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Original Investigation |

A Contemporary Appraisal of the Heart Failure Epidemic in Olmsted County, Minnesota, 2000 to 2010 FREE

Yariv Gerber, PhD1,2; Susan A. Weston, MS1; Margaret M. Redfield, MD3; Alanna M. Chamberlain, PhD1; Sheila M. Manemann, MPH1; Ruoxiang Jiang, BS1; Jill M. Killian, BS1; Véronique L. Roger, MD, MPH1,3
[+] Author Affiliations
1Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
2Department of Epidemiology and Preventive Medicine, School of Public Health, Tel Aviv University, Tel Aviv, Israel
3Division of Cardiovascular Diseases, Department of Medicine, Mayo Clinic, Rochester, Minnesota
JAMA Intern Med. 2015;175(6):996-1004. doi:10.1001/jamainternmed.2015.0924.
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Published online

Importance  Heart failure (HF) is commonly referred to as an epidemic, posing major clinical and public health challenges. Yet, contemporary data on its magnitude and implications are scarce.

Objective  To evaluate recent trends in HF incidence and outcomes overall and by preserved ejection fraction (HFpEF) or reduced ejection fraction (HFrEF).

Design, Setting, and Participants  Incidence rates of HF in Olmsted County, Minnesota (population, approximately 144 248), between January 1, 2000, and December 31, 2010, were assessed.

Main Outcomes and Measures  Patients identified with incident HF (n = 2762) (mean age, 76.4 years; 43.1% male) were followed up for all-cause and cause-specific hospitalizations (through December 2012) and death (through March 2014).

Results  The age– and sex–adjusted incidence of HF declined substantially from 315.8 per100 000 in 2000 to 219.3 per 100 000 in 2010 (annual percentage change, −4.6), equating to a rate reduction of 37.5% (95% CI, −29.6% to −44.4%) over the last decade. The incidence declined for both HF types but was greater (interaction P = .08) for HFrEF (−45.1%; 95% CI, −33.0% to −55.0%) than for HFpEF (−27.9%; 95% CI, −12.9% to −40.3%). Mortality was high (24.4% for age 60 years and 54.4% for age 80 years at 5 years of follow-up), frequently ascribed to noncardiovascular causes (54.3%), and did not decline over time. The risk of cardiovascular death was lower for HFpEF than for HFrEF (multivariable-adjusted hazard ratio, 0.79; 95% CI, 0.67-0.93), whereas the risk of noncardiovascular death was similar (1.07; 95% CI, 0.89-1.29). Hospitalizations were common (mean, 1.34; 95% CI, 1.25-1.44 per person-year), particularly among men, and did not differ between HFpEF and HFrEF. Most hospitalizations (63.0%) were due to noncardiovascular causes. Hospitalization rates for cardiovascular causes did not change over time, whereas those for noncardiovascular causes increased.

Conclusions and Relevance  Over the last decade, the incidence of HF declined substantially, particularly for HFrEF, contrasting with no apparent change in mortality. Noncardiovascular conditions have an increasing role in hospitalizations and remain the most frequent cause of death. These results underscore the need to augment disease-centric management approaches with holistic strategies to reduce the population burden of HF.

Figures in this Article

Heart failure (HF) is a major clinical and public health problem owing to its high prevalence, mortality, hospitalization, and health care expenditures.1 Accordingly, it is commonly referred to as an epidemic.24 A recent statement from the American Heart Association forecasted the prevalence and cost of care of HF to increase markedly in the United States over the next decades, reflecting the aging of the population and improving patient survival.5 However, contemporary data on key components of this epidemic are lacking. To this end, estimates of HF incidence and its temporal trends in the population are scarce and inconsistent. Data are frequently derived from hospital discharge records, self-reports, or administrative databases1,613 and cannot accurately distinguish between incident and prevalent cases, have uncertain validity because of evolving coding practices,1417 or cannot fully capture the burden of the disease because of the shift of care toward outpatient settings.9,18 Moreover, because HF is a syndrome and not a disease, its diagnosis is challenging, standardized diagnostic criteria are inconsistently applied, and ejection fraction (EF) is not routinely measured, precluding the study of HF with preserved EF (HFpEF), a major component of the HF burden.19,20 Estimates based on validated cases are outdated2125 and do not reflect recent changes in the key determinants of HF, such as myocardial infarction and hypertension.2628 Consequently, it should come as no surprise that existing results on temporal changes in HF incidence are conflicting, with reports of increasing,23 plateau-like,22 decreasing,7,9,13 or mixed6,21 trends. Most important, there is no current report on trends in HF incidence according to EF. This point is critical because the determinants of these 2 conditions are likely different29,30 and might have evolved over time. Indeed, while decreasing mortality rates after HF were reported during the 1990s to early 2000s,7,9,13,22 the change in case mix with a growing proportion of HFpEF26,29 (for which there is no specific treatment31) might have attenuated this decline. The change in case mix might also affect hospitalization rates among patients with HF, particularly in light of the major role of comorbidity, which is known to be higher in HFpEF.32 To address these gaps in knowledge, this study was designed to assess contemporary trends in the incidence of HF (validated using diagnostic criteria and categorized as reduced ejection fraction [HFrEF] or HFpEF) and cause-specific hospitalization and mortality after its onset in a geographically defined population.

Study Setting

This study was conducted in Olmsted County, Minnesota, which had an approximate population of 144 248 according to the 2010 census, 85.7% of whom are of white race/ethnicity, and 13.6% of whom are 65 years or older. The Olmsted County population is largely middle class, with a higher median household income ($66 252 vs $53 054) and a lower percentage below the poverty line (8.0% vs 15.4%) than the US total population in 2010, and the estimated health insurance uninsured rate is 5.0%.33 Olmsted County constitutes a highly suitable setting for epidemiological research because of its relative isolation from other urban centers and because medical care is practically self-contained within the community, with the largest health care provider being the Mayo Clinic. Medical records from all sources of care for residents are extensively indexed and linked via the Rochester Epidemiology Project.34,35

Study Design

The study was approved by the Mayo Clinic and Olmsted Medical Center institutional review boards, and patients were excluded from analysis if they declined to provide written Minnesota Research Authorization. The percentage of patients not providing research authorization was low overall (4.2%) and stable during the study period (trend P = .43).

A 2-stage design was implemented. Initially, a community surveillance study was conducted to estimate the incidence rates of HF between 2000 and 2010 in Olmsted County. Subsequently, patients with incident HF enrolled in the first stage were followed up for outcomes (mortality and hospitalizations) in a patient-level cohort study.

