The impact of multimorbidity and functional limitation on quality of life in patients with heart failure: A multi-site study.

BACKGROUND: Multimorbidity and functional limitation are associated with poor outcomes in heart failure (HF). However, the individual and combined effect of these on health-related quality of life in patients with HF is not well understood. METHODS: Patients aged ≥30 years with two or more HF diagnostic codes and one or more HF-related prescription drugs from four U.S. institutions were mailed a survey to measure patient-centric factors including functional status (activities of daily living [ADLs]) and health-related quality of life (PROMIS-29 Health Profile). Patients with HF from January 1, 2013 to February 1, 2018 were included. Multimorbidity was defined as ≥2 non-cardiovascular comorbidities; functional limitation as any limitation in at least one of eight ADLs. Patients were categorized into four groups by multimorbidity (Yes/No) and functional limitation (Yes/No). We dichotomized the PROMIS-29 sub-scale scores at the median and calculated odd ratios for the four multimorbidity/functional limitation groups. RESULTS: A total of 3330 patients with HF returned the survey (response rate 31%); 3020 completed the questions of interest and were retained. Among these patients (45% female; mean age 73 [standard deviation: 12] years), 29% had neither multimorbidity nor functional limitation, 24% had multimorbidity only, 22% had functional limitation only, and 25% had both. After adjustment, having functional limitation only was associated with higher anxiety (odds ratio [OR]: 3.44, 95% confidence interval [CI]: 2.66-4.45), depression (OR: 3.11, 95% CI: 2.39-4.06), and fatigue (OR: 4.19, 95% CI: 3.25-5.40); worse sleep (OR: 2.14, 95% CI: 1.69-2.72) and pain (OR: 6.73, 95% CI: 5.15-8.78); and greater difficulty with social activities (OR: 9.40, 95% CI: 7.19-12.28) compared with having neither. Results were similar for having both multimorbidity and functional limitation. CONCLUSION: Patients with only functional limitation have similar poor health-related quality of life scores as those with both multimorbidity and functional limitation, underscoring the important role that physical functioning plays in the well-being of patients with HF.

A large, multi-center survey assessing health, social support, literacy, and self-management resources in patients with heart failure.

BACKGROUND: Most patients with heart failure (HF) have multimorbidity which may cause difficulties with self-management. Understanding the resources patients draw upon to effectively manage their health is fundamental to designing new practice models to improve outcomes in HF. We describe the rationale, conceptual framework, and implementation of a multi-center survey of HF patients, characterize differences between responders and non-responders, and summarize patient characteristics and responses to the survey constructs among responders. METHODS: This was a multi-center cross-sectional survey study with linked electronic health record (EHR) data. Our survey was guided by the Chronic Care Model to understand the distribution of patient-centric factors, including health literacy, social support, self-management, and functional and mental status in patients with HF. Most questions were from existing validated questionnaires. The survey was administered to HF patients aged ≥ 30 years from 4 health systems in PCORnet® (the National Patient-Centered Clinical Research Network): Essentia Health, Intermountain Health, Mayo Clinic, and The Ohio State University. Each health system mapped their EHR data to a standardized PCORnet Common Data Model, which was used to extract demographic and clinical data on survey responders and non-responders. RESULTS: Across the 4 sites, 10,662 patients with HF were invited to participate, and 3330 completed the survey (response rate: 31%). Responders were older (74 vs. 71 years; standardized difference (95% CI): 0.18 (0.13, 0.22)), less racially diverse (3% vs. 12% non-White; standardized difference (95% CI): -0.32 (-0.36, -0.28)), and had higher prevalence of many chronic conditions than non-responders, and thus may not be representative of all HF patients. The internal reliability of the validated questionnaires in our survey was good (range of Cronbach's alpha: 0.50-0.96). Responders reported their health was generally good or fair, they frequently had cardiovascular comorbidities, > 50% had difficulty climbing stairs, and > 10% reported difficulties with bathing, preparing meals, and using transportation. Nearly 80% of patients had family or friends sit with them during a doctor visit, and 54% managed their health by themselves. Patients reported generally low perceived support for self-management related to exercise and diet. CONCLUSIONS: More than half of patients with HF managed their health by themselves. Increased understanding of self-management resources may guide the development of interventions to improve HF outcomes.

Reproductive health after thoracic transplantation: An ISHLT expert consensus statement.

