Unadjusted in-hospital mortality rates by precipitating factors for heart failure admission. ACSs indicates acute coronary syndromes.
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Fonarow GC, Abraham WT, Albert NM, et al. Factors Identified as Precipitating Hospital Admissions for Heart Failure and Clinical Outcomes: Findings From OPTIMIZE-HF. Arch Intern Med. 2008;168(8):847–854. doi:10.1001/archinte.168.8.847
Copyright 2008 American Medical Association. All Rights Reserved. Applicable FARS/DFARS Restrictions Apply to Government Use.2008
Few studies have examined factors identified as contributing to heart failure (HF) hospitalization, and, to our knowledge, none has explored their relationship to length of stay and mortality. This study evaluated the association between precipitating factors identified at the time of HF hospital admission and subsequent clinical outcomes.
During 2003 to 2004, 259 US hospitals in OPTIMIZE-HF submitted data on 48 612 patients, with a prespecified subgroup of at least 10% providing 60- to 90-day follow-up data. Identifiable factors contributing to HF hospitalization were captured at admission and included ischemia, arrhythmia, nonadherence to diet or medications, pneumonia/respiratory process, hypertension, and worsening renal function. Multivariate analyses were performed for length of stay, in-hospital mortality, 60- to 90-day follow-up mortality, and death/rehospitalization.
Mean patient age was 73.1 years, 52% of patients were female, and mean ejection fraction was 39.0%. Of 48 612 patients, 29 814 (61.3%) had 1 or more precipitating factors identified, with pneumonia/respiratory process (15.3%), ischemia (14.7%), and arrhythmia (13.5%) being most frequent. Pneumonia (odds ratio, 1.60), ischemia (1.20), and worsening renal function (1.48) were independently associated with higher in-hospital mortality, whereas uncontrolled hypertension (0.74) was associated with lower in-hospital mortality. Ischemia (1.52) and worsening renal function (1.46) were associated with a higher risk of follow-up mortality. Uncontrolled hypertension as a precipitating factor was associated with lower postdischarge death/rehospitalization (hazard ratio, 0.71).
Precipitating factors are frequently identified in patients hospitalized for HF and are associated with clinical outcomes independent of other predictive variables. Increased attention to these factors, many of which are avoidable, is important in optimizing the management of HF.
clinicaltrials.gov Identifier: NCT00344513
Heart failure (HF) is the leading cause of hospitalization among US adults older than 65 years, and these hospitalizations contribute substantially to the high costs of the disease. There are 3.6 million hospitalizations with HF as the primary or a secondary cause each year in the United States.1,2 Hospitalizations for HF are also associated with substantial morbidity and mortality; the likelihood of death and rehospitalization is considerably greater than for a comparable period of chronic but stable HF.3,4 Understanding precipitants that contribute to exacerbations of HF and lead to HF admissions, particularly those that are avoidable, is of great importance to clinicians and could favorably influence HF disease management.
A number of factors have been identified that may acutely exacerbate HF and contribute to hospitalization for it. These include arrhythmias, myocardial ischemia, respiratory infection, uncontrolled hypertension, and nonadherence to medications and diet.3-9 However, relatively few studies have examined the frequency at which these factors are present among patients hospitalized for HF.5-9 Most available data are limited by being obtained from relatively small numbers of patients hospitalized at a single center or derived from observations of patients enrolled in clinical trials, which have select enrollment criteria and closer monitoring than under usual care settings.5-9 Analyses of large representative patient populations from all regions of the country and all types of hospitals are critical in providing insight into the frequency of factors that precipitate HF hospitalizations. Furthermore, whether there is an association between factors identified at the time of hospital admission as contributing to HF exacerbation and subsequent clinical outcomes has not been previously studied, to our knowledge.
The Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure (OPTIMIZE-HF) is a registry and performance-improvement program for patients hospitalized for HF.10 The objectives of this analysis of OPTIMIZE-HF data were to determine the frequency at which various factors contributing to HF hospitalization are identified and to improve the understanding of whether and to what extent these factors influence clinical outcomes, including hospital length of stay, in-hospital mortality, early postdischarge mortality, and death/rehospitalization.
