Ideal AdherenceDeath/Left Ventricular Assist Device/Transplant, % 8.3 9.4 0.83All cause hospitalizations, per 1000 patient-days 2.7 1.5 0.09HF hospitalizations, per 1000 patient-days 1.2 0.4 0.08Emergency department visits, per 1000 patient-days 1.2 0.8 0.33Hospital length of stay, per 1000 patient-days 13.6 3.0 0.02Hospital length of stay - HF only, per 1000 patient-days 8.3 0.8 0.04Kansas City Cardiomyopathy Questionnaire Overall Summary Score 65.1±23.5 74.3±23.5 0.04