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Original Article
Association Between Atrial Fibrillation Symptoms,
Quality of Life, and Patient Outcomes
Results From the Outcomes Registry for Better Informed Treatment of
Atrial Fibrillation (ORBIT-AF)
James V. Freeman, MD, MPH, MS; DaJuanicia N. Simon, MS; Alan S. Go, MD;
John Spertus, MD, MPH; Gregg C. Fonarow, MD; Bernard J. Gersh, MB, ChB, DPhil;
Elaine M. Hylek, MD, MPH; Peter R. Kowey, MD; Kenneth W. Mahaffey, MD;
Laine E. Thomas, PhD; Paul Chang, MD; Eric D. Peterson, MD, MPH;
Jonathan P. Piccini, MD, MHS;
on behalf of the Outcomes Registry for Better Informed Treatment of
Atrial Fibrillation (ORBIT-AF) Investigators and Patients
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Background—Instruments to assess symptom burden and quality of life among patients with atrial fibrillation (AF) have not
been well evaluated in community practice or associated with patient outcomes.
Methods and Results—Using data from 10 087 AF patients in the Outcomes Registry for Better Informed Treatment of AF
(ORBIT-AF), symptom severity was evaluated using the European Heart Rhythm Association (EHRA) classification
system, and quality of life was assessed using the Atrial Fibrillation Effect on Quality-of-Life (AFEQT) questionnaire.
The association between AF-related symptoms, quality of life, and outcomes was assessed using Cox regression. The
majority of AF patients (61.8%) were symptomatic (EHRA >2) and 16.5% had severe or disabling symptoms (EHRA
3–4). EHRA symptom class was well correlated with the AFEQT score (Spearman correlation coefficient −0.39). Over
1.8 years of follow-up, AF symptoms were associated with a higher risk of hospitalization (adjusted hazard ratio for
EHRA ≥2 versus EHRA 1 1.23, 95% confidence interval, 1.15–1.31) and a borderline higher risk of major bleeding.
Lower quality of life was associated with a higher risk of hospitalization (adjusted hazard ratio for lowest quartile of
AFEQT versus highest 1.49, 95% confidence interval, 1.2–1.84), but not other major adverse events, including death.
Conclusions—In a community-based study, most patients with AF were symptomatic and had impaired quality of life.
Quality of life measured by the AFEQT correlated closely with symptom severity measured by the EHRA class.
AF symptoms and lower quality of life were associated with higher risk of hospitalization but not mortality during
follow-up. (Circ Cardiovasc Qual Outcomes. 2015;8:393-402. DOI: 10.1161/CIRCOUTCOMES.114.001303.)
Key Words: atrial fibrillation ◼ morbidity ◼ mortality ◼ quality of life ◼ symptoms
A
trial fibrillation (AF) substantially increases the risk of major
adverse clinical outcomes, such as stroke1,2 and death.3 Yet,
AF can also cause frequent symptoms, affect patient’s functional
status, and impair their quality of life.4 Although prior studies
have reported the range of AF-related symptoms in patient populations, these studies were generally from highly selected patients
and referral-based practices and may not reflect results in community practice or results with contemporary AF management..5–8
Additionally, although disease-specific symptom and
quality of life assessment tools have been developed for AF,
these tools have not been well assessed in large communitybased populations. For example, the European Heart Rhythm
Association (EHRA) has proposed a scoring system for
AF-related symptoms (1=asymptomatic, 2=mild, 3=severe,
4=disabling),9,10 but it remains unstudied in a large clinical
cohort. Like the New York Heart Association classification
Received July 24, 2014; accepted May 4, 2015.
From the Yale University School of Medicine, New Haven, CT (J.V.F.); Duke Clinical Research Institute, Durham, NC (D.N.S., L.E.T., E.D.P., J.P.P.);
Division of Research, Kaiser Permanente of Northern California, Oakland, CA (A.S.G.); Saint Luke’s Mid America Heart Institute and University of
Missouri–Kansas City (J.S.); Ronald Reagan-UCLA Medical Center, Los Angeles, CA (G.C.F.); Mayo Clinic Medical Center, Rochester, Minnesota
(B.J.G.); Boston University Medical Center, Boston, MA (E.M.H.); Lankenau Institute for Medical Research and Jefferson Medical College, Philadelphia,
PA (P.R.K.); and Stanford University School of Medicine, Stanford, CA (K.W.M.); Janssen Pharmaceuticals Inc., Bridgewater, NJ (P.C.).
This article was handled independently by Mathew Reeves, DVM, PhD, as a Guest Editor. The editors had no role in the evaluation of this manuscript
or in the decision about its acceptance.
The Data Supplement is available at http://circoutcomes.ahajournals.org/lookup/suppl/doi:10.1161/CIRCOUTCOMES.114.001303/-/DC1.
Correspondence to James V. Freeman MD, MPH, MS, Yale University School of Medicine, PO Box 208017, New Haven, CT 06520. E-mail
[email protected]
© 2015 American Heart Association, Inc.
Circ Cardiovasc Qual Outcomes is available at http://circoutcomes.ahajournals.org
393
DOI: 10.1161/CIRCOUTCOMES.114.001303
394 Circ Cardiovasc Qual Outcomes July 2015
WHAT IS KNOWN
• Atrial fibrillation causes symptoms, such as palpitations and dyspnea with exertion and may decrease
patient quality of life.
WHAT THE STUDY ADDS
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• The majority of atrial fibrillation patients (61.8%)
were symptomatic, and 16.5% had severe or disabling symptoms.
• The physician-reported European Heart Rhythm
Association (EHRA) symptom class was well correlated with the patient-reported Atrial Fibrillation
Effect on Quality-of-Life (AFEQT) questionnaire
score (Spearman correlation coefficient, −0.39).
• Atrial fibrillation symptoms were associated with
a higher risk of hospitalization (adjusted HR for
EHRA ≥2 versus EHRA 1 1.23, 95% CI 1.15–1.31)
and a borderline higher risk of major bleeding, but
not death.
• Lower quality of life was associated with a higher
risk of hospitalization (adjusted HR for lowest quartile of AFEQT versus highest 1.49, 95%
CI 1.2–1.84), but not other major adverse events,
including death.
for heart failure, the EHRA reflects physicians’ perspectives
of patients’ health status (symptoms, function, and quality
of life) and may offer a simple and valuable tool for guiding
treatment decisions and conducting research. Similarly, the
Atrial Fibrillation Effect on Quality-of-Life (AFEQT) questionnaire11 was recently developed as a disease-specific tool
for assessing quality of life and health status from patients’
perspectives, but has yet to be evaluated in a large community-based patient cohort. Finally, the association between
AF-related symptoms or quality of life from these assessment
tools with clinical outcomes, including death, hospitalization,
stroke, myocardial infarction, or major bleeding events, has
not been previously evaluated.
Using the Outcomes Registry for Better Informed
Treatment of Atrial Fibrillation (ORBIT-AF), a large, contemporary, prospective, community-based outpatient cohort, we
evaluated the type and frequency of symptoms in patients with
AF. In addition, we measured the degree to which symptom
severity (using the EHRA classification system) was correlated with quality of life (assessed by the AFEQT questionnaire) and the association between symptoms or quality of
life with clinical outcomes, including death, hospitalization,
stroke, and major bleeding.
Methods
ORBIT-AF Registry
The ORBIT-AF is an ongoing national, observational, communitybased, registry of outpatients with AF. The ORBIT-AF study has been
described previously.12 The primary data set for this analysis included
baseline data for 10 132 patients >18 years of age with electrocardiographically documented AF collected between June 2010 and August
2011 from 176 sites (82.4% community-based practice groups and
17.6% academic teaching facilities) throughout the United States.
Trained personnel at participating outpatient practices, including internal medicine, cardiology, and electrophysiology clinics, abstracted
data on consecutive eligible AF patients and submitted them to the
ORBIT-AF registry via Web-enabled case report forms.
Using standard definitions, data include demographic and clinical characteristics, insurance status, education level, medical history
and prior treatments, type of AF, pharmacological treatment strategy,
antithrombotic therapy and monitoring, EHRA symptom score, and
the patient-reported outcome questionnaire.
Study Population
We enrolled 10 132 patients >18 years of age with electrocardiographically documented AF. For the current analysis, 45 patients without
documented EHRA status were excluded, leaving 10 087 patients
in the study cohort. Patient quality of life data were derived from a
subsample of 2006 (19.8%) subjects administered a patient-reported
outcome questionnaire at the baseline visit. Of the sites in the main
cohort, 58% participated in the quality of life survey. All patients enrolled in the main cohort at these sites were approached to complete
the questionnaire on a voluntary basis until the quality of life subsample enrollment goal was met. Of the patients with documented EHRA
status, 2006 patients were administered the patient-reported outcome questionnaire. All subjects provided written, informed consent.
Institutional review boards of the Duke Clinical Research Institute and
the participating enrollment sites approved the study.
Physician-Assessed Symptom Burden, PatientReported Symptoms and Quality of Life, and
Outcomes
At baseline, we assessed physician-assessed AF symptom burden
(EHRA score) and patient-reported AF symptoms and quality of
life (AFEQT score). Individual patient-reported symptoms were assessed, including palpitations, syncope or fainting, dyspnea on exertion, exercise intolerance, lightheadedness or dizziness, dyspnea at
rest, fatigue, and chest tightness or discomfort. In addition, physicianassessed AF symptom severity and burden was assessed by treating
physicians using the EHRA symptom classification defined as asymptomatic (EHRA 1), mild symptoms (EHRA 2), severe symptoms
(EHRA 3), and disabling symptoms (EHRA 4).9,10 Treating physicians were blinded to the patient AFEQT responses when providing
EHRA scores.
Quality of life data were derived from the patient-reported outcome questionnaires administered to a subsample of ≈20% of patients from the overall ORBIT-AF registry population. All patients
at sites agreeing to participate in the questionnaire substudy were
approached until the enrollment goals were met. The baseline characteristics were similar between the overall cohort and the subsample
cohort (Table I in the Data Supplement). AF-related quality of life
was measured in this group using the previously validated AFEQT
questionnaire (St Jude Medical, St Paul, MN). The AFEQT is a 20item questionnaire assessing 3 domains of AF-related quality of life,
including activity, symptoms, and treatment concerns.11,13 An overall
summary score can be calculated from these domains and was used
for the primary analyses in this study.