OPTIMIZE-HF is a comprehensive hospital-based registry and process-of-case improvement program designed to provide optimal medical care and education to patients hospitalized for HF. The OPTIMIZE-HF program has been described in detail elsewhere10-13 and will be briefly summarized.
Hospital teams used HF case-ascertainment methods identical to those of The Joint Commission.14 Patients qualified for enrollment if they were hospitalized for episodes of new or worsening HF as the primary cause of admission or if significant HF symptoms developed during hospitalization for another primary diagnosis, with HF being the primary discharge diagnosis.10-13 Consecutive patients were enrolled irrespective of their ventricular function, including systolic dysfunction documented by a left ventricular ejection fraction less than 40%, HF symptoms in the setting of preserved left ventricular systolic function (diastolic dysfunction HF), or HF without left ventricular function measurement.10-13
From March 1, 2003, to December 31, 2004, 48 612 patients hospitalized at 259 centers in the United States were enrolled in the OPTIMIZE-HF registry. All regions of the United States were represented, and institutions from community hospitals to large tertiary medical centers participated.10,11 A prespecified patient subgroup (targeted to be ≥ 10% of the total number) was followed up for 60 to 90 days after discharge for the collection of outcomes data, as previously described.10 Sites had the option of participating in the follow-up data collection, and the protocol was approved by each participating center's institutional review board or through use of a central institutional review board. Ninety-one hospitals provided 60- to 90-day follow-up data, and this cohort was demographically similar to patients in the overall registry.10-13 Automated electronic data checks were used to prevent out-of-range entry or duplicate patients. A database audit was performed, on the basis of predetermined criteria, of a random sample of 5% of the first 10 000 patients verified against source documents.10,11 Written informed consent was obtained before enrollment from patients who participated in the follow-up data collection. Participants were screened for inclusion before hospital discharge or identified from administrative databases subsequent to discharge.
The registry captured data on important characteristics (demographic, pathophysiologic, and clinical), treatment patterns, and outcomes of patients hospitalized for HF by means of the Web-based case report form. Data on factors contributing to exacerbation of the patients' HF were prespecified and collected as follows: ischemia/acute coronary syndromes (ACSs), uncontrolled hypertension, pneumonia/respiratory process, worsening renal function, arrhythmia, nonadherence–diet, nonadherence–medications, and other. More than 1 factor could be selected if applicable. Admission staff, medical staff, or both recorded race/ethnicity, usually as the patient was registered. Previous studies in patients hospitalized for HF have suggested differences in characteristics and outcomes based on race/ethnicity. The registry coordinating center was Outcome Sciences Inc (Cambridge, Massachusetts).
All statistical analyses were performed independently at the Duke Clinical Research Institute. The data are reported as mean and standard deviation for continuous variables and as percentages of nonmissing values for categorical variables. Patient characteristics and evidence-based treatments at hospital discharge were compared by Pearson χ2 test for categorical variables and Wilcoxon rank sum test for continuous variables. Multivariate models of in-hospital death, length of hospital stay, postdischarge mortality, and postdischarge death or rehospitalization were developed to be used for consistent covariate adjustment across all studies as previously described.10-13 The types of models were logistic for in-hospital mortality, general linear modeling for length of stay, Cox proportional hazards for postdischarge mortality, and logistic for postdischarge mortality and rehospitalization (date of rehospitalization was not available for survival modeling). The model-development process was similar for all 4 outcomes and used stepwise and backward variable selection methods. The linearity assumption for continuous measures was evaluated by means of restricted cubic spline transformations. When needed, appropriate transformations such as piecewise linear splines were applied. P < .05 was used for both entry and remaining in the model. The potential covariates were preselected, with 45 for in-hospital mortality, 39 for length of stay, 19 for postdischarge mortality, and 70 for postdischarge mortality or rehospitalization (posted at http://www.optimize-hf.org).10-13 To test the association of precipitating factors and clinical outcomes in the final adjusted models, indicators for the presence or absence of each precipitating factor were added to the previously developed models. Additional models were constructed to compare risk-adjusted outcomes for patients with no vs 1 or more precipitating factors identified. SAS version 8.2 statistical software (SAS Institute Inc, Cary, North Carolina) was used for all statistical analyses.
