Donate Help Contact The AHA Sign In Home
American Heart Association
Circulation: Heart Failure
Search: search_blue_button Advanced Search
Circulation: Heart Failure. 2008;1:91-97
Published online before print May 28, 2008, doi: 10.1161/CIRCHEARTFAILURE.107.743146
Free Article
This Article
Free upon publication Free Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
1/2/91    most recent
CIRCHEARTFAILURE.107.743146v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrowRequest Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Henkel, D. M.
Right arrow Articles by Roger, V. L.
Right arrow Search for Related Content
PubMed
Right arrow Articles by Henkel, D. M.
Right arrow Articles by Roger, V. L.
Related Collections
Right arrow Epidemiology
Right arrow Other heart failure
Right arrow Congestive
Right arrowRelated Article

Original Articles

Death in Heart Failure

A Community Perspective

Danielle M. Henkel, MD; Margaret M. Redfield, MD; Susan A. Weston, MS; Yariv Gerber, PhD and Véronique L. Roger, MD, MPH

From the Department of Medicine (D.M.H), Division of Cardiovascular Diseases, Department of Medicine (M.M.R., Y.G., V.L.R.), Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, Minn (S.A.W., V.L.R.), Department of Epidemiology and Preventive Medicine, School of Public Health, Sackler Medical School (Y.G.), Tel Aviv University, Tel Aviv, Israel.

Correspondence to Véronique L. Roger, MD, MPH, Division of Cardiovascular Diseases, Mayo Clinic, 200 First Street SW, Rochester, MN 55905. E-mail roger.veronique{at}mayo.edu

Received October 2, 2007; accepted May 7, 2008.


    Abstract
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Background— Mortality in patients with heart failure (HF) remains high, but causes of death are incompletely defined. As HF is a heterogeneous syndrome categorized according to the ejection fraction (EF), the association between EF and causes of death is important, yet elusive.

Methods and Results— Community subjects with HF were classified according to the preserved (≥50%) and the reduced EF (<50%). Deaths were classified as due to coronary heart disease and other cardiovascular and noncardiovascular diseases. Among 1063 persons with HF, 45% had preserved EF with fewer cardiovascular risk factors and less coronary disease than those with reduced EF. At 5 years, survival was 45% (95% CI, 43% to 49%), and 43% of the deaths were noncardiovascular. The leading cause of death in subjects with preserved EF was noncardiovascular disease (49%) versus coronary heart disease (43%) for subjects with reduced EF. The proportion of cardiovascular deaths decreased from 69% in 1979–1984 to 40% in 1997–2002 (P=0.007) among subjects with preserved EF, which is in contrast to a modest change among those with reduced EF (77% to 64%, P=0.08). Advanced age, male sex, diabetes, smoking, and kidney disease were associated with an increased risk of all-cause and cardiovascular deaths. After adjustment, preserved EF was associated with a lower risk of cardiovascular death but not all-cause death.

Conclusions— Community subjects with HF experience a persistently high mortality, and a large proportion of deaths is noncardiovascular. Cardiovascular disease before death is less in subjects with preserved EF, and they are less likely to experience cardiovascular deaths compared with those with reduced EF. In those with preserved EF, the proportion of cardiovascular deaths declined over time.

Key Words: heart failure • ejection fraction • epidemiology • mortality


    Introduction
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Despite progress in the management of heart failure (HF),1 the burden of HF, driven largely by aging of the population, is staggering.2 Mortality rates remain high, with only modest improvements in survival during the past decades.3,4

Editorial see p 89

As HF is a disease of the elderly, subjects with HF have a high prevalence of comorbid conditions,5,6 which can themselves cause death. Although several studies have examined mortality in HF, there is a paucity of knowledge on cause-specific death, particularly according to EF. Indeed, as stated recently in the Journal of the American College of Cardiology, "no study to date has provided detailed data on the causes of deaths in patients with HF and preserved EF, information that should be of value in the development and testing of treatment for this type of HF."7 Finally, whether causes of death are changing over time in HF is unknown. This is important as marginal improvement in survival of patients with HF in the community3,4 could reflect in part a shift in the distributions of the causes of death, with a decrease in cardiovascular deaths, offset by an increase in noncardiovascular deaths in an elderly population.

HF is a syndrome that encompasses heterogeneous disease processes, customarily categorized according to the left ventricular ejection fraction (EF) into HF with preserved EF versus HF with reduced EF.1 The association between mortality and the EF remains controversial,7–18 likely owing to the differences in time period, study design, sample size, and ascertainment of EF across studies.

This study was thus undertaken to address these gaps in knowledge and to examine the overall and cause-specific deaths among a geographically defined cohort of subjects with validated HF and how their distribution may have changed over time. We sought to evaluate whether these differed according to EF and to identify factors associated with increased mortality.


