Contemporary Prevalence and Correlates of Incident Heart Failure with Preserved Ejection Fraction (original) (raw)
. Author manuscript; available in PMC: 2014 May 1.
Abstract
Background
We assessed the prevalence of preserved left ventricular ejection fraction (LVEF) in patients with incident heart failure, and differences in the demographic and clinical characteristics that may differentiate patients presenting with heart failure with preserved versus reduced LVEF.
Methods
We identified all patients with newly diagnosed heart failure between 2005 and 2008 from four sites in the Cardiovascular Research Network based on hospital discharge and ambulatory visit diagnoses, and assigned a category of preserved, borderline, or reduced LVEF using data from electronic databases and chart review.
Results
We identified 11,994 patients with incident heart failure; of these, 6,210 (51.8%) had preserved LVEF, 1870 (15.6%) had borderline systolic dysfunction, and 3,914 (32.6%) had reduced LVEF. For those with heart failure with preserved LVEF, mean age was 74.7 years, and 57.1% were women; for those with borderline systolic dysfunction, mean age was 71.6 years and 38.4% were women; and for those with reduced LVEF, mean age was 69.1 years, and 32.6% were women. Compared with white patients, black patients were less likely to have heart failure with preserved systolic function. Those with a history of coronary artery bypass surgery, mitral and/or aortic valvular disease, atrial fibrillation or flutter, or a diagnosis of hypertension were more likely to have heart failure with preserved systolic function, as were those with a diverse range of non-cardiac comorbid conditions including chronic lung disease, chronic liver disease, a history of a hospitalized bleed, a history of a mechanical fall, a diagnosis of depression, and a diagnosis of dementia. Patients with a history of acute myocardial infarction, and a history of ventricular fibrillation or ventricular tachycardia were less likely to have heart failure with preserved LVEF. Patients with higher systolic blood pressures at baseline and lower LDL levels were more likely to have heart failure with preserved LVEF, as were those with lower hemoglobin levels and the lowest glomerular filtration rates.
Conclusions
Heart failure with preserved LVEF is the most common form of the heart failure syndrome among patients newly presenting with this condition, and women and older adults are especially affected. Evidence-based treatment strategies apply to less than a third of patients newly diagnosed with heart failure.
Keywords: Heart Failure, Prevalence, Ejection Fraction, Systolic Function, Elderly, Gender
Introduction
The heterogeneity of the heart failure syndrome is well appreciated, and the importance of heart failure with preserved left ventricular ejection fraction (HF-PEF) as a prominent contributor to the heart failure epidemic has been unequivocally established.1,2 Heart failure with “normal ventricular performance” has been described in case reports and small hospital-based case series dating back to the 1970s.3 However, there have been very few large population-based studies of this condition.
In a community-wide study of residents of Olmsted County, Minnesota, among 556 individuals with either incident or prevalent heart failure identified in the early to mid-2000’s, more than half had HF-PEF.4 Another study of patients hospitalized with decompensated heart failure at Mayo Clinic Hospitals from 1987 through 2001 determined that the prevalence of HF-PEF increased from 38% to 47% to 54% over the three consecutive five-year periods encompassed in the study.5
We conducted a large population-based study to provide a contemporary estimate of the prevalence of HF-PEF and heart failure with reduced left ventricular ejection fraction (HF-REF) among newly diagnosed patients with the heart failure syndrome. An additional goal was to describe the demographic and clinical characteristics that may differentiate HF-PEF from heart failure with HF-REF at the time of initial clinical presentation. To address these questions, we identified all patients with newly diagnosed heart failure from four sites participating in the Cardiovascular Research Network (CVRN) between 2005 and 2008.
Methods
The source population included members from four participating health plans within the National Heart, Lung and Blood Institute-sponsored CVRN.6 Sites included Kaiser Permanente Northern California, Kaiser Permanente Colorado, Kaiser Permanente Northwest, and Fallon Community Health Plan. Contributing sites provide care to an ethnically and socioeconomically diverse population across varying clinical practice settings and geographically diverse areas. Each site also had a Virtual Data Warehouse (VDW),6,7 which served as the primary data source for subject identification and characterization. The VDW is a distributed standardized data resource comprised of electronic datasets at each CVRN site, populated with linked demographic, administrative, ambulatory pharmacy, outpatient laboratory test results, and health care utilization (ambulatory visits and network and non-network hospitalizations with diagnoses and procedures) data for members receiving care at participating sites.
Institutional review boards at participating sites approved the study, and waiver of consent was obtained due to the nature of the study.
