- Email: [email protected]
Ischemic and Bleeding Outcomes in Patients With Atrial Fibrillation and Contraindications to Oral Anticoagulation
JACC: CLINICAL ELECTROPHYSIOLOGY
VOL.
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ª 2019 BY THE AMERICAN COLLEGE OF CARDIOLOGY FOUNDATION PUBLISHED BY ELSEVIER
Ischemic and Bleeding Outcomes in Patients With Atrial Fibrillation and Contraindications to Oral Anticoagulation Benjamin A. Steinberg, MD, MHS,a Nicholas G. Ballew, PHD,b Melissa A. Greiner, MS,b Steven J. Lippmann, PHD,b Lesley H. Curtis, PHD,b,c Emily C. O’Brien, PHD,b,c Manesh R. Patel, MD,c,d Jonathan P. Piccini, MD, MHSb,c,d
ABSTRACT OBJECTIVES This study sought to describe clinical outcomes among patients with atrial fibrillation (AF) and contraindications to oral anticoagulation (OAC). BACKGROUND Treatment with OAC prevents stroke and death in patients with AF, but may be contraindicated among patients at high bleeding risk. METHODS This was an observational, longitudinal analysis of a nationally representative 5% Medicare sample of patients with chronic AF and CHA2DS2-VASc (congestive heart failure, hypertension, age $75 years, diabetes mellitus, prior stroke or transient ischemic attack or thromboembolism, vascular disease, age 65–74 years, sex category) score $2. They were stratified by both the presence of high bleeding risk contraindications to OAC and by OAC use. We assessed 3-year ischemic and bleeding outcomes using multivariable Cox proportional hazards models adjusted for relevant patient characteristics. RESULTS Among 26,684 AF patients not treated with OAC, 8,283 (31%) had a high bleeding risk contraindication, primarily a blood dyscrasia (75%) or history of gastrointestinal bleeding (40%). Without OAC, patients with contraindications had worse ischemic and bleeding outcomes at 3 years compared with those without contraindications. We also identified 12,454 patients with OAC contraindications who received OAC. Compared with patients not receiving OAC, use of OAC was associated with reduced mortality (adjusted hazard ratio [HR]: 0.79; 95% confidence interval [CI]: 0.76 to 0.83), stroke (adjusted HR: 0.90; 95% CI: 0.83 to 0.99), and all-cause hospitalization (adjusted HR: 0.93; 95% CI: 0.90 to 0.96) but increased risk of intracranial hemorrhage (adjusted HR: 1.42; 95% CI: 1.17 to 1.72). CONCLUSIONS High bleeding risk contraindications to OAC are common among older patients with AF, and these patients have higher mortality compared with untreated patients without OAC contraindications. The use of OAC in these patients is associated with lower rates of all-cause stroke, hospitalization, and death but higher risk of intracranial hemorrhage. (J Am Coll Cardiol EP 2019;-:-–-) © 2019 by the American College of Cardiology Foundation.
From the aDivision of Cardiovascular Medicine, University of Utah Health Sciences Center, Salt Lake City, Utah; bDepartment of Population Health Sciences, Duke University, Durham, North Carolina; cDuke Clinical Research Institute, Durham, North Carolina; and the dCardiology Division, Department of Medicine, Duke University Medical Center, Durham, North Carolina. This work was supported by a grant from Boston Scientific. Dr. Steinberg was supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under Award Number K23HL143156. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Dr. Steinberg has received research support from Boston Scientific and Janssen; and served as a consultant for Biosense Webster, Janssen, and Merit Medical. Dr. Curtis has received grants from GlaxoSmithKline, Novartis, Boston Scientific, and St Jude. O’Brien has received grants from Novartis, BristolMyers Squibb, GlaxoSmithKline, Sanofi, and Janssen. Dr. Patel has received grant support from Novartis; and has served on the advisory board, as a consultant, and as a speaker for Bayer Pharmaceuticals, AstraZeneca, and Janssen. Dr. Piccini has received funding for clinical research from Abbott Medical, ARCA biopharma, Boston Scientific, Gilead, Janssen Pharmaceuticals, and Verily; and served as a consultant for Allergan, Bayer, Johnson and Johnson, Medtronic, Sanofi, and Phillips. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose. The authors attest they are in compliance with human studies committees and animal welfare regulations of the authors’ institutions and Food and Drug Administration guidelines, including patient consent where appropriate. For more information, visit the JACC: Clinical Electrophysiology author instructions page. Manuscript received April 5, 2019; revised manuscript received June 21, 2019, accepted July 11, 2019.
ISSN 2405-500X/$36.00
https://doi.org/10.1016/j.jacep.2019.07.011
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ABBREVIATIONS AND ACRONYMS AF = atrial fibrillation CI = confidence interval DOAC = direct oral anticoagulant
GI = gastrointestinal HR = hazard ratio ICD-9-CM = International Classification of Diseases-9th Revision-Clinical Modification
ICH = intracranial hemorrhage LAAO = left atrial appendage
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AF and Contraindications to Anticoagulation
ral anticoagulation (OAC) signifi-
claims $6 months apart. At least 1 of the claims must
cantly reduces the occurrence of
have been as an outpatient. Additionally, we required
stroke or systemic embolism in pa-
that beneficiaries were 65 years of age or older, living
tients with atrial fibrillation (AF) and addi-
in the United States on January 1, 2008, and had
tional risk factors (1–3). Yet, failure to
continuous enrollment in Medicare fee for service in
prescribe OAC in patients with AF who are
the prior colander year. This is consistent with prior,
at risk for stroke is common for a variety of
similar analyses of AF patients in Medicare datasets
reasons (4–8). Contraindication to OAC is
(11–13).
frequently cited as the reason for with-
The present analysis was further limited to pa-
holding therapy, often due to the perceived
tients with CHA 2 DS2-VASc (congestive heart failure,
increased risk of bleeding in these patients
hypertension, age $75 years, diabetes mellitus, prior
(9).
stroke or transient ischemic attack or thromboembo-
We have previously described the preva-
lism, vascular disease, age 65–74 years, sex category)
occlusion
lence of OAC contraindications in older U.S.
score $2 (calculated from claims between January 1
OAC = oral anticoagulation
patients with AF (10); however, the subse-
and December 31, 2007).
quent outcomes of these patients, when they are and are not treated with OAC have not been
OAC USE. We defined OAC use as the use of warfarin
described. Treatment of patients with significant
based on $2 of the following: prothrombin time lab-
contraindications to OAC is challenging. The risks of
oratory test (Current Procedural Terminology code
stroke and bleeding among patients with significant
85610) or home international normalized ratio moni-
contraindications to OAC in clinical practice are not
toring instruction, equipment, or interpretation of
well known, particularly for those who receive OAC
results (Healthcare Common Procedure Coding Sys-
despite contraindications.
tem codes G0248, G0249, G0250) claims in any carrier
The objectives of the current study were to: 1)
or outpatient facility claims found within 90 days
describe the prevalence of OAC contraindications and
before the index diagnosis (January 1, 2008). The
use of OAC among patients 65 years of age and older
study period predated the use of direct oral antico-
with AF; 2) compare rates of thromboembolism and
agulants (DOACs).
bleeding in AF patients with and without contrain-
The presence of OAC contraindication was defined
dications to OAC; and 3) compare outcomes in AF
by the presence of any 1 or more of the following 5
patients with OAC contraindications who do and do
conditions, as described previously (10): 1) intracra-
not receive OAC therapy.
nial
mass;
2)
severe,
chronic
blood
dyscrasia
(including thrombocytopenias, anemias, hemoglo-
METHODS
binopathies, and hematological and lymphatic malignancies); 3) severe or major gastrointestinal (GI)
We used standard analytic files from a nationally
bleeding; 4) intracranial hemorrhage (ICH) (traumatic
representative 5% sample of Medicare beneficiaries
and nontraumatic); and 5) end-stage liver disease.
and corresponding denominator files from the Cen-
The full listing of ICD-9-CM codes used to define the
ters for Medicare and Medicaid Services for 2007 to
study population, contraindication status, and out-
2010. These included inpatient institutional claims
comes can be found in Online Table 1 (14).
covered under Medicare Part A and outpatient claims from institutional outpatient providers. We also used noninstitutional provider claims for services covered under Medicare Part B. Denominator files contained beneficiary vital status and demographic data, as well as eligibility and enrollment information.
PATIENT CHARACTERISTICS. Patient demographics
(age, sex, race, and state of residence) were derived from the denominator files; comorbid conditions were defined using validated coding algorithms (15,16) for dementia, diabetes, ischemic heart disease, peripheral vascular disease, congestive heart failure,
STUDY POPULATIONS. We defined a 2008 cohort of
cerebrovascular
Medicare beneficiaries with prevalent AF not due to a
obstructive pulmonary disease, renal disease, stroke
reversible cause, based on claims-based diagnoses in
or transient ischemic attack, cancer, and valvular
2007. To establish a chronic, prevalent diagnosis
heart disease. The presence of a pacemaker or
of AF, we required at least 2 diagnoses of AF (Inter-
implantable
national Classification of Diseases-9th Revision-
identified on the basis of Current Procedural Termi-
Clinical Modification [ICD-9-CM] code 427.31) found
nology and ICD-9-CM codes for device in situ, im-
in any position on separate inpatient or outpatient
plantation, revision, or monitoring.
disease,
hypertension,
cardioverter-defibrillator
chronic
device
was
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STATISTICAL ANALYSIS. Primary analysis: contraindications
and outcomes without OAC. We initially described the
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AF and Contraindications to Anticoagulation
T A B L E 1 Characteristics of Patients With AF Who Were Not on OAC Medication, Stratified
by Eligibility for OAC
prevalence of contraindications using frequencies and proportions among patients not receiving OAC. Baseline characteristics were presented for categori-
Age, yrs
cal variables as frequencies and continuous variables
Age groups
No Contraindication (n ¼ 18,401)
OAC Contraindication (n ¼ 8,283)
p Value
81.1 7.9
81.9 7.5
<0.001
540 (6.5)
<0.001
as mean SD. We tested for differences between
65–69 years of age
1,644 (8.9)
contraindication groups (presence or absence) using
70–74 years of age
2,503 (13.6)
915 (11.0)
chi-square tests for categorical variables and Wil-
75–79 years of age
3,547 (19.3)
1,570 (19.0)
80þ years of age
10,707 (58.2)
5,258 (63.5)
11,103 (60.3)
5,134 (62.0)
coxon rank sum tests for continuous variables. Among patients not receiving OAC, we described 3year event rates between those with and without any
Female White
17,197 (93.5)
7,631 (92.1)
OAC contraindication, including transient ischemic
Black
643 (3.5)
402 (4.9)
attack, stroke (ischemic and hemorrhagic), ICH, se-
Other
561 (3.0)
250 (3.0)
vere GI bleeding that required a blood transfusion,
<0.001
Region
all-cause hospitalization, and all-cause mortality. For
Northeast
3,795 (20.6)
1,945 (23.5)
mortality, we calculated incidence based on Kaplan-
South
7,208 (39.2)
3,265 (39.4)
Meier estimates. We tested for mortality differences
Midwest
4,322 (23.5)
1,878 (22.7)
West
3,076 (16.7)
1,195 (14.4)
between groups using log-rank tests. For the other endpoints, we calculated cumulative incidence estimates. The cumulative incidence function accounts for the competing risk of mortality, which is high in this population (17,18). We tested for differences be-
Contraindications 1
0 (0)
6,223 (75.1)
2
0 (0)
1,958 (23.6)
3þ
0 (0)
102 (1.2)
Contraindication type
tween groups on these other outcomes using Gray’s
End-stage liver disease
0 (0)
65 (0.8)
tests. For all survival analyses, we censored data for
Blood dyscrasia
0 (0)
6,191 (74.7)
patients if they enrolled in Medicare managed care (i.e., fee-for-service end date), at the end of claims follow-up data (December 31, 2010) and at the time of death for outcomes other than mortality.