Follow-up data collection occurred at 6-month intervals for a
minimum of 2 years. The primary outcomes for this analysis were
all-cause death, first hospitalization, first stroke or transient ischemic
attack, first myocardial infarction, and first major bleeding event using standard definitions.12 Primary outcome events were verified by
single-source document submission (eg, hospital discharge report)
and central review at the data coordinating center. Outcomes within
the first 2 years of baseline enrollment were analyzed.
Statistical Analysis
All analyses were performed using SAS statistical software (version 9.3, SAS Institute, Cary, NC). We compared the baseline
Freeman et al Atrial Fibrillation Symptoms and Outcomes 395
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characteristics for patients in the ORBIT-AF study population overall
and according to the EHRA symptom classification as asymptomatic (EHRA 1) or symptomatic (EHRA ≥2) using the χ2 test for categorical variables and the Wilcoxon rank-sum test for continuous/
ordinal variables. We also compared the baseline characteristics for
the subset of patients in the ORBIT-AF study population who completed the AFEQT patient-reported outcome questionnaire overall
and according to quartiles of the AFEQT score using the χ2 test for
categorical variables and the Kruskal–Wallis test for continuous/
ordinal variables. AF symptom prevalence was calculated using frequencies and percentages overall and by each EHRA symptom class,
which were then compared using the χ2 test for categorical variables.
AFEQT overall scores were calculated and compared across EHRA
symptom classes using the nonparametric Kruskal–Wallis test for
continuous variables. The Spearman rank correlation coefficient was
calculated between overall AFEQT score and EHRA class. AFEQT
overall scores were calculated for each AF symptom (present/absent)
and compared using the nonparametric Wilcoxon rank-sum test for
continuous variables.
Using multiply imputed data, Cox frailty regression modeling
(which takes into account clustering of patient outcomes within a
site by adding a random effect for site) was used to examine the association between EHRA classes or AFEQT scores at baseline and
clinical outcomes during follow-up. Previously developed models
for each outcome were used for adjustment.14 Briefly, a multiply
imputed data set was used for model construction. Using the first
imputed data set, all continuous variables were evaluated for nonlinearity with the outcome while adjusting for 55 candidate variables.
Those which did not meet the linear relationship criteria (P value
<0.05) were accounted for using linear splines. Backward selection
with stay criteria of P value <0.05 was then performed on the first
imputed data set to construct the Cox frailty regression model for
each outcome using the variables from the list of 55 candidate variables. Rates of missingness were <2% for all candidate variables in
the model, with the following exceptions: level of education (4%),
eGFR (8%), left ventricular ejection fraction (11%), hematocrit
(11%), and left atrial diameter (14%). All available follow-up data
were used in the model construction process. Imputed values were
obtained by the Markov chain Monte Carlo method or regression
methods.15 The results from each model were then combined to produce statistically valid inferences when imputed data sets were used.
Adjusted associations for outcomes were displayed as hazard ratios,
95% confidence intervals, and P values. For the evaluation of the
association between AF symptoms and outcomes, the risk of each
outcome for those with an EHRA score of 1 was compared with the
risk of each outcome for those with an EHRA score of ≥2. For the
evaluation of the association between quality of life and outcomes,
the risk of each outcome for those in the highest quartile of AFEQT
was compared with those in each of the other quartiles. A hazard
ratio and P value were generated for each of these comparisons and a
global P value was generated for the highest quartile compared with
all of the other quartiles.
Kaplan–Meier estimates were used to calculate the mortality
curves by EHRA score and AFEQT quartiles. We estimated the cumulative incidence rate by EHRA score and AFEQT quartiles for the
all-cause hospitalization curves. This method accounts for the competing risk of mortality, which makes it impossible for a patient to
experience a subsequent hospitalization.
All statistical analyses for this study were performed using SAS
software (version 9.3, Cary, NC). All P values were 2-sided.
Results
Baseline Characteristics Stratified by Symptom
Status
Among 10 087 adults who had AF between June 2010 and
August 2011, 6235 (61.8%) were symptomatic at baseline as
defined by the physicians-assessed EHRA classification system and 3852 (38.2%) were asymptomatic (Table 1).
Patients with AF symptoms were less likely to be male
(53.6% versus 64.3%, P<0.0001). They were also more likely
to have heart failure, chronic obstructive pulmonary disease,
frailty,16 and obstructive sleep apnea. They were more likely to
have a lower (but normal range) left ventricular ejection fraction. Patients with symptoms were more likely to have paroxysmal AF (53.8% versus 45.3%, P<0.001). Symptomatic
patients were treated less with angiotensin-converting enzyme
inhibitors, calcium channel blockers, statins, and warfarin, but
more with antiarrhythmic medications. Other clinical differences were small in absolute terms (<2.5%) yet were statistically significant because of the large sample size in the study.
Patient-Reported Symptoms and EHRA Symptom
Severity Class
The most common patient-reported symptoms were palpitations (32.7%), dyspnea with exertion (27.6%), fatigue
(26.4%), and lightheadedness or dizziness (20.6%; Table 2).
Less common symptoms included dyspnea at rest (10.3%),
exercise intolerance (10%), chest tightness or discomfort
(9.4%), and syncope (4.5%).
Using the EHRA classification system, 61.8% of patients
had at least mild symptoms and 16.5% had severe or disabling symptoms. Among those identified by physicians
as asymptomatic using the EHRA score, the vast majority
reported no individual symptoms, but 11% reported at least
one symptom, with palpitations being most common (6%).
Among those assessed by physicians as having mild to disabling symptoms (EHRA 2–4), the most common patientreported symptoms were palpitations (49.1%), dyspnea with
exertion (43.1%), fatigue (41.1%), and lightheadedness
or dizziness (32.0%). The prevalence of these symptoms
increased ≤2-fold as EHRA symptom severity increased
from mild (EHRA 2) to disabling (EHRA 4). Less common
symptoms among those with EHRA mild to disabling symptoms included dyspnea at rest (16.3%), exercise intolerance
(15.6%), chest tightness or discomfort (14.9%), and syncope (6.9%). The prevalence of these symptoms increased
4- to 5-fold as EHRA symptom severity increased from mild
(EHRA 2) to disabling (EHRA 4).
Baseline Characteristics in the Quality of Life
Substudy
In the quality of life substudy, 2007 adults completed the
patient-reported outcome AFEQT questionnaire and 2006
patients had adequate data for subsequent analysis. There were
no substantial differences between the patients in the overall
cohort and the patients in the quality of life substudy population (data not shown). Patients in the highest quartile of quality of life had AFEQT scores of 93.5 to 100, whereas those in
the lowest quartile of quality of life had AFEQT scores of 0 to
65.7 (Table II in the Data Supplement).
Patients in the lowest quartile of quality of life compared
with those in the highest quartile were younger (73 versus 78
years, P<0.001) and more likely to be female (50.5% versus
36.1%, P<0.0001). Those with worse quality of life were
more likely to have a history of peripheral vascular disease,
congestive heart failure, chronic obstructive pulmonary disease, and obstructive sleep apnea. They were also more likely
396 Circ Cardiovasc Qual Outcomes July 2015
Table 1. Baseline Characteristics of 10 087 Adults With Atrial Fibrillation in the ORBIT-AF Registry Enrolled
Between June 2010 and August 2011 Overall and Stratified by the Presence of Symptoms
Characteristic
Overall (N=10087)
Asymptomatic (EHRA 1)
(N=3852)
Symptomatic (EHRA ≥2)
(N=6235)
P Value
74 (66–81)
<0.001
Demographics
Age, median, year (IQR)
Sex male, %
75 (67–82)
76 (68–82)
5814 (57.6)
2475 (64.3)
3339 (53.6)
<0.001
8997 (89.2)
3435 (89.2)
5562 (89.2)
<0.001
Race, %
White
Black
506 (5)
165 (4.3)
341 (5.5)
Hispanic
425 (4.2)
196 (5.1)
229 (3.7)
Other
143 (1.4)
51 (1.3)
92 (1.5)
Peripheral vascular disease
1344 (13.3)
521 (13.5)
823 (13.2)
Sinus node dysfunction
1769 (17.5)
634 (16.5)
1135 (18.2)
0.025
Stroke/transient ischemic attack
1520 (15.1)
561 (14.6)
959 (15.4)
0.27
Congestive heart failure
3275 (32.5)
1118 (29)
2157 (34.6)
<0.001
Coronary artery disease
3619 (35.9)
1396 (36.2)
2223 (35.7)
0.55
Prior myocardial infarction
1591 (15.8)
644 (16.7)
947 (15.2)
0.04
Prior coronary artery bypass surgery
1476 (14.6)
610 (15.9)
866 (13.9)
0.007
Prior percutaneous coronary
intervention
1723 (17.1)
608 (15.8)
1115 (17.9)
0.007
Diabetes mellitus
2963 (29.4)
1134 (29.4)
1829 (29.3)
0.91
Hyperlipidemia
7249 (71.9)
2857 (74.2)
4392 (70.4)
<0.001
Hypertension
8373 (83)
3217 (83.5)
5156 (82.7)
0.29
0.042
Cardiovascular history, %
0.64
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Cardiovascular risk factors, %
Other medical history, %
Alcohol abuse
407 (4.0)
175 (4.5)
232 (3.7)
Cancer
2389 (23.7)
963 (25)
1426 (22.9)
0.015
Chronic obstructive pulmonary disease
1649 (16.4)
569 (14.8)
1080 (17.3)
<0.001
<0.001
Frailty
583 (5.8)
152 (4)
431 (6.9)
Gastrointestinal bleed
908 (9)
350 (9.1)
558 (9)
0.82
Obstructive sleep apnea
1832 (18.2)
609 (15.8)
1223 (19.6)
<0.001
Thyroid disease
2264 (22.4)
804 (20.9)
1460 (23.4)
0.003
1865 (18.5)
665 (17.3)
1200 (19.2)
0.013
490 (4.9)
184 (4.8)
306 (4.9)
0.77
91 (0.9)
27 (0.7)
64 (1)
0.093
380 (3.8)
135 (3.5)
245 (3.9)
0.28
<0.001
Implanted devices, %
Pacemaker
Implantable cardioverter defibrillator
Biventricular pacemaker
Biventricular implantable cardioverter
defibrillator
Type of AF, %
New onset
477 (4.7)
137 (3.6)
340 (5.5)
Paroxysmal
5096 (50.5)
1743 (45.3)
3353 (53.8)
Persistent
1695 (16.8)
653 (17)
1042 (16.7)
Long-standing persistent
2819 (28)
1319 (34.2)
1500 (24.1)
Vital statistics and vital signs (IQR)
Body mass index, median, kg/m2
29.1 (25.4–34)
29 (25.6–33.5)
29.2 (25.2–34.4)
0.42
Heart rate, median, bpm
70 (63–80)
70 (62–79)
70 (63–80)
0.004
Blood pressure–systolic,
median, mm Hg
126 (116–138)
126 (118–138)
124 (115–138)
0.001
(Continued)
Freeman et al Atrial Fibrillation Symptoms and Outcomes 397
Table 1. Continued
Characteristic
Overall (N=10087)
Asymptomatic (EHRA 1)
(N=3852)
Symptomatic (EHRA ≥2)
(N=6235)
P Value
Echocardiography and
laboratory data (IQR)
Left ventricular ejection fraction,
median, %
55 (50–61)
Estimated glomerular filtration rate,
median, mg/dL
67 (52.7–82.3)
67.6 (53.6–82.6)
66.6 (52.3–82.1)
0.20
13.5 (12.3–14.6)
13.6 (12.4–14.7)
13.4 (12.2–14.6)
<0.001
Hemoglobin, median, g/dL
57 (50–62)
55 (50–60)
<0.001
Cardiac medications, %
Aldosterone antagonist
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555 (5.5)
200 (5.2)
355 (5.7)
0.28
Angiotensin-converting enzyme
inhibitor
3567 (35.4)
1485 (38.6)
2082 (33.4)
<0.001
Angiotensin receptor blocker
1800 (17.8)
661 (17.2)
1139 (18.2)
0.16
Antiarrhythmic therapy
2894 (28.7)
862 (22.4)
2032 (32.6)
<0.001
Antiplatelet therapy
4757 (47.2)
1771 (46)
2986 (47.9)
0.061
Beta-blockers
6448 (63.9)
2437 (63.3)
4011 (64.3)
0.27
Calcium channel blockers
3038 (30.1)
1234 (32)
1804 (28.9)
0.001
Digoxin
2365 (23.5)
885 (23)
1480 (23.7)
0.38
Diuretic
4938 (49)
1862 (48.3)
3076 (49.3)
0.32
Statin
5553 (55.1)
2223 (57.7)
3330 (53.4)
<0.001
Warfarin
7192 (71.3)
2830 (73.5)
4362 (70)
<0.001
AF indicates atrial fibrillation; EHRA, European Heart Rhythm Association; IQR, interquartile range; and ORBIT-AF, Outcomes Registry for
Better Informed Treatment of AF.