Study sample and characterization of left ventricular systolic function
We first identified all persons aged ≥21 years with diagnosed heart failure based on either having being hospitalized with a primary discharge diagnosis of heart failure and/or having >3 ambulatory visits coded for heart failure with at least one visit being with a cardiologist between January 1, 2005 through December 31, 2008. We used the following International Classification of Diseases, 9th Edition (ICD-9) codes: 398.91, 402.01, 402.11, 402.91, 404.01, 404.03, 404.11, 404.13, 404.91, 404.93, 428.0, 428.1, 428.20, 428.21, 428.22, 428.23, 428.30, 428.31, 428.32, 428.33, 428.40, 428.41, 428.42, 428.43, and 428.9. Prior studies have shown a positive predictive value of >95% for admissions with a primary discharge diagnosis of heart failure based on these codes when compared against chart review and Framingham clinical criteria.8,9,10 We defined incident heart failure as having no hospitalization or ambulatory heart failure diagnosis at any time during the five-year period before each patient’s first heart failure diagnosis.
We ascertained information on quantitative and/or qualitative assessments of LVEF from the results of echocardiograms, radionuclide scintigraphy, other nuclear imaging modalities, and left ventriculography test results available from site-specific databases complemented by manual chart review. We classified patients into categories of preserved and reduced ejection fraction. We defined HF-PEF as either a reported left ventricular ejection fraction > 50% and/or based on a physician’s qualitative assessment of preserved or normal systolic function.11 We defined HF-REF as either a reported left ventricular ejection fraction ≤40% and/or based on a physician’s qualitative assessment of moderate, moderate to severe, or severe systolic dysfunction. A third category termed “borderline” systolic dysfunction was defined as an LVEF of 41-49% and/or based on a physician’s qualitative assessment of mildly reduced systolic function.
Covariates
We ascertained information on coexisting illnesses based on diagnoses or procedures using relevant ICD-9 codes, laboratory results, or filled outpatient prescriptions from health plan hospitalization discharge, ambulatory visit, laboratory, and pharmacy databases, as well as site-specific diabetes mellitus and cancer registries.7,8, 12 We collected baseline data on diagnoses of acute myocardial infarction, unstable angina, coronary artery revascularization, stroke or transient ischemic attack, cerebrovascular disease, other thromboembolism, atrial fibrillation or flutter, ventricular fibrillation or tachycardia, mitral or aortic valvular heart disease, peripheral arterial disease, rheumatic heart disease, receipt of a pacemaker, receipt of cardiac resynchronization therapy, receipt of an implantable cardioverter defibrillator, dyslipidemia, hypertension, diabetes mellitus, hospitalized bleed, diagnosed dementia, diagnosed depression, chronic lung disease, chronic liver disease, mechanical fall, and systemic cancer based on ICD-9 codes and CPT procedure codes.
We ascertained available ambulatory results for systolic and diastolic blood pressure, serum LDL (low-density lipoprotein) and HDL (high-density lipoprotein) cholesterol measurements, estimated glomerular filtration rate, and hemoglobin level on or before the index date from each site’s VDW.6,7
Statistical analysis
We compared baseline characteristics across groups of left ventricular systolic function using ANOVA or relevant non-parametric tests for continuous variables and chi-squared tests for categorical variables. Given the large sample size, we focused only on differences in baseline characteristics that may be clinically meaningful.
We constructed a logistic regression model to identify demographic and clinical correlates of incident HF-PEF vs. HF-REF. The model adjusted for age, sex, race, and any other variables that differed between groups with a P<0.2. We also explored whether additional adjustment for clustering at the site level was necessary. All analyses were conducted using SAS statistical software, version 9.1 (Cary, N.C.).
Results
We identified 11,994 patients with incident heart failure over the period of study; the mean age of these patients was 72.4 years (SD 13.1) and 46.2% were female. Nearly half (48.3%) of all patients were 75 years of age or older (Table 1). A total of 6,210 (51.8%) patients had HF-PEF and 3,914 (32.6%) persons had HF-REF, with 1,870 (15.6%) having borderline systolic dysfunction.
Table 1.