    Methods
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Study Setting
This study was conducted in Olmsted County, Minn. Epidemiological studies in Olmsted County are possible because the county is relatively isolated, and only a few providers deliver nearly all health care to local residents. Healthcare providers in Olmsted County include Mayo Clinic, Olmsted Medical Center, and a handful of private practitioners. Each provider uses a comprehensive medical record system in which the details of every encounter are entered and can be easily retrieved. Medical records are reviewed under the auspices of the Rochester Epidemiology Project, a record-linkage system that allows the indexing of all medical records of Olmsted County residents according to the clinical and pathological diagnoses, surgical procedures, and billing information. This indexing system enables the retrieval of all medical records for use in the epidemiological studies and ensures the complete capture of all healthcare-related events occurring in Olmsted County for local residents. This centralized system encompasses the medical records of a population representing an estimated 3 600 000 person-years of health care. The potential of this data source has been described elsewhere.19 The appropriate institutional review boards approved all aspects of the study.

HF Incidence Cohort
The validated incident HF cohort was assembled from a random sample of all potential HF cases in Olmsted County between 1979 and 2002 and thus does not include all cases of HF in the community within the study period. Cases were identified by screening the medical records of all Olmsted County patients from 1979 to 2002 using the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code 428. Focus on code 428 was based on the previously reported yields of all codes relating to HF.4 Nurse abstractors then reviewed the random sample of 2072 cases and validated HF diagnosis according to the Framingham Criteria.4 Persons who had a clinical diagnosis of HF in their medical record before 1979 or who were not residents of Olmsted County were excluded. After validation, 1063 cases of HF met Framingham criteria and were included in this study. Clinical characteristics, including a detailed assessment of comorbidity, were collected from the medical record.

Clinical Characteristics
Hypertension was defined by the criteria of the 6th report of the Joint National Committee on Detection, Evaluation, and Treatment of High Blood Pressure (6th report, 97). Persons were considered hypertensive if 2 or more ambulatory blood pressure readings were greater than or equal to 140 mm Hg systolic and/or 90 mm Hg diastolic. Physician’s diagnosis of hypertension and treatment with antihypertensive drugs were also considered.

Persons who met the standardized criteria of two consecutive fasting glucose levels greater than or equal to 140 mg/dL or 1- to 2-hour levels greater than or equal to 200 mg/dL obtained using a standard glucose tolerance test before HF were diagnosed with diabetes mellitus according to the National Diabetes Data Group recommendations (Anonymous, classification, 1979). Smoking status was categorized as never or ever (past or current).

Height and weight measurements reported in the last outpatient visit before meeting criteria for HF were abstracted. Body mass index was calculated as weight (in kilograms) divided by height (in meters squared). Documented coronary disease was defined as the occurrence of a myocardial infarction validated with epidemiological criteria,20 a history of coronary surgery, or the presence of significant coronary disease at angiography, occurring before the index date of HF.

Creatinine clearance was calculated using the last outpatient serum creatinine value before the diagnosis of HF by Cockcroft and Gault equation: [(140–age) x (weight in kilograms) x (0.85 for women) / (72 x creatinine) (mg/dL)] and was used as an estimate of glomerular filtration rate after adjustment for body surface area.21 Chronic kidney disease was deemed severe when the glomerular filtration rate was less than or equal to 29 mL/min per 1.73 m2, whereas moderate kidney disease was defined by the glomerular filtration rate of 30 to 59 mL/min per 1.73 m2.22,23

Left ventricular EF (%) was determined using the values collected from any echocardiogram, radionuclide ventriculogram, or left ventricular angiogram performed within 90 days of HF diagnosis. The value closest in time to HF diagnosis was used when multiple values were available. When multiple values were measured as part of one test on the same day, the average value was used. EF greater than or equal to 50% defined HF with preserved EF, whereas reduced EF was defined as EF less than 50%.24

Comorbid conditions were categorized as peripheral vascular/cerebrovascular disease, chronic obstructive pulmonary disease, gastrointestinal or liver disease, cancer, or rheumatologic disease on the basis of ICD-9 and ICD-10 code groupings defined with the Centers for Disease Control and Prevention ICD code finder (http://wonder.cdc.gov/wonder/cgi-bin/asp/ICDFinder.asp). In addition, the Charlson Index25 was used to measure the global burden of comorbidity.

Ascertainment of Death and Cause of Death Classification
Follow-up was performed by using all inpatient and outpatient medical records. The ascertainment of death included several procedures. In addition to the deaths noted during clinical care, all death certificates for Olmsted County residents are obtained each year from the county office. The Mayo Clinic registration office records the obituaries and notices of death in the local newspapers. Finally, data on all Minnesota deaths are obtained from the State of Minnesota every year.