to have new onset AF and less likely to have paroxysmal or
long-standing persistent AF. They had higher body weights
and were more likely to be taking aldosterone antagonists and
diuretics. Other clinical differences were small in absolute
terms (<2.5%), yet were statistically significant because of the
large sample size in the study.
Atrial Fibrillation Effect on Quality-of-Life
Questionnaire Score
As with the overall cohort, the most common symptoms in the
subgroup of patients who completed the AFEQT survey were
palpitations (33.0%), dyspnea with exertion (32.6%), fatigue
(32.0%), and lightheadedness or dizziness (27.3%; Table III in
the Data Supplement). The prevalence of every symptom was
highest among those in the lowest quartile of quality of life
and decreased with increasing quality of life.
All of the symptoms assessed were associated with a statistically significant decrease in quality of life (P<0.001) with
a decrement of AFEQT score ranging from 9 to 17 (Figure 1).
Dyspnea at rest, exercise intolerance, and chest discomfort or
tightness were associated with the largest decreases in quality
of life as measured by the AFEQT.
Correlation of EHRA Classification and Quality of
Life
Patients assessed by physicians to be asymptomatic
(EHRA=1) had the highest quality of life as measured by
the AFEQT, and the AFEQT score decreased with increasing
Table 2. Atrial Fibrillation–Associated Symptoms in 10 087 Adults With Atrial Fibrillation in the ORBIT-AF Registry Enrolled
Between June 2010 and August 2011 Overall and Stratified by European Heart Rhythm Association (EHRA) Symptom Severity
Classification
Atrial Fibrillation Symptom
Overall (N=10 087)
Asymptomatic
(EHRA=1) (N=3852)
232 (6)
Mild (EHRA=2)
(N=4575)
Severe (EHRA=3)
(N=1474)
Disabling (EHRA=4)
(N=186)
P Value
Palpitations
3296 (32.7)
2135 (46.7)
817 (55.4)
112 (60.2)
<0.001
Dyspnea with exertion
2779 (27.6)
95 (2.5)
1756 (38.4)
817 (55.4)
111 (59.7)
<0.001
Fatigue
2664 (26.4)
102 (2.7)
1604 (35.1)
840 (57.0)
118 (63.4)
<0.001
Lightheadedness/dizziness
2081 (20.6)
86 (2.2)
1254 (27.4)
650 (44.1)
91 (48.9)
<0.001
Dyspnea at rest
1040 (10.3)
26 (0.7)
499 (10.9)
414 (28.1)
101 (54.3)
<0.001
Exercise intolerance
1005 (10)
33 (0.9)
485 (10.6)
411 (27.9)
76 (40.9)
<0.001
Chest tightness/discomfort
948 (9.4)
19 (0.5)
509 (11.1)
337 (22.9)
83 (44.6)
<0.001
Syncope/fainting
455 (4.5)
23 (0.6)
215 (4.7)
167 (11.4)
50 (26.9)
<0.001
EHRA indicates European Heart Rhythm Association; and ORBIT-AF, Outcomes Registry for Better Informed Treatment of AF.
398 Circ Cardiovasc Qual Outcomes July 2015
EHRA symptom severity class with a Spearman’s correlation
coefficient of −0.39 (Figure 2). Those assessed by physicians
as asymptomatic (EHRA=1) had a median AFEQT score of
90 (interquartile range [IQR] 79–97), those with mild symptoms (EHRA=2) had a median score of 81 (IQR 67–91), those
with severe symptoms (EHRA=3) had a median score of 63
(IQR 48–82), and those with disabling symptoms (EHRA=4)
had a median score of 61 (IQR 41–78).
AF-Related Symptoms and Quality of Life and
Associations With Outcomes
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Over a median of 1.8 years (IQR 1.4–2.1 years) of follow-up
in 9600 adults with follow-up data, patients with AF-related
symptoms at baseline (EHRA≥2) had a higher risk of hospitalization (adjusted hazard ratio 1.23, 95% confidence interval 1.15–1.31, P=<0.001, Table 3, Figure 3)) and a borderline
higher risk of major bleeding (adjusted hazard ratio 1.21,
95% confidence interval 1.02–1.45, P=0.03). In contrast, AFrelated symptoms at baseline were not associated with significant differences in the risk of death (Figure 4), stroke, or
myocardial infarction.
Among 1925 adults with follow-up data, patients in the
lowest quartile of quality of life at baseline (AFEQT ≤65.7)
had a higher risk of hospitalization compared with those in the
highest quartile (AFEQT >93.1; adjusted hazard ratio 1.49,
95% confidence interval 1.2–1.84, P≤0.001, Table 4, Figure I
in the Data Supplement). This finding was consistent for the
comparison of the second and third quartiles compared with
highest quartile of quality of life, and the global P value for all
of the other quartiles compared with the highest quartile was
0.001 (Table 4). In addition, this finding was consistent when
AFEQT was modeled as a continuous variable (Table IV in
the Data Supplement). In contrast, quality of life at baseline
was not associated with significant differences in the risk of
death (Figure II in the Data Supplement) or major bleeding.
The number of events for stroke/transient ischemic attack and
myocardial infarction did not differ substantially between
quartiles of quality of life, but they were not adequate to perform our regression models for risk assessment.
Discussion
In a large, diverse, community-based cohort of adults with
AF, we found that most patients (61.8%) were symptomatic
as measured by the EHRA classification system. The most
common symptoms were palpitations, dyspnea with exertion,
fatigue, and lightheadedness or dizziness. Symptom severity
measured by physicians using the EHRA classification was
correlated with decreasing patient-reported quality of life as
measured by the AFEQT questionnaire. AF symptoms were
associated with a higher risk of hospitalization and a borderline higher risk of major bleeding, and decreased quality of
life was associated with a higher risk of hospitalization, but
there were no differences in the risk of death or other major
adverse events.
This study is novel in its use of the EHRA AF symptom
classification system in a large, community-based cohort and its
demonstration of a correlation between physician-assessed AF
symptom status and patient-reported quality of life. Although
most patients in our cohort were assessed by physicians as
symptomatic (EHRA 2–4), 38.2% were reported to be asymptomatic (EHRA 1). Interestingly, 11% of those assessed as
asymptomatic by physicians (EHRA 1) reported experiencing
Figure 1. Boxplot of overall Atrial Fibrillation Effect on Quality-of-Life questionnaire (AFEQT) score stratified by European Heart Rhythm
Association (EHRA) symptom class (correlation coefficient =−0.40, P<0.0001). AF indicates atrial fibrillation.
Freeman et al Atrial Fibrillation Symptoms and Outcomes 399
Downloaded from http://circoutcomes.ahajournals.org/ by guest on May 5, 2017
Figure 2. Atrial Fibrillation Effect on Quality-of-Life questionnaire (AFEQT) score stratified by the presence or absence of each atrial
fibrillation–related symptom. EHRA indicates European Heart Rhythm Association.
individual symptoms, with palpitations being the most common,
suggesting that physicians may underestimate patient symptoms when they are mild. Regardless, this frequency of asymptomatic patients is substantially higher than has previously
been reported, likely because of selection biases in prior studies.5–8 Prior studies reporting higher symptom burden included
selected patients from referral-based practices, and therefore our
community-based population likely more accurately represents
the prevalence of symptoms in outpatients with AF.