Pregnancy after thoracic organ transplantation is feasible for select individuals but requires multidisciplinary subspecialty care. Key components for a successful pregnancy after lung or heart transplantation include preconception and contraceptive planning, thorough risk stratification, optimization of maternal comorbidities and fetal health through careful monitoring, and open communication with shared decision-making. The goal of this consensus statement is to summarize the current evidence and provide guidance surrounding preconception counseling, patient risk assessment, medical management, maternal and fetal outcomes, obstetric management, and pharmacologic considerations.

Risk score-guided multidisciplinary team-based Care for Heart Failure Inpatients is associated with lower 30-day readmission and lower 30-day mortality.

OBJECTIVE: Using augmented intelligence clinical decision tools and a risk score-guided multidisciplinary team-based care process (MTCP), this study evaluated the MTCP for heart failure (HF) patients' 30-day readmission and 30-day mortality across 20 Intermountain Healthcare hospitals. BACKGROUND: HF inpatient care and 30-day post-discharge management require quality improvement to impact patient health, optimize utilization, and avoid readmissions. METHODS: HF inpatients (N = 6182) were studied from January 2013 to November 2016. In February 2014, patients began receiving care via the MTCP based on a phased implementation in which the 8 largest Intermountain hospitals (accounting for 89.8% of HF inpatients) were crossed over sequentially in a stepped manner from control to MTCP over 2.5 years. After implementation, patient risk scores were calculated within 24 hours of admission and delivered electronically to clinicians. High-risk patients received MTCP care (n = 1221), while lower-risk patients received standard HF care (n = 1220). Controls had their readmission and mortality scores calculated retrospectively (high risk: n = 1791; lower risk: n = 1950). RESULTS: High-risk MTCP recipients had 21% lower 30-day readmission compared to high-risk controls (adjusted P = .013, HR = 0.79, CI = 0.66, 0.95) and 52% lower 30-day mortality (adjusted P < .001, HR = 0.48, CI = 0.33, 0.69). Lower-risk patients did not experience increased readmission (adjusted HR = 0.88, P = .19) or mortality (adjusted HR = 0.88, P = .61). Some utilization was higher, such as prescription of home health, for MTCP recipients, with no changes in length of stay or overall costs. CONCLUSIONS: A risk score-guided MTCP was associated with lower 30-day readmission and 30-day mortality in high-risk HF inpatients. Further evaluation of this clinical management approach is required.

Clinical Decision Support to Efficiently Identify Patients Eligible for Advanced Heart Failure Therapies.

BACKGROUND: Patients who need and receive timely advanced heart failure (HF) therapies have better long-term survival. However, many of these patients are not identified and referred as soon as they should be. METHODS: A clinical decision support (CDS) application sent secure email notifications to HF patients' providers when they transitioned to advanced disease. Patients identified with CDS in 2015 were compared with control patients from 2013 to 2014. Kaplan-Meier methods and Cox regression were used in this intention-to-treat analysis to compare differences between visits to specialized and survival. RESULTS: Intervention patients were referred to specialized heart facilities significantly more often within 30 days (57% vs 34%; P < .001), 60 days (69% vs 44%; P < .0001), 90 days (73% vs 49%; P < .0001), and 180 days (79% vs 58%; P < .0001). Age and sex did not predict heart facility visits, but renal disease did and patients of nonwhite race were less likely to visit specialized heart facilities. Significantly more intervention patients were found to be alive at 30 (95% vs 92%; P = .036), 60 (95% vs 90%; P = .0013), 90 (94% vs 87%; P = .0002), and 180 days (92% vs 84%; P = .0001). Age, sex, and some comorbid diseases were also predictors of mortality, but race was not. CONCLUSIONS: We found that CDS can facilitate the early identification of patients needing advanced HF therapy and that its use was associated with significantly more patients visiting specialized heart facilities and longer survival.

Early inpatient calculation of laboratory-based 30-day readmission risk scores empowers clinical risk modification during index hospitalization.