The OPTIMIZE-HF enrolled a total of 48 612 patients hospitalized for HF at 259 academic and community hospitals of varying size from all regions of the United States. Mean patient age was 73.1 years; 52% of patients were female and 74% were white (Table 1). Comorbidities were frequent and included hypertension in 71% of patients, diabetes mellitus in 42%, and chronic obstructive pulmonary disease in 28%. The cause of HF was ischemic in 46% of enrolled patients, and the mean left ventricular ejection fraction was 39.0%. Of patients assessed, 48.8% had documented left ventricular systolic dysfunction and 51.2% had HF with preserved systolic function. The follow-up cohort included 5791 patients, whose characteristics were similar to those of the overall registry (Table 1).
One or more precipitating factors for HF admission were identified in 61.3% of patients. The frequencies of these individual factors are shown in Table 1 for the hospital and follow-up cohorts. The precipitating factors of pneumonia/respiratory processes (15.3%), ischemia/ACSs (14.7%), arrhythmia (13.5%), and uncontrolled hypertension (10.7%) were identified as the most common in the hospital cohort. Nonadherence to medications was identified in 8.9% and nonadherence to diet in 5.2% of patients. Two or more precipitating factors were identified in 9310 patients (19.2%) (Table 1). Specific precipitating factors were identified with greater frequency among the follow-up cohort.
There were 1834 in-hospital deaths reported among 48 612 enrolled patients (3.8%). The in-hospital mortality rates (unadjusted) by precipitating factors are shown in the Figure. Patients in whom no precipitating factor was identified were at modestly lower risk of in-hospital mortality than those with 1 or more precipitating factors risk (3.4% vs 4.0%; adjusted odds ratio, 0.88; 95% confidence interval, 0.78-1.00; P = .046). Risk-adjusted in-hospital mortality was significantly increased when admission was related to pneumonia/respiratory process, ischemia/ACSs, or worsening renal function (Table 2). Admission with uncontrolled hypertension or nonadherence to diet as a contributing factor was associated with a lower risk-adjusted in-hospital mortality. There were no significant interactions between the precipitating factors within the models. Other covariates that were independently associated with in-hospital mortality included patient age, admission systolic blood pressure and heart rate, serum sodium and creatinine levels, and comorbidities such as chronic obstructive pulmonary disease, liver disease, and peripheral vascular disease (data posted at http://www.optimize-hf.org). The median hospital length of stay was 4.0 days (25th-75th interquartile range, 3.0-7.0) and mean length of stay was 6.4 days (SD, 85.2 days). Mean length of stay was shortest (5.1 days) in patients with uncontrolled hypertension and nonadherence to medications and longest in patients with worsened renal function (6.9 days). In multivariate analysis, arrhythmia, pneumonia/respiratory process, and worsening renal function were associated with significantly longer risk-adjusted length of stay, whereas uncontrolled hypertension, nonadherence to diet, and nonadherence to medications were associated with shorter risk-adjusted length of stay (Table 2).
During the 60- to 90-day period after hospital discharge, the follow-up cohort experienced 465 deaths (8.3%), occurring a median of 42.0 days (25th-75th interquartile range, 24.0-66.0) after discharge. Rehospitalization within the follow-up period occurred in 1715 patients (29.6%). The combined end point of death/rehospitalization was met in 36.0% of patients. The rates of death and death/rehospitalization for patients with each of the precipitating factors are shown in Table 3. Patients without a precipitating factor identified had risk-adjusted postdischarge mortality similar to that of patients with 1 or more precipitating factors (6.9% vs 8.9%; adjusted odds ratio, 0.84; 95% confidence interval, 0.66-1.07; P = .15). Risk-adjusted postdischarge mortality was significantly increased in patients whose admission was precipitated by ischemia/ACSs or worsening renal function, independent of other predictive variables (Table 4; additional data posted at http://www.optimize-hf.org). Among patients with uncontrolled hypertension, there was significantly decreased risk-adjusted in-hospital mortality and significantly decreased mortality or readmission at 60 to 90 days after discharge. None of the other precipitating factors were associated with significantly higher or lower postdischarge death/rehospitalization.