Baseline characteristics among 11,994 patients newly diagnosed heart failure identified between 2005-2008
Variable | OverallN = 11,994 | Preserved EFN = 6,210 | Borderline EFN = 1,870 | Reduced EFN = 3,914 | p-value |
---|---|---|---|---|---|
Mean (SD) age, yr | 72.4 (13.1) | 74.7 (12.1) | 71.6 (12.9) | 69.1 (14.0) | <0.001 |
Age categories | <0.001 | ||||
Age <45 | 404 (3.4) | 123 (2.0) | 60 (3.2) | 221 (5.6) | |
Age 45-54 | 894 (7.5) | 312 (5.0) | 141 (7.5) | 441 (11.3) | |
Age 55-64 | 1974 (16.5) | 827 (13.3) | 365 (19.5) | 782 (20.0) | |
Age 65-74 | 2929 (24.4) | 1508 (24.3) | 457 (24.4) | 964 (24.6) | |
Age 75-84 | 3815 (31.8) | 2218 (35.7) | 564 (30.2) | 1033 (26.4) | |
Age ≥ 85 | 1978 (16.5) | 1222 (19.7) | 283 (15.1) | 473 (12.1) | |
Female gender, n (%) | 5539 (46.2) | 3543 (57.1) | 719 (38.4) | 1277 (32.6) | <0.001 |
Race categories | <0.001 | ||||
White | 8922 (74.4) | 4759 (76.6) | 1421 (76.0) | 2742 (70.1) | |
Black/African American | 972 (8.1) | 428 (6.9) | 157 (8.4) | 387 (9.9) | |
Asian American | 711 (5.9) | 374 (6.0) | 104 (5.6) | 233 (6.0) | |
Native Hawaiian or other Pacific Islander | 99 (0.8) | 52 (0.8) | 13 (0.7) | 34 (0.9) | |
American Indian or Alaska Native | 33 (0.3) | 15 (0.2) | 4 (0.2) | 14 (0.4) | |
Missing/Unknown | 1257 (10.5) | 582 (9.4) | 171 (9.1) | 504 (12.9) | |
Medical History, n (%) | |||||
Acute myocardial Infraction | 858 (7.2) | 381 (6.1) | 198 (10.6) | 279 (7.1) | <0.001 |
Unstable angina | 473 (3.9) | 273 (4.4) | 93 (5.0) | 107 (2.7) | <0.001 |
Coronary artery bypass surgery | 475 (4.0) | 256 (4.1) | 116 (6.2) | 103 (2.6) | <0.001 |
Percutaneous coronary intervention | 875 (7.3) | 393 (6.3) | 198 (10.6) | 284 (7.3) | <0.001 |
Ischemic stroke or transient ischemic attack | 753 (6.3) | 438 (7.1) | 128 (6.8) | 187 (4.8) | <0.001 |
Cerebrovascular disease | 1803 (15.0) | 1027 (16.5) | 304 (16.3) | 472 (12.1) | <0.001 |
Other thromboembolic event | 68 (0.6) | 42 (0.7) | 13 (0.7) | 13 (0.3) | 0.06 |
Atrial fibrillation or flutter | 3699 (30.8) | 2195 (35.3) | 586 (31.3) | 918 (23.5) | <0.001 |
Ventricular tachycardia or fibrillation | 207 (1.7) | 69 (1.1) | 40 (2.1) | 98 (2.5) | <0.001 |
Mitral and/or aortic valvular disease | 2038 (17.0) | 1315 (21.2) | 315 (16.8) | 408 (10.4) | <0.001 |
Peripheral arterial disease | 718 (6.0) | 398 (6.4) | 129 (6.9) | 191 (4.9) | 0.001 |
Rheumatic heart disease | 224 (1.9) | 128 (2.1) | 32 (1.7) | 64 (1.6) | 0.26 |
Implantable cardioverter defibrillator | 116 (1.0) | 22 (0.4) | 23 (1.2) | 71 (1.8) | <0.001 |
Pacemaker | 512 (4.3) | 282 (4.5) | 80 (4.3) | 150 (3.8) | 0.23 |
Dyslipidemia | 7175 (59.8) | 3833 (61.7) | 1191 (63.7) | 2151 (55.0) | <0.001 |
Hypertension | 8994 (75.0) | 5114 (82.4) | 1402 (75.0) | 2478 (63.3) | <0.001 |
Diabetes mellitus | 2301 (19.2) | 1217 (19.6) | 383 (20.5) | 701 (17.9) | 0.03 |
Hospitalized bleeds | 498 (4.2) | 306 (4.9) | 78 (4.2) | 114 (2.9) | <0.001 |
Diagnosed dementia | 803 (6.7) | 480 (7.7) | 128 (6.8) | 195 (5.0) | <0.001 |
Diagnosed depression | 1959 (16.3) | 1141 (18.4) | 294 (15.7) | 524 (13.4) | <0.001 |
Chronic lung disease | 4148 (34.6) | 2369 (38.1) | 629 (33.6) | 1150 (29.4) | <0.001 |
Chronic liver disease | 428 (3.6) | 242 (3.9) | 57 (3.0) | 129 (3.3) | 0.12 |
Mechanical fall | 264 (2.2) | 178 (2.9) | 31 (1.7) | 55 (1.4) | <0.001 |
Systemic cancer | 862 (7.2) | 493 (7.9) | 120 (6.4) | 249 (6.4) | 0.004 |
Baseline eGFR category, ml/min/1.73 m2, n (%) | <0.001 | ||||
eGFR ≥130 | 23 (0.2) | 9 (0.1) | 6 (0.3) | 8 (0.2) | |
eGFR 90-130 | 1503 (12.5) | 690 (11.1) | 235 (12.6) | 578 (14.8) | |