The AFEQT questionnaire11 has been validated as a disease-specific tool for assessing patient quality of life in AF,
but it has not previously been used in a large community-based
cohort. All of the symptoms assessed in our study were associated with statistically significant decreases in quality of life,
but dyspnea at rest, exercise intolerance, and chest discomfort
or tightness were associated with the largest decreases. This is
consistent with our finding that these symptoms, although relatively rare overall, were common among those who reported
severe or disabling symptoms (EHRA 3–4) in our cohort and
deserve special attention by treating clinicians.
We demonstrated an inverse correlation between the
EHRA AF symptom severity classification system and quality
of life as measured by the AFEQT in our population. This consistency across test instruments supports their clinical use for
assessment of AF symptom burden and quality of life. We also
demonstrated that those with mild symptoms (EHRA 2) had an
AFEQT score of <90 and those with severe or disabling symptoms (EHRA 3–4) had an AFEQT score of <64. These AFEQT
thresholds may serve as clinically significant quality of life categories for future clinical trials or observational studies.
Table 3. Association Between Symptoms and Outcomes in 9600 Adults With Atrial Fibrillation in the ORBIT-AF Registry*
Outcome
Death
Asymptomatic (EHRA=1)
events (events per 100
patient-years) (N=3682)
Symptomatic (EHRA≥2)
events (events per 100
patient-years) (N=5918)
Unadjusted HR (95% CI)
Adjusted HR (95% CI)
Adjusted P Value
311 (5.0)
561 (5.7)
1.16 (1.00–1.34)
1.00 (0.86–1.16)
0.98
First stroke/TIA
99 (1.6)
168 (1.7)
1.12 (0.86–1.45)
1.13 (0.87–1.46)
0.37
First myocardial infarction
47 (0.8)
79 (0.8)
1.09 (0.75–1.58)
1.05 (0.72–1.53)
0.80
First hospitalization
1495 (30.8)
2812 (40.1)
1.32 (1.24–1.42)
1.23 (1.15–1.31)
<0.001
First major bleeding
219 (3.6)
397 (4.2)
1.29 (1.08–1.53)
1.21 (1.02–1.45)
0.031
AF indicates atrial fibrillation; BMI, body mass index; CAD, coronary artery disease; CHF, congestive heart failure; CI, confidence interval; COPD, chronic obstructive
pulmonary disease; eGFR, estimated glomerular filtration rate; EHRA, European Heart Rhythm Association; HR, hazard ratio; LAD, left anterior descending artery; LVEF,
left ventricular ejection fraction; MI, myocardial infarction; ORBIT-AF, Outcomes Registry for Better Informed Treatment of AF; OSA, obstructive sleep apnea; PCI,
percutaneous intervention; and TIA, transient ischemic attack.
*Variables included in the adjusted models (baseline covariates): Death adjusted for level of education, rhythm control, cognitive impairment/dementia, hyperlipidemia,
linear spline eGFR ≤80, linear spline eGFR >80, LAD bypass graft type, cancer, diastolic blood pressure, intraventricular conduction delay, frailty, height, heart rate,
hematocrit, diabetes mellitus, smoking, linear spline systolic blood pressure ≤120, COPD, BMI, sex, CHF, age, functional status. Stroke adjusted for peripheral vascular
disease, race, rhythm control, AF type, AV node/His bundle ablation, female, hypertension, age, history of stroke/TIA. MI adjusted for diabetes mellitus, eGFR, peripheral
vascular disease, history of CAD, LVEF. Hospitalization for linear spline age ≤70, linear spline age >70, BMI, weight, osteoporosis, height, PCI, cancer, OSA, anemia,
frailty, insurance status, history of CAD, site specialty, prior antiarrhythmic drug use, peripheral vascular disease, functional status, linear spline heart rate >68, diabetes
mellitus, hematocrit, linear spline eGFR ≤80, COPD, diastolic blood pressure truncated above at 70, EHRA score, CHF. Major bleeding adjusted for COPD, OSA, LAD type,
cancer, functional status, level of education, intraventricular conduction delay, rhythm control, smoking status, significant valvular disease, eGFR, insurance status,
history of gastrointestinal bleed, anemia, hematocrit.
400 Circ Cardiovasc Qual Outcomes July 2015
Figure 3. Cumulative incidence curves for
hospitalization in asymptomatic patients
(EHRA=1) compared with symptomatic
patients (EHRA≥2) in 9600 adults with
atrial fibrillation in the Outcomes Registry
for Better Informed Treatment of AF
(ORBIT-AF) Registry. EHRA indicates
European Heart Rhythm Association.
Downloaded from http://circoutcomes.ahajournals.org/ by guest on May 5, 2017
Finally, our study demonstrated an association between physician-assessed AF symptom burden (EHRA) and patient-reported
decrease in quality of life and a higher risk of hospitalization.
We did not show any differences in the risk of death or other
major adverse events, except for a borderline association between
AF symptoms assessed by EHRA class and hospitalization. This
finding is noteworthy because the patients with the highest burden of symptoms and the lowest quality of life were substantially
younger and healthier than less symptomatic patients and those
with higher self-reported quality of life. These patients did not
have an increased risk of death, stroke, myocardial infarction, or
major bleeding, suggesting that their hospitalizations were likely
related to their symptoms and lower quality of life and not major
adverse events. Interventions targeted at improvement in symptoms and quality of life in these patients, including more aggressive outpatient follow-up or rhythm control therapies may be
important for minimizing resource utilization in this population.
Our study has important limitations. Although our large,
community-based cohort is broadly representative of patients
with AF in the United States, we evaluated patients who are
undergoing treatment for AF, and the results may not be generalizable to a disadvantaged or untreated population. In addition, the population of patients who chose to participate in the
quality of life substudy may not be fully generalizable to a
general population with AF. Finally, despite controlling for
a large number of covariates, we cannot exclude residual or
unmeasured confounding in our analyses, evaluating the association between AF symptoms or quality of life and outcomes.
Conclusions
In summary, in a large nationally representative communitybased cohort of individuals with AF, most patients were
reported by physicians to be symptomatic (61.8%) and a substantial minority (16.6%) had severe or disabling symptoms
Figure 4. Kaplan–Meier curves for
mortality in asymptomatic patients
(EHRA=1) compared with symptomatic
patients (EHRA≥2) in 9600 adults with
atrial fibrillation in the Outcomes Registry
for Better Informed Treatment of AF
(ORBIT-AF) Registry. EHRA indicates
European Heart Rhythm Association.
Freeman et al Atrial Fibrillation Symptoms and Outcomes 401
Table 4. Association Between Quality of Life and Outcomes in 1925 Adults With Atrial Fibrillation in the ORBIT-AF Registry*
Outcome
Death
First Quartile QoL
(AFEQT ≤65.7)
(Events per 100
Patient-Years)
(N=468)
Second Quartile Third Quartile QoL Fourth Quartile
QoL (AFEQT 66.7– (AFEQT 81.9– QoL (AFEQT≥93.5)
81.5) (Events per 93.1) (Events per (Events per 100 Adjusted HR First Adjusted HR Adjusted HR Third
100 Patient100 PatientPatient-Years) vs Fourth Quartile Second vs Fourth vs Fourth Quartile Adjusted
Years) (N=488) Years) (N=480)
(N=489)
(95% CI)
Quartile (95% CI)
(95% CI)
Global P Value
45 (5.2)
42 (4.5)
36 (3.8)
43 (4.4)
1.21 (0.77–1.90) 1.04 (0.67–1.62) 0.98 (0.62–1.55)
0.81
247 (44.0)
249 (39.3)
233 (34.4)
199 (26.0)
1.49 (1.20–1.84) 1.42 (1.17–1.74) 1.33 (1.09–1.62)
0.001
First stroke/TIA†
10 (1.2)
14 (1.5)
8 (0.9)
13 (1.3)
-
-
-
First myocardial
infarction†
8 (0.9)
11 (1.2)
5 (0.53)
3 (0.3)
-
-
-
30 (3.6)
36 (4.0)
First hospitalization
First major bleeding
28 (3.0)
23 (2.4)
1.47 (0.83–2.58) 1.72 (1.0–2.94)
1.39 (0.79–2.44)
0.27
Downloaded from http://circoutcomes.ahajournals.org/ by guest on May 5, 2017
AF indicates atrial fibrillation; BMI, body mass index; CAD, coronary artery disease; CHF, congestive heart failure; CI, confidence interval; COPD, chronic obstructive
pulmonary disease; eGFR, estimated glomerular filtration rate; EHRA, European Heart Rhythm Association; HR, hazard ratio; LAD, left anterior descending artery; LVEF,
left ventricular ejection fraction; MI, myocardial infarction; ORBIT-AF, Outcomes Registry for Better Informed Treatment of AF; OSA, obstructive sleep apnea; PCI,
percutaneous intervention; and TIA, transient ischemic attack.
*Variables included in the adjusted models (baseline covariates): Death adjusted for level of education, rhythm control, cognitive impairment/dementia, hyperlipidemia,
linear spline eGFR ≤80, linear spline eGFR >80, LAD bypass graft type, cancer, diastolic blood pressure, intraventricular conduction delay, frailty, height, heart rate,
hematocrit, diabetes mellitus, smoking, linear spline systolic blood pressure ≤120, COPD, BMI, sex, CHF, age, functional status. Stroke adjusted for peripheral vascular
disease, race, rhythm control, AF type, AV node/His bundle ablation, female, hypertension, age, history of stroke/TIA. MI adjusted for diabetes mellitus, eGFR, peripheral
vascular disease, history of CAD, LVEF. Hospitalization for linear spline age ≤70, linear spline age >70, BMI, weight, osteoporosis, height, PCI, cancer, OSA, anemia,
frailty, insurance status, history of CAD, site specialty, prior antiarrhythmic drug use, peripheral vascular disease, functional status, linear spline heart rate >68, diabetes
mellitus, hematocrit, linear spline eGFR ≤80, COPD, diastolic blood pressure truncated above at 70, EHRA score, CHF. Major bleeding adjusted for COPD, OSA, LAD type,
cancer, functional status, level of education, intraventricular conduction delay, rhythm control, smoking status, significant valvular disease, eGFR, insurance status,
history of gastrointestinal bleed, anemia, hematocrit.