Assignment of the cause of death relied on the underlying cause of death listed on the death certificate and was classified into 3 categories, including coronary heart disease and other cardiovascular and noncardiovascular cause of death, based on ICD-9 and ICD-10 codes. The categories of cardiovascular deaths, including ischemic heart diseases and other cardiovascular diseases, were adapted from the classification used by the American Heart Association.26

The procedures in place in Olmsted County to complete death certificates differ from the procedures in most other locations.27 The coroner (chief medical examiner) or a pathologist member of the staff of the Mayo Clinic completes the death certificates of more than 75% of Olmsted County residents, irrespective of whether an autopsy is performed. The entire medical record is reviewed before assigning the cause of death. Death certificates for in-hospital decedents were not verified manually. However, it is less subject to misclassification than outpatient events because of the availability of the medical record.28 When an autopsy is performed, its findings are taken into account to complete the death certificate and take precedent over the clinical information. Infrequently, the oncologist assigns the cause of death for hospice patients and an internist for nursing home patients. Death certificates for patients under the care of physicians not affiliated with the Mayo Clinic are completed by their physicians.

Statistical Analysis
The data are presented as frequency or mean ± standard deviation. Associations between patient characteristics and EF category were examined with logistic regression. Survival was analyzed with the Kaplan-Meier method. Trends in the cause of death over time were analyzed with logistic regression with a 4-level categorical year variable as the predictor variable, with levels representing 1979–1984, 1985–1990, 1991–1996, and 1997–2002. Trends in baseline characteristics over time were analyzed with linear regression for continuous variables and with the Mantel-Haenszel {chi}2 test for categorical variables. Proportional hazards regression was used to examine the association between death and baseline characteristics. First-order interactions between EF and baseline characteristics were examined and reported when present. Missing values did not exceed 5% for any variable used in the regression analyses except for EF, which was missing in 39% of the cases. Multiple imputation was used to impute missing values using the Markov Chain Monte Carlo method and assuming that the missing data mechanism was missing at random. This means that the probability of missingess may depend on data that are observed but not on values that are missing. The model used to impute EF included demographic variables, cardiovascular risk factors, and comorbidities. Five complete data sets were created for the analyses. The relative efficiency from using 5 imputed data sets is 93%, which is desirable for estimating model parameters. Each of the complete data sets was analyzed using standard statistical analyses. Results were combined, with standard errors obtained using the rules given by Rubin.29 A probability value of 0.05 was selected for the threshold of statistical significance, except when testing for interactions when a probability value of 0.10 was used. Analyses were performed using SAS statistical software, version 8 (SAS Institute, Cary, NC).

The authors had full access to and take full responsibility for the integrity of the data. All authors have read and agree to the manuscript as written.


    Results
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Clinical Characteristics
One thousand sixty-three persons with incident HF diagnosed between 1979 and 2002 were included in the study. Their mean age was 76±12 years, and 46% were men. Most subjects had a prior diagnosis of hypertension or were smokers. Comorbid conditions were common (Table 1). Mean age increased over time (P=0.04) as did the number of comorbidities (P<0.001).


View this table:
[in this window]
[in a new window]

 
Table 1. Clinical Characteristics of Subjects With Heart Failure According to Ejection Fraction
 
Forty-five percent of subjects had HF with preserved EF. These subjects were older and more often women. Subjects with preserved EF had a lesser global burden of cardiovascular risk factors, as they were equally likely to be overweight and hypertensive but less likely to have diabetes mellitus or to have a smoking history compared with their counterparts with reduced EF.

Congruent with the prevalence of cardiovascular risk factors, the antemortem prevalence of documented coronary disease was markedly lower among subjects with preserved EF. This was particularly noticeable for myocardial infarction, which was recorded among 16% of patients with preserved EF compared with 28% among persons with reduced EF (P<0.001). The total comorbidity burden, as measured by the Charlson Index, did not differ according to EF. Among subjects with preserved EF, 52% had a Charlson Index of 2 or more, whereas 56% of subjects with reduced EF had a Charlson Index of 2 or more (P=0.34).

All-Cause and Cardiovascular Deaths
After a median follow-up of 4.3 years (minimum=0 years, maximum=27.7 years), 917 deaths were noted, corresponding to a 5-year survival of 45% (95% CI, 43% to 49%). Overall, 525 (57%) deaths were categorized as cardiovascular. A total of 330 coronary heart disease deaths occurred, which represented 36% of all deaths and 63% of cardiovascular deaths.

Of the 392 (43%) noncardiovascular deaths, the most common causes of death were pulmonary disease (28%) and cancer (25%), followed by central nervous system disease (12%), gastrointestinal disease or genitourinary disease (12%), and diabetes mellitus or endocrine disorders (9%).

Over time, a shift in the distribution of causes of death occurred. The proportion of deaths occurring within 5 years of incident HF that were categorized as cardiovascular decreased from 74% in 1979–1984 to 51% in 1997–2002 (P<0.001).