eGFR 60-89 | 4746 (39.6) | 2382 (38.4) | 758 (40.5) | 1606 (41.0) | |
eGFR 45-59 | 2583 (21.5) | 1406 (22.6) | 386 (20.6) | 791 (20.2) | |
eGFR 30-44 | 1614 (13.5) | 983 (15.8) | 239 (12.8) | 392 (10.0) | |
eGFR 15-29 | 572 (4.8) | 376 (6.1) | 75 (4.0) | 121 (3.1) | |
eGFR <15 | 99 (0.8) | 70 (1.1) | 15 (0.8) | 14 (0.4) | |
Dialysis | 209 (1.7) | 117 (1.9) | 40 (2.1) | 52 (1.3) | |
Missing | 645 (5.4) | 177 (2.9) | 116 (6.2) | 352 (9.0) | |
Baseline hemoglobin category, g/L, n (%) | <0.001 | ||||
≥ 16.0 | 804 (6.7) | 303 (4.9) | 131 (7.0) | 370 (9.5) | |
15.0-15.9 | 1225 (10.2) | 495 (8.0) | 202 (10.8) | 528 (13.5) | |
14.0-14.9 | 2101 (17.5) | 976 (15.7) | 341 (18.2) | 784 (20.0) | |
13.0-13.9 | 2338 (19.5) | 1295 (20.9) | 349 (18.7) | 694 (17.7) | |
12.0-12.9 | 1925 (16.0) | 1147 (18.5) | 304 (16.3) | 474 (12.1) | |
11.0-11.9 | 1285 (10.7) | 829 (13.3) | 185 (9.9) | 271 (6.9) | |
10.0-10.9 | 788 (6.6) | 508 (8.2) | 116 (6.2) | 164 (4.2) | |
9.0-9.9 | 343 (2.9) | 219 (3.5) | 51 (2.7) | 73 (1.9) | |
<9.0 | 166 (1.4) | 101 (1.6) | 29 (1.6) | 36 (0.9) | |
Missing | 1019 (8.5) | 337 (5.4) | 162 (8.7) | 520 (13.3) | |
Systolic blood pressure category, mmHg, n (%) | <0.001 | ||||
≥180 | 383 (3.2) | 234 (3.8) | 56 (3.0) | 93 (2.4) | |
160-179 | 894 (7.5) | 533 (8.6) | 132 (7.1) | 229 (5.9) | |
140-159 | 2486 (20.7) | 1351 (21.8) | 412 (22.0) | 723 (18.5) | |
130-139 | 2416 (20.1) | 1283 (20.7) | 368 (19.7) | 765 (19.5) | |
121-129 | 1791 (14.9) | 899 (14.5) | 280 (15.0) | 612 (15.6) | |
110-120 | 2603 (21.7) | 1253 (20.2) | 417 (22.3) | 933 (23.8) | |
100-109 | 609 (5.1) | 290 (4.7) | 79 (4.2) | 240 (6.1) | |
< 100 | 283 (2.4) | 120 (1.9) | 41 (2.2) | 122 (3.1) | |
Missing | 529 (4.4) | 247 (4.0) | 85 (4.5) | 197 (5.0) | |
Diastolic blood pressure category, mmHg, n (%) | <0.001 | ||||
≥110 | 153 (1.3) | 59 (1.0) | 22 (1.2) | 72 (1.8) | |
100-109 | 341 (2.8) | 129 (2.1) | 49 (2.6) | 163 (4.2) | |
90-99 | 853 (7.1) | 366 (5.9) | 146 (7.8) | 341 (8.7) | |
85-89 | 726 (6.1) | 311 (5.0) | 118 (6.3) | 297 (7.6) | |
81-84 | 951 (7.9) | 482 (7.8) | 153 (8.2) | 316 (8.1) | |
≤80 | 8440 (70.4) | 4616 (74.3) | 1297 (69.4) | 2527 (64.6) | |
Missing | 530 (4.4) | 247 (4.0) | 85 (4.5) | 198 (5.1) | |
HDL cholesterol category, g/dL, n (%) | <0.001 | ||||
≥60 | 2110 (17.6) | 1229 (19.8) | 291 (15.6) | 590 (15.1) | |
50-50.9 | 2174 (18.1) | 1180 (19.0) | 306 (16.4) | 688 (17.6) | |
40-49.9 | 3147 (26.2) | 1663 (26.8) | 517 (27.6) | 967 (24.7) | |
35-39.9 | 1516 (12.6) | 784 (12.6) | 244 (13.0) | 488 (12.5) | |
<35 | 1532 (12.8) | 730 (11.8) | 286 (15.3) | 516 (13.2) | |
Missing | 1515 (12.6) | 624 (10.0) | 226 (12.1) | 665 (17.0) | |
LDL cholesterol category, g/dL, n (%) | <0.001 | ||||
≥200 | 118 (1.0) | 45 (0.7) | 20 (1.1) | 53 (1.4) | |
160-199.9 | 483 (4.0) | 234 (3.8) | 84 (4.5) | 165 (4.2) | |
130-159.9 | 1341 (11.2) | 668 (10.8) | 216 (11.6) | 457 (11.7) | |
100-129.9 | 2746 (22.9) | 1453 (23.4) | 417 (22.3) | 876 (22.4) | |
70-99.9 | 3837 (32.0) | 2114 (34.0) | 576 (30.8) | 1147 (29.3) | |
<70 | 1837 (15.3) | 1016 (16.4) | 320 (17.1) | 501 (12.8) | |
Missing | 1632 (13.6) | 680 (11.0) | 237 (12.7) | 715 (18.3) |
Among those with HF-PEF, their mean age was 74.7 years and 55.4% were aged 75 years or older; 57.1% of these patients were women. For those with HF-REF, their mean age was 69.1 years and 38.5% were 75 years or older; 32.6% of these patients were women. For those with borderline systolic dysfunction, their mean age was 71.6 years and 45.2% were 75 years of age or older; 38.4% of these patients were women (Table 1).