†There were not enough events for the unadjusted and adjusted models for stroke/TIA and MI.
(EHRA 3–4). The most common patient-reported symptoms
reported in our cohort were palpitations, dyspnea with exertion, fatigue, and lightheadedness or dizziness. We demonstrated that physician-assessed AF symptom burden using the
European Heart Rhythm Association (EHRA) classification
system correlated with decreased patient-reported quality of
life as measured by the AFEQT questionnaire, supporting
the clinical use of both instruments. Finally, our study demonstrated an association between AF-related symptoms or
decreased quality of life and a higher risk of hospitalization,
although not mortality, thus identifying an important population of patients who may require aggressive interventions to
minimize symptoms and lower resource utilization.
Sources of Funding
This work was supported by a grant from Janssen Scientific Affairs,
LLC. The funder was not involved in the design and conduct of the
study; collection, management, analysis, and interpretation of the
data; or preparation, review, or approval of the article.
Disclosures
J.V Freeman is consultant of Janssen Scientific (modest). D.N. Simon
receives personal fees from Janssen Scientific Affairs. J. Spertus
received grants and contracts from National Institute of Health,
American College of Cardiology Foundation, Abbott Vascular,
Genentech, Amorcyte; Was consultant for Janssen, United Healthcare,
Novartis, and Amgen; and received equity interest in Health Outcomes
Sciences, and this company owns the copyright to the Seattle Angina
Questionnaire, the Kansas City Cardiomyopathy Questionnaire, the
Peripheral Artery Questionnaire, and the Atrial Fibrillation Effect on
QualiTy-of-life (AFEQT) questionnaire (licensed by St. Jude Medical).
G.C. Fonarow is consultant for Janssen Scientific Affairs (modest). B.J. Gersh received personal fees from Medtronic, Inc, Baxter
Healthcare Corporation, Cardiovascular Research Foundation, Merck
& Co, Inc, St Jude Medical, Inc, Ortho-McNeil Janssen Scientific
Affairs, TEVA Pharmaceuticals, Boston Scientific, outside the submitted work. E.M. Hylek is advisory capacity for Bayer, Boehringer
Ingelheim, Bristol Myers Squibb, Daiichi Sankyo, Janssen, Pfizer, and
Roche. P.R. Kowey received grants and personal fees from Johnson
& Johnson not related to the submitted work. K.W. Mahaffey received grants and personal fees from Johnson & Johnson, grants from
Regeneron, grants and personal fees from Cubist Pharmaceuticals,
grants and personal fees from Sanofi, grants from Baxter, grants from
Roche Diagnostics, grants from Ikaria, grants from Amgen, grants
from Regado, grants and personal fees from Merck, grants and personal fees from Glaxo Smith Kline, grants from Amylin, grants from
Novartis, grants and personal fees from AstraZeneca, grants from
Portola, grants and personal fees from Eli Lilly, grants from Edwards
Lifesciences, grants and personal fees from Boehringer Ingelhein,
grants from National Institute of Health, grants from National Heart,
Lung & Blood Institute, grants from National Institute of Allergy &
Infectious Diseases, personal fees from Bayer, personal fees from
Biotronik, personal fees from Daiichi Sankyo, personal fees from
Gilead Sciences, personal fees from Medtronic, personal fees from
Ortho/McNeill, personal fees from Pfizer, personal fees from St Jude,
personal fees from ACC, personal fees from John Hopkins University,
personal fees from South East Area Health Education Center, personal
fees from Sun Pharma, grants and personal fees from Bristol MyersSquibb, personal fees from Duke Center for Educational Excellence,
personal fees from University of British Columbia, personal fees
from WebMD, personal fees from Perdue Pharma, personal fees from
Dialouges, personal fees from Springer Publishing, personal fees from
Haemonetics, personal fees from Forest, personal fees from Amgen,
personal fees from Elsevier during the conduct of the study; and Other
Relationships: http://www.dcri.duke.edu/research/coi.jsp and www.
med.stanford.edu/profiles/Kenneth_Mahaffey. P. Chang received substantial personal fees from Janssen Pharmaceuticals, Inc. during the
conduct of the study; other from Janssen Pharmaceuticals, Inc., outside the submitted work. E.D. Peterson received grants from Eli Lilly,
grants and personal fees from Janssen Scientific Affairs, personal fees
from Boehringer Ingelheim. J.P. Piccini received grants for clinical
research from ARCA biopharma, Boston Scientific, GE Healthcare,
Janssen Pharmaceuticals, and ResMed. J.P. Piccini is a consultant to
Johnson & Johnson and Spectranetics.
402 Circ Cardiovasc Qual Outcomes July 2015
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Association Between Atrial Fibrillation Symptoms, Quality of Life, and Patient Outcomes:
Results From the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation
(ORBIT-AF)
James V. Freeman, DaJuanicia N. Simon, Alan S. Go, John Spertus, Gregg C. Fonarow, Bernard
J. Gersh, Elaine M. Hylek, Peter R. Kowey, Kenneth W. Mahaffey, Laine E. Thomas, Paul
Chang, Eric D. Peterson and Jonathan P. Piccini
on behalf of the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation
(ORBIT-AF) Investigators and Patients
Circ Cardiovasc Qual Outcomes. 2015;8:393-402; originally published online June 9, 2015;
doi: 10.1161/CIRCOUTCOMES.114.001303
Circulation: Cardiovascular Quality and Outcomes is published by the American Heart Association, 7272
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Copyright © 2015 American Heart Association, Inc. All rights reserved.
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SUPPLEMENTAL MATERIAL
Supplemental Table 1. Baseline characteristics of 10,087 adults with atrial fibrillation in the overall ORBIT-AF
Registry compared with the 2006 enrolled in the Atrial Fibrillation Effect on QualiTy-of-life questionnaire (AFEQT) substudy.
Characteristic
Overall
(N=10087)
AFEQT subsample
(N=2006)
Demographics
Age, median, year (IQR)
Gender male (%)
75 (67-82)
76 (67-82)
5814 (57.6)
1141 (56.9)
8997 (89.2)
1804 (89.9)
Race (%)
White
Black
506 (5)
116 (5.8)
Hispanic
425 (4.2)
53 (2.6)
Other
143 (1.4)
28 (1.4)
Peripheral Vascular Disease
1344 (13.3)
247 (12.3)
Sinus Node Dysfunction
1769 (17.5)
378 (18.8)
Stroke/ Transient Ischemic
Attack
1520 (15.1)
316 (15.8)
Congestive Heart Failure
3275 (32.5)
547 (27.3)
Coronary Artery Disease
3619 (35.9)
630 (31.4)
Prior Myocardial Infarction
1591 (15.8)
296 (14.8)
Cardiovascular History (%)
Characteristic
Overall
(N=10087)
AFEQT subsample
(N=2006)
Prior Coronary Artery Bypass
Surgery
1476 (14.6)
299 (14.9)
Prior Percutaneous Coronary
Intervention
1723 (17.1)
332 (16.6)
Diabetes
2963 (29.4)
554 (27.6)
Hyperlipidemia
7249 (71.9)
1417 (70.6)
Hypertension
8373 (83)
1656 (82.6)
Cardiovascular Risk
Factors (%)
Other Medical History (%)
Alcohol Abuse
407 (4.0)
81 (4)
Cancer
2389 (23.7)
497 (24.8)
Chronic Obstructive
Pulmonary Disease
1649 (16.4)
341 (17)
Frailty
583 (5.8)
126 (6.3)
Gastrointestinal Bleed
908 (9)
156 (7.8)
Obstructive Sleep Apnea
1832 (18.2)
405 (20.2)
Thyroid Disease
2264 (22.4)
453 (22.6)
1865 (18.5)
416 (20.7)
490 (4.9)
98 (4.9)
Implanted Devices (%)
Pacemaker
Implantable Cardioverter
Characteristic
Overall
(N=10087)
AFEQT subsample
(N=2006)
Biventricular Pacemaker
91 (0.9)
15 (0.8)
Biventricular Implantable
Cardioverter Defibrillator
380 (3.8)
63 (3.1)
New Onset
477 (4.7)
197 (9.8)
Paroxysmal
5096 (50.5)
954 (47.6)
Persistent
1695 (16.8)
300 (15)
Long-Standing Persistent
2819 (28)
555 (27.7)
29.1 (25.4-34)
28.8 (25.4-33.7)
Defibrillator
Type of AF (%)
Vital Statistics and Vital
Signs (IQR)
Body Mass Index, Median,
kg/m^2
Heart Rate, Median, bpm
Blood Pressure- Systolic,
Median, mm Hg
70 (63-80)
126 (116138)
70 (63-79)
126 (118-138)
Echocardiography and
Laboratory Data (IQR)
Left Ventricular Ejection
Fraction, Median, %
55 (50-61)
Estimated Glomerular
Filtration Rate, Median, mg/dl
67 (52.782.3)
66.7 (52.8-82.9)
13.5 (12.3-
13.4 (12.3-14.5)
Hemoglobin, Median, g/dl
56 (50-61)
Characteristic
Overall
(N=10087)
14.6)
AFEQT subsample
(N=2006)
Cardiac Medications (%)
Aldosterone Antagonist
555 (5.5)
100 (5)
Angiotensin Converting
Enzyme Inhibitor
3567 (35.4)
658 (32.8)
Angiotensin Receptor Blocker
1800 (17.8)
411 (20.5)
Antiarrhythmic Therapy
2894 (28.7)
541 (27)
Antiplatelet therapy
4757 (47.2)
909 (45.3)
Beta Blockers
6448 (63.9)
Calcium Channel Blockers
3038 (30.1)
573 (28.6)
Digoxin
2365 (23.5)
467 (23.3)
Diuretic
4938 (49)
902 (44.8)
Statin
5553 (55.1)
1034 (51.6)
Warfarin
7192 (71.3)
1576 (78.6)
1303 (65)
Supplemental Table 2. Baseline characteristics of 2006 adults with atrial fibrillation between June 2010 and August 2011
overall and stratified by quartiles of Atrial Fibrillation Effect on QualiTy-of-life questionnaire (AFEQT).