0.01 <0.001
Race/ethnicity
Intracranial mass
0 (0)
237 (2.9)
GI bleed
0 (0)
3,314 (40.0)
ICH
0 (0)
647 (7.8)
Comorbid conditions Atrial flutter
1,310 (7.1)
833 (10.1)
<0.001
Dementia
2,122 (11.5)
1,440 (17.4)
<0.001
indication and clinical outcomes, we used multivari-
Diabetes mellitus
5,759 (31.3)
3,422 (41.3)
<0.001
able Cox proportional hazards regression models.
Ischemic heart disease
9,674 (52.6)
5,463 (66.0)
<0.001
Adjustment variables included all of the baseline
Peripheral vascular disease
5,235 (28.4)
3,395 (41.0)
<0.001
Congestive heart failure
7,378 (40.1)
4,930 (59.5)
<0.001
Cerebrovascular disease
4,594 (25.0)
3,343 (40.4)
<0.001
Hypertension
15,941 (86.6)
7,628 (92.1)
different for each background characteristic we
<0.001
COPD
5,866 (31.9)
3,871 (46.7)
<0.001
investigated). The primary analysis was performed on
Renal disease
2,369 (12.9)
2,533 (30.6)
<0.001
the AF and no OAC use population in which OAC
Stroke/TIA
3,310 (18.0)
2,501 (30.2)
<0.001
status is statically assessed as of the index date
Cancer
2,424 (13.2)
2,082 (25.1)
<0.001
January 1, 2008 (see previous algorithm).
Valvular heart disease
6,164 (33.5)
3,756 (45.3)
<0.001
CHA2DS2-VASc score
4.9 1.6
5.7 1.6
<0.001
2
892 (4.8)
162 (2.0)
<0.001
3
2,526 (13.7)
502 (6.1)
<0.001
14,983 (81.4)
7,619 (92.0)
<0.001
To measure the association between OAC contra-
demographic information and comorbid conditions described previously (the groups were significantly
Secondary analyses: OAC use and contraindications. In secondary analyses, we identified patients with OAC contraindications who nonetheless were receiving OAC. Baseline characteristics were stratified by OAC
>4
2.7 1.3
3.4 1.4
<0.001
use and compared using chi-square tests for cate-
0
290 (1.6)
52 (0.6)
<0.001
gorical variables and Wilcoxon rank sum tests for
1
2,707 (14.7)
550 (6.6)
<0.001
continuous variables.
>2
15,404 (83.7)
7,681 (92.7)
<0.001
570 (3.1)
336 (4.1)
<0.001
3,231 (17.6)
1,752 (21.2)
<0.001
To assess the association between OAC use and clinical outcomes among these patients with OAC contraindications, we used multivariable Cox proportional hazards regression models. In addition to demographics and baseline comorbidities, contraindication characteristics that significantly differed between groups (number of contraindications, blood
CHADS2 score
Devices in place ICD Pacemaker Values are mean SD or n (%). AF ¼ atrial fibrillation; CHA2DS2 ¼ congestive heart failure, hypertension, age $75 years, diabetes mellitus, prior stroke or transient ischemic attack or thromboembolism; CHA2DS2-VASc ¼ congestive heart failure, hypertension, age $75 years, diabetes mellitus, prior stroke or transient ischemic attack or thromboembolism, vascular disease, age 65–74 years, sex category; COPD ¼ chronic obstructive pulmonary disease; GI ¼ gastrointestinal; ICD ¼ implantable cardioverter-defibrillator; ICH ¼ intracranial hemorrhage; OAC ¼ oral anticoagulation; TIA ¼ transient ischemic attack.
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AF and Contraindications to Anticoagulation
dyscrasia, GI bleed, and ICH frequency) were also
at least 1 major contraindication to OAC (Table 1). The
adjusted for in the models. The analysis was per-
most common OAC contraindication was the presence
formed on the contraindicated AF population in
of a blood dyscrasia (n ¼ 6,191, 75%); however, 2,060
which OAC status is statically assessed as of the index
patients (25% of all patients with contraindications)
date January 1, 2008 (see previous algorithm).
had 2 or more OAC contraindications (Online Table 2).
Sensitivity
a n a l y s e s . We
performed
multiple
sensitivity analyses for both the primary and secfirst
Patients with OAC contraindications were marginally older (mean age 81.9 years vs. 81.1 years; p < 0.0001),
analyses
were more likely to be women (62% vs. 60%; p ¼ .01),
allowed for changes in OAC status during follow-up:
and had significantly higher mean CHA 2DS2-VASc
OAC status was recorded for every 90-day period
scores (5.7 vs. 4.9; p < 0.0001).
ondary
analyses.
The
sensitivity
following the index date (January 1, 2008). If a patient
Cumulative event rates among patients with and
experienced a change in OAC status (e.g. crossover to
without OAC contraindications are shown in the
the opposite exposure group), they were censored
Central Illustration, Parts A and B. Raw and adjusted
from the analysis. This analysis was a sensitivity
event rates are shown in Table 2. The presence of an
analysis (as opposed to the primary) because it had
OAC contraindication was associated with a signifi-
the potential to produce biased results. Patients that
cantly higher 3-year adjusted hazard ratio (HR) for
start or stop using an OAC are likely to have a
death (1.17; 95% confidence interval [CI]: 1.12 to 1.22),
different patient profile (including OAC contraindi-
GI bleed (adjusted HR: 2.31; 95% CI: 1.64 to 3.24), and
cation status) than do those that do not start to use an
all-cause hospitalization (adjusted HR: 1.20, 95% 1.16
OAC and the differences are likely to relate to study
to 1.24).
outcomes. We also repeated the original analysis, without censoring, using an alternative definition of OAC use—based on Part D claims for warfarin use
instead
of
international
normalized
ratio
measurements. Additional sensitivity analyses were performed in patients not on OAC whose only contraindication was ICH. This analysis was performed to address what many clinicians consider to be the strongest contraindication to OAC (ICH). Last, to assess for residual confounding due to healthy user bias, we performed a sensitivity analysis between OAC treatment and a negative control outcome. In this comparison, hospitalization for nutritional and miscellaneous metabolic disorders (Diagnosis Related Group 640 or 641) served as the negative control. We used SAS software version 9.4 (SAS Institute, Cary, North Carolina) and R software version 3.53 (R Foundation for Statistical Computing, Vienna, Austria) for all analyses. We chose a 2-tailed alpha threshold of 0.05 for statistical significance. The
ANTICOAGULATION USE. In the secondary analysis
among only patients with OAC contraindications, baseline characteristics according to the presence or absence of OAC therapy are shown in Table 3. Those receiving OAC were younger (mean age 80.0 years vs. 81.9 years; p < 0.001), were less likely to be women (57% vs. 62%; p < 0.001), had lower mean CHA2DS 2VASc scores (5.5 vs. 5.7; p < 0.001), and less commonly had prior GI bleeding (37.5% vs. 40.0%; p < 0.001) or prior ICH (3.9% vs. 7.8%; p < 0.001). Unadjusted and adjusted outcomes comparing OAC use versus no OAC use, among patients with OAC contraindications, are shown in Table 4 (see also Central Illustration, Part C). Use of OAC among these patients was significantly associated with a lower risk of all-cause death (adjusted HR: 0.79; 95% CI: 0.76 to 0.83), any stroke (adjusted HR: 0.90; 95% CI: 0.83 to 0.99), and all-cause hospitalization (adjusted HR: 0.93; 95% CI: 0.90 to 0.96), but a higher risk of ICH (adjusted HR: 1.42; 95% CI: 1.17 to 1.72).
Institutional Review Board of the Duke University
SENSITIVITY ANALYSES. Results of all sensitivity
Health System approved the study. This work was
analyses are shown in Online Tables 3 to 6. They were
supported by a grant from Boston Scientific. The au-
consistently similar to the overall results reported
thors are solely responsible for the design and
previously. The use of alternative definition for OAC
conduct of this study, all study analyses, and the
use (Part D claims for warfarin vs. international
drafting and editing of the paper and its final
normalized ratio testing) did not significantly alter
contents.
the results. In the negative control sensitivity analysis, we found no significant association between
RESULTS
OAC use and readmission for nutritional or metabolic disorders, which suggests adequate control for con-
The primary study population consisted of 26,684 AF
founding variables in the OAC comparison models.
patients with CHA 2DS2 -VASc score $2 and who were
When classification of contraindication was limited to
not receiving OAC. Of these patients, 8,283 (31%) had
only ICH (Online Table 4), results were qualitatively
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Steinberg et al. AF and Contraindications to Anticoagulation
C ENTR AL I LL U STRA T I O N Outomes Among for Atrial Fibrillation Patients by OAC Contraindications and OAC Use
Steinberg, B.A. et al. J Am Coll Cardiol EP. 2019;-(-):-–-. (A and B) Unadjusted cumulative 3-year event rates for patients with atrial fibrillation who were not on oral anticoagulation (OAC) medication. Event rates are presented by contraindication status to OAC. For mortality, we calculated the event rate as the Kaplan-Meier estimator. For all other outcomes, we calculated the event rate using the cumulative incidence function, which accounts for competing risk of death. The vertical dashed gray lines note 1 and 2 years from the index date (January 1, 2008). (C) Adjusted hazard ratios for the associations between OAC use and outcomes, among only AF patients with at least 1 OAC contraindication. GI ¼ gastrointestinal; HR ¼ hazard ratio; ICH ¼ intracranial hemorrhage; OAC ¼ oral anticoagulation; TIA ¼ transient ischemic attack.