Advanced age, male sex, diabetes mellitus, history of smoking, and chronic kidney disease were associated with the increased risk of all-cause mortality and cardiovascular mortality (Table 2). In particular, severe chronic kidney disease was associated with more than a 2-fold increase in the risk of overall and cardiovascular death adjusting for other clinical characteristics.


View this table:
[in this window]
[in a new window]

 
Table 2. Predictors of Death Among Subjects With Heart Failure in the Community
 
Death in HF According to EF
Among subjects with preserved EF, death was most commonly attributed to noncardiovascular causes (49% of all deaths; Figure). Noncardiovascular deaths included deaths most commonly due to pulmonary disease (29%) and cancer (23%), followed by central nervous system disease (14%), gastrointestinal or genitourinary disease (11%), and diabetes mellitus or endocrine disorders (7%). Coronary heart disease and other cardiovascular deaths occurred in 29% and 22% of cases, respectively.


Figure 1743146
View larger version (20K):
[in this window]
[in a new window]
[Download PPT slide]
 
Figure. Causes of death by EF.

 
In contrast, among subjects with reduced EF, the leading cause of death was coronary heart disease (43%), whereas 36% of deaths were attributed to noncardiac causes. These included deaths most commonly due to cancer (28%) and pulmonary disease (27%), followed by gastrointestinal or genitourinary disease (14%), central nervous system disease (10%), and diabetes mellitus or endocrine disorders (10%).

Over time, a shift in the distribution of causes of death occurred among those with preserved EF. The proportion of deaths occurring within 5 years of incident HF that were categorized as cardiovascular decreased from 69% in 1979–1984 to 40% in 1997–2002 (P=0.007). In contrast, among subjects with reduced EF, the temporal decrease in the proportion of cardiovascular deaths was modest and not statistically significant (77% in 1979–1984 to 64% in 1997–2002, P=0.08).

EF was not associated with all-cause death (hazard ratio for preserved versus reduced EF, 0.95; 95% CI, 0.81 to 1.11; P=0.52). Adjustment for age, sex, diabetes mellitus, smoking, documented coronary disease, and chronic kidney disease did not unmask any significant association between EF and death (Table 2). Conversely, preserved EF was univariately associated with a markedly lower risk of cardiovascular death (hazard ratio, 0.76; 95% CI, 0.61 to 0.94; P=0.014). This association remained after the adjustment for age, sex, diabetes mellitus, smoking, documented coronary disease, and chronic kidney disease.


    Discussion
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
In the community, all subjects with HF experienced high mortality, irrespective of EF, and the frequency of noncardiovascular deaths is high. Subjects with preserved EF had less documented coronary disease. Accordingly, cardiovascular deaths were less frequent among subjects with preserved EF. Age, male sex, diabetes, smoking, and kidney disease were important indicators of an increased risk of overall and cardiovascular death, whereas reduced EF was associated with an increased risk of cardiovascular death but not all-cause death.

Few studies have reported on cause-specific deaths in HF. Results of such studies underscored that noncardiac causes of death were frequent in HF. In a cohort of hospitalized patients from Canada, this was estimated at nearly one-third.30

The present community-based findings support and extend previous findings by demonstrating that patients with HF have a poor survival and that the frequency of noncardiovascular deaths in this cohort, including both outpatients and hospitalized subjects, is higher than previously reported,30 accounting for nearly half of all deaths. Factors associated with worse survival include advanced age, male sex, preexisting diabetes, smoking history, and chronic kidney disease.16,31,32 In our cohort, patients with HF were becoming older and had increasing comorbidity over the study period. This underscores the importance of the identification and management of comorbid diseases among all patients with HF. Indeed, as noncardiac comorbidities are highly prevalent in patients with HF in the community, further improvement in the survival of patients with HF may be hindered by comorbid conditions, which interfere with HF management strategies and adversely affect outcomes.33

HF is a disease of the elderly, typically with a similar distribution across sexes or a slight female preponderance. Community studies have consistently indicated a high prevalence, even predominance, of preserved EF among subjects with HF.7 As HF is a syndrome, its pathogenesis differs by EF,34 and the mechanisms of HF with preserved EF, although remaining controversial, are likely related to impaired myocardial relaxation and reduced left ventricular compliance, leading to impaired left ventricular filling.34–36 Within this context, examining the cause of death in HF can enhance our understanding of the pathophysiology of the disease.7

Herein, patients with preserved EF were less likely to have a history of diabetes, smoking, or documented coronary disease compared with those with reduced EF. During a long follow-up period, EF was not associated with mortality. These data extend a prior report from our group showing no difference in short-term mortality according to EF.18 Additionally, the SENIORS study of older adults with HF showed no difference in all-cause mortality between patients with preserved or reduced EF.37 Other studies, however, indicated that preserved EF was associated with better survival.7,8,14,15 These conflicting results likely reflect differences in study design, sample size, and cause of death ascertainment and distributions. These methodological considerations are important as they determine the applicability of these results to different populations and thus the clinical usefulness of such data.