Characteristic
Overall
(N=2006)
Quartile 1
(AFEQT 0-65.7)
(N=497)
Quartile 2
(AFEQT 66.7-81.5)
(N=507)
Quartile 3
(AFEQT 81.9-93.1)
(N=500)
Quartile 4
(93.5-100)
(N=502)
P-value
Demographics
Age, median, year (IQR)
Gender male (%)
76 (67-82)
73 (66-81)
74 (67-81)
75 (67-82)
78 (70-83)
<0.001
1141 (56.9)
246 (49.5)
285 (56.2)
289 (57.8)
321 (63.9)
<0.001
White
1804 (89.9)
449 (90.3)
453 (89.4)
452 (90.4)
450 (89.6)
0.037
Black
116 (5.8)
29 (5.8)
25 (4.9)
28 (5.6)
Hispanic
53 (2.6)
7 (1.4)
21 (4.1)
9 (1.8)
16 (3.2)
Other
28 (1.4)
8 (1.6)
9 (1.8)
1 (0.2)
56 (11.2)
47 (9.4)
0.032
85 (17)
94 (18.7)
0.36
0.94
Race (%)
10 (2)
34 (7)
Cardiovascular History
(%)
Peripheral Vascular
Disease
247 (12.3)
68 (13.7)
76 (15)
Sinus Node Dysfunction
378 (18.8)
91 (18.3)
108 (21.3)
Stroke/ Transient Ischemic
Attack
316 (15.8)
76 (15.3)
77 (15.2)
81 (16.2)
82 (16.3)
Congestive Heart Failure
547 (27.3)
168 (33.8)
151 (29.8)
118 (23.6)
110 (21.9)
Coronary Artery Disease
630 (31.4)
172 (34.6)
154 (30.4)
163 (32.6)
141 (28.1)
<0.001
0.14
Characteristic
Overall
(N=2006)
Quartile 1
(AFEQT 0-65.7)
(N=497)
76 (15.3)
Quartile 2
(AFEQT 66.7-81.5)
(N=507)
67 (13.2)
Quartile 3
(AFEQT 81.9-93.1)
(N=500)
81 (16.2)
Quartile 4
(93.5-100)
(N=502)
72 (14.3)
P-value
Prior Myocardial Infarction
296 (14.8)
Prior Coronary Artery
Bypass Surgery
299 (14.9)
75 (15.1)
82 (16.2)
77 (15.4)
65 (13)
0.52
Prior Percutaneous
Coronary Intervention
332 (16.6)
93 (18.7)
82 (16.2)
75 (15)
82 (16.3)
0.45
159 (32)
133 (26.2)
135 (27)
127 (25.3)
0.083
0.58
Cardiovascular Risk
Factors (%)
Diabetes
554 (27.6)
Hyperlipidemia
1417 (70.6)
334 (67.2)
376 (74.2)
352 (70.4)
355 (70.7)
0.12
Hypertension
1656 (82.6)
429 (86.3)
423 (83.4)
401 (80.2)
403 (80.3)
0.031
81 (4)
19 (3.8)
19 (3.8)
18 (3.6)
0.65
Other Medical History (%)
Alcohol Abuse
25 (5)
Cancer
497 (24.8)
103 (20.7)
120 (23.7)
131 (26.2)
143 (28.5)
0.03
Chronic Obstructive
Pulmonary Disease
341 (17)
112 (22.5)
95 (18.7)
70 (14)
64 (12.8)
<0.001
24 (1.2)
6 (1.2)
2 (0.4)
7 (1.4)
9 (1.8)
0.22
Gastrointestinal Bleed
156 (7.8)
40 (8.1)
43 (8.5)
28 (5.6)
45 (9.0)
0.20
Frailty
126 (6.3)
40 (8.1)
36 (7.1)
22 (4.4)
28 (5.6)
0.084
Obstructive Sleep Apnea
405 (20.2)
131 (26.4)
119 (23.5)
88 (17.6)
67 (13.4)
<0.001
Thyroid Disease
453 (22.6)
120 (24.1)
108 (21.3)
123 (24.6)
102 (20.3)
0.28
Drug Abuse
Implanted Devices (%)
Characteristic
Overall
(N=2006)
Quartile 1
(AFEQT 0-65.7)
(N=497)
Quartile 2
(AFEQT 66.7-81.5)
(N=507)
Quartile 3
(AFEQT 81.9-93.1)
(N=500)
Quartile 4
(93.5-100)
(N=502)
P-value
Pacemaker
416 (20.7)
109 (21.9)
114 (22.5)
Implantable Cardioverter
Defibrillator
98 (4.9)
27 (5.4)
27 (5.3)
Biventricular Pacemaker
15 (0.8)
4 (0.8)
5 (1)
3 (0.6)
Biventricular Implantable
Cardioverter Defibrillator
63 (3.1)
15 (3)
16 (3.2)
17 (3.4)
15 (3)
0.98
30 (6)
0.001
95 (19.0)
98 (19.5)
0.43
20 (4)
24 (4.8)
0.71
3 (0.6)
0.87
Type of AF (%)
New Onset
197 (9.8)
71 (14.3)
46 (9.1)
50 (10.1)
Paroxysmal
954 (47.6)
216 (43.5)
248 (48.9)
245 (49.0)
245 (48.8)
Persistent
300 (15)
88 (17.7)
74 (14.6)
58 (11.6)
80 (15.9)
Long-Standing Persistent
555 (27.7)
122 (24.6)
139 (27.4)
147 (29.4)
147 (29.3)
28.8 (25.433.7)
30.2 (26.336.3)
29 (25.134.3)
Vital Statistics and Vital
Signs (IQR)
Body Mass Index, Median,
kg/m^2
Heart Rate, Median
Blood Pressure- Systolic,
Median
70 (63-79)
126 (118138)
72 (64-80)
125 (114136)
70 (64-80)
126 (118138)
28.8 (25.3-33)
70 (63-76)
124 (116138)
28 (25-32.4)
70 (61-76)
128 (118138)
<0.001
0.017
0.079
Echocardiographic and
Laboratory Data (IQR)
Left Ventricular Ejection
Fraction, Median, %
56 (50-61)
55 (50-60)
55 (50-62)
58 (50-62)
60 (50-64)
0.012
Characteristic
Overall
(N=2006)
Quartile 1
(AFEQT 0-65.7)
(N=497)
Quartile 2
(AFEQT 66.7-81.5)
(N=507)
Quartile 3
(AFEQT 81.9-93.1)
(N=500)
Quartile 4
(93.5-100)
(N=502)
P-value
Estimated Glomerular
Filtration Rate, Median,
mg/dl
66.7 (52.882.9)
66.5 (51.982.1)
67.5 (51.684.6)
66.6 (52.882.5)
66.7 (55.381.6)
0.93
Hemoglobin, Median, g/dl
13.4 (12.314.5)
13.3 (12.114.4)
13.4 (12.314.5)
13.6 (12.414.7)
13.5 (12.314.6)
0.11
37 (7.4)
27 (5.3)
23 (4.6)
13 (2.6)
0.005
Cardiac Medications (%)
Aldosterone Antagonist
100 (5)
Angiotensin Converting
Enzyme Inhibitor
658 (32.8)
148 (29.8)
160 (31.6)
176 (35.2)
174 (34.7)
0.22
Angiotensin Receptor
Blocker
411 (20.5)
88 (17.7)
118 (23.3)
100 (20.0)
105 (20.9)
0.18
Antiarrhythmic Therapy
541 (27)
151 (30.4)
135 (26.6)
135 (27)
120 (23.9)
0.15
Antiplatelet therapy
909 (45.3)
247 (49.7)
218 (43)
226 (45.2)
218 (43.4)
0.13
334 (67.2)
320 (63.1)
322 (64.4)
327 (65.1)
0.56
Beta Blockers
1303 (65)
Calcium Channel Blockers
573 (28.6)
147 (29.6)
150 (29.6)
129 (25.8)
147 (29.3)
0.47
Digoxin
467 (23.3)
139 (28)
119 (23.5)
101 (20.2)
108 (21.5)
0.021
Diuretic
902 (44.8)
254 (51.1)
241 (47.5)
212 (42.4)
195 (38.8)
<0.001
Statin
1034 (51.6)
237 (47.7)
258 (50.9)
274 (54.8)
265 (52.8)
0.15
Warfarin
1576 (78.6)
402 (80.9)
397 (78.3)
386 (77.2)
391 (77.9)
0.51
Supplemental Table 3. Atrial fibrillation associated quality of life in 2006 adults with atrial fibrillation in the ORBIT-AF
Registry enrolled between June 2010 and August 2011 overall and stratified by quartiles of the Atrial Fibrillation Effect on
QualiTy-of-life questionnaire (AFEQT).
Atrial Fibrillation Symptom
Overall
(N=2006)
Quartile 1
(N=497)
Quartile 2
(N=507)
Quartile 3
(N=500)
Quartile 4
(N=502)
P-value
Palpitations
661 ( 33.0)
244 (49.1)
185 (36.5)
139 (27.8)
93 (18.5)
<0.001
Dyspnea with Exertion
653 ( 32.6)
244 (49.1)
174 (34.3)
142 (28.4)
93 (18.5)
<0.001
Fatigue
641 (32.0)
249 (50.1)
164 (32.4)
124 (24.8)
104 (20.7)
<0.001
Lightheadedness/Dizziness
547 (27.3)
212 (42.7)
128 (25.3)
128 (25.6)
79 (15.7)
<0.001
Exercise Intolerance
268 (13.4)
126 (25.4)
63 (12.4)
49 (9.8)
30 (6.0)
<0.001
Dyspnea at Rest
193 (9.6)
97 (19.5)
48 (9.5)
22 (4.4)
26 (5.2)
<0.001
Chest Tightness/Discomfort
204 (10.2)
93 (18.7)
56 (11.1)
30 (6.0)
25 (5.0)
<0.001
Syncope/Fainting
102 (5.1)
40 (8.1)
26 (5.1)
18 (3.6)
18 (3.6)
0.003
EHRA= European Heart Rhythm Association
Supplemental Table 4. Association between quality of life and outcomes in 1925 adults with atrial fibrillation in the ORBITAF Registry with AFEQT modeled as a continuous variable.