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AF and Contraindications to Anticoagulation
T A B L E 2 Oral Anticoagulation Contraindication Status and Outcomes Over 3 Years in Patients With Prevalent AF Who Were Not on OAC
Medication (n ¼ 26,684) Event Rate Percentage at 3 Yrs*
Outcome
Death
Unadjusted
Adjusted†
No Contraindication (n ¼ 18,401)
Contraindication (n ¼ 8,283)
p Value
HR (95% CI)
HR (95% CI)
p Value
34.6
49.6
<0.001
1.64 (1.57–1.70)
1.17 (1.12–1.22)
<0.001
Stroke-broad
10.1
11.3
0.003
1.28 (1.18–1.39)
1.01 (0.93–1.10)
0.83
Ischemic stroke
5.64
6.04
0.195
1.22 (1.09–1.36)
0.98 (0.87–1.10)
0.70
TIA
2.28
2.74
0.025
1.38 (1.17–1.62)
1.08 (0.91–1.29)
0.37
ICH
1.82
2.03
0.227
1.29 (1.06–1.55)
1.08 (0.89–1.32)
0.44
GI bleed-transfusion‡
0.42
0.99
<0.001
2.70 (1.96–3.72)
2.31 (1.64–3.24)
<0.001
Hospitalization
63.1
74.1
<0.001
1.53 (1.48–1.58)
1.20 (1.16–1.24)
<0.001
*The death event rate p value is from the log-rank test. All other outcome event rate p values are from Gray’s tests. †Adjusted for age, race, gender, region, implantable device (ICD and cardiac resynchronization therapy with defibrillator), and comorbidities (atrial flutter, dementia, diabetes, coronary heart disease, peripheral vascular disease, congestive heart failure, cardiovascular disease, hypertension, COPD, renal disease, prior stroke, cancer, and valvular heart disease). ‡Required a blood transfusion. CI ¼ confidence interval; HR ¼ hazard ratio; other abbreviations as in Table 1.
similar (though reflected the lower power with wider
challenge has been identifying those patients in
CIs).
which the associated risk of significant bleeding with
DISCUSSION
Some analyses have focused on the underlying
OAC outweighs the benefits of stroke prevention. bleeding risk of a population, based on bleeding There are several findings from our nationwide
scores, and demonstrated a net clinical benefit of OAC
analysis, which may have important implications for
even among patients with very high bleeding risk
the management of high-risk, older patients with AF
(23). This is likely due at least in part to the fact that
and significant contraindications to OAC. First, there
many of the same factors that increase bleeding risk
is a high prevalence of significant contraindications to
are also associated with increased stroke risk.
OAC, with nearly one-third of untreated patients
Furthermore, though those patients had increased
having $1 comorbid illness that could represent a
risk of bleeding as defined by a bleeding score, few of
contraindication to OAC (and nearly 8% overall
those factors are commonly regarded as absolute
with $2 such conditions). Second, patients with OAC
contraindications to anticoagulation. Given such
contraindications are at increased risk of bleeding,
challenges in assessing the net clinical benefit of OAC
hospitalization, and death compared with patients
in these patients, guidelines still do not recommend
who do not have a contraindication (but are not
routine use of a bleeding risk score to determine
treated with OAC). Finally, and perhaps most impor-
when to withhold OAC.
tantly, among patients with an OAC contraindication,
In this study, we sought to analyze specific
the use of OAC was associated with lower rates of all-
comorbidities that are often perceived by providers to
cause stroke, hospitalization, and death at the
indicate not only a higher risk of bleeding, but also a
expense of a 42% relative increased risk of ICH. Un-
sufficiently high risk of bleeding that in many cases
derstanding the trade-offs associated with OAC use in
the patient may be labeled as indefinitely ineligible
this population is important to optimize pharmaco-
for OAC therapy. The presence of hematologic dys-
logic and nonpharmacologic treatment decisions and
crasias and intracranial bleeding are 2 such condi-
outcomes in these high-risk patients.
tions. Yet our results demonstrate that even these
Risk factors for bleeding are a well-known and
conditions should be considered less stringently—
primary barrier to effective utilization of stroke pre-
they are risk factors for bleeding, which may or may
vention therapy in patients with AF, particularly
not tip the scale of net clinical benefit in favor of
among older individuals (19). Although several
withholding OAC. Importantly, many of these pa-
studies have attempted to define and measure the
tients may instead be treated with aspirin for stroke
prevalence of contraindications to OAC among pa-
prevention, despite evidence that it is inferior to OAC
tients with AF, they remain highly subjective across
for preventing stroke and may not be of significantly
clinicians and patients (20). Although there is agree-
lower bleeding risk compared with OAC (24).
ment that several factors can increase an individual’s
Although risk of ICH was higher among patients
risk of bleeding while taking OAC (21,22), the
with contraindications who were treated with OAC,
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AF and Contraindications to Anticoagulation
rates of death, hospitalization, and stroke were lower than their untreated counterparts. At the
T A B L E 3 Patient Baseline Characteristics of the AF and Contraindicated to OAC Cohorts
by OAC Status
population level, it appears that the higher risk of bleeding events may be outweighed by favorable stroke and mortality risk reduction. Nevertheless,
Age, yrs
there still may be individual patients for whom the
Age group
No OAC Use (n ¼ 8,283)
OAC Use (n ¼ 12,454)
p Value
81.9 7.5
80.0 6.7
<0.001
540 (6.5)
900 (7.2)
<0.001
risk of a fatal hemorrhagic complication truly is
65–69 years of age
prohibitively high—identifying those patients is an
70–74 years of age
915 (11.0)
1,852 (14.9)
important goal and may include those with a
75–79 years of age
1,570 (19.0)
2,936 (23.6)
80þ years of age
5,258 (63.5)
6,766 (54.3)
5,134 (62.0)
7,140 (57.3)
White
7,631 (92.1)
11,760 (94.4)
Black
402 (4.9)
428 (3.4)
Other
250 (3.0)
266 (2.1) 3,414 (27.4)
persistent or irreversible, high risk of ICH (e.g., intracranial mass, amyloid angiopathy). Such patients may be candidates for alternative approaches to stroke prevention in AF. The majority of data on DOACs suggest that these agents have lower risks of the most serious bleeding,
Female
<0.001
Region
ICH, compared with warfarin (25). However, for
Northeast
1,945 (23.5)
some DOACs, there may be an increased risk of GI
South
3,265 (39.4)
4,363 (35.0)
Midwest
1,878 (22.7)
2,966 (23.8)
West
1,195 (14.4)
1,711 (13.7)
bleeding, compared with warfarin (26). Thus, for some patients at very high risk of bleeding, DOACs
<0.001
Contraindications
may be appropriate, and for others, the incremental
1
6,223 (75.1)
10,278 (82.5)
risk of bleeding, compared with warfarin, may be
2
1,958 (23.6)
2,094 (16.8)
negligible. Alternatively, patients who are at the
3þ
102 (1.2)
82 (0.7)
highest risk of bleeding with long-term OAC may
Contraindication type
have the most to gain from nonpharmacological
End-stage liver disease
stroke
Blood dyscrasia
prevention
strategies
in
AF.
Left
atrial
appendage occlusion (LAAO) has become an attractive alternative for such patients. However, the current data supporting the only Food and Drug
<0.001 <0.001
Race/ethnicity
Intracranial mass GI bleed ICH
65 (0.8)
86 (0.7)
.43
6,191 (74.7)
9,148 (73.5)
.04
237 (2.9)
320 (2.6)
.20
3,314 (40.0)
4,673 (37.5)
<0.001
647 (7.8)
489 (3.9)
<0.001
Comorbid conditions
Administration–approved LAAO device have been
Atrial flutter
833 (10.1)
1,455 (11.7)
<0.001
largely limited to patients tolerant of long-term OAC
Dementia
1,440 (17.4)
1,102 (8.8)
<0.001
(27). This is due in part to the fact that intra-
Diabetes mellitus
3,422 (41.3)
5,203 (41.8)
.51
procedural parenteral anticoagulation and short-
Ischemic heart disease
5,463 (66.0)
8,143 (65.4)
.40
Peripheral vascular disease
3,395 (41.0)
4,550 (36.5)
<0.001
Congestive heart failure
4,930 (59.5)
6,953 (55.8)
<0.001
Cerebrovascular disease
3,343 (40.4)
4,491 (36.1)
<0.001
Hypertension
7,628 (92.1)
11,370 (91.3)
.04
devices (28). Additional data are needed regarding
COPD
3,871 (46.7)
5,291 (42.5)
<0.001
term postoperative OAC are recommended with the use of that device, and emerging data have raised the awareness for thrombotic complications of LAAO the net clinical benefit and long-term outcomes of
Renal disease
2,533 (30.6)
3,186 (25.6)
<0.001
LAAO among patients with AF and high risks of both
Stroke/TIA
2,501 (30.2)
3,223 (25.9)
<0.001
stroke and bleeding, who cannot tolerate any OAC.
Cancer
2,082 (25.1)
3,384 (27.2)
.001
Studies such as the ASAP-TOO (Assessment of the
Valvular heart disease
3,756 (45.3)
6,153 (49.4)
<0.001 <0.001
Watchman Device in Patients Unsuitable for Oral Anticoagulation) trial will provide valuable additional data (29). STUDY LIMITATIONS. Several limitations should be
acknowledged when considering these data. First, they are observational, and include only patients 65 years of age and older. Second, defining major con-
5.7 1.6
5.5 1.6
2
162 (2.0)
288 (2.3)
.08
3
502 (6.1)
934 (7.5)
<0.001
7,619 (92.0)
11,232 (90.2)
<0.001
3.4 1.4
3.2 1.3
<0.001
CHA2DS2-VASc score
$4 CHADS2 score 0
52 (0.6)
77 (0.6)
.93
1
550 (6.6)
1,002 (8.0)
<0.001
7,681 (92.7)
11,375 (91.3)
<0.001
336 (4.1)
753 (6.0)
<0.001
1,752 (21.2)
2,947 (23.7)
<0.001
$2 Devices in place
traindications can be challenging and is limited by
ICD
lack of data on severity and a finite lookback period of
Pacemaker
1 year. Furthermore, the definition of OAC contraindication in of itself may be subjective and often requires nuanced risk-benefit calculation in individual
Values are mean SD or n (%). Abbreviations as in Table 1.