Improving 30-day readmission continues to be problematic for most hospitals. This study reports the creation and validation of sex-specific inpatient (i) heart failure (HF) risk scores using electronic data from the beginning of inpatient care for effective and efficient prediction of 30-day readmission risk. METHODS: HF patients hospitalized at Intermountain Healthcare from 2005 to 2012 (derivation: n=6079; validation: n=2663) and Baylor Scott & White Health (North Region) from 2005 to 2013 (validation: n=5162) were studied. Sex-specific iHF scores were derived to predict post-hospitalization 30-day readmission using common HF laboratory measures and age. Risk scores adding social, morbidity, and treatment factors were also evaluated. RESULTS: The iHF model for females utilized potassium, bicarbonate, blood urea nitrogen, red blood cell count, white blood cell count, and mean corpuscular hemoglobin concentration; for males, components were B-type natriuretic peptide, sodium, creatinine, hematocrit, red cell distribution width, and mean platelet volume. Among females, odds ratios (OR) were OR=1.99 for iHF tertile 3 vs. 1 (95% confidence interval [CI]=1.28, 3.08) for Intermountain validation (P-trend across tertiles=0.002) and OR=1.29 (CI=1.01, 1.66) for Baylor patients (P-trend=0.049). Among males, iHF had OR=1.95 (CI=1.33, 2.85) for tertile 3 vs. 1 in Intermountain (P-trend <0.001) and OR=2.03 (CI=1.52, 2.71) in Baylor (P-trend < 0.001). Expanded models using 182-183 variables had predictive abilities similar to iHF. CONCLUSIONS: Sex-specific laboratory-based electronic health record-delivered iHF risk scores effectively predicted 30-day readmission among HF patients. Efficient to calculate and deliver to clinicians, recent clinical implementation of iHF scores suggest they are useful and useable for more precise clinical HF treatment.

Automated identification and predictive tools to help identify high-risk heart failure patients: pilot evaluation.

OBJECTIVE: Develop and evaluate an automated identification and predictive risk report for hospitalized heart failure (HF) patients. METHODS: Dictated free-text reports from the previous 24 h were analyzed each day with natural language processing (NLP), to help improve the early identification of hospitalized patients with HF. A second application that uses an Intermountain Healthcare-developed predictive score to determine each HF patient's risk for 30-day hospital readmission and 30-day mortality was also developed. That information was included in an identification and predictive risk report, which was evaluated at a 354-bed hospital that treats high-risk HF patients. RESULTS: The addition of NLP-identified HF patients increased the identification score's sensitivity from 82.6% to 95.3% and its specificity from 82.7% to 97.5%, and the model's positive predictive value is 97.45%. Daily multidisciplinary discharge planning meetings are now based on the information provided by the HF identification and predictive report, and clinician's review of potential HF admissions takes less time compared to the previously used manual methodology (10 vs 40 min). An evaluation of the use of the HF predictive report identified a significant reduction in 30-day mortality and a significant increase in patient discharges to home care instead of to a specialized nursing facility. CONCLUSIONS: Using clinical decision support to help identify HF patients and automatically calculating their 30-day all-cause readmission and 30-day mortality risks, coupled with a multidisciplinary care process pathway, was found to be an effective process to improve HF patient identification, significantly reduce 30-day mortality, and significantly increase patient discharges to home care.

The intermountain risk score predicts incremental age-specific long-term survival and life expectancy.

The Intermountain Risk Score (IMRS) encapsulates the mortality risk information from all components of the complete blood count (CBC) and basic metabolic profile (BMP), along with age. To individualize the IMRS more clearly, this study evaluated whether IMRS weightings for 1-year mortality predict age-specific survival over more than a decade of follow-up. Sex-specific 1-year IMRS values were calculated for general medical patients with CBC and BMP laboratory tests drawn during 1999-2005. The population was divided randomly 60% (N = 71,921, examination sample) and 40% (N = 47,458, validation sample). Age-specific risk thresholds were established, and both survival and life expectancy were compared across low-, moderate-, and high-risk IMRS categories. During 7.3 ± 1.8 years of follow-up (range, 4.5-11.1 years), the average IMRS of decedents was higher than censored in all age/sex strata (all P < 0.001). For examination and validation samples, every age stratum had incrementally lower survival for higher risk IMRS, with hazard ratios of 2.5-8.5 (P < 0.001). Life expectancies were also significantly shorter for higher risk IMRS (all P < 0.001): For example, among 50-59 year-olds, life expectancy was 7.5, 6.8, and 5.9 years for women with low-, moderate-, and high-risk IMRS (with mortality in 5.7%, 16.3%, and 37.0% of patients, respectively). In Men, life expectancy was 7.3, 6.8, and 5.4 for low-, moderate-, and high-risk IMRS (with patients having 7.3%, 19.5%, and 40.0% mortality), respectively. IMRS significantly stratified survival and life expectancy within age-defined subgroups during more than a decade of follow-up. IMRS may be used to stratify age-specific risk of mortality in research, clinical/preventive, and quality improvement applications. A web calculator is located at http://intermountainhealthcare.org/IMRS.