Outcome
Unadjusted HR for every 5%
decrease in AFEQT (95% CI)
Adjusted HR (95% CI)
Adjusted P-value
Death
1.03 (0.99-1.07)
1.03 (0.98-1.07)
0.24
First hospitalization
1.05 (1.03-1.07)
1.03 (1.01-1.05)
0.001
First stroke/TIA**
0.98 (0.91-1.06)
-
-
First myocardial
infarction**
1.08 (1.00-1.18)
-
-
First major bleeding
1.03 (0.99-1.08)
1.02 (0.97-1.07)
0.39
*Variables included in the adjusted models (baseline covariates):
Death adjusted for: level of education, rhythm control, cognitive impairment/dementia, hyperlipidemia, linear spline eGFR ≤ 80, linear spline eGFR
> 80, LAD bypass graft type, cancer, diastolic blood pressure, intraventricular conduction delay, frailty, height, heart rate, hematocrit, diabetes,
smoking, linear spline systolic blood pressure ≤ 120, COPD, BMI, sex, CHF, age, functional status
Stroke adjusted for: peripheral vascular disease, race, rhythm control, AF type, AV node/His bundle ablation, female, hypertension, age, history of
stroke/TIA
MI adjusted for: diabetes, eGFR, peripheral vascular disease, history of CAD, LVEF
Hospitalization for: linear spline age ≤ 70, linear spline age > 70, BMI, weight, osteoporosis, height, PCI, cancer, OSA, anemia, frailty, insurance
status, history of CAD, site specialty, prior antiarrhythmic drug use, peripheral vascular disease, functional status, linear spline heart rate > 68,
diabetes, hematocrit, linear spline eGFR ≤ 80, COPD, diastolic blood pressure truncated above at 70, EHRA score, CHF
Major bleeding adjusted for: COPD, OSA, LAD type, cancer, functional status, level of education, intraventricular conduction delay, rhythm control,
smoking status, significant valvular disease, eGFR, insurance status, history of gastrointestinal bleed, anemia, hematocrit
**There were not enough events for the adjusted models for stroke/TIA and MI.
SUPPLEMENTARY FIGURE LEGENDS
Supplementary Figure 1. Cumulative incidence curves for hospitalization in quartiles of AFEQT in 1925 adults with atrial
fibrillation in the ORBIT-AF Registry.
Supplementary Figure 2. Kaplan-Meier curves for mortality in quartiles of AFEQT in 1925 adults with atrial fibrillation in the
ORBIT-AF Registry.
Supplementary Figure 1.
Quartile 2
Quartile 1
Cumulative Incidence Rate for All-Cause Hospitalization (%)
50
Quartile 3
40
Quartile 4
30
20
10
0
0
50
100
150
200
250
300
350
400
450
Time (Days)
500
550
600
650
700
750
800
Supplementary Figure 2.
Quartile 1
Quartile 2
8
Cumulative Incidence Rate for Mortality (%)
Quartile 4
Quartile 3
6
4
2
0
0
50
100
150
200
250
300
350
400
450
Time (Days)
500
550
600
650
700
750
800
ORBIT-AF Investigators
Executive Committee Members
Eric D. Peterson
Duke University Medical Center
Jack Ansell
Lenox Hill Hospital
Gregg C. Fonarow
UCLA Division of Cardiology
Bernard J. Gersh
Mayo Clinic
Alan S. Go
Kaiser Permanente of Northern California
Elaine Hylek
Boston University Medical Center
Peter R. Kowey
MLH Heart Center
Kenneth W. Mahaffey
Stanford University
Jonathan P. Piccini
Duke University Medical Center
Laine Thomas
Duke Clinical Research Institute
Paul Burton
Janssen Scientific
Steering Committee Members
James V. Freeman
Yale University School of Medicine
Larry A. Allen
University of Colorado Denver
Paul S. Chan
Mid-America Heart Institute, University of Missouri
Michael D Ezekowitz
Jefferson Medical College
James A. Reiffel
Columbia University
Gerald Naccarelli
Penn State University School of Medicine
Steven Rothman
Lankenau Hospital
Daniel E. Singer
Harvard Medical School
Peter Berger
Geisinger Medical Center
Study Site Primary Investigators
Alvin McElveen, MD
Bradenton Research Center
Paul McLaughlin, MD
Paul McLaughlin, M.D.
Robert Mendelson, MD
The Jamaica Hospital Medical Center
Roberto Moscoso, MD
Inland Heart Doctors Medical Group
Ahed Nahhas, M.D.
Toledo Clinic Incorporated
Joel Neutel, MD
Orange County Research Center
Saumil Oza, M.D.
Diagnostic Cardiology Associates, P.A.
Benzy Padanilam, M.D.
The Care Group
David Pan, MD
Orange County Heart Institute and Research Center
Parag Patel, MD
Advocate Lutheran General Hospital
James Poock, MD
Northeast Iowa Family Practice Center
Joseph Raffetto, MD
Peninsula Cardiology Associates
Richard Greengold, MD
Therapeutic Research Institute of Orange County
Michael Renzi, Doctor of
Advocare Heights Primary Care
Osteopathy
Peter Roan, MD
Mercy Physician Group Cardiology
Fadi Saba, MD
Professional Health Care of Pinellas, INC
Matthew Sackett, MD
Centra Cardiovascular group
Jay Sandberg, MD
Oakland Medical Research Center
Ricky Schneider, MD
holy Cross Medical Group
Andrew Schreiber, M.D.
SDS Clinical Trials, Inc,
Zachary Seymour, MD
AnMed Hospital
Saurabh Shah, MD
Illinois Heart and Vascular Foundation
Jeffrey Shanes, MD
Consultants in Cardiovascular Medicine
James Shoemaker, MD
Ormond Medical Arts Research Center
Victor Simms, MD, MPH
Kelsey Research Foundation
Nasser Smiley, MD
Northwest Ohio Cardiology Consultants
David Smith, MD
Tallahassee Research Institute
William Smith, IV, MD
Coastal Cardiology Associates
Calvin Snipes, MD
Foothills Internal Medicine
Rodolfo Sotolongo, MD
Southeast Texas Clinical Research Center
Shawn Speirs, D.O.
Eastern Idaho Medical Consultants, LLC
Cezar Staniloae, MD
Gotham Cardiovascular Research, PC
Steven Stoltz, MD
South Texas Institutes of Health
Damodhar P. Suresh, MD
St. Elizabeth Physicians
Tahir Tak, MD
FSH/Mayo Health System
Alan Tannenbaum, MD
PRIMARY CARE ASSOCIATES
Jose Teixeira
Black Hills Cardiovascular Research / Regional Heart Docotrs
Samir Turk, MD
Trinity Health Organization
Nampalli Vijay, MD
Aurora Denver Cardiology Associates
Kishor Vora, MD
Research Integrity
Mancel Wakham, DO
Mancel Wakham, D.O., R.Ph.
Preet Randhawa
NJ Heart
Vance Wilson, MD
Daytona Heart Group
Christina Wjasow, MD
Drexel University College of Medicine
Asim Yunus, MD
Michigan CardoVascular Institute
James Zebrack, MD
Heart Center
Eugene Silva, MD
Rockford Cardiovascular Associates
Preetham Jetty, M.D.
Community Heart and Vascular
Eustace Riley, MD
Piedmont Health Group
Debra Weinstein, MD
Atlantic Clinical Research
Tomas Vasiliauskas, MD, FACC
Tomas Vasiliauskas
Seth Goldbarg
New York Hospital Queens
Daniel Hayward, MD
Southwestern Medical Clinic
David Solis, D.O.
Phoenixville Family Practice
Chakri Yarlagadda, MD
Ohio Heart Institute
John Griffin, MD
Cardiovascular Associates, Ltd.
David Roberts, M.D.
Sutter Medical Group Cardiology
Munaf Shamji, MD,Fellowship-
The Heart Group
Cardiology,Interventional
Cardiology
Donald Laurion, D.O.
Nanticoke Cardiology, P.A.
Catherine LaRuffa, MD
La Ruffa Family Practice
Abayomi Osunkoya, MD
Profen Research Network @ East Carolina Medical Associates
Randall Burns, MD
Heart Center Research, LLC
Terrance Castor, MD
Worthington Internal Medicine
Dennis Spiller
South Florida Research Solutions, LLC.
Christopher Luttman
LGLN Cardiology Consultants, LLC
Salwan Anton, D.O.
Advanced Cardiovascular Health Specialists
Joseph McGarvey, MD
Central Bucks Specialists
Barry Collins, MD
Advanced Clinical Research
Roger Guthrie, M.D.
Arroyo Medical Group, Inc.
Michael Frais, M.D.
Michael A. Frais, Cardiologist, P.A.
George Deriso, MD
WellStar Health System
Roy Flood, MD
Virgin Islands Heart
Leslie Fleischer, MD
White-Wilson Medical Center
G. Keith Bruce, M.D
The Chattanooga Heart Institute
Jeffrey S. Fierstein
Clinlogix Spring House Corporate Center
Rahul Aggarwal, MD
CVMS Research Institute, LLC
Glenn Jacobs
Cardiology Consultants
Nasser Adjei, M.D
Sparks Regional Medical Center
Ayim Akyea-Djamson, MD
Metropolitan Cardiovascular Consultants, LLC
Anthony Alfieri, MD, FACC
ALFIERI CARDIOLOGY
Eduardo Almaguer, MD
Eastern Research
Jerome Anderson
Plaza Medical Group
Fernando Arzola
Cardiovascular Institute of the South of Opelousas
James Bacon, MD
Mid Ohio Heart Clinic, Inc
Noel Bedwell, CPI, MD
Mobile Heart Specialists, PC
Peter Berger, MD
Geisinger Medical Center
John Berry, MD
Cardiovascular Associates, P.C.
Ravi Bhagwat, MD
Cardiology Associates of Northwest Indiana, P.C.
John Blair, MD
Wilford Hall Medical Center
Stephen Bloom, MD
Midwest Heart and Vascular
Salvador Borromeo, III, MD
Medical Research Incorporated of Las Vegas
Andrew Burger, MD
University of Cincinnati
Fernando Boccalandro, MD
Permian Research Foundation
James Capo, MD
Executive Health and Research Associates, Inc.