The OPTIMIZE-HF has demonstrated that, among a large, representative population of patients admitted to the hospital for HF, 1 or more exacerbating factors contributing to HF hospitalization were identified in most patients. The contributing factors of pneumonia/respiratory processes (15.3%), ischemia (14.7%), arrhythmia (13.5%), and uncontrolled hypertension (10.7%) were identified the most frequently. Certain of these precipitating factors were independently associated with worse clinical outcomes. Pneumonia/respiratory processes and worsening renal function as precipitating factors for hospitalization identified patients at significantly increased risk of greater length of stay and in-hospital mortality. Ischemia and worsening renal function as precipitating factors for admission were associated with increased risk of mortality at 60 to 90 days after discharge. Nonadherence to medications, nonadherence to diet, and uncontrolled hypertension each were associated with shorter stay and lower in-hospital mortality. These findings provide important insights into the factors that contribute to admission for HF and their influence on subsequent outcomes.
Worsening of renal function during hospitalization for HF has previously been identified as being associated with worse outcomes.15,16 The OPTIMIZE-HF data further extend those findings and demonstrate that HF admission precipitated by worsening renal function is also associated with significantly worse patient outcomes, both in-hospital and after discharge. The finding that pneumonia or another respiratory process as an admission precipitant is associated with increased mortality is consistent with previous studies of administrative databases showing that patients hospitalized for HF and chronic obstructive pulmonary disease or pneumonia have higher mortality risk.17 Improved in-hospital and postdischarge prognosis among patients with HF admitted with highly elevated systolic blood pressure has been previously reported and parallels the finding that uncontrolled hypertension as a precipitant of HF admission is associated with better outcomes.11 Patients with decompensation of HF resulting from uncontrolled hypertension can usually be readily stabilized in the hospital with blood pressure control with relatively short length of stay and lower risk of adverse near-term outcomes.11
Patient adherence to dietary restrictions and evidence-based medications is a cornerstone of HF disease management, and nonadherence to medications has been associated with increased risk of hospitalization and mortality in outpatients with chronic HF.2,3,18 Patients with nonadherence to medications or diet are likely to be admitted with excessive sodium retention, which was the leading decompensation factor in 55% of 975 patients in a retrospective audit at 2 large midwestern medical centers.19 These patients may more readily achieve compensation in response to salt restriction, adjustment of diuretics, and provision of medications during the inpatient hospitalization. It should be noted that patients with nonadherence to medications or diet as an admission precipitant were at high adjusted risk of 60- to 90-day postdischarge mortality and death/rehospitalization similar to the overall HF population. Patients identified as nonadherent to medications would be expected to be counseled during the index hospitalization regarding the importance of adherence to their medical regimen and thus may be less likely, at least in the short term, to repeat the medication nonadherence that precipitated a recent HF hospitalization. It should also be emphasized that the use of evidence-based HF medications in eligible patients at discharge is strongly associated with improved postdischarge outcomes.12
Previous studies have assessed the frequency at which precipitating factors are present among hospitalized patients with HF.5-9 A single-center study using retrospective chart review reported on causal factors among 435 patients hospitalized for HF.5 The most commonly identified factors for HF exacerbations leading to hospitalization in that study were acute chest pain in 33% of patients, respiratory tract infection in 16%, uncontrolled hypertension in 15%, and nonadherence to medications in 15%. An analysis of 328 HF hospitalizations from 161 unique patients referred to a hospital HF service for transplantation in Italy showed the most common potential causative factors to be the presence of arrhythmias in 24% of hospitalizations, infections in 23%, poor adherence in 15%, and angina in 14%.6 Study of 179 consecutive patients admitted to a teaching hospital in Germany identified dietary sodium excess in 43% of patients, nonadherence to medications in 24%, ischemia in 13%, and uncontrolled hypertension in 8%.7 Another single-center study reported on precipitating factors leading to decompensation of HF in 101 patients of low socioeconomic status using systematic patient interviews and medical record review.8 The most common precipitating factors identified were lack of adherence to a low-sodium diet, medications, or both in 64% of patients. Uncontrolled hypertension was an identified cause in 44% and cardiac arrhythmias in 29% of patients. A multicenter study of HF precipitating factors involving 768 patients with systolic HF enrolled in the Randomized Evaluation of Strategies for Left Ventricular Dysfunction Pilot Study included a total of 323 episodes of worsening of HF in 180 patients, whether resulting in an HF hospitalization or not, during 43 weeks of follow-up.9 Factors implicated in worsening of HF status in that study included nonadherence to salt restriction (22% of patients); pulmonary infections (20%); use of antiarrhythmic agents (15%), arrhythmias (13%), and calcium-channel blockers (13%); and inappropriate reductions in HF therapy (10%).