Case Identification and Validation

Residents diagnosed as having HF by International Classification of Diseases, Ninth Revision (ICD-9) code 428 between 2000 and 2010 were identified. These clinical codes were based on physician diagnoses during outpatient visits or at hospital discharge. From all patients with this code, a subset was randomly selected to undergo case validation and data abstraction (50% sample from 2000-2006 and 100% sample from 2007-2010). Abstractors reviewed records to validate HF using Framingham Study criteria. These criteria require the presence of at least 2 major criteria to confirm HF or 1 major criterion in addition to 2 minor criteria.36 This approach was applied previously, showing minimal missing data and excellent interobserver agreement.22 The ICD-9 codes 425 (cardiomyopathy), 429.3 (cardiomegaly), and 514 (pulmonary congestion) were also reviewed as sources of potential HF cases. For each code, a random sample of 20 patients was selected, and records were reviewed to validate HF using Framingham Study criteria. One case of validated HF was found in the cardiomyopathy and pulmonary congestion samples, and no cases were found in the cardiomegaly sample, confirming the appropriateness of using only ICD-9 code 428 to construct the HF cohort. Patients with validated HF before the study period were excluded, as were nonresidents of Olmsted County.22,37

Ejection fraction was measured using an approach that was previously described.38 Briefly, all echocardiography in Olmsted County during the study period was performed at the Mayo Clinic. No other health care providers offered these services. The assessment of EF is based on the echocardiographer’s combination of multiple methods (M-mode or 2-dimensional echocardiography using the Quinones formula from the parasternal views or by the quantitative 2-dimensional biplane volumetric Simpson method from 4-chamber and 2-chamber views) into an EF assessment quoted in the final impressions.39,40 The EF measurement that was closest to the HF diagnosis (applying a predefined maximum period of 90 days) was recorded for each participant. The cutoff of 50% was used to define HFpEF (≥50%) or HFrEF (<50%) according to the guidelines.41

Outcome Measures

For mortality, follow-up was performed through March 2014 using the medical record. In addition to death notes in clinical care, the Mayo Clinic registration office records obituaries and local death notices, and death data are obtained quarterly from the State of Minnesota Department of Vital and Health Statistics. Information on the date of death and its underlying cause was obtained, through which deaths were classified as cardiovascular (ICD-9 codes 390-459) and noncardiovascular.42

For hospitalizations, data on all-cause hospitalizations occurring after incident HF through December 2012 were obtained through the Rochester Epidemiology Project. The principal discharge diagnosis for each hospitalization was assessed using the primary ICD-9 code, which was assigned by clinical personnel after discharge and reflects the main reason for admission. The primary reason for hospitalization was divided into cardiovascular (ICD-9 codes 390-459) and noncardiovascular.

Patient-Level Data

Baseline characteristics were abstracted from medical and administrative records. Cigarette smoking was classified as current, past, or none. Body mass index (calculated as weight in kilograms divided by height in meters squared) was obtained using the current weight and earliest available adult height measurement. Clinical definitions were used to assess whether patients had prior myocardial infarction, hypertension, or hyperlipidemia. Diabetes mellitus was defined according to the American Diabetes Association or by the use of diabetic medications. Overall comorbidity burden was assessed by the Charlson Comorbidity Index.

Statistical Analysis

Sampling was accounted for in the analysis through weighting. Characteristics of patients with validated HF are presented as frequencies or means (SDs). Age-specific, sex-specific, and year-specific incidence rates of validated HF were calculated. The counts of validated cases (overall and by HFrEF or HFpEF) were used as the numerators, and the denominators were the Olmsted County population 20 years or older (as determined by census data for 2000 and 2010), with linear interpolation for the intercensus years.22 The rates were directly standardized to the age and sex distribution of the 2010 US total population. Poisson regression models were used to examine overall and category-specific mean annual percentage changes and temporal trends (using 2-way interaction terms) in HF incidence rates. Based on these models, the percentage changes during the entire period from 2000 to 2010 and corresponding 95% CIs were estimated. Age (as a continuous variable) and sex (when applicable) were adjusted for in the models.

Trends over time in the distribution of cardiovascular risk factors and HF characteristics were assessed with logistic regression or linear regression, as appropriate. Proportional hazards regression modeling was used to examine the associations of year of HF and other baseline characteristics with all-cause and cause-specific (ie, cardiovascular and noncardiovascular) mortality. Age-adjusted (using the age categorization of ≤65, 66-75, 76-85, and >85 years) and multivariable-adjusted hazard ratios for death are reported for each variable with respective 95% CIs. Age-specific 1-year and 5-year mortality rates were estimated from the proportional hazards regression models. For the latter purpose, age was modeled with linear and quadratic terms because of its nonlinear effect on mortality.

Overall and year-specific hospitalization rates within 2 years of follow-up (the last follow-up was December 2012) were estimated using negative binomial regression. Rates were estimated for all-cause and cause-specific (ie, cardiovascular and noncardiovascular) hospitalizations and are presented for patients 76.4 years old, the mean age of this cohort. Temporal trends in hospitalization rates were examined with year as a continuous variable after adjusting for age (as a continuous variable) and sex.

Data on EF were missing in 21.6% of the cases. A multiple imputation analysis was performed to impute missing EF values. Five data sets were created, with missing values replaced by imputed values based on a model that incorporated various demographic and clinical variables. The latter model included variables previously recognized as predictors of missing EF in HF43 and others identified in the present analysis. The results of these data sets were then combined using rules by Rubin.44

Analyses were performed with statistical software. Version 9.3 of SAS (SAS Institute Inc) was used.

In total, 2762 incident HF cases were estimated in the population between January 1, 2000, and December 31, 2010. The mean (SD) age of the cohort was 76.4 (13.4) years, and 43.1% were male. The proportion of individuals diagnosed as outpatients was 31.9%, and 52.5% were categorized as having HFpEF.

Over time, the proportion of cases with HFpEF increased from 47.8% in 2000 to 2003 to 56.9% in 2004 to 2007 and to 52.3% in 2008 to 2010 (P = .06). The proportion of men and the prevalence of hypertension at the time of HF increased in patients with HFrEF (Table 1). Among patients with HFpEF, the prevalence of hypertension, diabetes mellitus, and hyperlipidemia at the time of HF increased, as did the burden of comorbid conditions.

Table Graphic Jump LocationTable 1.  Characteristics of Patients With Validated Heart Failure by Ejection Fraction and Year Category in Olmsted County, Minnesota, 2000 to 2010a
HF Incidence

The age– and sex–adjusted incidence rates of HF declined substantially over time from 315.8 per 100 000 in 2000 to 219.3 per 100 000 in 2010. The overall mean annual percentage change was −4.6 (95% CI, −3.5 to −5.7), equating to a 37.5% (95% CI, −29.6% to −44.4%) decline over the last decade. This decline applied to both men and women and for HFrEF and HFpEF in absolute (Figure 1) and relative (Figure 2) terms. However, the magnitude of trends differed by sex and EF. Women (overall rate change, −43%) experienced a greater decline (interaction P = .06) than men (overall rate change, −29%), and the rates of HFrEF (−45%; 95% CI, −33% to −55%) decreased more sharply (interaction P = .08) than the rates of HFpEF (−28%; 95% CI, −13% to −40%) from 2000 to 2010. The heterogeneity by EF was largely limited to women, who exhibited a markedly larger decline in the incidence of HFrEF than HFpEF (−61% vs −27%, interaction P = .001) compared with men (−29% vs −27%, interaction P = .91) (Figure 2).