Medication use in the 120 days prior to the diagnosis date is summarized in Table 2. Of note, nearly half of all patients were receiving ACE (angiotensin-converting-enzyme) inhibitors or angiotensin II receptor blockers during this time period; more than half were receiving beta-blockers and nearly a third were receiving loop diuretics.
Table 2.
Baseline medication use among 11,994 patients with newly diagnosed heart failure identified between 2005-2008.
Medication Category | OverallN = 11,994 | PreservedEFN = 6,210 | BorderlineEFN = 1,870 | Reduced EFN = 3,914 | p-value |
---|---|---|---|---|---|
ACE inhibitors/Angiotensin II receptor blockers(ARB) | 5688 (47.4) | 3080 (49.6) | 927 (49.6) | 1681 (42.9) | <0.001 |
Aldosterone receptor antagonist | 221 (1.8) | 93 (1.5) | 29 (1.6) | 99 (2.5) | 0.001 |
Beta-blocker | 6416 (53.5) | 3877 (62.4) | 1000 (53.5) | 1539 (39.3) | <0.001 |
Calcium channel blocker | 3140 (26.2) | 2099 (33.8) | 442 (23.6) | 599 (15.3) | <0.001 |
Digoxin | 865 (7.2) | 498 (8.0) | 117 (6.3) | 250 (6.4) | 0.002 |
Diuretic (loop) | 3571 (29.8) | 2085 (33.6) | 513 (27.4) | 973 (24.9) | <0.001 |
Diuretic (thiazide) | 2807 (23.4) | 1728 (27.8) | 401 (21.4) | 678 (17.3) | <0.001 |
Nitrate | 1403 (11.7) | 723 (11.6) | 272 (14.5) | 408 (10.4) | <0.001 |
Statin | 5463 (45.5) | 2980 (48.0) | 911 (48.7) | 1572 (40.2) | <0.001 |
Other lipid-lowering drug | 636 (5.3) | 366 (5.9) | 106 (5.7) | 164 (4.2) | 0.001 |
Antiplatelet agent | 973 (8.1) | 484 (7.8) | 202 (10.8) | 287 (7.3) | <0.001 |
Anticoagulant | 2033 (17.0) | 1198 (19.3) | 322 (17.2) | 513 (13.1) | <0.001 |
Those with incident HF-PEF differed significantly from those with HF-REF across a range of demographic and clinical characteristics (Table 3). In multivariable analyses, older patients were more likely to be diagnosed with HF-PEF. For example, the odds of having HF-PEF for those aged 65-74 were 14% higher than for those aged 55-64; the odds for those aged 75-84 were 34% higher, and the odds for persons aged 85 or older were 51% higher. Women were over two-fold more likely than men to have HF-PEF (adjusted odds ratio: 2.24; 95% confidence interval 2.06-2.44). Compared with white patients, black patients were less likely to have heart failure with preserved systolic function (adjusted odds ratio: 0.69; 95% confidence interval 0.67-0.71).
Table 3.
Adjusted odds ratios for preserved left ventricular ejection fraction among adults with newly diagnosed heart failure (2005-2008).