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AF and Contraindications to Anticoagulation
T A B L E 4 OAC Use and Outcomes Over 3 Years in Patients With Prevalent AF and a Contraindication to OAC Use (n ¼ 20,737)
Event Rate Percentage at 3 Years*
Unadjusted
Adjusted†
No OAC (n ¼ 8,283)
OAC (n ¼ 12,454)
p Value
HR (95% CI)
HR (95% CI)
p Value
49.6
36.6
<0.001
0.65 (0.63–0.68)
0.79 (0.76–0.83)
<0.001
Death Stroke-broad
11.3
10.4
0.03
0.81 (0.74–0.88)
0.90 (0.83–0.99)
0.03
Ischemic stroke
6.04
5.18
0.01
0.76 (0.67–0.85)
0.87 (0.77–0.98)
0.03
TIA
2.74
2.53
0.36
0.82 (0.69–0.98)
0.90 (0.75–1.07)
0.23
ICH
2.03
2.84
<0.001
1.26 (1.04–1.52)
1.42 (1.17–1.72)
<0.001
GI bleed-transfusion‡
0.99
1.33
0.03
1.20 (0.92–1.58)
1.29 (0.98–1.70)
0.08
Hospitalization
74.1
73.5
<0.001
0.87 (0.84–0.89)
0.93 (0.90–0.96)
<0.001
*The death event rate p value is from the log-rank test. All other outcome event rate p values are from Gray’s tests. †Adjusted for age, race, gender, region, implantable device (ICD and cardiac resynchronization therapy with defibrillator), contraindication characteristics (number of contraindications, blood dyscrasia, ICH, and GI bleed), and comorbidities (atrial flutter, dementia, diabetes, coronary heart disease, peripheral vascular disease, congestive heart failure, cardiovascular disease, hypertension, COPD, renal disease, prior stroke, cancer, and valvular heart disease). ‡Required a blood transfusion. Abbreviations as in Tables 1 and 2.
patients. Nonetheless, we attempted to include a set
patients versus other potential treatment modalities
of factors that are generally considered higher risk.
such as LAAO.
Although our data predate the availability of DOACs, several sensitivity analyses of only patients with Part
ADDRESS FOR CORRESPONDENCE: Dr. Benjamin A.
D data were consistent with the topline results. Last,
Steinberg, University of Utah Cardiovascular Center,
these are observational data, and despite multivari-
50 North Medical Drive, Salt Lake City, Utah 84132.
able adjustment, residual or unmeasured confound-
E-mail: [email protected].
ing may remain—patients with contraindications who received OAC were significantly different from those
PERSPECTIVES
who did not receive OAC. Although incomplete adjustment, as previous, may influence the quanti-
COMPETENCY IN MEDICAL KNOWLEDGE:
tative results, all the event rates are pathophysio-
Patients with contraindications to OAC are at high
logically consistent and of the expected effect size,
risk of adverse events. However, the risk of OAC-
suggesting a likely true association.
associated ICH in these patients must be weighed against the lower rates of stroke, hospitalization, and mortality observed in these patients.
CONCLUSIONS High bleeding risk contraindications to OAC are common among older patients with AF and increased stroke risk, and these patients have higher mortality compared with untreated patients without OAC contraindications. However, the use of OAC is associated with lower rates of all-cause stroke, hospitalization, and death but higher risk of ICH. Future research should identify subgroups in which the net clinical
TRANSLATIONAL OUTLOOK: AF-related stroke is primarily driven by cardioembolism, and OAC reduces this risk at the expense of increased bleeding risk. Among patients at very high bleeding risk, the net clinical benefit of nonpharmacological stroke prevention strategies may be preferable to OAC. However, further studies are needed to assess the optimal balance.
benefit favors OAC in these high bleeding risk
REFERENCES 1. Hart RG, Benavente O, McBride R, Pearce LA.
with the special contribution of the European
Practice Guidelines. J Am Coll Cardiol 2011;57:
Antithrombotic therapy to prevent stroke in patients with atrial fibrillation: a meta-analysis. Ann Intern Med 1999;131:492–501.
Heart Rhythm Association. Eur Heart J 2012; 33:2719–47.
1330–7.
2. Camm AJ, Lip GY, De Caterina R, et al. 2012 focused update of the ESC Guidelines for the management of atrial fibrillation: an update of the 2010 ESC Guidelines for the management of atrial fibrillation. Developed
3. Wann LS, Curtis AB, January CT, et al. 2011 ACCF/AHA/HRS focused update on the management of patients with atrial fibrillation (updating the 2006 guideline): a report of the American College of Cardiology Foundation/ American Heart Association Task Force on
4. Fang MC, Stafford RS, Ruskin JN, Singer DE. National trends in antiarrhythmic and antithrombotic medication use in atrial fibrillation. Arch Intern Med 2004;164:55–60. 5. Gage BF, Boechler M, Doggette AL, et al. Adverse outcomes and predictors of underuse of
JACC: CLINICAL ELECTROPHYSIOLOGY VOL.
-, NO. -, 2019
Steinberg et al.
- 2019:-–-
AF and Contraindications to Anticoagulation
antithrombotic therapy in medicare beneficiaries with chronic atrial fibrillation. Stroke 2000;31: 822–7. 6. Bungard TJ, Ghali WA, Teo KK, McAlister FA, Tsuyuki RT. Why do patients with atrial fibrillation not receive warfarin? Arch Intern Med 2000;160: 41–6. 7. Go AS, Hylek EM, Borowsky LH, Phillips KA, Selby JV, Singer DE. Warfarin use among ambu-
14. Goldberg D, Lewis J, Halpern S, Weiner M, Lo Re V 3rd. Validation of three coding algorithms to identify patients with end-stage liver disease in an administrative database. Pharmacoepidemiol Drug
23. Friberg L, Rosenqvist M, Lip GY. Net clinical benefit of warfarin in patients with atrial fibrillation: a report from the Swedish atrial fibrillation cohort study. Circulation 2012;125:
Saf 2012;21:765–9.
2298–307.
15. Birman-Deych E, Waterman AD, Yan Y, Nilasena DS, Radford MJ, Gage BF. Accuracy of
24. Connolly SJ, Eikelboom J, Joyner C, et al.
ICD-9-CM codes for identifying cardiovascular and stroke risk factors. Med Care 2005;43:480–5.
latory patients with nonvalvular atrial fibrillation: the anticoagulation and risk factors in atrial fibrillation (ATRIA) study. Ann Intern Med 1999; 131:927–34.
16. Quan H, Sundararajan V, Halfon P, et al. Coding algorithms for defining comorbidities in ICD-9CM and ICD-10 administrative data. Med Care 2005;43:1130–9.
8. Ogilvie IM, Newton N, Welner SA, Cowell W, Lip GY. Underuse of oral anticoagulants in atrial fibrillation: a systematic review. Am J Med 2010; 123:638–45.e4.
17. Prentice RL, Kalbfleisch JD, Peterson AV Jr., Flournoy N, Farewell VT, Breslow NE. The analysis of failure times in the presence of competing risks. Biometrics 1978;34:541–54.
9. O’Brien EC, Simon DN, Allen LA, et al. Reasons for warfarin discontinuation in the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation
18. Gray RJ. A class of K-sample tests for comparing the cumulative incidence of a competing risk. Ann Stat 1988;16:1141–54.
(ORBIT-AF). Am Heart J 2014;168:487–94. 10. Steinberg BA, Greiner MA, Hammill BG, et al. Contraindications to anticoagulation therapy and eligibility for novel anticoagulants in older patients with atrial fibrillation. Cardiovasc Ther 2015; 33:177–83.
19. McCrory DC, Matchar DB, Samsa G, Sanders LL, Pritchett EL. Physician attitudes about anticoagulation for nonvalvular atrial fibrillation in the elderly. Arch Intern Med 1995;155:277–81. 20. O’Brien EC, Holmes DN, Ansell JE, et al.
11. Piccini JP, Sinner MF, Greiner MA, et al. Outcomes of Medicare beneficiaries undergoing catheter ablation for atrial fibrillation. Circulation 2012;126:2200–7.
Physician practices regarding contraindications to oral anticoagulation in atrial fibrillation: findings from the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT-AF) registry. Am Heart J 2014;167:601–9.e1.
12. Piccini JP, Hammill BG, Sinner MF, et al. Incidence and prevalence of atrial fibrillation and associated mortality among Medicare beneficiaries, 1993-2007. Circ Cardiovasc Qual Out-
21. O’Brien EC, Simon DN, Thomas LE, et al. The ORBIT bleeding score: a simple bedside score to assess bleeding risk in atrial fibrillation. Eur Heart J 2015;36:3258–64.
comes 2012;5:85–93. AS,
22. Pisters R, Lane DA, Nieuwlaat R, de Vos CB, Crijns HJ, Lip GY. A novel user-friendly score
Hernandez AF, Curtis LH. Pharmacotherapy in Medicare beneficiaries with atrial fibrillation. Heart Rhythm 2012;9:1403–8.
(HAS-BLED) to assess 1-year risk of major bleeding in patients with atrial fibrillation: the Euro Heart Survey. Chest 2010;138:1093–100.
13. Piccini
JP,
Mi
X,
Dewald
TA,
Go
Apixaban in patients with atrial fibrillation. N Engl J Med 2011;364:806–17. 25. Ruff CT, Giugliano RP, Braunwald E, et al. Comparison of the efficacy and safety of new oral anticoagulants with warfarin in patients with atrial fibrillation: a meta-analysis of randomised trials. Lancet 2014;383:955–62. 26. Sherwood MW, Nessel CC, Hellkamp AS, et al. Gastrointestinal bleeding in patients with atrial fibrillation treated with rivaroxaban or warfarin: ROCKET AF trial. J Am Coll Cardiol 2015;66: 2271–81. 27. Reddy VY, Doshi SK, Kar S, et al. 5-year outcomes after left atrial appendage closure: from the PREVAIL and PROTECT AF trials. J Am Coll Cardiol 2017;70:2964–75. 28. Dukkipati SR, Kar S, Holmes DR Jr., et al. Device-related thrombus after left atrial appendage closure: incidence, predictors, and outcomes. Circulation 2018;138:874–85. 29. Holmes DR, Reddy VY, Buchbinder M, et al. The Assessment of the Watchman Device in Patients Unsuitable for Oral Anticoagulation (ASAPTOO) trial. Am Heart J 2017;189:68–74.