Genome-wide significance and replication of the chromosome 12p11.22 locus near the PTHLH gene for peripartum cardiomyopathy.

BACKGROUND: Peripartum (PP) cardiomyopathy (CM) is a rare condition of unknown etiology that occurs in late pregnancy or early postpartum. Initial evidence suggests that genetic factors may influence PPCM. This study evaluated and replicated genome-wide association of single nucleotide polymorphisms with PPCM. METHODS AND RESULTS: Genome-wide single nucleotide polymorphisms in women with verified PPCM diagnosis (n=41) were compared separately with local control subjects (n=49 postmenopausal age-discordant women with parity ≥1 and no heart failure) and iControls (n=654 women ages 30 to 84 years with unknown phenotypes). A replication study of independent population samples used new cases (PPCM2, n=30) compared with new age-discordant control subjects (local2, n=124) and with younger control subjects (n=89) and obstetric control subjects (n=90). A third case set of pregnancy-associated CM cases not meeting strict PPCM definitions (n=29) was also studied. In the genome-wide association study, 1 single nucleotide polymorphism (rs258415) met genome-wide significance for PPCM versus local control subjects (P=2.06×10(-8); odds ratio [OR], 5.96). This was verified versus iControls (P=7.92×10(-19); OR, 8.52). In the replication study for PPCM2 cases, rs258415 (ORs are per C allele) replicated at P=0.009 versus local2 control subjects (OR, 2.26). This replication was verified for PPCM2 versus younger control subjects (P=0.029; OR, 2.15) and versus obstetric control subjects (P=0.013; OR, 2.44). In pregnancy-associated cardiomyopathy cases, rs258415 had a similar effect versus local2 control subjects (P=0.06; OR, 1.79), younger control subjects (P=0.14; OR, 1.65), and obstetric control subjects (P=0.038; OR, 1.99). CONCLUSIONS: Genome-wide association with PPCM was discovered and replicated for rs258415 at chromosome 12p11.22 near PTHLH. This study indicates a role of genetic factors in PPCM and provides a new locus for further pathophysiological and clinical investigation.

The Intermountain Risk Score (including the red cell distribution width) predicts heart failure and other morbidity endpoints.

AIMS: The complete blood count (CBC) and basic metabolic profile are common, low-cost blood tests, which have previously been used to create and validate the Intermountain Risk Score (IMRS) for mortality prediction. Mortality is the most definitive clinical endpoint, but medical care is more easily applied to modify morbidity and thereby prevent death. This study tested whether IMRS is associated with clinical morbidity endpoints. METHODS AND RESULTS: Patients seen for coronary angiography (n = 3927) were evaluated using a design similar to a genome-wide association study. The Bonferroni correction for 102 tests required a P-value of ≤ 4.9 × 10⁻4 for significance. A second set of angiography patients (n = 10 413) was used to validate significant findings from the first patient sample. In the first patient sample, IMRS predicted heart failure (HF) (P(trend) = 1.6 × 10(-26)), coronary disease (P(trend) = 2.6 × 10(-11)), myocardial infarction (MI) (P(trend) = 3.1 × 10(-25)), atrial fibrillation (P(trend) = 2.5 × 10(-20)), and chronic obstructive pulmonary disease (P(trend) = 4.7 × 10⁻4). Even more, IMRS predicted HF readmission [hazard ratio (HR) = 2.29/category, P(trend) = 1.2 × 10⁻6), incident HF (HR = 1.88/category, P(trend) = 0.02), and incident MI (HR = 1.56/category, P(trend) = 4.7 × 10⁻4). These findings were verified in the second patient sample. CONCLUSION: Intermountain Risk Score, a predictor of mortality, was associated with morbidity endpoints that often lead to mortality. Further research is required to fully characterize its clinical utility, but its low-cost CBC and basic metabolic profile composition may make it ideal for initial risk estimation and prevention of morbidity and mortality. An IMRS web calculator is freely available at http://intermountainhealthcare.org/IMRS.

Health literacy and the patient with heart failure--implications for patient care and research: a consensus statement of the Heart Failure Society of America.

