Download Ejection fraction and outcomes in patients with atrial fibrillation and

European Journal of Heart Failure (2012) 14, 295–301
doi:10.1093/eurjhf/hfs005
Ejection fraction and outcomes in patients with
atrial fibrillation and heart failure: the Loire
Valley Atrial Fibrillation Project
Amitava Banerjee 1, Sophie Taillandier 2, Jonas Bjerring Olesen1,3, Deirdre A. Lane 1,
Benedicte Lallemand 2, Gregory Y.H. Lip 1*, and Laurent Fauchier 2*
1
University of Birmingham Centre for Cardiovascular Sciences, City Hospital, Birmingham B18 7QH, UK; 2Service de Cardiologie, Pôle Coeur Thorax Vasculaire, Centre Hospitalier,
Universitaire Trousseau et Faculté de Médecine, Université François Rabelais, Tours, France; and 3Department of Cardiology, Copenhagen University Hospital Gentofte,
Hellerup 2900, Denmark
Received 24 October 2011; revision requested 1 December 2011; accepted 23 December 2011; online publish-ahead-of-print 30 January 2012
Aims
Heart failure (HF) increases the risk of stroke and thrombo-embolism (TE) in non-valvular atrial fibrillation (NVAF),
and is incorporated in stroke risk stratification scores. We aimed to establish the role of ejection fraction (EF) in risk
prediction in patients with NVAF and HF.
.....................................................................................................................................................................................
Methods
Patients with NVAF, history of HF, and measured EF were included in a retrospective analysis. Patients with HF and
preserved ejection fraction (HFPEF) were defined as those with clinical HF and EF ≥ 50% in this study. Among 7156
and results
patients with NVAF, 1276 (17.8%) patients with HF and measured EF were included. Of these, 747/1276 (58.5%)
patients were on vitamin K antagonists. The stroke/TE event rate per 100 person-years was 1.05 [95% confidence
interval (CI) 0.87–1.25]. Patients with HFPEF were more likely to be female (P , 0.001), older (P , 0.001), and
hypertensive (P , 0.001), and less likely to have prior vascular disease (P , 0.001). There were no differences in
rates of stroke (P ¼ 0.17) and stroke/TE (P ¼ 0.11) between patients with HFPEF and those with HF and reduced
EF. There were no significant differences in rates of all-cause mortality when patients were stratified by EF. In multivariate analyses, only previous stroke (hazard ratio 2.36, 95% CI 1.45–3.86) and vascular disease (1.57, 1.07– 2.30)
increased the risk of stroke/TE amongst NVAF patients with HF, but EF ,35% did not (0.75, 0.44 –1.30).
.....................................................................................................................................................................................
Conclusion
In NVAF patients with HF, there were no differences in rates of stroke, TE, or death between EF categories. Only
previous stroke and vascular disease (and not decreased EF) independently increased risk of stroke/TE in multivariate
analyses.
----------------------------------------------------------------------------------------------------------------------------------------------------------Keywords
Heart failure † Atrial fibrillation † Ejection fraction † Stroke † Thrombo-embolism † Risk
Introduction
With lifetime risks of one in four and one in five, respectively, nonvalvular atrial fibrillation (NVAF) and heart failure (HF) present
major public health burdens in terms of morbidity, mortality, and
costs to health systems, with future increases predicted.1,2 HF is
both a cause and an effect of NVAF.3 – 6 In patients with NVAF,
HF is associated with increased risk of stroke and thromboembolism (TE),7 – 9 and has been incorporated in validated risk
stratification scores.10213
Heart failure may be associated with a spectrum of left ventricular (LV) function. There is considerable debate about definitions of
HF based on quantitative measures such as LV ejection fraction
(EF) and there is variation across guidelines, clinical trials, and epidemiological studies.14,15 For example, the European AF guidelines
classify HF (moderate to severe systolic LV dysfunction, defined arbitrarily as LVEF ≤ 40%) as a risk factor for stroke and TE, suggesting that HF can be defined not only by symptoms, but also by a
decrease in EF in the setting of AF.12 There is lack of consensus
with regard to the cut-off for defining ‘preserved EF’,16 and the
* Corresponding authors. L. Fauchjier, Tel: +33 2 47 47 46 50, Fax: +33 6 65 17 30 82, Email: [email protected] or G.Y.H. Lip, Tel: +44 121 507 5080, Fax: +44 121 554 4083,
Email: [email protected]
Published on behalf of the European Society of Cardiology. All rights reserved. & The Author 2012. For permissions please email: [email protected].