KEY WORDS anticoagulation, atrial fibrillation, contraindication, outcomes, Medicare
A PP END IX For supplemental tables, please see the online version of this paper.
9
VOL.
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ª 2019 BY THE AMERICAN COLLEGE OF CARDIOLOGY FOUNDATION PUBLISHED BY ELSEVIER
Ischemic and Bleeding Outcomes in Patients With Atrial Fibrillation and Contraindications to Oral Anticoagulation Benjamin A. Steinberg, MD, MHS,a Nicholas G. Ballew, PHD,b Melissa A. Greiner, MS,b Steven J. Lippmann, PHD,b Lesley H. Curtis, PHD,b,c Emily C. O’Brien, PHD,b,c Manesh R. Patel, MD,c,d Jonathan P. Piccini, MD, MHSb,c,d
ABSTRACT OBJECTIVES This study sought to describe clinical outcomes among patients with atrial fibrillation (AF) and contraindications to oral anticoagulation (OAC). BACKGROUND Treatment with OAC prevents stroke and death in patients with AF, but may be contraindicated among patients at high bleeding risk. METHODS This was an observational, longitudinal analysis of a nationally representative 5% Medicare sample of patients with chronic AF and CHA2DS2-VASc (congestive heart failure, hypertension, age $75 years, diabetes mellitus, prior stroke or transient ischemic attack or thromboembolism, vascular disease, age 65–74 years, sex category) score $2. They were stratified by both the presence of high bleeding risk contraindications to OAC and by OAC use. We assessed 3-year ischemic and bleeding outcomes using multivariable Cox proportional hazards models adjusted for relevant patient characteristics. RESULTS Among 26,684 AF patients not treated with OAC, 8,283 (31%) had a high bleeding risk contraindication, primarily a blood dyscrasia (75%) or history of gastrointestinal bleeding (40%). Without OAC, patients with contraindications had worse ischemic and bleeding outcomes at 3 years compared with those without contraindications. We also identified 12,454 patients with OAC contraindications who received OAC. Compared with patients not receiving OAC, use of OAC was associated with reduced mortality (adjusted hazard ratio [HR]: 0.79; 95% confidence interval [CI]: 0.76 to 0.83), stroke (adjusted HR: 0.90; 95% CI: 0.83 to 0.99), and all-cause hospitalization (adjusted HR: 0.93; 95% CI: 0.90 to 0.96) but increased risk of intracranial hemorrhage (adjusted HR: 1.42; 95% CI: 1.17 to 1.72). CONCLUSIONS High bleeding risk contraindications to OAC are common among older patients with AF, and these patients have higher mortality compared with untreated patients without OAC contraindications. The use of OAC in these patients is associated with lower rates of all-cause stroke, hospitalization, and death but higher risk of intracranial hemorrhage. (J Am Coll Cardiol EP 2019;-:-–-) © 2019 by the American College of Cardiology Foundation.
From the aDivision of Cardiovascular Medicine, University of Utah Health Sciences Center, Salt Lake City, Utah; bDepartment of Population Health Sciences, Duke University, Durham, North Carolina; cDuke Clinical Research Institute, Durham, North Carolina; and the dCardiology Division, Department of Medicine, Duke University Medical Center, Durham, North Carolina. This work was supported by a grant from Boston Scientific. Dr. Steinberg was supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under Award Number K23HL143156. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Dr. Steinberg has received research support from Boston Scientific and Janssen; and served as a consultant for Biosense Webster, Janssen, and Merit Medical. Dr. Curtis has received grants from GlaxoSmithKline, Novartis, Boston Scientific, and St Jude. O’Brien has received grants from Novartis, BristolMyers Squibb, GlaxoSmithKline, Sanofi, and Janssen. Dr. Patel has received grant support from Novartis; and has served on the advisory board, as a consultant, and as a speaker for Bayer Pharmaceuticals, AstraZeneca, and Janssen. Dr. Piccini has received funding for clinical research from Abbott Medical, ARCA biopharma, Boston Scientific, Gilead, Janssen Pharmaceuticals, and Verily; and served as a consultant for Allergan, Bayer, Johnson and Johnson, Medtronic, Sanofi, and Phillips. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose. The authors attest they are in compliance with human studies committees and animal welfare regulations of the authors’ institutions and Food and Drug Administration guidelines, including patient consent where appropriate. For more information, visit the JACC: Clinical Electrophysiology author instructions page. Manuscript received April 5, 2019; revised manuscript received June 21, 2019, accepted July 11, 2019.
ISSN 2405-500X/$36.00
https://doi.org/10.1016/j.jacep.2019.07.011
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ABBREVIATIONS AND ACRONYMS AF = atrial fibrillation CI = confidence interval DOAC = direct oral anticoagulant
GI = gastrointestinal HR = hazard ratio ICD-9-CM = International Classification of Diseases-9th Revision-Clinical Modification
ICH = intracranial hemorrhage LAAO = left atrial appendage
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AF and Contraindications to Anticoagulation
ral anticoagulation (OAC) signifi-
claims $6 months apart. At least 1 of the claims must
cantly reduces the occurrence of
have been as an outpatient. Additionally, we required
stroke or systemic embolism in pa-
that beneficiaries were 65 years of age or older, living
tients with atrial fibrillation (AF) and addi-
in the United States on January 1, 2008, and had
tional risk factors (1–3). Yet, failure to
continuous enrollment in Medicare fee for service in
prescribe OAC in patients with AF who are
the prior colander year. This is consistent with prior,
at risk for stroke is common for a variety of
similar analyses of AF patients in Medicare datasets
reasons (4–8). Contraindication to OAC is
(11–13).
frequently cited as the reason for with-
The present analysis was further limited to pa-
holding therapy, often due to the perceived
tients with CHA 2 DS2-VASc (congestive heart failure,
increased risk of bleeding in these patients
hypertension, age $75 years, diabetes mellitus, prior
(9).
stroke or transient ischemic attack or thromboembo-
We have previously described the preva-
lism, vascular disease, age 65–74 years, sex category)
occlusion
lence of OAC contraindications in older U.S.
score $2 (calculated from claims between January 1
OAC = oral anticoagulation
patients with AF (10); however, the subse-
and December 31, 2007).
quent outcomes of these patients, when they are and are not treated with OAC have not been
OAC USE. We defined OAC use as the use of warfarin
described. Treatment of patients with significant
based on $2 of the following: prothrombin time lab-
contraindications to OAC is challenging. The risks of
oratory test (Current Procedural Terminology code
stroke and bleeding among patients with significant
85610) or home international normalized ratio moni-
contraindications to OAC in clinical practice are not
toring instruction, equipment, or interpretation of
well known, particularly for those who receive OAC
results (Healthcare Common Procedure Coding Sys-
despite contraindications.
tem codes G0248, G0249, G0250) claims in any carrier
The objectives of the current study were to: 1)
or outpatient facility claims found within 90 days
describe the prevalence of OAC contraindications and
before the index diagnosis (January 1, 2008). The
use of OAC among patients 65 years of age and older
study period predated the use of direct oral antico-
with AF; 2) compare rates of thromboembolism and
agulants (DOACs).
bleeding in AF patients with and without contrain-
The presence of OAC contraindication was defined
dications to OAC; and 3) compare outcomes in AF
by the presence of any 1 or more of the following 5
patients with OAC contraindications who do and do
conditions, as described previously (10): 1) intracra-
not receive OAC therapy.
nial
mass;
2)
severe,
chronic
blood
dyscrasia
(including thrombocytopenias, anemias, hemoglo-
METHODS
binopathies, and hematological and lymphatic malignancies); 3) severe or major gastrointestinal (GI)
We used standard analytic files from a nationally
bleeding; 4) intracranial hemorrhage (ICH) (traumatic
representative 5% sample of Medicare beneficiaries
and nontraumatic); and 5) end-stage liver disease.
and corresponding denominator files from the Cen-
The full listing of ICD-9-CM codes used to define the
ters for Medicare and Medicaid Services for 2007 to
study population, contraindication status, and out-
2010. These included inpatient institutional claims
comes can be found in Online Table 1 (14).
covered under Medicare Part A and outpatient claims from institutional outpatient providers. We also used noninstitutional provider claims for services covered under Medicare Part B. Denominator files contained beneficiary vital status and demographic data, as well as eligibility and enrollment information.
PATIENT CHARACTERISTICS. Patient demographics
(age, sex, race, and state of residence) were derived from the denominator files; comorbid conditions were defined using validated coding algorithms (15,16) for dementia, diabetes, ischemic heart disease, peripheral vascular disease, congestive heart failure,
STUDY POPULATIONS. We defined a 2008 cohort of
cerebrovascular
Medicare beneficiaries with prevalent AF not due to a
obstructive pulmonary disease, renal disease, stroke
reversible cause, based on claims-based diagnoses in
or transient ischemic attack, cancer, and valvular
2007. To establish a chronic, prevalent diagnosis
heart disease. The presence of a pacemaker or
of AF, we required at least 2 diagnoses of AF (Inter-
implantable
national Classification of Diseases-9th Revision-
identified on the basis of Current Procedural Termi-
Clinical Modification [ICD-9-CM] code 427.31) found
nology and ICD-9-CM codes for device in situ, im-
in any position on separate inpatient or outpatient
plantation, revision, or monitoring.
disease,
hypertension,
cardioverter-defibrillator
chronic
device
was
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STATISTICAL ANALYSIS. Primary analysis: contraindications
and outcomes without OAC. We initially described the
3
AF and Contraindications to Anticoagulation
T A B L E 1 Characteristics of Patients With AF Who Were Not on OAC Medication, Stratified
by Eligibility for OAC
prevalence of contraindications using frequencies and proportions among patients not receiving OAC. Baseline characteristics were presented for categori-
Age, yrs
cal variables as frequencies and continuous variables
Age groups
No Contraindication (n ¼ 18,401)
OAC Contraindication (n ¼ 8,283)
p Value
81.1 7.9
81.9 7.5
<0.001
540 (6.5)
<0.001
as mean SD. We tested for differences between
65–69 years of age
1,644 (8.9)
contraindication groups (presence or absence) using
70–74 years of age
2,503 (13.6)
915 (11.0)
chi-square tests for categorical variables and Wil-
75–79 years of age
3,547 (19.3)
1,570 (19.0)
80þ years of age
10,707 (58.2)
5,258 (63.5)
11,103 (60.3)
5,134 (62.0)
coxon rank sum tests for continuous variables. Among patients not receiving OAC, we described 3year event rates between those with and without any
Female White
17,197 (93.5)
7,631 (92.1)
OAC contraindication, including transient ischemic
Black
643 (3.5)
402 (4.9)
attack, stroke (ischemic and hemorrhagic), ICH, se-
Other
561 (3.0)
250 (3.0)
vere GI bleeding that required a blood transfusion,
<0.001
Region
all-cause hospitalization, and all-cause mortality. For
Northeast
3,795 (20.6)
1,945 (23.5)
mortality, we calculated incidence based on Kaplan-
South
7,208 (39.2)
3,265 (39.4)
Meier estimates. We tested for mortality differences
Midwest
4,322 (23.5)
1,878 (22.7)
West
3,076 (16.7)
1,195 (14.4)
between groups using log-rank tests. For the other endpoints, we calculated cumulative incidence estimates. The cumulative incidence function accounts for the competing risk of mortality, which is high in this population (17,18). We tested for differences be-
Contraindications 1
0 (0)
6,223 (75.1)
2
0 (0)
1,958 (23.6)
3þ
0 (0)
102 (1.2)
Contraindication type
tween groups on these other outcomes using Gray’s
End-stage liver disease
0 (0)
65 (0.8)
tests. For all survival analyses, we censored data for
Blood dyscrasia
0 (0)
6,191 (74.7)
patients if they enrolled in Medicare managed care (i.e., fee-for-service end date), at the end of claims follow-up data (December 31, 2010) and at the time of death for outcomes other than mortality.