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Figure 1.
Temporal Trends in Heart Failure Incidence Rates Overall and by Reduced or Preserved Ejection Fraction Among Women and Men in Olmsted County, Minnesota, 2000 to 2010

Yearly rates (smoothed using 3-year moving average) per 100 000 persons have been standardized by the direct method to the age distribution of the US population in 2010. HFpEF indicates heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.
Estimated Percentage Changes in Heart Failure Incidence From 2000 to 2010 in Olmsted County, Minnesota, Overall and Across Specific Demographic Groups and Heart Failure Types

Estimates are adjusted for age and sex (when applicable) and presented with 95% CIs. HFpEF indicates heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction.

Graphic Jump Location
Outcomes After HF Diagnosis

Among the incident HF cases, 2644 patients had follow-up data available for analysis. The outcomes after HF diagnosis were assessed.

For mortality, after a mean (SD) of 4.5 (3.5) years of follow-up, 1793 deaths were enumerated, which equated to mortality rates of 20.2% (95% CI, 18.7%-21.8%) at 1 year after diagnosis and 52.6% (95% CI, 50.6%-54.5%) at 5 years after diagnosis. Mortality rates increased with age: for 60-year-olds, the rates were 7.4% and 24.4% at 1 year and 5 years, respectively, and for 80-years-olds, the rates were 19.5% and 54.4% at 1 and 5 years, respectively (P < .001). Mortality was frequently (54.3%) ascribed to noncardiovascular causes. Among 1700 patients with cause of death available, the top 3 categories of noncardiovascular causes of death were respiratory (n = 241) (14.2%), neoplasm (n = 215) (12.6%), and mental or behavioral health (n = 121) (7.1%). Among patients with measured EF, the top 3 categories for the 594 patients with HFrEF and cause of death available were neoplasm (n = 76) (12.8%), respiratory (n = 57) (9.6%), and mental or behavioral health (n = 29) (4.9%). For the 668 patients with HFpEF and cause of death available, they were respiratory (n = 104) (15.6%), neoplasm (n = 83) (12.4%), and mental or behavioral health (n = 44) (6.6%). The hazard ratios for all-cause and cause-specific mortality associated with patient characteristics at the time of HF diagnosis are listed in Table 2. In addition to age, factors positively associated with all-cause death were diabetes mellitus, smoking, and increasing number of comorbidities. Body mass index, hyperlipidemia, HFpEF (borderline significance), and HF diagnosis at an outpatient visit showed an inverse association. In the cause-specific analysis, smoking and the Charlson Comorbidity Index were more strongly associated with noncardiovascular death than with cardiovascular death. Conversely, age and prior myocardial infarction were more strongly associated with cardiovascular death than with noncardiovascular death. An inverse association of HFpEF with cardiovascular death was found, with no apparent association with noncardiovascular death. Outpatient diagnosis of HF was inversely associated with cardiovascular and noncardiovascular death. No temporal trends in mortality were detected in all-cause or cause-specific analysis.

Table Graphic Jump LocationTable 2.  Hazard Ratios for Mortality Associated With Baseline Characteristics at the Time of Incident Heart Failure Diagnosisa

For hospitalizations, 4631 occurred during the first 2 years of follow-up. Hospitalizations were common (mean, 1.34; 95% CI, 1.25-1.44 per person-year), and most (63.0%) were due to noncardiovascular causes. The top 3 noncardiovascular causes of hospitalization were categorized as respiratory (n = 655) (14.1% of all hospitalizations); other symptoms, signs, and abnormal findings (including but not limited to alteration of consciousness, convulsions, and fever and other physiologic disturbances) (n = 437) (9.4%); and injury, poisoning, and other consequences of external causes (n = 351) (7.6%). For the 1699 hospitalizations among the 985 patients with HFrEF, the top 3 noncardiovascular causes of hospitalization were categorized as respiratory (n = 201) (11.8%); other symptoms, signs, and abnormal findings (n = 176) (10.4%); and infectious and parasitic diseases (n = 103) (6.1%). For the 2079 hospitalizations among the 1089 patients with HFpEF, the top 3 noncardiovascular causes of hospitalization were categorized as respiratory (n = 277) (13.3%); other symptoms, signs, and abnormal findings (n = 194) (9.3%); and injury, poisoning, and other consequences of external causes (n = 186) (8.9%). Total and cause-specific hospitalization rate estimates are listed in Table 3. A higher overall hospitalization rate was associated with male sex (particularly for noncardiovascular causes), while age showed little association (P = .15). Total hospitalization rates were similar regardless of EF, with some evidence of a higher rate of cardiovascular hospitalizations among those with HFrEF, offset by a higher rate of noncardiovascular hospitalizations among those with HFpEF. Hospitalization rates did not change significantly during the study period as a result of an increase in noncardiovascular hospitalizations, combined with a small, nonsignificant decrease in cardiovascular hospitalizations (particularly among HFrEF cases).

Table Graphic Jump LocationTable 3.  Hospitalization Rate Estimates After Heart Failure Diagnosis by Year Category Among Patients Aged 76.4 Yearsa
Ancillary Analyses

Several ancillary analyses were performed to assess the robustness of our results. To determine the effect on the results of using 50% as a cutoff for defining HFrEF, analyses were repeated using a cutoff of 40%. Similar trends were observed. In addition, a complete case analysis was performed in which individuals with missing EF were excluded. Similar results were obtained compared with the multiple imputation analysis. The HF-specific hospitalizations, defined as ICD-9 code 428, were analyzed as a separate outcome. Overall, the rates of HF hospitalizations over the study period remained constant (P = .54), with no change in HFrEF (P = .64) or HFpEF (P = .99).

Herein, we report major changes in the epidemiology of HF in the last decade, with a large decrease in incidence and a shift toward HFpEF, for which there is no specific treatment. Mortality did not change during the study period, nor did hospitalization rates. However, the cause of hospitalization transitioned toward noncardiovascular causes, likely reflecting the increasing comorbidity burden in this elderly population of patients.