Each of these studies had 1 or more major limitations, including retrospective nature of the data collection, limited number of patients studied, involvement of a single center, referral of patients to a specialty service or enrollment of select patients in a double-blind trial of systolic HF therapy, and inability to define whether the precipitant was a cause or an effect of HF exacerbation.9 Identifying precipitants of HF exacerbation within the context of a clinical trial raises the issue of patient selection bias because these patients are more likely to adhere to medical advice and receive closer follow-up than in a usual care setting. Thus, the patients in these previous studies may not represent the general hospitalized HF population, limiting the applicability of the findings.
The strengths of the present study include that it was performed with the use of a systematic approach to identify factors contributing to HF hospitalization and was conducted in 259 US hospitals from all regions of the country with a well-defined cohort of patients.10-13 Another important feature of the present study is that it is the first, to our knowledge, that assessed the relationship between precipitating factors and clinical outcomes independent of other prognostic variables. Understanding whether and to what extent precipitants of HF hospitalization influence length of stay, mortality, and rehospitalization risk is important because this knowledge may help guide clinicians in designing more effective management strategies for hospitalized patients with HF and to prevent HF hospitalizations.3,20
National HF guidelines recommend that patients hospitalized for HF undergo evaluation for precipitating factors and suggest that proper detection and treatment of precipitating factors is an important part of the management of acute decompensated HF.3 These recommendations were level of evidence C, expert opinion only. These OPTIMIZE-HF data lend further support to these recommendations and provide data demonstrating that certain precipitating factors are associated with clinical outcomes independent of other established prognostic factors. Patients identified as being at higher risk of adverse outcomes may benefit from closer monitoring during hospitalization and more frequent follow-up after discharge. Several of these precipitating factors, including nonadherence to diet and medications, may be influenced by optimizing patient education techniques and disease management strategies.2,3,20 Because pneumonia/respiratory process was the most common precipitating factor and was associated with worse outcomes, every effort should be made to prevent pneumonia in patients with HF, including rigorous influenza and pneumococcal vaccination.3 Risk of ischemia and ACSs may be reduced with antiplatelet agents, statin therapy, and, possibly, revascularization in eligible patients.2,3 Disease management programs and treatment plans for patients with HF should include appropriate strategies for these concomitant conditions, and exacerbation of these conditions should be avoided to the extent possible.2,3 Future studies should be designed to prospectively test interventions targeting these contributing factors in this high-risk HF patient population.
This analysis of OPTIMIZE-HF data may be influenced by several limitations. Precipitating factors of HF were abstracted from documentation in the medical record and may have been underreported. It is known that patient interview or clinician impression may be insufficient to detect poor adherence to medications or diet.21 Follow-up data were obtained in a subset of patients and were limited to 60 to 90 days. Participation in OPTIMIZE-HF was voluntary, and sites received payment to defray costs associated with data collection. These findings may not apply to hospitals that differ from OPTIMIZE-HF hospitals in patient characteristics or care patterns, although a recent study22 suggests that Medicare patients enrolled in OPTIMIZE-HF had demographics similar to those of Medicare patients hospitalized for HF in the nation as a whole. Given the overall large number of patients observed, some differences, though statistically significant, may not be clinically relevant. Also, despite multivariate analyses, we cannot exclude that residual measured and unmeasured confounding accounts for some of these observations. Despite these limitations, this analysis provides new insights into the factors contributing to HF hospitalizations from a large representative data set of patients hospitalized for HF from all regions of the country and including patients with preserved systolic function and multiple comorbidities.