Shaival Kapadia
Cardiovascular Assoc of Virginia
Rene Casanova, MD
Deerfield Beach Cardiology Research
J. E. Morriss III
Southern Clinic, PC
Tom Christensen, MD
Calabash Medical Center
Sammy Cox, MD
PharmaTex Research, LLC
Susan Datta, Medical Degree
Palmetto Medical Research
Steven Eisenberg, MD
Cardiovascular Specialists, P.C.
John Elsen, MD
Pharmakon Inc.
Ramin Farsad, MD
Diagnamics Inc.
Donald Fox, MD
Eastwick Primary Care PC
Brad Frandsen, MD
Sound Medical Research
Mark Gelernt, MD
Cardiovascular Associates of the Delaware Valley
Santosh Gill, MD, MBA
Fox Valley Clinical Research Center, LLC
Harinder Gogia, MD
Cardiology Consultants of Orange County Medical Group Inc.
Daniel Gottlieb, MD
Daniel W. Gottlieb, MD, PS
Stephen Grubb, MD
Tabor City Family Medicine
Christopher Hall, MD
Portage Medical Group
Hoadley Harris, MD
Odyssey Research/Plains Medical Clinic
William Herzog, MD
Cardiovascular Specialists of Central Maryland, PA
David Hotchkiss, MD
Charlotte Cardiovascular Institute
John Ip, MD
Thoracic & Cardiovascular Healthcare Foundation
Naseem Jaffrani, MD
CAMBRIDGE MEDICAL TRIALS
Alan Jones, MD
Northwest Medical Associates PS
John Kazmierski, MD
Mount Clemens Regional Medical Center
Frank Waxman, MD
Deerfield Beach Cardiology Associates
Waqar Khan, MD MPH
Cardiovascular Clinic of Texas
Steven Klein, MD
LeBauer Cardiovascular Research Foundation
G. L. Kneller, MD
Memorial Medical Group d/b/a LaPorte Medical Group
Ajay Labroo, MD
Advanced Cardiovascular Consultants
Brian Jaffe, MD
Munson Medical Center
Eli Lavie, MD
North Shore Cardiologists
Mark Lebenthal, MD
Cardiology Associates of Somerset County, PA
Daniel Lee, MD
Bay Regional Medical Center
Michael Lillestol, MD
Lillestol Research LLC
Kenneth LeClerc
Brooke Army Medical Center
Paul Maccaro, MD
Huntington Hospital
Nolan Mayer, MD
Ventura Cardiology Consultants
Jay Kozlowski, M.D.
Cardiology and Vascular Associates, Huron Valley Sinai
Hospital
Sabrina Benjamin, MD
Universal Research Group, LLC
Robert Detweiler, DO
Detweiler Family Medicine and Associates
Nelson Sandoval, M.D.
Arizona Community Physicians
Carlos Benitez-Colon, MD
Las Americas Professional Center
Michael Ahearn, MD
Marion Medical Research
Stephen Raskin, MD
PhaseCare, LLC
Petar Igic, MD
Meriter Wisconsin Heart
Timothy Jackson, MD
Heritage Valley Medical Group, Inc.
John Pappas, MD
Cardiology Associates of Corpus Christi
Ronald Littlefield, M.D.
Palmetto Research Center, LLC
Anthony Frey, MD
Atlantic Cardiology Associates, P.A.
Robert Vranian, MD
Virginia Cardiovascular Consultants
William Long, MD
Barat Research
Paul Grena, DO
Cardiology Consultants of Philadelphia
Eric Thomsen, M.D.
Gage County Medical Clinic,P.C.
Jawad Zar Shaikh, MD
Quality Assurance Research Center
Amy Arouni
The Creighton Cardiac Center
Gregory Bashian
Centennial Heart Cardiovascular Consultants, LLC
Timothy Smith
Mercy Health Research
Robert Orchard
New Mexico Heart Institute, PA
Ross Downey
New Mexico Heart Institute, PA
Daniel O'Dea
Hudson Valley Heart Ceter
John Quinn
Winchester Medical Center
Kevin Browne
Watson Clinic Center for Research, Inc.
Steven Forman
Los Alamitos Cardiovascular
Russell Reeves
Cardiovascular Associates of North Alabama, P.C.
Matthew Ebinger
Genesys Regional Medical Center
Ronald Blonder
Pikes Peak Cardiology
Harvey Snyder
Cardiovascular Associates of the Delaware Valley
Stan Slabic
Stan F. Slabic, MD Internal Medicine and Lipid Management
David Williams, MD
Black Warrior Research
Charles Herring
New Hanover Medical Research
Robert Stein
Penobscot Bay Medical Center
Stephen Kirkland, MD
Piedmont Medical Research
Kenneth Cohen
New West Physicians
Maurice Buchbinder
Foundation for Cardiovascular Medicine
Stephen Christiansen
Ozark Medical Surgical Associates
Michael Guese
Michael Guese
Walter Walthall
Oakwell Clinical Research, LLC
Keith Davis
Pinehurst Medical Clinic
Brian Snoddy
Birmingham Heart Clinic, P.C.
Odilon Alvarado
The Medical Group of Texas
Charles Leach
Charles R Leach MD
Steven Rothman
Lankenau Hospital
Amit Sharma, MD
University of Alabama at Birmingham - Health Center
Montgomery
Eric Buch
UCLA Medical Center
Abiodun Olatidoye
Southern Heart Research Institute, LLC
Soufian AlMahameed
Carilion Clinic
Steven Rosenthal
Atlanta Institute for Medical Research, Inc.
Michael Melucci
South Texas Cardiovascular Consultants
Gary Sutter
HealthCare Partners Medical Group
William Reiter
Community Hospital of Anaconda
Troy Thompson
Southwestern Medical Clinic
Stephen Thew
Kootenai Heart Clinics, LLC
John Kobayashi
Memorial Medcical Group / John Kobayashi
Marcus Williams, MD
The Valley Hospital
Stiliano Efstratiadis, MD
Quincy Medical Group
Jeffrey Kramer, MD
Cardiovascular Associates of the Delaware Valley
Shuaib A. Latif, MD
The Reading Hospital and Medical Center
Ralph Vicari, MD
MIMA
Benjamin Rhee, MD
Carle Foundation Hospital
Steven Turner, MD
The Heart Group, P.C.
Alexander Adler, MD
Methodist Medical Center of Illinois
Denis Ruiz-Serrano, MD
Denis Ruiz Serrano Cardologia
Stanley Stringam, MD
Saltzer Medical Group
Kenneth Wolok, DO
Tri-County Medical Clinic
Jamal Islam, MD, MS
Texas Tech University Health Science Center of the Permian
Basin
Ramesh Arora, MD, FACC
Medvin Clinical Research
Michael Burnam, MD
Medvin Clinical Research
Leo Polosajian, MD
Cardiac Rhythm Services
Augusto Focil, MD
Diverse Research Solutions
Samuel Butman, MD
Verde Valley Medical Center
Henry Ingersoll, MD
Sharp Rees-Stealy Medical Group
Richard Borge, MD
Abington Medical Specialists
Youssef Al-Saghir, MD
First Coast Cardiovascular Institute
Peter Coats, MD
Mobile Diagnostic Center
Kashyap Patel, MD
Peninsula Reseach, Inc.
Neil Farris, MD
The Research Group of Lexington, LLC
Kenneth Shore, MD
Medical Clinic of North Texas
Philip Casino, MD, FACC
St. Mary's Medical Center
Michael B. Schwartz, MD
DuPage Medical Group
John Bartholomew, MD
Cleveland Clinic Foundation
Charles Gornick
Minneapolis Heart Institute Foundation
Paz Eilat, MD
Devise Research
Pedro Ortega, MD
Central Florida Primary Care
Edward Quinlan, MD
Southern Maine Medical Center PrimeCare Physicians
Yogesh Paliwal, MD
Indus Clinical Research Institute
Raman Mitra, MD
Memorial Medical Group / Raman Mitra
Stanley Golanty, MD
Pacific Internal Medicine Group
Eric Batres, MD
Futura Research
Reginald Coates, MD
San Fernando Valley Research
Ahmad Jingo, MD
RST Data Research Inc.
Chris Bovetas, MD
Citrus Valley Family Practice
A. A. Aslam, MD
Northwest Houston Heart Center
Larry Allen, MD
University of Colorado Denver
Randy Watson, MD
Jean Brown Research
Stephen Welka, DO
Aurora Burlington Clinic
Stephen Voyce, MD
Advanced Cardiology Specialists
Jerome Williams, MD
Mid Carolina Cardiology
Michael Dickinson, MD
West Michigan Heart
Melissa Robinson, MD
Univeristy of Illinois at Chicago
Minang Turakhia, MD
VA Palo Alto Healthcare System
Dina Goytia-Leos, MD
Sonterra Clinical Research
Luisito Gonzales, MD
Indiana Medical Research
Mark King, MD
Quality Control Research, Inc
Scott Yates, MD
North Texas Medical Research
Daniel Singer, MD
Massachusetts General Hospital
Mark Lurie, MD
Torrance Memorial Medical Center
George Mallis, MD
VAMC-Northport
Brett Atwater, MD
Durham VAMC
Nizar Daboul, MD
Advanced Medical Research LLC
Showkat Hossain, MD
Advent CRC
John Strobel, MD
Premier Healthcare LLC
John Murray, MD
Meharry Medical College Clinical Research Center
Daniel Fisher, MD
Capitol Interventional Cardiology
Elaine Hylek, MD
Boston Medical Center
Robert Fishberg, MD
Associates in Cardiovascular Disease LLC
Mahmoud Atieh, MD
Sanford Cardiology
Robert Landes, MD
Piqua Family Practice
Andrew Drabick, MD
Family Medical Associates of Raleigh
Eric Harman, MD
Mountain Region Family Medicine
Brent Ashcraft, MD
Mound Family Practice Associates
Matthew Krista, MD
Prime Care
Andrea Videlefsky, MD
Urban Family Practice
Elvin Rivera-Zayas, MD
Ashford Medical Center
Melanie Kelly, MD
Kula Research, LLC
Alfred E. Tan, MD
West Coast Research LLC