Trends in Incidence

Few studies have examined trends in the incidence of HF, and a systematic review found no evidence of any clear or consistent change in rates over time.45 Outside the United States, the results of some studies7,9,13 (but not the findings of another study46) suggested a recent decline in HF incidence in specific populations. In the United States, HF hospitalizations had increased from 1979 to 2004 among patients 65 years or older.12 More recently, a substantial decline in HF-related hospitalization rates was reported among fee-for-service Medicare beneficiaries in the United States.11 Hospitalizations do not reflect incidence. As previously reviewed,19,20 most of these data were derived from hospital discharge records or administrative databases. In these situations, standardized diagnostic criteria are not used, and case ascertainment is often affected by shifts in coding because of reimbursement incentives.14,15 The studies tend to be event based (not person based), with multiple hospitalizations counted per person.11,12 Furthermore, inpatient data (the sole information source in many reports) do not capture all cases of HF because care is increasingly delivered in the outpatient setting.9,18 In addition, published data were frequently based on a limited run-in (look-back) period to distinguish incident from prevalent HF.7,13 Using a run-in period can substantially overestimate the incidence rate if data covering a sufficient duration of time are unavailable.47 These inherent drawbacks underscore the importance of conducting population-based studies applying standardized case validation procedures in the framework of ongoing surveillance of all residents in a defined community. The few such studies available did not detect a decline in HF incidence in the past. In the Framingham Heart Study21 and in Olmsted County,22 the incidence of HF had been stable from the 1970s to the 1990s. The incidence increased only among the elderly in a study23 of Kaiser Permanente health plan members over that period.

Therefore, the present findings of a major decline in HF incidence over the last decade represent a large departure from previous reports, including from our group. Although decreased incidence over the last decade occurred in all demographic groups, a less pronounced decline was observed in men compared with women. Moreover, the present study provides one of the first longitudinal reports of trends in HF by type—information that was lacking in previous publications.19,20 We found a substantial decline over time in both HF types, yet the decline was greater for HFrEF. This finding in turn resulted in a change in the case mix, with a growing proportion of HFpEF, for which there is no specific treatment. Because it is often assumed that patients with HF and underlying coronary disease are more likely to present with reduced EF,48 the change in case mix may reflect the recent decrease in the incidence of myocardial infarction in the population,49,50 the increasing use of timely reperfusion in acute myocardial infarction, and the reduced risk of HF after myocardial infarction.26 While complex, the role of changes in cardiovascular risk factors in the genesis of HF is also important to consider. Although the prevalence of hypertension and diabetes mellitus has increased over time,1 so have the diagnostic criteria, which may have resulted in detection at earlier stages. The management of these conditions has improved, thereby leading to better outcomes, as recently shown in particular for diabetes mellitus.51

Outcomes After HF Diagnosis

Heart failure survival improved substantially during the early 1990s and early to mid-2000s,6,7,9,13,22 likely reflecting increased use of evidence-based medications (eg, β-blockers, angiotensin-converting enzyme inhibitors, and angiotensin receptor blockers). As shown herein, survival after HF diagnosis seemingly leveled off thereafter, possibly reflecting the transition from HFrEF to HFpEF and the increasing comorbidity burden in HF. The increasing proportion of noncardiovascular causes of death (neoplasm, respiratory conditions) supports this hypothesis.52

Data on the cause of hospitalization among patients with HF suggest that cardiovascular hospitalizations may be less common than noncardiovascular hospitalizations.10,37 In our study, the latter were responsible for 63.0% of all HF hospitalizations. While hospitalization rates for cardiovascular causes did not change over time, the rates for noncardiovascular causes increased; while the range of noncardiovascular causes is extensive, the role of respiratory conditions and symptoms is noteworthy. This shift in the distribution of the cause of hospitalizations toward noncardiovascular causes is congruent with the major burden of comorbid conditions in HF and is critical to manage HF and interpret its outcomes. Indeed, current therapies (eg, medications, devices) are intrinsically disease centric and directed at reducing HF exacerbation. Therefore, HF-specific hospitalizations are a key indicator of the effectiveness of HF-specific treatments, but disease-specific interventions cannot be expected to reduce all hospitalizations appreciably among persons living with HF given the high prevalence of comorbidity in these patients. Our results support this hypothesis because cardiovascular hospitalizations declined over time among HFrEF cases; however, overall hospitalization rates did not decline, and noncardiovascular hospitalizations even increased. Within this context, it is important to distinguish hospitalizations due to HF11 from all hospitalizations experienced by patients living with HF. Our study captures all hospitalizations occurring among an incidence cohort of patients living with HF and allows partitioning of the cause of hospitalization. Therefore, we are able to report on a trend not previously documented.

Limitations, Strengths, and Implications

Some limitations should be acknowledged in interpreting these data. These results emanate from a single community of predominantly of white race/ethnicity. As in any study, the racial/ethnic composition of the population may limit the generalizability to groups underrepresented in the population. However, the population of Olmsted County is representative of the state of Minnesota and the Upper Midwest region of the United States.53 Furthermore, age and sex–specific mortality rates are similar for Olmsted County, the state of Minnesota, and the entire United States, and broad disease trends in Olmsted County are commensurate with national trends, supporting the broad relevance of our data.53 Finally, the age of our patients is representative of the broad clinical experience of patients with HF, as shown, for example, in the Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure registry.54

We cannot rule out an effect of the use of tests (B-type natriuretic peptide and others) in practice on temporal trends in HF incidence. However, the use of tests can operate in both directions, increasing incidence by diagnosing individuals as having HF that would have been otherwise classified as noncardiac dyspnea or ruling out HF and decreasing incidence.

The study has several notable strengths. The data are recent, reflecting the current burden of HF in a defined community, and are comprehensive, including inpatient and outpatient data. These factors are important because approximately one-third of the patients in our community cohort were diagnosed in the outpatient setting. Echocardiographic data allowed examination of the respective contributions of HFpEF and HFrEF to the burden of HF, which is important to note in understanding the HF syndrome.32

Our findings document a major change in the epidemiology of HF, which is consistent with the recent changes in the epidemiology of acute coronary syndromes.49,50 The changes in heart disease over the last decades have important implications for the planning of health care delivery and use in communities. Indeed, further reductions in mortality and hospitalizations among patients living with HF will require concerted efforts to address multimorbidity, augmenting disease-centric therapeutic guidelines with the deployment of holistic care models. While the rationale for such a strategy has been envisioned,55 the present data provide definite evidence to support a call for action in this regard.

We report major changes in the epidemiology of HF over the last decade, with a large decrease in incidence and a change in case mix toward HFpEF, for which there is no specific treatment. Mortality and hospitalization rates remained stable, while the cause of hospitalization changed, with an increase in noncardiovascular causes, likely reflecting the increasing comorbidity burden in these elderly patients. These findings have important implications to designing effective strategies to optimize the care of patients living with HF.

Accepted for Publication: January 12, 2015.

Corresponding Author: Véronique L. Roger, MD, MPH, Division of Cardiovascular Diseases, Department of Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (roger.veronique@mayo.edu).

Published Online: April 20, 2015. doi:10.1001/jamainternmed.2015.0924.