0.01 <0.001
Race/ethnicity
Intracranial mass
0 (0)
237 (2.9)
GI bleed
0 (0)
3,314 (40.0)
ICH
0 (0)
647 (7.8)
Comorbid conditions Atrial flutter
1,310 (7.1)
833 (10.1)
<0.001
Dementia
2,122 (11.5)
1,440 (17.4)
<0.001
indication and clinical outcomes, we used multivari-
Diabetes mellitus
5,759 (31.3)
3,422 (41.3)
<0.001
able Cox proportional hazards regression models.
Ischemic heart disease
9,674 (52.6)
5,463 (66.0)
<0.001
Adjustment variables included all of the baseline
Peripheral vascular disease
5,235 (28.4)
3,395 (41.0)
<0.001
Congestive heart failure
7,378 (40.1)
4,930 (59.5)
<0.001
Cerebrovascular disease
4,594 (25.0)
3,343 (40.4)
<0.001
Hypertension
15,941 (86.6)
7,628 (92.1)
different for each background characteristic we
<0.001
COPD
5,866 (31.9)
3,871 (46.7)
<0.001
investigated). The primary analysis was performed on
Renal disease
2,369 (12.9)
2,533 (30.6)
<0.001
the AF and no OAC use population in which OAC
Stroke/TIA
3,310 (18.0)
2,501 (30.2)
<0.001
status is statically assessed as of the index date
Cancer
2,424 (13.2)
2,082 (25.1)
<0.001
January 1, 2008 (see previous algorithm).
Valvular heart disease
6,164 (33.5)
3,756 (45.3)
<0.001
CHA2DS2-VASc score
4.9 1.6
5.7 1.6
<0.001
2
892 (4.8)
162 (2.0)
<0.001
3
2,526 (13.7)
502 (6.1)
<0.001
14,983 (81.4)
7,619 (92.0)
<0.001
To measure the association between OAC contra-
demographic information and comorbid conditions described previously (the groups were significantly
Secondary analyses: OAC use and contraindications. In secondary analyses, we identified patients with OAC contraindications who nonetheless were receiving OAC. Baseline characteristics were stratified by OAC
>4
2.7 1.3
3.4 1.4
<0.001
use and compared using chi-square tests for cate-
0
290 (1.6)
52 (0.6)
<0.001
gorical variables and Wilcoxon rank sum tests for
1
2,707 (14.7)
550 (6.6)
<0.001
continuous variables.
>2
15,404 (83.7)
7,681 (92.7)
<0.001
570 (3.1)
336 (4.1)
<0.001
3,231 (17.6)
1,752 (21.2)
<0.001
To assess the association between OAC use and clinical outcomes among these patients with OAC contraindications, we used multivariable Cox proportional hazards regression models. In addition to demographics and baseline comorbidities, contraindication characteristics that significantly differed between groups (number of contraindications, blood
CHADS2 score
Devices in place ICD Pacemaker Values are mean SD or n (%). AF ¼ atrial fibrillation; CHA2DS2 ¼ congestive heart failure, hypertension, age $75 years, diabetes mellitus, prior stroke or transient ischemic attack or thromboembolism; CHA2DS2-VASc ¼ congestive heart failure, hypertension, age $75 years, diabetes mellitus, prior stroke or transient ischemic attack or thromboembolism, vascular disease, age 65–74 years, sex category; COPD ¼ chronic obstructive pulmonary disease; GI ¼ gastrointestinal; ICD ¼ implantable cardioverter-defibrillator; ICH ¼ intracranial hemorrhage; OAC ¼ oral anticoagulation; TIA ¼ transient ischemic attack.
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AF and Contraindications to Anticoagulation
dyscrasia, GI bleed, and ICH frequency) were also
at least 1 major contraindication to OAC (Table 1). The
adjusted for in the models. The analysis was per-
most common OAC contraindication was the presence
formed on the contraindicated AF population in
of a blood dyscrasia (n ¼ 6,191, 75%); however, 2,060
which OAC status is statically assessed as of the index
patients (25% of all patients with contraindications)
date January 1, 2008 (see previous algorithm).
had 2 or more OAC contraindications (Online Table 2).
Sensitivity
a n a l y s e s . We
performed
multiple
sensitivity analyses for both the primary and secfirst
Patients with OAC contraindications were marginally older (mean age 81.9 years vs. 81.1 years; p < 0.0001),
analyses
were more likely to be women (62% vs. 60%; p ¼ .01),
allowed for changes in OAC status during follow-up:
and had significantly higher mean CHA 2DS2-VASc
OAC status was recorded for every 90-day period
scores (5.7 vs. 4.9; p < 0.0001).
ondary
analyses.
The
sensitivity
following the index date (January 1, 2008). If a patient
Cumulative event rates among patients with and
experienced a change in OAC status (e.g. crossover to
without OAC contraindications are shown in the
the opposite exposure group), they were censored
Central Illustration, Parts A and B. Raw and adjusted
from the analysis. This analysis was a sensitivity
event rates are shown in Table 2. The presence of an
analysis (as opposed to the primary) because it had
OAC contraindication was associated with a signifi-
the potential to produce biased results. Patients that
cantly higher 3-year adjusted hazard ratio (HR) for
start or stop using an OAC are likely to have a
death (1.17; 95% confidence interval [CI]: 1.12 to 1.22),
different patient profile (including OAC contraindi-
GI bleed (adjusted HR: 2.31; 95% CI: 1.64 to 3.24), and
cation status) than do those that do not start to use an
all-cause hospitalization (adjusted HR: 1.20, 95% 1.16
OAC and the differences are likely to relate to study
to 1.24).
outcomes. We also repeated the original analysis, without censoring, using an alternative definition of OAC use—based on Part D claims for warfarin use
instead
of
international
normalized
ratio
measurements. Additional sensitivity analyses were performed in patients not on OAC whose only contraindication was ICH. This analysis was performed to address what many clinicians consider to be the strongest contraindication to OAC (ICH). Last, to assess for residual confounding due to healthy user bias, we performed a sensitivity analysis between OAC treatment and a negative control outcome. In this comparison, hospitalization for nutritional and miscellaneous metabolic disorders (Diagnosis Related Group 640 or 641) served as the negative control. We used SAS software version 9.4 (SAS Institute, Cary, North Carolina) and R software version 3.53 (R Foundation for Statistical Computing, Vienna, Austria) for all analyses. We chose a 2-tailed alpha threshold of 0.05 for statistical significance. The
ANTICOAGULATION USE. In the secondary analysis
among only patients with OAC contraindications, baseline characteristics according to the presence or absence of OAC therapy are shown in Table 3. Those receiving OAC were younger (mean age 80.0 years vs. 81.9 years; p < 0.001), were less likely to be women (57% vs. 62%; p < 0.001), had lower mean CHA2DS 2VASc scores (5.5 vs. 5.7; p < 0.001), and less commonly had prior GI bleeding (37.5% vs. 40.0%; p < 0.001) or prior ICH (3.9% vs. 7.8%; p < 0.001). Unadjusted and adjusted outcomes comparing OAC use versus no OAC use, among patients with OAC contraindications, are shown in Table 4 (see also Central Illustration, Part C). Use of OAC among these patients was significantly associated with a lower risk of all-cause death (adjusted HR: 0.79; 95% CI: 0.76 to 0.83), any stroke (adjusted HR: 0.90; 95% CI: 0.83 to 0.99), and all-cause hospitalization (adjusted HR: 0.93; 95% CI: 0.90 to 0.96), but a higher risk of ICH (adjusted HR: 1.42; 95% CI: 1.17 to 1.72).
Institutional Review Board of the Duke University
SENSITIVITY ANALYSES. Results of all sensitivity
Health System approved the study. This work was
analyses are shown in Online Tables 3 to 6. They were
supported by a grant from Boston Scientific. The au-
consistently similar to the overall results reported
thors are solely responsible for the design and
previously. The use of alternative definition for OAC
conduct of this study, all study analyses, and the
use (Part D claims for warfarin vs. international
drafting and editing of the paper and its final
normalized ratio testing) did not significantly alter
contents.
the results. In the negative control sensitivity analysis, we found no significant association between
RESULTS
OAC use and readmission for nutritional or metabolic disorders, which suggests adequate control for con-
The primary study population consisted of 26,684 AF
founding variables in the OAC comparison models.
patients with CHA 2DS2 -VASc score $2 and who were
When classification of contraindication was limited to
not receiving OAC. Of these patients, 8,283 (31%) had
only ICH (Online Table 4), results were qualitatively
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Steinberg et al. AF and Contraindications to Anticoagulation
C ENTR AL I LL U STRA T I O N Outomes Among for Atrial Fibrillation Patients by OAC Contraindications and OAC Use
Steinberg, B.A. et al. J Am Coll Cardiol EP. 2019;-(-):-–-. (A and B) Unadjusted cumulative 3-year event rates for patients with atrial fibrillation who were not on oral anticoagulation (OAC) medication. Event rates are presented by contraindication status to OAC. For mortality, we calculated the event rate as the Kaplan-Meier estimator. For all other outcomes, we calculated the event rate using the cumulative incidence function, which accounts for competing risk of death. The vertical dashed gray lines note 1 and 2 years from the index date (January 1, 2008). (C) Adjusted hazard ratios for the associations between OAC use and outcomes, among only AF patients with at least 1 OAC contraindication. GI ¼ gastrointestinal; HR ¼ hazard ratio; ICH ¼ intracranial hemorrhage; OAC ¼ oral anticoagulation; TIA ¼ transient ischemic attack.