To this end, in the Digitalis Investigation Group trial, EF was associated with increased mortality.32 These data present some striking differences compared with the present community study. Indeed, participants in the Digitalis Investigation Group trial were more than 10 years younger than the present community population and included one fourth of women as compared with half in the present study, and 63% of trial enrollees had a history of myocardial infarction compared with 23% herein. Accordingly, 78% of deaths were due to cardiovascular diseases in the Digitalis Investigation Group trial compared with 57% in the present study. Similarly, participants in the Candesartan in Heart Failure: Assessment of Reduction in Mortality and Morbidity trial38 were younger and more likely to be male, with a preponderance of coronary disease and most deaths (85%) of cardiovascular cause. Thus, in the Candesartan in Heart Failure: Assessment of Reduction in Mortality and Morbidity trial, as in the Digitalis Investigation Group, the association between EF and overall mortality reflects the characteristics and outcomes of selected clinical trial participants that differ markedly from that of community populations. The discrepancies between the clinical trial findings and the present community-based data illustrate the limitations of extrapolating the observations made in clinical trials to the community.39 Among hospitalized patients in Ontario, no association between EF and survival was detected.40 This study, however, included only subjects who underwent an assessment of EF, which represented only 42% of all patients with HF hospitalized during the time period. Thus, this by design led to a substantial selection bias, which may have impact on the external validity of these results amplified by the fact that outpatient subjects with HF were excluded. This underscores in turn the importance and relevance of the present data to the community practice. These findings contribute to resolving the aforementioned controversy on the impact of EF on death in HF by indicating that preserved EF carries a lower risk of cardiovascular, but not overall, death. Patients with preserved EF have fewer comorbid cardiovascular conditions than do their counterparts with reduced EF; thus, deaths from noncardiac causes predominate among subjects with preserved EF. Further, the present study indicates that the proportion of cardiovascular deaths has decreased over time among subjects with HF and preserved EF, a finding previously not reported, which should be interpreted in light of a previous report from our group indicating that the prevalence of HF with preserved EF increased over time, with no improvement in survival among these patients.8 This may help to explain findings such as those in the Perindopril in Elderly People with Chronic Heart Failure study, in which older patients with preserved EF had no 1-year mortality benefit with use of perindopril therapy.41 Indeed, the present findings extend data by indicating that within the context of stable overall survival, the distribution of the causes of death is shifting toward less cardiovascular causes, which has important implications for the understanding of secular trends in HF and for therapeutic trials for this condition.

Limitations and Strengths
As no study will be generalizable to the entire US population, the racial and ethnic composition of the present population may impact the extrapolation of the data to under-represented populations. Although the population of the present study consists mainly of white subjects, the value of Olmsted County studies lies in the ability to measure in one population the occurrence of disease and subsequent outcomes and provide benchmarks for needed comparisons to other populations. Ascertainment of the cause of death relied on death certificates. The procedure for death certificate completion, as indicated in the Methods section, is standardized. The validity of a death certificate to diagnose deaths due to coronary disease in the outpatient setting is robust.42 Although we cannot exclude that some deaths could be misclassified, it seems unlikely, however, that misclassification would differ appreciably according to EF such that it should not affect the primary findings of the study. Further, misclassification tends to be less problematic for broad categories of death causes, such as were used herein. We acknowledge that there are limitations to the Framingham criteria for the diagnosis of HF.43,44

Our community-based study has notable strengths. The HF cohort, validated using standardized criteria,18 includes both inpatient and outpatient data. Our findings address the stated need for more data on the cause of death among subjects with preserved EF7 in a community cohort, which optimizes its applicability to clinical practice. EF was directly measured in a larger proportion of subjects than most previous reports.45 Further, multiple imputation was used to impute EF values when EF was not directly measured, thereby enabling to report on the entire experience of all subjects with HF in the community. This methodology provides unbiased estimates and, therefore, is a better approach to handling missing data than using an indicator variable to represent missing EF that has known biases.46

Conclusions
Community subjects with HF experience high mortality whether EF is preserved or reduced, and the frequency of noncardiovascular deaths is high. Subjects with preserved EF have a lower burden of cardiovascular comorbidity before death and experience fewer cardiovascular deaths than do subjects with reduced EF. Among subjects with preserved EF, the proportion of noncardiovascular deaths increases over time. These findings underscore the heterogeneity of HF and have implications for the design and interpretation of interventions aiming at reducing mortality in HF.