Author Contributions: Dr Roger 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: Gerber, Weston, Roger.

Drafting of the manuscript: Gerber, Weston, Redfield, Chamberlain, Manemann, Roger.

Critical revision of the manuscript for important intellectual content: Gerber, Weston, Redfield, Chamberlain, Manemann, Roger.

Statistical analysis: Gerber, Weston, Jiang, Killian.

Obtained funding: Roger.

Administrative, technical, or material support: Roger.

Study supervision: Gerber, Roger.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was supported by grants R01 HL72435 and R01 HL120859 from the National Institutes of Health and was made possible by Rochester Epidemiology Project grant R01 AG034676 from the National Institute on Aging and Mayo Clinic Center for Translational Science Activities through grant UL1 TR000135 from the National Center for Advancing Translational Sciences, a component of the National Institutes of Health.

Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review or approval of the manuscript; and decision to submit the manuscript for publication.

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Loehr  LR, Rosamond  WD, Chang  PP, Folsom  AR, Chambless  LE.  Heart failure incidence and survival (from the Atherosclerosis Risk in Communities study). Am J Cardiol. 2008;101(7):1016-1022.
PubMed   |  Link to Article
Yeung  DF, Boom  NK, Guo  H, Lee  DS, Schultz  SE, Tu  JV.  Trends in the incidence and outcomes of heart failure in Ontario, Canada: 1997 to 2007. CMAJ. 2012;184(14):E765-E773. doi:10.1503/cmaj.111958.
PubMed   |  Link to Article
Blecker  S, Paul  M, Taksler  G, Ogedegbe  G, Katz  S.  Heart failure–associated hospitalizations in the United States. J Am Coll Cardiol. 2013;61(12):1259-1267.
PubMed   |  Link to Article
Chen  J, Normand  SL, Wang  Y, Krumholz  HM.  National and regional trends in heart failure hospitalization and mortality rates for Medicare beneficiaries, 1998-2008. JAMA. 2011;306(15):1669-1678.
PubMed   |  Link to Article
Fang  J, Mensah  GA, Croft  JB, Keenan  NL.  Heart failure–related hospitalization in the U.S., 1979 to 2004. J Am Coll Cardiol. 2008;52(6):428-434.
PubMed   |  Link to Article
Teng  TH, Finn  J, Hobbs  M, Hung  J.  Heart failure: incidence, case fatality, and hospitalization rates in Western Australia between 1990 and 2005. Circ Heart Fail. 2010;3(2):236-243.
PubMed   |  Link to Article
Assaf  AR, Lapane  KL, McKenney  JL, Carleton  RA.  Possible influence of the prospective payment system on the assignment of discharge diagnoses for coronary heart disease. N Engl J Med. 1993;329(13):931-935.
PubMed   |  Link to Article
Jollis  JG, Ancukiewicz  M, DeLong  ER, Pryor  DB, Muhlbaier  LH, Mark  DB.  Discordance of databases designed for claims payment versus clinical information systems: implications for outcomes research. Ann Intern Med. 1993;119(8):844-850.
PubMed   |  Link to Article
Psaty  BM, Boineau  R, Kuller  LH, Luepker  RV.  The potential costs of upcoding for heart failure in the United States. Am J Cardiol. 1999;84(1):108-109, A9.
PubMed   |  Link to Article
Quach  S, Blais  C, Quan  H.  Administrative data have high variation in validity for recording heart failure. Can J Cardiol. 2010;26(8):306-312.
PubMed   |  Link to Article
Ezekowitz  JA, Kaul  P, Bakal  JA, Quan  H, McAlister  FA.  Trends in heart failure care: has the incident diagnosis of heart failure shifted from the hospital to the emergency department and outpatient clinics? Eur J Heart Fail. 2011;13(2):142-147.
PubMed   |  Link to Article
Roger  VL.  Epidemiology of heart failure. Circ Res. 2013;113(6):646-659.
PubMed   |  Link to Article
Bui  AL, Horwich  TB, Fonarow  GC.  Epidemiology and risk profile of heart failure. Nat Rev Cardiol. 2011;8(1):30-41.
PubMed   |  Link to Article
Levy  D, Kenchaiah  S, Larson  MG,  et al.  Long-term trends in the incidence of and survival with heart failure. N Engl J Med. 2002;347(18):1397-1402.
PubMed   |  Link to Article
Roger  VL, Weston  SA, Redfield  MM,  et al.  Trends in heart failure incidence and survival in a community-based population. JAMA. 2004;292(3):344-350.
PubMed   |  Link to Article
Barker  WH, Mullooly  JP, Getchell  W.  Changing incidence and survival for heart failure in a well-defined older population, 1970-1974 and 1990-1994. Circulation. 2006;113(6):799-805.
PubMed   |  Link to Article
Bahrami  H, Kronmal  R, Bluemke  DA,  et al.  Differences in the incidence of congestive heart failure by ethnicity: the Multi-Ethnic Study of Atherosclerosis. Arch Intern Med. 2008;168(19):2138-2145.
PubMed   |  Link to Article
Goldberg  RJ, Spencer  FA, Farmer  C, Meyer  TE, Pezzella  S.  Incidence and hospital death rates associated with heart failure: a community-wide perspective. Am J Med. 2005;118(7):728-734.
PubMed   |  Link to Article
Gerber  Y, Weston  SA, Berardi  C,  et al.  Contemporary trends in heart failure with reduced and preserved ejection fraction after myocardial infarction: a community study. Am J Epidemiol. 2013;178(8):1272-1280.
PubMed   |  Link to Article
He  J, Ogden  LG, Bazzano  LA, Vupputuri  S, Loria  C, Whelton  PK.  Risk factors for congestive heart failure in US men and women: NHANES I epidemiologic follow-up study. Arch Intern Med. 2001;161(7):996-1002.
PubMed   |  Link to Article
Dunlay  SM, Weston  SA, Jacobsen  SJ, Roger  VL.  Risk factors for heart failure: a population-based case-control study. Am J Med. 2009;122(11):1023-1028.
PubMed   |  Link to Article
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(3):251-259.
PubMed   |  Link to Article
Bhatia  RS, Tu  JV, Lee  DS,  et al.  Outcome of heart failure with preserved ejection fraction in a population-based study. N Engl J Med. 2006;355(3):260-269.
PubMed   |  Link to Article
Borlaug  BA, Paulus  WJ.  Heart failure with preserved ejection fraction: pathophysiology, diagnosis, and treatment. Eur Heart J. 2011;32(6):670-679.
PubMed   |  Link to Article