Variable | Adjusted Odds Ratio for Preserved SystolicFunction(95% Confidence Interval) |
---|---|
Age group, yr | |
Age <45 | 0.77 (0.70-0.85) |
Age 45-54 | 0.79 (0.72-0.86) |
Age 55-64 | Reference |
Age 65-74 | 1.14 (1.08-1.20) |
Age 75-84 | 1.34 (1.31-1.37) |
Age ≥ 85 | 1.51 (1.41-1.61) |
Female gender, n (%) | 2.24 (2.06-2.44) |
Race categories | |
White | Reference |
Black/African American | 0.69 (0.67-0.71) |
Asian American | 1.02 (0.94-1.12) |
Native Hawaiian or other Pacific Islander | 1.09 (0.89-1.33) |
American Indian or Alaska Native | 0.53 (0.46-0.62) |
Missing/Unknown | 0.79 (0.70-0.89) |
Medical History, n (%) | |
Acute myocardial Infarction | 0.78 (0.65-0.95) |
Coronary artery bypass surgery | 1.79 (1.39-2.33) |
Percutaneous coronary intervention | 0.95 (0.80-1.13) |
Ischemic stroke or transient ischemic attack | 1.05 (0.95-1.17) |
Other thromboembolic event | 1.05 (0.83-1.34) |
Atrial fibrillation or atrial flutter | 1.66 (1.57-1.76) |
Ventricular tachycardia or fibrillation | 0.53 (0.49-0.58) |
Mitral and/or aortic valvular disease | 1.99 (1.64-2.40) |
Peripheral arterial disease | 0.98 (0.87-1.09) |
Rheumatic heart disease | 0.86 (0.74-1.01) |
Implantable cardioverter defibrillator | 0.29 (0.24-0.35) |
Pacemaker | 0.89 (0.78-1.01) |
Dyslipidemia | 1.09 (0.98-1.22) |
Hypertension | 1.75 (1.62-1.88) |
Diabetes mellitus | 1.06 (0.99-1.14) |
Hospitalized bleeds | 1.31 (1.11-1.54) |
Diagnosed dementia | 1.10 (1.01-1.20) |
Diagnosed depression | 1.20 (1.16-1.24) |
Chronic lung disease | 1.38 (1.22-1.55) |
Chronic liver disease | 1.27 (1.07-1.49) |
Mechanical fall | 1.38 (1.07-1.78) |
Systemic cancer | 1.02 (0.87-1.21) |
Estimated GFR (ml/min/1.73 m2) | |
eGFR ≥130 | 1.36 (0.86-2.16) |
eGFR 90-130 | 1.02 (0.96-1.10) |
eGFR 60-89 | Reference |
eGFR 45-59 | 0.95 (0.90-1.00) |
eGFR 30-44 | 1.07 (0.98-1.18) |
eGFR 15-29 | 1.31 (0.99-1.73) |
eGFR <15 | 2.12 (1.77-2.54) |
Dialysis | 1.47 (1.26-1.71) |
Missing | 0.84 (0.61-1.17) |
Hemoglobin (g/L) | |
≥ 16.0 | 0.72 (0.62-0.82) |
15.0-15.9 | 0.70 (0.65-0.74) |
14.0-14.9 | 0.76 (0.75-0.78) |
13.0-13.9 | Reference |
12.0-12.9 | 1.15 (1.01-1.31) |
11.0-11.9 | 1.42 (1.35-1.50) |
10.0-10.9 | 1.36 (1.10-1.67) |
9.0-9.9 | 1.37 (1.17-1.60) |
<9.0 | 1.34 (1.03-1.75) |
Missing | 0.65 (0.53-0.80) |
Systolic blood pressure (mmHg) | |
≥180 | 2.04 (1.59-2.60) |
160-179 | 1.60 (1.41-1.80) |
140-159 | 1.28 (1.13-1.45) |
130-139 | 1.13 (1.06-1.21) |
121-129 | 1.00 (0.95-1.04) |
110-120 | Reference |
100-109 | 0.80 (0.66-0.97) |
< 100 | 0.68 (0.62-0.75) |
Missing | 1.67 (1.30-2.14) |
HDL cholesterol (g/dL) | |
≥60 | 0.87 (0.79-0.97) |
50-50.9 | 0.83 (0.79-0.88) |
40-49.9 | Reference |
35-39.9 | 1.01 (0.91-1.13) |
<35 | 0.90 (0.81-1.01) |
Missing | 0.96 (0.75-1.23) |
LDL cholesterol (g/dL) | |
≥200 | 0.56 (0.42-0.73) |
160-199.9 | 0.98 (0.83-1.16) |
130-159.9 | Reference |
100-129.9 | 1.08 (0.96-1.21) |
70-99.9 | 1.14 (1.04-1.25) |
<70 | 1.22 (1.09-1.36) |
Missing | 0.84 (0.71-0.98) |
Individuals with a history of coronary artery bypass surgery, mitral and/or aortic valvular disease, atrial fibrillation or flutter, or a diagnosis of hypertension were more likely to have HF-PEF, as were those with a diverse range of non-cardiac comorbid conditions including chronic lung disease, chronic liver disease, a history of a hospitalized bleed, a history of a mechanical fall, a diagnosis of depression, and a diagnosis of dementia. Patients with a history of acute myocardial infarction, and a history of ventricular fibrillation or ventricular tachycardia were less likely to have HF-PEF (Table 3).