    Acknowledgments
 
We thank the following individuals for their support with data collection, data entry, and manuscript preparation: Kay A Traverse, RN, Susan Stotz, RN, and Kristie K. Shorter.

Sources of Funding

This study was supported in part by grants from the Public Health Service and the National Institutes of Health (AR30582, R01 HL59205, R01 HL72435, RO1 HL64112).

Disclosures

None.


    References
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
1. Hunt SA. ACC/AHA 2005 guideline update for the diagnosis and management of chronic heart failure in the adult: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Writing Committee to Update the 2001 Guidelines for the Evaluation and Management of Heart Failure). J Am Coll Cardiol. 2005; 46: e1–e82.[Free Full Text]

2. Stewart S, MacIntyre K, Capewell S, McMurray JJ. Heart failure and the aging population: an increasing burden in the 21st century? Heart. 2003; 89: 49–53.[Abstract/Free Full Text]

3. Levy D, Kenchaiah S, Larson MG, Benjamin EJ, Kupka MJ, Ho KK, Murabito JM, Vasan RS. Long-term trends in the incidence of and survival with heart failure. N Engl J Med. 2002; 347: 1397–1402.[Abstract/Free Full Text]

4. Roger VL, Weston SA, Redfield MM, Hellermann-Homan JP, Killian J, Yawn BP, Jacobsen SJ. Trends in heart failure incidence and survival in a community-based population. JAMA. 2004; 292: 344–350.[Abstract/Free Full Text]

5. Brown AM, Cleland JG. Influence of concomitant disease on patterns of hospitalization in patients with heart failure discharged from Scottish hospitals in 1995. Eur Heart J. 1998; 19: 1063–1609.[Abstract/Free Full Text]

6. Dahlstrom U. Frequent non-cardiac comorbidities in patients with chronic heart failure. Eur J Heart Fail. 2005; 7: 309–316.[CrossRef][Medline]

7. Hogg K, Swedberg K, McMurray J. Heart failure with preserved left ventricular systolic function; epidemiology, clinical characteristics, and prognosis. J Am Coll Cardiol. 2004; 43: 317–327.[Abstract/Free Full Text]

8. Owan TE, Hodge DO, Herges RM, Jacobsen SJ, Roger VL, Redfield MM. Trends in prevalence and outcome of heart failure with preserved ejection fraction. N Engl J Med. 2006; 355: 251–259.[Abstract/Free Full Text]

9. Ahmed A. A propensity matched study of New York Heart Association class and natural history end points in heart failure. Am J Cardiol. 2007; 99: 549–553.[CrossRef][Medline]

10. Pocock SJ, Wang D, Pfeffer MA, Yusuf S, McMurray JJ, Swedberg KB, Ostergren J, Michelson EL, Pieper KS, Granger CB. Predictors of mortality and morbidity in patients with chronic heart failure. Eur Heart J. 2006; 27: 65–75.[Abstract/Free Full Text]

11. Senni M, Tribouilloy CM, Rodeheffer RJ, Jacobsen SJ, Evans JM, Bailey KR, Redfield MM. Congestive heart failure in the community: trends in incidence and survival in a 10-year period. Arch Intern Med. 1999; 159: 29–34.[Abstract/Free Full Text]

12. Senni M, Redfield MM. Heart failure with preserved systolic function. A different natural history? J Am Coll Cardiol. 2001; 38: 1277–1282.[Abstract/Free Full Text]

13. Redfield MM, Jacobsen SJ, Burnett JC, Jr, Mahoney DW, Bailey KR, Rodeheffer RJ. Burden of systolic and diastolic ventricular dysfunction in the community: appreciating the scope of the heart failure epidemic. JAMA. 2003; 289: 194–202.[Abstract/Free Full Text]

14. Solomon SD, Anavekar N, Skali H, McMurray JJ, Swedberg K, Yusuf S, Granger CB, Michelson EL, Wang D, Pocock S, Pfeffer MA. Influence of ejection fraction on cardiovascular outcomes in a broad spectrum of heart failure patients. Circulation. 2005; 112: 3738–3744.[Abstract/Free Full Text]

15. Vasan RS, Larson MG, Benjamin EJ, Evans JC, Reiss CK, Levy D. Congestive heart failure in subjects with normal versus reduced left ventricular ejection fraction: prevalence and mortality in a population-based cohort. J Am Coll Cardiol. 1999; 33: 1948–1955.[Abstract/Free Full Text]

16. Kearney MT, Fox KA, Lee AJ, Prescott RJ, Shah AM, Batin PD, Baig W, Lindsay S, Callahan TS, Shell WE, Eckberg DL, Zaman AG, Williams S, Neilson JM, Nolan J. Predicting death due to progressive heart failure in patients with mild-to-moderate chronic heart failure. J Am Coll Cardiol. 2002; 40: 1801–1808.[Abstract/Free Full Text]