Fonarow  GC, Stough  WG, Abraham  WT,  et al; OPTIMIZE-HF Investigators and Hospitals.  Characteristics, treatments, and outcomes of patients with preserved systolic function hospitalized for heart failure: a report from the OPTIMIZE-HF Registry. J Am Coll Cardiol. 2007;50(8):768-777.
PubMed   |  Link to Article
United States Census Bureau. American FactFinder.http://factfinder.census.gov/faces/nav/jsf/pages/community_facts.xhtml. Accessed December 11, 2014.
Melton  LJ  III.  History of the Rochester Epidemiology Project. Mayo Clin Proc. 1996;71(3):266-274.
PubMed   |  Link to Article
Rocca  WA, Yawn  BP, St Sauver  JL, Grossardt  BR, Melton  LJ  III.  History of the Rochester Epidemiology Project: half a century of medical records linkage in a US population. Mayo Clin Proc. 2012;87(12):1202-1213.
PubMed   |  Link to Article
McKee  PA, Castelli  WP, McNamara  PM, Kannel  WB.  The natural history of congestive heart failure: the Framingham Study. N Engl J Med. 1971;285(26):1441-1446.
PubMed   |  Link to Article
Dunlay  SM, Redfield  MM, Weston  SA,  et al.  Hospitalizations after heart failure diagnosis: a community perspective. J Am Coll Cardiol. 2009;54(18):1695-1702.
PubMed   |  Link to Article
Dunlay  SM, Roger  VL, Weston  SA, Jiang  R, Redfield  MM.  Longitudinal changes in ejection fraction in heart failure patients with preserved and reduced ejection fraction. Circ Heart Fail. 2012;5(6):720-726.
PubMed   |  Link to Article
Quinones  MA, Waggoner  AD, Reduto  LA,  et al.  A new, simplified and accurate method for determining ejection fraction with two-dimensional echocardiography. Circulation. 1981;64(4):744-753.
PubMed   |  Link to Article
Lang  RM, Bierig  M, Devereux  RB,  et al; Chamber Quantification Writing Group; American Society of Echocardiography’s Guidelines and Standards Committee; European Association of Echocardiography.  Recommendations for chamber quantification: a report from the American Society of Echocardiography’s Guidelines and Standards Committee and the Chamber Quantification Writing Group, developed in conjunction with the European Association of Echocardiography, a branch of the European Society of Cardiology. J Am Soc Echocardiogr. 2005;18(12):1440-1463.
PubMed   |  Link to Article
Yancy  CW, Jessup  M, Bozkurt  B,  et al; Writing Committee Members; American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines.  2013 ACCF/AHA guideline for the management of heart failure: a report of the American College of Cardiology Foundation/American Heart Association Task Force on practice guidelines. Circulation. 2013;128(16):e240-e327. doi:10.1161/CIR.0b013e31829e8776.
PubMed   |  Link to Article
Gerber  Y, Jacobsen  SJ, Frye  RL, Weston  SA, Killian  JM, Roger  VL.  Secular trends in deaths from cardiovascular diseases: a 25-year community study. Circulation. 2006;113(19):2285-2292.
PubMed   |  Link to Article
Kurtz  CE, Gerber  Y, Weston  SA, Redfield  MM, Jacobsen  SJ, Roger  VL.  Use of ejection fraction tests and coronary angiography in patients with heart failure. Mayo Clin Proc. 2006;81(7):906-913.
PubMed   |  Link to Article
Rubin  DB. Multiple Imputation for Nonresponse in Surveys. New York, NY: John Wiley & Sons; 1987.
Najafi  F, Jamrozik  K, Dobson  AJ.  Understanding the “epidemic of heart failure”: a systematic review of trends in determinants of heart failure. Eur J Heart Fail. 2009;11(5):472-479.
PubMed   |  Link to Article
Mehta  PA, Dubrey  SW, McIntyre  HF,  et al.  Improving survival in the 6 months after diagnosis of heart failure in the past decade: population-based data from the UK. Heart. 2009;95(22):1851-1856.
PubMed   |  Link to Article
Brameld  KJ, Holman  CD, Lawrence  DM, Hobbs  MS.  Improved methods for estimating incidence from linked hospital morbidity data. Int J Epidemiol. 2003;32(4):617-624.
PubMed   |  Link to Article
Sutton  MG, Sharpe  N.  Left ventricular remodeling after myocardial infarction: pathophysiology and therapy. Circulation. 2000;101(25):2981-2988.
PubMed   |  Link to Article
Yeh  RW, Sidney  S, Chandra  M, Sorel  M, Selby  JV, Go  AS.  Population trends in the incidence and outcomes of acute myocardial infarction. N Engl J Med. 2010;362(23):2155-2165.
PubMed   |  Link to Article
Roger  VL, Weston  SA, Gerber  Y,  et al.  Trends in incidence, severity, and outcome of hospitalized myocardial infarction. Circulation. 2010;121(7):863-869.
PubMed   |  Link to Article
Gregg  EW, Li  Y, Wang  J,  et al.  Changes in diabetes-related complications in the United States, 1990-2010. N Engl J Med. 2014;370(16):1514-1523.
PubMed   |  Link to Article
Henkel  DM, Redfield  MM, Weston  SA, Gerber  Y, Roger  VL.  Death in heart failure: a community perspective. Circ Heart Fail. 2008;1(2):91-97.
PubMed   |  Link to Article
St Sauver  JL, Grossardt  BR, Leibson  CL, Yawn  BP, Melton  LJ  III, Rocca  WA.  Generalizability of epidemiological findings and public health decisions: an illustration from the Rochester Epidemiology Project. Mayo Clin Proc. 2012;87(2):151-160.
PubMed   |  Link to Article
Abraham  WT, Fonarow  GC, Albert  NM,  et al; OPTIMIZE-HF Investigators and Coordinators.  Predictors of in-hospital mortality in patients hospitalized for heart failure: insights from the Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure (OPTIMIZE-HF). J Am Coll Cardiol. 2008;52(5):347-356.
PubMed   |  Link to Article
Sochalski  J, Jaarsma  T, Krumholz  HM,  et al.  What works in chronic care management: the case of heart failure. Health Aff (Millwood). 2009;28(1):179-189.
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Figure 1.
Temporal Trends in Heart Failure Incidence Rates Overall and by Reduced or Preserved Ejection Fraction Among Women and Men in Olmsted County, Minnesota, 2000 to 2010

Yearly rates (smoothed using 3-year moving average) per 100 000 persons have been standardized by the direct method to the age distribution of the US population in 2010. HFpEF indicates heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.
Estimated Percentage Changes in Heart Failure Incidence From 2000 to 2010 in Olmsted County, Minnesota, Overall and Across Specific Demographic Groups and Heart Failure Types