5
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AF and Contraindications to Anticoagulation
T A B L E 2 Oral Anticoagulation Contraindication Status and Outcomes Over 3 Years in Patients With Prevalent AF Who Were Not on OAC
Medication (n ¼ 26,684) Event Rate Percentage at 3 Yrs*
Outcome
Death
Unadjusted
Adjusted†
No Contraindication (n ¼ 18,401)
Contraindication (n ¼ 8,283)
p Value
HR (95% CI)
HR (95% CI)
p Value
34.6
49.6
<0.001
1.64 (1.57–1.70)
1.17 (1.12–1.22)
<0.001
Stroke-broad
10.1
11.3
0.003
1.28 (1.18–1.39)
1.01 (0.93–1.10)
0.83
Ischemic stroke
5.64
6.04
0.195
1.22 (1.09–1.36)
0.98 (0.87–1.10)
0.70
TIA
2.28
2.74
0.025
1.38 (1.17–1.62)
1.08 (0.91–1.29)
0.37
ICH
1.82
2.03
0.227
1.29 (1.06–1.55)
1.08 (0.89–1.32)
0.44
GI bleed-transfusion‡
0.42
0.99
<0.001
2.70 (1.96–3.72)
2.31 (1.64–3.24)
<0.001
Hospitalization
63.1
74.1
<0.001
1.53 (1.48–1.58)
1.20 (1.16–1.24)
<0.001
*The death event rate p value is from the log-rank test. All other outcome event rate p values are from Gray’s tests. †Adjusted for age, race, gender, region, implantable device (ICD and cardiac resynchronization therapy with defibrillator), and comorbidities (atrial flutter, dementia, diabetes, coronary heart disease, peripheral vascular disease, congestive heart failure, cardiovascular disease, hypertension, COPD, renal disease, prior stroke, cancer, and valvular heart disease). ‡Required a blood transfusion. CI ¼ confidence interval; HR ¼ hazard ratio; other abbreviations as in Table 1.
similar (though reflected the lower power with wider
challenge has been identifying those patients in
CIs).
which the associated risk of significant bleeding with
DISCUSSION
Some analyses have focused on the underlying
OAC outweighs the benefits of stroke prevention. bleeding risk of a population, based on bleeding There are several findings from our nationwide
scores, and demonstrated a net clinical benefit of OAC
analysis, which may have important implications for
even among patients with very high bleeding risk
the management of high-risk, older patients with AF
(23). This is likely due at least in part to the fact that
and significant contraindications to OAC. First, there
many of the same factors that increase bleeding risk
is a high prevalence of significant contraindications to
are also associated with increased stroke risk.
OAC, with nearly one-third of untreated patients
Furthermore, though those patients had increased
having $1 comorbid illness that could represent a
risk of bleeding as defined by a bleeding score, few of
contraindication to OAC (and nearly 8% overall
those factors are commonly regarded as absolute
with $2 such conditions). Second, patients with OAC
contraindications to anticoagulation. Given such
contraindications are at increased risk of bleeding,
challenges in assessing the net clinical benefit of OAC
hospitalization, and death compared with patients
in these patients, guidelines still do not recommend
who do not have a contraindication (but are not
routine use of a bleeding risk score to determine
treated with OAC). Finally, and perhaps most impor-
when to withhold OAC.
tantly, among patients with an OAC contraindication,
In this study, we sought to analyze specific
the use of OAC was associated with lower rates of all-
comorbidities that are often perceived by providers to
cause stroke, hospitalization, and death at the
indicate not only a higher risk of bleeding, but also a
expense of a 42% relative increased risk of ICH. Un-
sufficiently high risk of bleeding that in many cases
derstanding the trade-offs associated with OAC use in
the patient may be labeled as indefinitely ineligible
this population is important to optimize pharmaco-
for OAC therapy. The presence of hematologic dys-
logic and nonpharmacologic treatment decisions and
crasias and intracranial bleeding are 2 such condi-
outcomes in these high-risk patients.
tions. Yet our results demonstrate that even these
Risk factors for bleeding are a well-known and
conditions should be considered less stringently—
primary barrier to effective utilization of stroke pre-
they are risk factors for bleeding, which may or may
vention therapy in patients with AF, particularly
not tip the scale of net clinical benefit in favor of
among older individuals (19). Although several
withholding OAC. Importantly, many of these pa-
studies have attempted to define and measure the
tients may instead be treated with aspirin for stroke
prevalence of contraindications to OAC among pa-
prevention, despite evidence that it is inferior to OAC
tients with AF, they remain highly subjective across
for preventing stroke and may not be of significantly
clinicians and patients (20). Although there is agree-
lower bleeding risk compared with OAC (24).
ment that several factors can increase an individual’s
Although risk of ICH was higher among patients
risk of bleeding while taking OAC (21,22), the
with contraindications who were treated with OAC,
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AF and Contraindications to Anticoagulation
rates of death, hospitalization, and stroke were lower than their untreated counterparts. At the
T A B L E 3 Patient Baseline Characteristics of the AF and Contraindicated to OAC Cohorts
by OAC Status
population level, it appears that the higher risk of bleeding events may be outweighed by favorable stroke and mortality risk reduction. Nevertheless,
Age, yrs
there still may be individual patients for whom the
Age group
No OAC Use (n ¼ 8,283)
OAC Use (n ¼ 12,454)
p Value
81.9 7.5
80.0 6.7
<0.001
540 (6.5)
900 (7.2)
<0.001
risk of a fatal hemorrhagic complication truly is
65–69 years of age
prohibitively high—identifying those patients is an
70–74 years of age
915 (11.0)
1,852 (14.9)
important goal and may include those with a
75–79 years of age
1,570 (19.0)
2,936 (23.6)
80þ years of age
5,258 (63.5)
6,766 (54.3)
5,134 (62.0)
7,140 (57.3)
White
7,631 (92.1)
11,760 (94.4)
Black
402 (4.9)
428 (3.4)
Other
250 (3.0)
266 (2.1) 3,414 (27.4)
persistent or irreversible, high risk of ICH (e.g., intracranial mass, amyloid angiopathy). Such patients may be candidates for alternative approaches to stroke prevention in AF. The majority of data on DOACs suggest that these agents have lower risks of the most serious bleeding,
Female
<0.001
Region
ICH, compared with warfarin (25). However, for
Northeast
1,945 (23.5)
some DOACs, there may be an increased risk of GI
South
3,265 (39.4)
4,363 (35.0)
Midwest
1,878 (22.7)
2,966 (23.8)
West
1,195 (14.4)
1,711 (13.7)
bleeding, compared with warfarin (26). Thus, for some patients at very high risk of bleeding, DOACs
<0.001
Contraindications
may be appropriate, and for others, the incremental
1
6,223 (75.1)
10,278 (82.5)
risk of bleeding, compared with warfarin, may be
2
1,958 (23.6)
2,094 (16.8)
negligible. Alternatively, patients who are at the
3þ
102 (1.2)
82 (0.7)
highest risk of bleeding with long-term OAC may
Contraindication type
have the most to gain from nonpharmacological
End-stage liver disease
stroke
Blood dyscrasia
prevention
strategies
in
AF.
Left
atrial
appendage occlusion (LAAO) has become an attractive alternative for such patients. However, the current data supporting the only Food and Drug
<0.001 <0.001
Race/ethnicity
Intracranial mass GI bleed ICH
65 (0.8)
86 (0.7)
.43
6,191 (74.7)
9,148 (73.5)
.04
237 (2.9)
320 (2.6)
.20
3,314 (40.0)
4,673 (37.5)
<0.001
647 (7.8)
489 (3.9)
<0.001
Comorbid conditions
Administration–approved LAAO device have been
Atrial flutter
833 (10.1)
1,455 (11.7)
<0.001
largely limited to patients tolerant of long-term OAC
Dementia
1,440 (17.4)
1,102 (8.8)
<0.001
(27). This is due in part to the fact that intra-
Diabetes mellitus
3,422 (41.3)
5,203 (41.8)
.51
procedural parenteral anticoagulation and short-
Ischemic heart disease
5,463 (66.0)
8,143 (65.4)
.40
Peripheral vascular disease
3,395 (41.0)
4,550 (36.5)
<0.001
Congestive heart failure
4,930 (59.5)
6,953 (55.8)
<0.001
Cerebrovascular disease
3,343 (40.4)
4,491 (36.1)
<0.001
Hypertension
7,628 (92.1)
11,370 (91.3)
.04
devices (28). Additional data are needed regarding
COPD
3,871 (46.7)
5,291 (42.5)
<0.001
term postoperative OAC are recommended with the use of that device, and emerging data have raised the awareness for thrombotic complications of LAAO the net clinical benefit and long-term outcomes of
Renal disease
2,533 (30.6)
3,186 (25.6)
<0.001
LAAO among patients with AF and high risks of both
Stroke/TIA
2,501 (30.2)
3,223 (25.9)
<0.001
stroke and bleeding, who cannot tolerate any OAC.
Cancer
2,082 (25.1)
3,384 (27.2)
.001
Studies such as the ASAP-TOO (Assessment of the
Valvular heart disease
3,756 (45.3)
6,153 (49.4)
<0.001 <0.001
Watchman Device in Patients Unsuitable for Oral Anticoagulation) trial will provide valuable additional data (29). STUDY LIMITATIONS. Several limitations should be
acknowledged when considering these data. First, they are observational, and include only patients 65 years of age and older. Second, defining major con-
5.7 1.6
5.5 1.6
2
162 (2.0)
288 (2.3)
.08
3
502 (6.1)
934 (7.5)
<0.001
7,619 (92.0)
11,232 (90.2)
<0.001
3.4 1.4
3.2 1.3
<0.001
CHA2DS2-VASc score
$4 CHADS2 score 0
52 (0.6)
77 (0.6)
.93
1
550 (6.6)
1,002 (8.0)
<0.001
7,681 (92.7)
11,375 (91.3)
<0.001
336 (4.1)
753 (6.0)
<0.001
1,752 (21.2)
2,947 (23.7)
<0.001
$2 Devices in place
traindications can be challenging and is limited by
ICD
lack of data on severity and a finite lookback period of
Pacemaker
1 year. Furthermore, the definition of OAC contraindication in of itself may be subjective and often requires nuanced risk-benefit calculation in individual
Values are mean SD or n (%). Abbreviations as in Table 1.