BACKGROUND: Low health literacy compromises patient safety, quality health care, and desired health outcomes. Specifically, low health literacy is associated with decreased knowledge of one's medical condition, poor medication recall, nonadherence to treatment plans, poor self-care behaviors, compromised physical and mental health, greater risk of hospitalization, and increased mortality. METHODS: The health literacy literature was reviewed for: definitions, scope, risk factors, assessment, impact on health outcomes (cardiovascular disease and heart failure), and interventions. Implications for future research and for clinical practice to address health literacy in heart failure patients were summarized. RESULTS: General health literacy principles should be applied to patients with heart failure, similar to others with chronic conditions. Clinicians treating patients with heart failure should address health literacy using five steps: recognize the consequences of low health literacy, screen patients at risk, document literacy levels and learning preferences, and integrate effective strategies to enhance patients' understanding into practice. CONCLUSION: Although the literature specifically addressing low health literacy in patients with heart failure is limited, it is consistent with the larger body of health literacy evidence. Timely recognition of low health literacy combined with tailored interventions should be integrated into clinical practice.

Superior predictive ability for death of a basic metabolic profile risk score.

BACKGROUND: The basic metabolic profile (BMP) is a common blood test containing information about standard blood electrolytes and metabolites. Although individual variables are checked for cardiovascular health and risk, combining them into a total BMP-derived score, as to maximize BMP predictive ability, has not been previously attempted. METHODS: Patients (N = 279,337) that received a BMP and had long-term follow-up for death were studied. Risk models were created in a training group (60% of study population, n = 167,635), validated in a test group (40% of study population, n = 111,702), and confirmed in the NHANES III (Third National Health and Nutrition Examination Survey) participants (N = 17,752). The BMP models were developed for 30-day, 1-year, and 5-year death using logistic regression with adjustment for age and sex. The BMP parameters were categorized as low, normal, or high based on the standard range of normal. Glucose was categorized as normal, intermediate, and high. Creatinine >or=2 mg/dL was further categorized as very high. RESULTS: Average age was 53.2 +/- 20.1 years, and 44.3% were male. The areas under the curve for the training and test groups for 30-day, 1-year, and 5-year death were 0.887 and 0.882, 0.850 and 0.848, and 0.858 and 0.847, respectively. The predictive ability of these risk scores was further confirmed in the NHANES III population and independent of the Framingham Risk Score. CONCLUSION: In large, prospectively followed populations, a highly significant predictive ability for death was found for a BMP risk model. We propose a total BMP score as an optimization of this routine baseline test to provide an important new addition to risk prediction.

Incremental survival benefit with adherence to standardized heart failure core measures: a performance evaluation study of 2958 patients.

BACKGROUND: In 2002, the Joint Commission on Accreditation of Healthcare Organizations (JCAHO) established four heart failure (HF) core measures to standardize and improve health care quality in the United States. Although adherence to these HF care processes may be improving, their collective impact on survival is not yet settled. METHODS: JCAHO HF measures were implemented within a 20-hospital health care system. Eligible patients had a principal discharge diagnosis of HF. Metrics representing compliance with these measures were derived and their relationship with 1-year survival was examined using an adjusted Cox proportional hazards regression. RESULTS: A total of 2958 patients met study criteria. The average age was 73 years, 50% were male, and 9.9% were smokers. One-year survival benefits were seen in an item-by-item evaluation of HF measures for angiotensin-converting enzyme inhibitor/angiotensin receptor blocker therapy (hazard ratio [HR] = 0.69), left ventricular function assessment (HR = 0.83), and patient education (HR = 0.79). When assessed collectively, improved survival was seen among patients eligible for two (HR = 0.53), three (HR = 0.36), or four HF measures (HR = 0.65). Further, we found a positive and incremental relationship between the degree of adherence and survival (P = .008). CONCLUSION: Adherence to JCAHO HF core measures is associated with improved 1-year survival after HF hospitalization. This validates these simple and effective performance measures and justifies efforts to implement them in all eligible patients with HF.

Long-term outcomes of cardiac transplantation for peri-partum cardiomyopathy: a multiinstitutional analysis.