Estimates are adjusted for age and sex (when applicable) and presented with 95% CIs. HFpEF indicates heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1.  Characteristics of Patients With Validated Heart Failure by Ejection Fraction and Year Category in Olmsted County, Minnesota, 2000 to 2010a
Table Graphic Jump LocationTable 2.  Hazard Ratios for Mortality Associated With Baseline Characteristics at the Time of Incident Heart Failure Diagnosisa
Table Graphic Jump LocationTable 3.  Hospitalization Rate Estimates After Heart Failure Diagnosis by Year Category Among Patients Aged 76.4 Yearsa

References

Go  AS, Mozaffarian  D, Roger  VL,  et al; American Heart Association Statistics Committee and Stroke Statistics Subcommittee.  Heart disease and stroke statistics: 2014 update: a report from the American Heart Association. Circulation. 2014;129(3):e28-e292. doi:10.1161/01.cir.0000441139.02102.80.
PubMed   |  Link to Article
Braunwald  E.  Shattuck Lecture: cardiovascular medicine at the turn of the millennium: triumphs, concerns, and opportunities. N Engl J Med. 1997;337(19):1360-1369.
PubMed   |  Link to Article
Bleumink  GS, Knetsch  AM, Sturkenboom  MC,  et al.  Quantifying the heart failure epidemic: prevalence, incidence rate, lifetime risk and prognosis of heart failure: the Rotterdam Study. Eur Heart J. 2004;25(18):1614-1619.
PubMed   |  Link to Article
McCullough  PA, Philbin  EF, Spertus  JA, Kaatz  S, Sandberg  KR, Weaver  WD; Resource Utilization Among Congestive Heart Failure (REACH) Study.  Confirmation of a heart failure epidemic: findings from the Resource Utilization Among Congestive Heart Failure (REACH) study. J Am Coll Cardiol. 2002;39(1):60-69.
PubMed   |  Link to Article
Heidenreich  PA, Albert  NM, Allen  LA,  et al; American Heart Association Advocacy Coordinating Committee; Council on Arteriosclerosis, Thrombosis and Vascular Biology; Council on Cardiovascular Radiology and Intervention; Council on Clinical Cardiology; Council on Epidemiology and Prevention; Stroke Council.  Forecasting the impact of heart failure in the United States: a policy statement from the American Heart Association. Circ Heart Fail. 2013;6(3):606-619.
PubMed   |  Link to Article
Curtis  LH, Whellan  DJ, Hammill  BG,  et al.  Incidence and prevalence of heart failure in elderly persons, 1994-2003. Arch Intern Med. 2008;168(4):418-424.
PubMed   |  Link to Article
Jhund  PS, Macintyre  K, Simpson  CR,  et al.  Long-term trends in first hospitalization for heart failure and subsequent survival between 1986 and 2003: a population study of 5.1 million people. Circulation. 2009;119(4):515-523.
PubMed   |  Link to Article
Loehr  LR, Rosamond  WD, Chang  PP, Folsom  AR, Chambless  LE.  Heart failure incidence and survival (from the Atherosclerosis Risk in Communities study). Am J Cardiol. 2008;101(7):1016-1022.
PubMed   |  Link to Article
Yeung  DF, Boom  NK, Guo  H, Lee  DS, Schultz  SE, Tu  JV.  Trends in the incidence and outcomes of heart failure in Ontario, Canada: 1997 to 2007. CMAJ. 2012;184(14):E765-E773. doi:10.1503/cmaj.111958.
PubMed   |  Link to Article
Blecker  S, Paul  M, Taksler  G, Ogedegbe  G, Katz  S.  Heart failure–associated hospitalizations in the United States. J Am Coll Cardiol. 2013;61(12):1259-1267.
PubMed   |  Link to Article
Chen  J, Normand  SL, Wang  Y, Krumholz  HM.  National and regional trends in heart failure hospitalization and mortality rates for Medicare beneficiaries, 1998-2008. JAMA. 2011;306(15):1669-1678.
PubMed   |  Link to Article
Fang  J, Mensah  GA, Croft  JB, Keenan  NL.  Heart failure–related hospitalization in the U.S., 1979 to 2004. J Am Coll Cardiol. 2008;52(6):428-434.
PubMed   |  Link to Article
Teng  TH, Finn  J, Hobbs  M, Hung  J.  Heart failure: incidence, case fatality, and hospitalization rates in Western Australia between 1990 and 2005. Circ Heart Fail. 2010;3(2):236-243.
PubMed   |  Link to Article
Assaf  AR, Lapane  KL, McKenney  JL, Carleton  RA.  Possible influence of the prospective payment system on the assignment of discharge diagnoses for coronary heart disease. N Engl J Med. 1993;329(13):931-935.
PubMed   |  Link to Article
Jollis  JG, Ancukiewicz  M, DeLong  ER, Pryor  DB, Muhlbaier  LH, Mark  DB.  Discordance of databases designed for claims payment versus clinical information systems: implications for outcomes research. Ann Intern Med. 1993;119(8):844-850.
PubMed   |  Link to Article
Psaty  BM, Boineau  R, Kuller  LH, Luepker  RV.  The potential costs of upcoding for heart failure in the United States. Am J Cardiol. 1999;84(1):108-109, A9.
PubMed   |  Link to Article
Quach  S, Blais  C, Quan  H.  Administrative data have high variation in validity for recording heart failure. Can J Cardiol. 2010;26(8):306-312.
PubMed   |  Link to Article
Ezekowitz  JA, Kaul  P, Bakal  JA, Quan  H, McAlister  FA.  Trends in heart failure care: has the incident diagnosis of heart failure shifted from the hospital to the emergency department and outpatient clinics? Eur J Heart Fail. 2011;13(2):142-147.
PubMed   |  Link to Article
Roger  VL.  Epidemiology of heart failure. Circ Res. 2013;113(6):646-659.
PubMed   |  Link to Article
Bui  AL, Horwich  TB, Fonarow  GC.  Epidemiology and risk profile of heart failure. Nat Rev Cardiol. 2011;8(1):30-41.
PubMed   |  Link to Article
Levy  D, Kenchaiah  S, Larson  MG,  et al.  Long-term trends in the incidence of and survival with heart failure. N Engl J Med. 2002;347(18):1397-1402.
PubMed   |  Link to Article
Roger  VL, Weston  SA, Redfield  MM,  et al.  Trends in heart failure incidence and survival in a community-based population. JAMA. 2004;292(3):344-350.
PubMed   |  Link to Article
Barker  WH, Mullooly  JP, Getchell  W.  Changing incidence and survival for heart failure in a well-defined older population, 1970-1974 and 1990-1994. Circulation. 2006;113(6):799-805.
PubMed   |  Link to Article
Bahrami  H, Kronmal  R, Bluemke  DA,  et al.  Differences in the incidence of congestive heart failure by ethnicity: the Multi-Ethnic Study of Atherosclerosis. Arch Intern Med. 2008;168(19):2138-2145.
PubMed   |  Link to Article