Patients with higher systolic blood pressures at baseline were more likely to have HF-PEF (Table 3). Compared with a baseline systolic blood pressure of 110-120 mm Hg, the odds for those patients with systolic blood pressures of 130-139 mm Hg were 13% higher; the odds for patients with systolic blood pressures of 140-159 and 160-170 mm Hg were 28% and 60% higher, respectively. For those patients with systolic blood pressures of >180 mm Hg, the adjusted odds ratio was 2.04 (95% confidence interval 1.59 to 2.60). Lower LDL levels, lower hemoglobin levels, and very low estimated glomerular filtration rates (<15 ml/min/1.73 m2) were more likely in those presenting with HF-PEF.
Discussion
In this very large, contemporary, multicenter cohort comprised of patients with newly diagnosed heart failure, more than 50% had HF-PEF. These findings are sobering in that of the 2011 American College of Cardiology Foundation/American Heart Association/American Medical Association-Physician Consortium for Performance Improvement (ACCF/AHA/AMA-PCPI) performance measures for adults with heart failure,13 all of the measures associated with therapeutic interventions focus solely on patients with HF-REF. Such patients comprise less than one-third of those with incident heart failure, according to the findings of our study.
The nomenclature regarding the classification of heart failure has been a subject of some controversy.5 The most recently revised ACC/AHA- guidelines for the diagnosis and management of heart failure use the term “heart failure with normal left ventricular ejection fraction.”14 In the present study, we took a somewhat less stringent approach to characterizing patients, as we employed both quantitative and qualitative assessments of left ventricular systolic function which represents how patients are frequently evaluated and classified in clinical practice, especially given the known challenges in the accuracy of the calculation of left ventricular ejection fraction.
As has been reported in previous studies, older age, female sex, hypertension, presence of atrial fibrillation, and lower hemoglobin levels were more likely to be present in patients with HF-PEF.5,15 Our study findings also serve to emphasize the complexity of the patient population with heart failure; a variety of non-cardiac conditions such as chronic lung disease, chronic liver disease, depression, and dementia were more likely to be present in patients diagnosed with HF-PEF. The implications of non-cardiac comorbidities, and how they relate to clinical decision-making and clinical outcomes in the patient population with heart failure, have been increasingly appreciated.16,17,18,19
Our study has some limitations. Insured populations in our participating health plans may not be fully representative of the general population. Nevertheless, this limitation is counterbalanced by the breadth of geographic and demographic diversity represented across four geographically diverse health plans, as well as the community-based nature of health care delivery, suggesting that findings from our study are likely to be highly generalizable to heart failure patients in “real-world” practice settings. In our study, heart failure diagnoses were not adjudicated through medical record abstraction and expert review. However, prior studies have shown a high positive predictive value for the approach we used to identify heart failure patients.
Our findings confirm that a majority of patients who present with heart failure have HF-PEF, and it is likely that the numbers of patients affected by this form of the heart failure syndrome will increase with the aging of the U.S. population over the coming decades. Yet, there remains a dearth of evidence to guide the management of these very complex patients, who suffer adverse outcomes including hospitalization and mortality at very high rates.
Few studies have been undertaken that have specifically focused on patients with HF-PEF, and clinical trials regarding heart failure have tended to exclude the types of patients most commonly presenting with this condition, including the elderly, women, and those with high burdens of comorbidity.1,20,21 The imperative to address this situation has never been more apparent and urgent.
Acknowledgments
Funding: The study was supported by 1RC1HL099395 and U19 HL91179 from the National Heart, Lung and Blood Institute of the National Institutes of Health (NIH). Support for Dr. McManus was additionally provided by NIH grant KL2RR031981 and Dr. Saczynski received additional support from NIH grant K01AG33643.
Acknowledgements
The authors wish to thank all of the project managers, data programmers and analysts for their critical technical contributions and support that made this study possible.
Role of Sponsors
The sponsors had no role in: the design and conduct of the study; collection management, analysis, or interpretation of the data; and preparation, review, or approval of the manuscript.
Footnotes
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Conflict of Interest: Larry Allen has served as a consultant for Amgen and J&J/Janssen.
Authorship: All authors had access to the data and a role in writing the manuscript.