Deterioration of clinical status leading to HF hospitalizations is frequently accompanied by identifiable factors that contribute to decompensations beyond the underlying HF disease state. Among patients admitted for an HF hospitalization in OPTIMIZE-HF, close to two-thirds of patients had 1 or more precipitating factors identified. The most common factors identified as precipitants of HF exacerbations necessitating hospitalization include arrhythmia, ischemia, pneumonia/respiratory process, and nonadherence to diet and medications. Furthermore, factors contributing to HF admission identify patients at higher and lower risk of in-hospital and postdischarge adverse outcomes, independent of other predictive variables. Increased attention to these factors, many of which are avoidable, is important in optimizing the management of HF.
Correspondence: Gregg C. Fonarow, MD, Ahmanson-UCLA Cardiomyopathy Center, UCLA Medical Center, 10833 LeConte Ave, Room 47-123 CHS, Los Angeles, CA 90095-1679 (email@example.com).
Accepted for Publication: November 11, 2007.
Author Contributions: Dr Fonarow had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Fonarow, Abraham, Albert, Stough, Greenberg, and O’Connor. Acquisition of data: Fonarow, Abraham, Albert, Greenberg, and Young. Analysis and interpretation of data: Fonarow, Abraham, Albert, Gheorghiade, Greenberg, O’Connor, Pieper, Sun, Yancy, and Young. Drafting of the manuscript: Fonarow and Greenberg. Critical revision of the manuscript for important intellectual content: Fonarow, Abraham, Albert, Stough, Gheorghiade, Greenberg, O’Connor, Pieper, Sun, Yancy, and Young. Statistical analysis: Fonarow, Pieper, and Sun. Obtained funding: Fonarow. Administrative, technical, and material support: Fonarow and Abraham. Study supervision: Fonarow, Greenberg, and O’Connor.
Financial Disclosure: Dr Fonarow has received research grants from Amgen, Biosite, Bristol-Myers Squibb, Boston Scientific/Guidant, GlaxoSmithKline, Medtronic, Merck & Co, Pfizer, Sanofi-Aventis, Scios Inc, and the National Institutes of Health (NIH). He is or has been on the speakers' bureau or has received honoraria in the past 5 years from Amgen, AstraZeneca, Biosite, Bristol-Myers Squibb, Boston Scientific/Guidant, GlaxoSmithKline, Kos, Medtronic, Merck & Co, NitroMed, Pfizer, Sanofi-Aventis, Schering-Plough, Scios Inc, St Jude Medical, Takeda, and Wyeth. He is or has been a consultant for Biosite, Bristol-Myers Squibb, Boston Scientific/Guidant, GlaxoSmithKline, Medtronic, Merck & Co, NitroMed, Orqis Medical, Pfizer, Sanofi-Aventis, Schering-Plough, Scios Inc, and Wyeth. Dr Abraham has received research grants from Amgen, Biotronik, CHF Solutions, GlaxoSmithKline, Heart Failure Society of America, Medtronic, Myogen, the NIH, Orqis Medical, Otsuka Maryland Research Institute, Paracor, and Scios Inc. He is or has been a consultant or on the speakers' bureau for Amgen, AstraZeneca, Boehringer-Ingelheim, CHF Solutions, GlaxoSmithKline, Guidant Corp, Medtronic, Merck & Co, Pfizer, ResMed, Respironics, Scios Inc, and St Jude Medical. He is on the advisory board of CardioKine, CardioKinetix Inc, CHF Solutions, Department of Veterans Affairs Cooperative Studies Program, Inovise, the NIH, and Savacor Inc. He has received honoraria from AstraZeneca, Boehringer-Ingelheim, GlaxoSmithKline, Guidant Corp, Medtronic, Merck & Co, Pfizer, ResMed, Respironics, Scios Inc, and St Jude Medical. Dr Albert is a consultant for GlaxoSmithKline and Medtronic. She is also on the speakers' bureau for GlaxoSmithKline, Medtronic, NitroMed, and Scios Inc and is employed