Goldberg  RJ, Spencer  FA, Farmer  C, Meyer  TE, Pezzella  S.  Incidence and hospital death rates associated with heart failure: a community-wide perspective. Am J Med. 2005;118(7):728-734.
PubMed   |  Link to Article
Gerber  Y, Weston  SA, Berardi  C,  et al.  Contemporary trends in heart failure with reduced and preserved ejection fraction after myocardial infarction: a community study. Am J Epidemiol. 2013;178(8):1272-1280.
PubMed   |  Link to Article
He  J, Ogden  LG, Bazzano  LA, Vupputuri  S, Loria  C, Whelton  PK.  Risk factors for congestive heart failure in US men and women: NHANES I epidemiologic follow-up study. Arch Intern Med. 2001;161(7):996-1002.
PubMed   |  Link to Article
Dunlay  SM, Weston  SA, Jacobsen  SJ, Roger  VL.  Risk factors for heart failure: a population-based case-control study. Am J Med. 2009;122(11):1023-1028.
PubMed   |  Link to Article
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(3):251-259.
PubMed   |  Link to Article
Bhatia  RS, Tu  JV, Lee  DS,  et al.  Outcome of heart failure with preserved ejection fraction in a population-based study. N Engl J Med. 2006;355(3):260-269.
PubMed   |  Link to Article
Borlaug  BA, Paulus  WJ.  Heart failure with preserved ejection fraction: pathophysiology, diagnosis, and treatment. Eur Heart J. 2011;32(6):670-679.
PubMed   |  Link to Article
Fonarow  GC, Stough  WG, Abraham  WT,  et al; OPTIMIZE-HF Investigators and Hospitals.  Characteristics, treatments, and outcomes of patients with preserved systolic function hospitalized for heart failure: a report from the OPTIMIZE-HF Registry. J Am Coll Cardiol. 2007;50(8):768-777.
PubMed   |  Link to Article
United States Census Bureau. American FactFinder.http://factfinder.census.gov/faces/nav/jsf/pages/community_facts.xhtml. Accessed December 11, 2014.
Melton  LJ  III.  History of the Rochester Epidemiology Project. Mayo Clin Proc. 1996;71(3):266-274.
PubMed   |  Link to Article
Rocca  WA, Yawn  BP, St Sauver  JL, Grossardt  BR, Melton  LJ  III.  History of the Rochester Epidemiology Project: half a century of medical records linkage in a US population. Mayo Clin Proc. 2012;87(12):1202-1213.
PubMed   |  Link to Article
McKee  PA, Castelli  WP, McNamara  PM, Kannel  WB.  The natural history of congestive heart failure: the Framingham Study. N Engl J Med. 1971;285(26):1441-1446.
PubMed   |  Link to Article
Dunlay  SM, Redfield  MM, Weston  SA,  et al.  Hospitalizations after heart failure diagnosis: a community perspective. J Am Coll Cardiol. 2009;54(18):1695-1702.
PubMed   |  Link to Article
Dunlay  SM, Roger  VL, Weston  SA, Jiang  R, Redfield  MM.  Longitudinal changes in ejection fraction in heart failure patients with preserved and reduced ejection fraction. Circ Heart Fail. 2012;5(6):720-726.
PubMed   |  Link to Article
Quinones  MA, Waggoner  AD, Reduto  LA,  et al.  A new, simplified and accurate method for determining ejection fraction with two-dimensional echocardiography. Circulation. 1981;64(4):744-753.
PubMed   |  Link to Article
Lang  RM, Bierig  M, Devereux  RB,  et al; Chamber Quantification Writing Group; American Society of Echocardiography’s Guidelines and Standards Committee; European Association of Echocardiography.  Recommendations for chamber quantification: a report from the American Society of Echocardiography’s Guidelines and Standards Committee and the Chamber Quantification Writing Group, developed in conjunction with the European Association of Echocardiography, a branch of the European Society of Cardiology. J Am Soc Echocardiogr. 2005;18(12):1440-1463.
PubMed   |  Link to Article
Yancy  CW, Jessup  M, Bozkurt  B,  et al; Writing Committee Members; American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines.  2013 ACCF/AHA guideline for the management of heart failure: a report of the American College of Cardiology Foundation/American Heart Association Task Force on practice guidelines. Circulation. 2013;128(16):e240-e327. doi:10.1161/CIR.0b013e31829e8776.
PubMed   |  Link to Article
Gerber  Y, Jacobsen  SJ, Frye  RL, Weston  SA, Killian  JM, Roger  VL.  Secular trends in deaths from cardiovascular diseases: a 25-year community study. Circulation. 2006;113(19):2285-2292.
PubMed   |  Link to Article
Kurtz  CE, Gerber  Y, Weston  SA, Redfield  MM, Jacobsen  SJ, Roger  VL.  Use of ejection fraction tests and coronary angiography in patients with heart failure. Mayo Clin Proc. 2006;81(7):906-913.
PubMed   |  Link to Article
Rubin  DB. Multiple Imputation for Nonresponse in Surveys. New York, NY: John Wiley & Sons; 1987.
Najafi  F, Jamrozik  K, Dobson  AJ.  Understanding the “epidemic of heart failure”: a systematic review of trends in determinants of heart failure. Eur J Heart Fail. 2009;11(5):472-479.
PubMed   |  Link to Article
Mehta  PA, Dubrey  SW, McIntyre  HF,  et al.  Improving survival in the 6 months after diagnosis of heart failure in the past decade: population-based data from the UK. Heart. 2009;95(22):1851-1856.
PubMed   |  Link to Article
Brameld  KJ, Holman  CD, Lawrence  DM, Hobbs  MS.  Improved methods for estimating incidence from linked hospital morbidity data. Int J Epidemiol. 2003;32(4):617-624.
PubMed   |  Link to Article
Sutton  MG, Sharpe  N.  Left ventricular remodeling after myocardial infarction: pathophysiology and therapy. Circulation. 2000;101(25):2981-2988.
PubMed   |  Link to Article
Yeh  RW, Sidney  S, Chandra  M, Sorel  M, Selby  JV, Go  AS.  Population trends in the incidence and outcomes of acute myocardial infarction. N Engl J Med. 2010;362(23):2155-2165.
PubMed   |  Link to Article
Roger  VL, Weston  SA, Gerber  Y,  et al.  Trends in incidence, severity, and outcome of hospitalized myocardial infarction. Circulation. 2010;121(7):863-869.
PubMed   |  Link to Article
Gregg  EW, Li  Y, Wang  J,  et al.  Changes in diabetes-related complications in the United States, 1990-2010. N Engl J Med. 2014;370(16):1514-1523.
PubMed   |  Link to Article
Henkel  DM, Redfield  MM, Weston  SA, Gerber  Y, Roger  VL.  Death in heart failure: a community perspective. Circ Heart Fail. 2008;1(2):91-97.
PubMed   |  Link to Article
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The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
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