17. Curtis JP, Sokol SI, Wang Y, Rathore SS, Ko DT, Jadbabaie F, Portnay EL, Marshalko SJ, Radford MJ, Krumholz HM. The association of left ventricular ejection fraction, mortality, and cause of death in stable outpatients with heart failure. J Am Coll Cardiol. 2003; 42: 736–742.[Abstract/Free Full Text]

18. Bursi F, Weston SA, Redfield MM, Jacobsen SJ, Pakhomov S, Nkomo VT, Meverden RA, Roger VL. Systolic and diastolic heart failure in the community. JAMA. 2006; 296: 2209–2216.[Abstract/Free Full Text]

19. Melton LJ III. History of the Rochester Epidemiology Project. Mayo Clin Proc. 1996; 71: 266–274.[Abstract]

20. Roger VL, Killian J, Henkel M, Weston SA, Goraya TY, Yawn BP, Kottke TE, Frye RL, Jacobsen SJ. Coronary disease surveillance in Olmsted County objectives and methodology. J Clin Epidemiol. 2002; 55: 593–601.[CrossRef][Medline]

21. Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron. 1976; 16: 31–41.[Medline]

22. Coresh J, Astor BC, Greene T, Eknoyan G, Levey AS. Prevalence of chronic kidney disease and decreased kidney function in the adult US population: Third National Health and Nutrition Examination Survey. Am J Kidney Dis. 2003; 41: 1–12.[Medline]

23. Coresh J, Selvin E, Stevens LA, Manzi J, Kusek JW, Eggers P, Van Lente F, Levey AS. Prevalence of chronic kidney disease in the United States. JAMA. 2007; 298: 2038–2047.[Abstract/Free Full Text]

24. Yturralde RF, Gaasch WH. Diagnostic criteria for diastolic heart failure. Prog Cardiovasc Dis. 2005; 47: 314–319.[CrossRef][Medline]

25. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987; 40: 373–383.[CrossRef][Medline]

26. American Heart Association. Heart Disease and Stroke Statistics—2005 Update. Dallas, Texas: American Heart Association; 2005.

27. Targonski P, Jacobsen SJ, Weston SA, Leibson CL, Pfeifer E, Nemetz P, Roger VL. Referral to autopsy: effect of antemortem cardiovascular disease: a population-based study in Olmsted County, Minnesota. Ann Epidemiol. 2001; 11: 264–270.[CrossRef][Medline]

28. Folsom AR, Gomez-Marin O, Gillum RF, Kottke TE, Lohman W, Jacobs D, Jr. Out-of-hospital coronary death in an urban population-validation of death certificate diagnosis. The Minnesota Heart Survey. Am J Epidemiol. 1987; 125: 1012–1018.[Abstract/Free Full Text]

29. Rubin DB. Multiple Imputation for Nonresponse in Surveys. New York: J. Wiley & Sons; 1987.

30. Ackman ML, Harjee KS, Mansell G, Campbell JB, Teo KK, Montague TJ. Cause-specific noncardiac mortality in patients with congestive heart failure—a contemporary Canadian audit. Clinical Quality Improvement Network (CQIN) Investigators. Can J Cardiol. 1996; 12: 809–813.[Medline]

31. Kearney MT, Fox KA, Lee AJ, Brooksby WP, Shah AM, Flapan A, Prescott RJ, Andrews R, Batin PD, Eckberg DL, Gall N, Zaman AG, Lindsay HS, Nolan J. Predicting sudden death in patients with mild to moderate chronic heart failure. Heart. 2004; 90: 1137–1143.[Abstract/Free Full Text]

32. Jones RC, Francis GS, Lauer MS. Predictors of mortality in patients with heart failure and preserved systolic function in the Digitalis Investigation Group trial. J Am Coll Cardiol. 2004; 44: 1025–1029.[Abstract/Free Full Text]

33. Braunstein JB, Anderson GF, Gerstenblith G, Weller W, Niefeld M, Herbert R, Wu AW. Noncardiac comorbidity increases preventable hospitalizations and mortality among Medicare beneficiaries with chronic heart failure. J Am Coll Cardiol. 2003; 42: 1226–1233.[Abstract/Free Full Text]

34. Zile MR, Brutsaert DL. New concepts in diastolic dysfunction and diastolic heart failure: Part II: Causal mechanisms and treatment. Circulation. 2002; 105: 1503–1508.[Free Full Text]

35. Kass DA. Is heart failure with decent systole due to bad diastole? J Card Fail. 2005; 11: 188–190.[CrossRef][Medline]

36. Kitzman DW, Little WC, Brubaker PH, Anderson RT, Hundley WG, Marburger CT, Brosnihan B, Morgan TM, Stewart KP. Pathophysiological characterization of isolated diastolic heart failure in comparison to systolic heart failure. JAMA. 2002; 288: 2144–2150.[Abstract/Free Full Text]