by the Cleveland Clinic Foundation. Dr Stough has received research grants from Actelion, GlaxoSmithKline, Medtronic, Otsuka, and Pfizer. She is a consultant or on the speakers' bureau for Abbott, AstraZeneca, GlaxoSmithKline, Medtronic, Novacardia, Otsuka, Protein Design Labs, RenaMed, Sigma Tau, and Scios Inc. She has received honoraria from Abbott, AstraZeneca, GlaxoSmithKline, Medtronic, and Pfizer. Dr Gheorghiade has received research grants from the NIH, Otsuka, Sigma Tau, Merck & Co, and Scios Inc. He is or has been a consultant for Debbio Pharm, Errekappa Terapeutici, GlaxoSmithKline, PDL, and Medtronic. He has received honoraria from Abbott, AstraZeneca, GlaxoSmithKline, Medtronic, Otsuka, Protein Design Lab,Scios Inc, and Sigma Tau. Dr Greenberg has received research grant support from Amgen, Cardiodynamics, GlaxoSmithKline, Millennium, Novacardia, Otsuka, Pfizer, Sanofi-Aventis, and Titan. He is on the speaker's bureau/consultant for Amgen, AstraZeneca, GlaxoSmithKline, Guidant Corp, Medtronic, Merck & Co, NitroMed, Pfizer, Remon Medical Technologies, and Scios Inc. He is an advisory board member for CHF Solutions, GlaxoSmithKline, and NitroMed. He has received honoraria from AstraZeneca, GlaxoSmithKline, Medtronic, Merck & Co, NitroMed, Novartis, Pfizer, and Scios Inc. Dr O’Connor has received research grant support from the NIH. He is on the speakers' bureau and/or a consultant for Amgen, AstraZeneca, Bristol-Myers Squibb, GlaxoSmithKline, Guidant Corp, Medtronic, Merck & Co, NitroMed, Novartis, Otsuka, Pfizer, and Scios Inc. He has received honoraria from GlaxoSmithKline, Pfizer, and Otsuka. Mss Pieper and Sun are employees of the Duke Clinical Research Institute. Dr Yancy has received research grants from Cardiodynamics, GlaxoSmithKline, Scios Inc, Medtronic, and NitroMed. He is also a consultant or on the speakers' bureau for AstraZeneca, Cardiodynamics, GlaxoSmithKline, Medtronic, NitroMed, Novartis, and Scios Inc. He is on the advisory board for CHF Solutions, the Food and Drug Administration cardiovascular device panel, and the NIH. He has received honoraria from AstraZeneca, Cardiodynamics, GlaxoSmithKline, Medtronic, Novartis, and Scios Inc. Dr Young has received research grants from Abbott, Acorn, Amgen, Artesion Therapeutics, AstraZeneca, Biosite, GlaxoSmithKline, Guidant Corp, Medtronic, MicroMed, the NIH, Scios Inc, Vasogen, and World Heart. He is a consultant for Abbott, Acorn, Amgen, Biomax Canada, Biosite, Boehringer-Ingelheim, Bristol-Myers Squibb, Cotherix, Edwards Lifescience, GlaxoSmithKline, Guidant Corp, Medtronic, MicroMed, Novartis, Paracor, Proctor & Gamble, Protemix, Scios Inc, Sunshine, Thoratec, Transworld Medical Corp, Vasogen, Viacor, and World Heart.
Funding/Support: GlaxoSmithKline funded the OPTIMIZE-HF registry under the guidance of the OPTIMIZE-HF Steering Committee.
Role of the Sponsor: GlaxoSmithKline was involved in the design and conduct of the OPTIMIZE-HF registry and funded data collection and management through Outcome Inc, data management and statistical analyses through the Duke Clinical Research Institute, and administrative and material support by Accel Health. The sponsor was not involved in the management, analysis, or interpretation of data or the preparation of the manuscript. GlaxoSmithKline did review the manuscript before submission.
Additional Information: All data analyses were performed independently at the Duke Clinical Research Institute by Mss Pieper and Sun, with the input of the OPTIMIZE-HF Steering Committee.
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