BACKGROUND: Outcomes of patients with a prior diagnosis of peri-partum cardiomyopathy (PPCM) undergoing heart transplantation are not well described but may be worse than for women who undergo transplantation for other etiologies. METHODS: Between 1999 and 2005, 69 women aged younger than 40 underwent transplantation for PPCM in 29 institutions participating in the Cardiac Transplant Research Database. Patients with PPCM were compared with 90 female recipients of similar age with idiopathic dilated cardiomyopathy (IDC) and history of pregnancy (P+), 53 with no prior pregnancy (P-), and with 459 men of a similar age with IDC. Rejection, infection, cardiac allograft vasculopathy, and survival were compared. RESULTS: Recipients with PPCM accounted for 1% of all transplants and 5% of transplants in women. Comparisons of the 4 patient groups were made. The risk of cumulative rejection was higher in the PPCM Group compared with the P- Group (p < 0.04) and the men (p < 0.0001). Cumulative risk of infection was lowest in the PPCM Group. Freedom from cardiac allograft vasculopathy was similar or higher in the PPCM Group compared with the other groups. Finally, the long-term survival of PPCM patients was comparable with the survival of men (p = 0.9), and there was a trend toward improved survival compared with the P+ Group (p = 0.07) and improved survival compared with the P- Group (p = 0.05). CONCLUSIONS: Heart transplantation for PPCM remains relatively infrequent. Survival and freedom from cardiac allograft vasculopathy in patients who receive a transplant for PPCM are no worse than in women who require a transplant for other indications, regardless of parity.

Validation of the Seattle Heart Failure Model in a community-based heart failure population and enhancement by adding B-type natriuretic peptide.

Management of heart failure (HF) remains complex with low 5-year survival. The Seattle Heart Failure Model (SHFM) is a recently described risk score derived predominantly from clinical trial populations that may enable the prediction of survival in patients with HF. This study sought to validate the SHFM in an independent, nonclinical trial-based HF population. Patients (n = 4,077) from the hospital-based Intermountain Heart Collaborative Study registry with a diagnosis of HF were evaluated using prospectively collected data (mean +/- SD follow-up 4.4 +/- 3.1 years). The SHFM was used to calculate a risk score for each patient. Receiver-operating characteristic area under the curve provided SHFM predictive ability for a composite end point of survival free from death, transplantation, or left ventricular assist device implantation. Addition of creatinine, serum urea nitrogen, diabetes status, and B-type natriuretic peptide (BNP) to the SHFM was also evaluated. Patient age averaged 67 +/- 13 years and 61% were men. Area under the curves were 0.70 (95% confidence interval 0.66 to 0.70), 0.67 (95% confidence interval 0.66 to 0.69), 0.67 (95% confidence interval 0.065 to 0.68), and 0.66 (95% confidence interval 0.63 to 0.67) for 1-, 2-, 3-, and 5-year survivals, respectively. Area under the curves were slightly attenuated in patients >75 years of age (n = 1,339), implantable cardioverter-defibrillator recipients (n = 693), and patients with an ejection fraction >40% (n = 1,634). BNP added significantly to the model (area under the curve +0.06). BNP was found to add additional predictive ability at 1 year (area under the curve change +0.05) and nominally at 5 years (area under the curve change +0.02). In conclusion, the SHFM predicts survival in patients with HF in a hospital-based population, with areas under the curve similar to those from data on which models were initially fit.

The paradox of obesity in patients with heart failure.

PURPOSE: Heart failure (HF) patients often have comorbid conditions that confound management and adversely affect prognosis. The purpose of this study was to determine whether the obesity paradox is also present in hospitalized HF patients in an integrated healthcare system. DATA SOURCES: A cohort of 2707 patients with a primary diagnosis of HF was identified within an integrated, 20-hospital healthcare system. Patients were identified by ICD-9 codes or a left ventricular ejection fraction < or =40% dating back to 1995. Body mass index (BMI) was calculated using the first measured height and weight when hospitalized with HF. Survival rates were calculated using Kaplan Meier estimation. Hazard ratios for 3-year mortality with 95% confidence intervals were assessed using Cox regression, controlling for age, gender, and severity of illness at time of diagnosis. CONCLUSIONS: Three-year survival rates paradoxically improved for patients with increasing BMI. Survival rates for the larger three BMI quartiles were significantly better than for the lowest quartile after adjusting for severity of illness, age, and gender. IMPLICATIONS FOR PRACTICE: While obesity increases the risk of developing HF approximately twofold, reports involving stable outpatients suggest that obesity is associated with improved survival after the development of HF. This finding is paradoxical because obesity increases the risk and worsens the prognosis of other cardiovascular diseases.