37. Flather MD, Shibata MC, Coats AJ, Van Veldhuisen DJ, Parkhomenko A, Borbola J, Cohen-Solal A, Dumitrascu D, Ferrari R, Lechat P, Soler-Soler J, Tavazzi L, Spinarova L, Toman J, Bohm M, Anker SD, Thompson SG, Poole-Wilson PA. Randomized trial to determine the effect of nebivolol on mortality and cardiovascular hospital admission in elderly patients with heart failure (SENIORS). Eur Heart J. 2005; 26: 215–225.[Abstract/Free Full Text]

38. Pfeffer MA, Swedberg K, Granger CB, Held P, McMurray JJ, Michelson EL, Olofsson B, Ostergren J, Yusuf S, Pocock S, Investigators C, Committees. Effects of candesartan on mortality and morbidity in patients with chronic heart failure: the CHARM-Overall programme. Lancet. 2003; 362: 759–766.[CrossRef][Medline]

39. Steg PG, Lopez-Sendon J, Lopez de Sa E, Goodman SG, Gore JM, Anderson FA, Jr., Himbert D, Allegrone J, Van de Werf F. External validity of clinical trials in acute myocardial infarction. Arch Intern Med. 2007; 167: 68–73.[Abstract/Free Full Text]

40. Bhatia RS, Tu JV, Lee DS, Austin PC, Fang J, Haouzi A, Gong Y, Liu PP. Outcome of heart failure with preserved ejection fraction in a population-based study. N Engl J Med. 2006; 355: 260–269.[Abstract/Free Full Text]

41. Cleland JG, Tendera M, Adamus J, Freemantle N, Polonski L, Taylor J. The perindopril in elderly people with chronic heart failure (PEP-CHF) study. Eur Heart J. 2006; 27: 2338–2345.[Abstract/Free Full Text]

42. Goraya TY, Jacobsen SJ, Belau PG, Weston SA, Kottke TE, Roger VL. Validation of death certificate diagnosis of out-of-hospital coronary heart disease deaths in Olmsted County, Minnesota. Mayo Clin Proc. 2000; 75: 681–687.[Abstract]

43. Di Bari M, Pozzi C, Cavallini MC, Innocenti F, Baldereschi G, De Alfieri W, Antonini E, Pini R, Masotti G, Marchionni N. The diagnosis of heart failure in the community. Comparative validation of four sets of criteria in unselected older adults: the ICARe Dicomano Study. J Am Coll Cardiol. 2004; 44: 1601–1608.[Abstract/Free Full Text]

44. Schellenbaum GD, Rea TD, Heckbert SR, Smith NL, Lumley T, Roger VL, Kitzman DW, Taylor HA, Levy D, Psaty BM. Survival associated with two sets of diagnostic criteria for congestive heart failure. Am J Epidemiol. 2004; 160: 628–635.[Abstract/Free Full Text]

45. Go AS, Yang J, Ackerson LM, Lepper K, Robbins S, Massie BM, Shlipak MG. Hemoglobin level, chronic kidney disease, and the risks of death and hospitalization in adults with chronic heart failure: the Anemia in Chronic Heart Failure: Outcomes and Resource Utilization (ANCHOR) Study. Circulation. 2006; 113: 2713–2723.[Abstract/Free Full Text]

46. Greenland S, Finkle WD. A critical look at methods for handling missing covariates in epidemiologic regression analyses. Am J Epidemiol. 1995; 142: 1255–1264.[Abstract/Free Full Text]


Related Article

Does It Matter Why and How Patients With Heart Failure Die?: A Debate That Lives On
Paul J. Hauptman
Circ Heart Fail 2008 1: 89-90. [Extract] [Full Text] [PDF]



This article has been cited by other articles:


Home page
J Am Coll CardiolHome page
W.H. W. Tang and G. S. Francis
The Year in Heart Failure
J. Am. Coll. Cardiol., November 11, 2008; 52(20): 1671 - 1678.
[Full Text] [PDF]


Home page
Circ Heart FailHome page
P. J. Hauptman
Does It Matter Why and How Patients With Heart Failure Die?: A Debate That Lives On
Circ Heart Fail, July 1, 2008; 1(2): 89 - 90.
[Full Text] [PDF]


This Article
Free upon publication Free Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
1/2/91    most recent
CIRCHEARTFAILURE.107.743146v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrowRequest Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Henkel, D. M.
Right arrow Articles by Roger, V. L.
Right arrow Search for Related Content
PubMed
Right arrow Articles by Henkel, D. M.
Right arrow Articles by Roger, V. L.
Related Collections
Right arrow Epidemiology
Right arrow Other heart failure
Right arrow Congestive
Right arrowRelated Article