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AF and Contraindications to Anticoagulation
T A B L E 4 OAC Use and Outcomes Over 3 Years in Patients With Prevalent AF and a Contraindication to OAC Use (n ¼ 20,737)
Event Rate Percentage at 3 Years*
Unadjusted
Adjusted†
No OAC (n ¼ 8,283)
OAC (n ¼ 12,454)
p Value
HR (95% CI)
HR (95% CI)
p Value
49.6
36.6
<0.001
0.65 (0.63–0.68)
0.79 (0.76–0.83)
<0.001
Death Stroke-broad
11.3
10.4
0.03
0.81 (0.74–0.88)
0.90 (0.83–0.99)
0.03
Ischemic stroke
6.04
5.18
0.01
0.76 (0.67–0.85)
0.87 (0.77–0.98)
0.03
TIA
2.74
2.53
0.36
0.82 (0.69–0.98)
0.90 (0.75–1.07)
0.23
ICH
2.03
2.84
<0.001
1.26 (1.04–1.52)
1.42 (1.17–1.72)
<0.001
GI bleed-transfusion‡
0.99
1.33
0.03
1.20 (0.92–1.58)
1.29 (0.98–1.70)
0.08
Hospitalization
74.1
73.5
<0.001
0.87 (0.84–0.89)
0.93 (0.90–0.96)
<0.001
*The death event rate p value is from the log-rank test. All other outcome event rate p values are from Gray’s tests. †Adjusted for age, race, gender, region, implantable device (ICD and cardiac resynchronization therapy with defibrillator), contraindication characteristics (number of contraindications, blood dyscrasia, ICH, and GI bleed), and comorbidities (atrial flutter, dementia, diabetes, coronary heart disease, peripheral vascular disease, congestive heart failure, cardiovascular disease, hypertension, COPD, renal disease, prior stroke, cancer, and valvular heart disease). ‡Required a blood transfusion. Abbreviations as in Tables 1 and 2.
patients. Nonetheless, we attempted to include a set
patients versus other potential treatment modalities
of factors that are generally considered higher risk.
such as LAAO.
Although our data predate the availability of DOACs, several sensitivity analyses of only patients with Part
ADDRESS FOR CORRESPONDENCE: Dr. Benjamin A.
D data were consistent with the topline results. Last,
Steinberg, University of Utah Cardiovascular Center,
these are observational data, and despite multivari-
50 North Medical Drive, Salt Lake City, Utah 84132.
able adjustment, residual or unmeasured confound-
E-mail: [email protected].
ing may remain—patients with contraindications who received OAC were significantly different from those
PERSPECTIVES
who did not receive OAC. Although incomplete adjustment, as previous, may influence the quanti-
COMPETENCY IN MEDICAL KNOWLEDGE:
tative results, all the event rates are pathophysio-
Patients with contraindications to OAC are at high
logically consistent and of the expected effect size,
risk of adverse events. However, the risk of OAC-
suggesting a likely true association.
associated ICH in these patients must be weighed against the lower rates of stroke, hospitalization, and mortality observed in these patients.
CONCLUSIONS High bleeding risk contraindications to OAC are common among older patients with AF and increased stroke risk, and these patients have higher mortality compared with untreated patients without OAC contraindications. However, the use of OAC is associated with lower rates of all-cause stroke, hospitalization, and death but higher risk of ICH. Future research should identify subgroups in which the net clinical
TRANSLATIONAL OUTLOOK: AF-related stroke is primarily driven by cardioembolism, and OAC reduces this risk at the expense of increased bleeding risk. Among patients at very high bleeding risk, the net clinical benefit of nonpharmacological stroke prevention strategies may be preferable to OAC. However, further studies are needed to assess the optimal balance.
benefit favors OAC in these high bleeding risk
REFERENCES 1. Hart RG, Benavente O, McBride R, Pearce LA.
with the special contribution of the European
Practice Guidelines. J Am Coll Cardiol 2011;57:
Antithrombotic therapy to prevent stroke in patients with atrial fibrillation: a meta-analysis. Ann Intern Med 1999;131:492–501.
Heart Rhythm Association. Eur Heart J 2012; 33:2719–47.
1330–7.
2. Camm AJ, Lip GY, De Caterina R, et al. 2012 focused update of the ESC Guidelines for the management of atrial fibrillation: an update of the 2010 ESC Guidelines for the management of atrial fibrillation. Developed
3. Wann LS, Curtis AB, January CT, et al. 2011 ACCF/AHA/HRS focused update on the management of patients with atrial fibrillation (updating the 2006 guideline): a report of the American College of Cardiology Foundation/ American Heart Association Task Force on
4. Fang MC, Stafford RS, Ruskin JN, Singer DE. National trends in antiarrhythmic and antithrombotic medication use in atrial fibrillation. Arch Intern Med 2004;164:55–60. 5. Gage BF, Boechler M, Doggette AL, et al. Adverse outcomes and predictors of underuse of
JACC: CLINICAL ELECTROPHYSIOLOGY VOL.
-, NO. -, 2019
Steinberg et al.
- 2019:-–-
AF and Contraindications to Anticoagulation
antithrombotic therapy in medicare beneficiaries with chronic atrial fibrillation. Stroke 2000;31: 822–7. 6. Bungard TJ, Ghali WA, Teo KK, McAlister FA, Tsuyuki RT. Why do patients with atrial fibrillation not receive warfarin? Arch Intern Med 2000;160: 41–6. 7. Go AS, Hylek EM, Borowsky LH, Phillips KA, Selby JV, Singer DE. Warfarin use among ambu-
14. Goldberg D, Lewis J, Halpern S, Weiner M, Lo Re V 3rd. Validation of three coding algorithms to identify patients with end-stage liver disease in an administrative database. Pharmacoepidemiol Drug
23. Friberg L, Rosenqvist M, Lip GY. Net clinical benefit of warfarin in patients with atrial fibrillation: a report from the Swedish atrial fibrillation cohort study. Circulation 2012;125:
Saf 2012;21:765–9.
2298–307.
15. Birman-Deych E, Waterman AD, Yan Y, Nilasena DS, Radford MJ, Gage BF. Accuracy of
24. Connolly SJ, Eikelboom J, Joyner C, et al.
ICD-9-CM codes for identifying cardiovascular and stroke risk factors. Med Care 2005;43:480–5.
latory patients with nonvalvular atrial fibrillation: the anticoagulation and risk factors in atrial fibrillation (ATRIA) study. Ann Intern Med 1999; 131:927–34.
16. Quan H, Sundararajan V, Halfon P, et al. Coding algorithms for defining comorbidities in ICD-9CM and ICD-10 administrative data. Med Care 2005;43:1130–9.
8. Ogilvie IM, Newton N, Welner SA, Cowell W, Lip GY. Underuse of oral anticoagulants in atrial fibrillation: a systematic review. Am J Med 2010; 123:638–45.e4.
17. Prentice RL, Kalbfleisch JD, Peterson AV Jr., Flournoy N, Farewell VT, Breslow NE. The analysis of failure times in the presence of competing risks. Biometrics 1978;34:541–54.
9. O’Brien EC, Simon DN, Allen LA, et al. Reasons for warfarin discontinuation in the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation
18. Gray RJ. A class of K-sample tests for comparing the cumulative incidence of a competing risk. Ann Stat 1988;16:1141–54.
(ORBIT-AF). Am Heart J 2014;168:487–94. 10. Steinberg BA, Greiner MA, Hammill BG, et al. Contraindications to anticoagulation therapy and eligibility for novel anticoagulants in older patients with atrial fibrillation. Cardiovasc Ther 2015; 33:177–83.
19. McCrory DC, Matchar DB, Samsa G, Sanders LL, Pritchett EL. Physician attitudes about anticoagulation for nonvalvular atrial fibrillation in the elderly. Arch Intern Med 1995;155:277–81. 20. O’Brien EC, Holmes DN, Ansell JE, et al.
11. Piccini JP, Sinner MF, Greiner MA, et al. Outcomes of Medicare beneficiaries undergoing catheter ablation for atrial fibrillation. Circulation 2012;126:2200–7.
Physician practices regarding contraindications to oral anticoagulation in atrial fibrillation: findings from the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT-AF) registry. Am Heart J 2014;167:601–9.e1.
12. Piccini JP, Hammill BG, Sinner MF, et al. Incidence and prevalence of atrial fibrillation and associated mortality among Medicare beneficiaries, 1993-2007. Circ Cardiovasc Qual Out-
21. O’Brien EC, Simon DN, Thomas LE, et al. The ORBIT bleeding score: a simple bedside score to assess bleeding risk in atrial fibrillation. Eur Heart J 2015;36:3258–64.
comes 2012;5:85–93. AS,
22. Pisters R, Lane DA, Nieuwlaat R, de Vos CB, Crijns HJ, Lip GY. A novel user-friendly score
Hernandez AF, Curtis LH. Pharmacotherapy in Medicare beneficiaries with atrial fibrillation. Heart Rhythm 2012;9:1403–8.
(HAS-BLED) to assess 1-year risk of major bleeding in patients with atrial fibrillation: the Euro Heart Survey. Chest 2010;138:1093–100.
13. Piccini
JP,
Mi
X,
Dewald
TA,
Go
Apixaban in patients with atrial fibrillation. N Engl J Med 2011;364:806–17. 25. Ruff CT, Giugliano RP, Braunwald E, et al. Comparison of the efficacy and safety of new oral anticoagulants with warfarin in patients with atrial fibrillation: a meta-analysis of randomised trials. Lancet 2014;383:955–62. 26. Sherwood MW, Nessel CC, Hellkamp AS, et al. Gastrointestinal bleeding in patients with atrial fibrillation treated with rivaroxaban or warfarin: ROCKET AF trial. J Am Coll Cardiol 2015;66: 2271–81. 27. Reddy VY, Doshi SK, Kar S, et al. 5-year outcomes after left atrial appendage closure: from the PREVAIL and PROTECT AF trials. J Am Coll Cardiol 2017;70:2964–75. 28. Dukkipati SR, Kar S, Holmes DR Jr., et al. Device-related thrombus after left atrial appendage closure: incidence, predictors, and outcomes. Circulation 2018;138:874–85. 29. Holmes DR, Reddy VY, Buchbinder M, et al. The Assessment of the Watchman Device in Patients Unsuitable for Oral Anticoagulation (ASAPTOO) trial. Am Heart J 2017;189:68–74.
KEY WORDS anticoagulation, atrial fibrillation, contraindication, outcomes, Medicare
A PP END IX For supplemental tables, please see the online version of this paper.
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