References
- 1.Kitzman DW, Rich MW. Age disparities in heart failure research. JAMA. 2010;304:1950–1951. doi: 10.1001/jama.2010.1592. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Bhuiyan T, Maurer MS. Heart failure with preserved ejection fraction: Persistent diagnosis, therapeutic enigma. Curr Cardiovasc Risk Rep. 2011;5:440–449. doi: 10.1007/s12170-011-0184-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Vasan RS, Benjamin EJ, Levy D. Prevalence, clinical features and prognosis of diastolic heart failure: An epidemiologic perspective. J Am Coll Cardiol. 1995;26:1565–1574. doi: 10.1016/0735-1097(95)00381-9. [DOI] [PubMed] [Google Scholar]
- 4.Bursi F, Weston SA, Redfield MM, Jacobsen SJ, Pakhomov S, Nkomo VT, Meverdem RA, Roger VL. Systolic and diastolic heart failure in the community. JAMA. 2006;296:2209–2216. doi: 10.1001/jama.296.18.2209. [DOI] [PubMed] [Google Scholar]
- 5.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. doi: 10.1056/NEJMoa052256. [DOI] [PubMed] [Google Scholar]
- 6.Go AS, Magid DJ, Wells B, et al. The Cardiovascular Research Network: a new paradigm for cardiovascular quality and outcomes research. Circ Cardiovasc Qual Outcomes. 2008;1:138–47. doi: 10.1161/CIRCOUTCOMES.108.801654. [DOI] [PubMed] [Google Scholar]
- 7.Magid DJ, Gurwitz JH, Rumsfeld JS, Go AS. Creating a research data network for cardiovascular disease: the CVRN. Expert Rev Cardiovasc Ther. 2008;6:1043–45. doi: 10.1586/14779072.6.8.1043. [DOI] [PubMed] [Google Scholar]
- 8.Go AS, Lee WY, Yang J, Lo JC, Gurwitz JH. Statin therapy and risks for death and hospitalization in chronic heart failure. JAMA. 2006;296(17):2105–2111. doi: 10.1001/jama.296.17.2105. [DOI] [PubMed] [Google Scholar]
- 9.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(23):2713–2723. doi: 10.1161/CIRCULATIONAHA.105.577577. [DOI] [PubMed] [Google Scholar]
- 10.McKee PA, Castelli WP, McNamara PM, Kannel WB. The natural history of congestive heart failure: the Framingham study. N Engl J Med. 1971;285:1441–6. doi: 10.1056/NEJM197112232852601. [DOI] [PubMed] [Google Scholar]
- 11.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(2):194–202. doi: 10.1001/jama.289.2.194. [DOI] [PubMed] [Google Scholar]
- 12.Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY. Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med. 2004;351:1296–305. doi: 10.1056/NEJMoa041031. [DOI] [PubMed] [Google Scholar]
- 13.Bonow RO, Ganiats TG, Beam CT, Blake K, Casey DE, Jr, Goodlin SJ, Grady KL, et al. ACCF/AHA/AMA-PCPI 2011 performance measures for adults with heart failure: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Performance Measures and the American Medical Association-Physician Consortium for Performance Improvement. Circulation. 2012;125:2382–2401. doi: 10.1161/CIR.0b013e3182507bec. [DOI] [PubMed] [Google Scholar]
- 14.2009 focused update incorporated into the ACC/AHA 2005 Guidelines for the Diagnosis and Management of Heart Failure in Adults: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines: developed in collaboration with the International Society for Heart and Lung Transplantation. Hunt SA, Abraham WT, Chin MH, Feldman AM, Francis GS, Ganiats TG, Jessup M, Konstam MA, Mancini DM, Michl K, Oates JA, Rahko PS, Silver MA, Stevenson LW, Yancy CW. Circulation. 2009 Apr 14;119(14):e391–479. doi: 10.1161/CIRCULATIONAHA.109.192065. Epub 2009 Mar 26. Review. No abstract available. Erratum in: Circulation. 2010 Mar 30;121(12):e258.
- 15.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. doi: 10.1001/jama.288.17.2144. [DOI] [PubMed] [Google Scholar]
- 16.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. doi: 10.1016/s0735-1097(03)00947-1. [DOI] [PubMed] [Google Scholar]
- 17.Wong CY, Shaudhry SI, Desai MM, Krumholz HM. Trends in comorbidity, disability, and polypharmacy in heart failure. Am J Med. 2011;124:136–143. doi: 10.1016/j.amjmed.2010.08.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Ahluwalia SC, Gross CP, Chaudhry SI, Leo-Summers L, Van Ness PH, Fried TR. Change in comorbidity prevalence with advancing age among persons with heart failure. J Gen Intern Med. 2011;26:1145–1151. doi: 10.1007/s11606-011-1725-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Ahluwalia SC, Gross CP, Chaudhry SI, Ning YM, Leo-Summers L, Van Ness PH, Fried TR. Impact of comorbidity on mortality among older persons with advanced heart failure. J Gen Intern Med. 2011;27:513–519. doi: 10.1007/s11606-011-1930-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Cherubini A, Oristrell J, Pla X, Ruggiero C, Ferretti R, Ciestre G, Clarfield M, et al. The persistent exclusion of older patients from ongoing clinical trials regarding heart failure. Arch Intern Med. 2011;171:550–556. doi: 10.1001/archinternmed.2011.31. [DOI] [PubMed] [Google Scholar]
- 21.Gurwitz JH, Goldberg RJ. Age-based exclusions from cardiovascular clinical trials: implications for elderly individuals (and for all of us) Arch Intern Med. 2011;171:557–558. doi: 10.1001/archinternmed.2011.33. [DOI] [PubMed] [Google Scholar]