296
distinction between ‘systolic HF’ and ‘diastolic HF’ is somewhat arbitrary since they often co-exist.14,15
Previous studies have shown differences in risk factor profile and
outcomes between patients with HF with preserved EF (HFPEF)
and patients with HF with reduced EF (HFREF).17 – 20 HFPEF may
represent up to 50% of patients with HF.21 Some studies have indicated similar mortality and morbidity and a more severe risk factor
profile in HFPEF compared with HFREF.22,23 In patients with systolic dysfunction, EF has been related to mortality and cardiovascular
outcomes.24
Clinical HF has been shown to add predictive value for stroke
and TE events in patients with NVAF,7 but the role of quantitative
EF in risk prediction in NVAF patients remains uncertain. The
largest echocardiographic analysis from the AF Investigators
found that moderate–severe left ventricular dysfunction on twodimensional echocardiography was the only independent predictor
on multivariate analysis.25 A recent systematic review did not find
a history of HF to be a consistent or significant risk factor for
stroke, but systolic impairment on echocardiography was a risk
factor,26 driven largely by the AF Investigators’ echocardiographic
analysis.25
Aim
In this study, we analysed a large hospitalized cohort of patients
with NVAF and HF with recorded EF to assess: (i) whether EF
was an independent risk factor for stroke/TE and bleeding in this
cohort; and (ii) the differences in risk factor profile and outcome
between patients with NVAF and HFREF, when compared with
patients with NVAF and HFPEF.
Figure 1 Study population in heart failure patients. LV, left ventricular.
A. Banerjee et al.
Methods
Study population
At the Centre Hospitalier Régional et Universitaire in Tours (France), all
patients diagnosed with NVAF or atrial flutter by the Department of
Cardiology between 2000 and 2010 were identified.5 Patients were followed from the first record of NVAF after 1 January 2000 (i.e. the index
date) up to the latest data collection at the time of study (December
2010). Treatment at discharge was obtained by screening hospitalization
reports, and information on co-morbidities was obtained from the computerized coding system. Co-morbidities were characterized using definitions from the International Classification of Diseases (ICD)-10.27 For
example, hypertension was identified by the physician for each patient
using the diagnosis quoted in the appropriate items in ICD-10 (I10–
I15), which defines hypertension as ‘a repeatedly elevated blood pressure exceeding 140 over 90 mmHg’. Patients were excluded from the
study if there was no history of chronic HF or if echocardiographic assessment of LV function was not available (Figure 1). All patients included
in the study underwent two-dimensional and colour Doppler echocardiography at baseline. EF was calculated using Simpson’s rule or the
Teichholz method.14,15 Patients with any degree of valvular dysfunction
were excluded from this study.
11
For each patient, the CHADS10
scores were
2 and CHA2DS2-VASc
calculated. The CHADS2 score was the sum of points obtained after
adding one point for congestive heart failure, hypertension, age ≥75,
and diabetes, and two points for previous stroke or TE.10 The CHA2DS2-VASc score was the sum of points after adding one point for congestive heart failure, hypertension, diabetes, vascular disease (including
history of coronary, cerebrovascular, or peripheral vascular disease),
age 65 – 74, and female gender, and two points for previous stroke
or TE and age ≥75.11 According to the two risk scores, patients
with a score of 0 on either schema were considered as ‘low risk’, 1
as ‘intermediate risk’, and ≥2 as ‘high risk’ of stroke and TE.
297
Ejection fraction in patients with AF and heart failure
The HAS-BLED {Hypertension, Abnormal renal and/or liver function, Stroke, Bleeding history or predisposition, Labile international
normalized ratio (INR), Elderly (.65 years), Drugs [antiplatelet
drugs or non-steroidal anti-inflammatory drugs (NSAIDS)/alcohol
excess concomitantly]} score is a validated scoring system for bleeding
risk stratification in AF patients.28 For each patient, the HAS-BLED
score was also calculated as the sum of the points obtained after
adding one point for the presence of each individual factor. Patients
with a HAS-BLED score of 0 – 2 were deemed to have low bleeding
risk and those with a HAS-BLED score of ≥3 were classified as
having a high bleeding risk.
During follow-up, information on the study outcomes of TE, stroke
(ischaemic or haemorrhagic), bleeding, and all-cause mortality was
recorded. Death was recorded using hospital coding as well as using
a website dedicated to local news covering 35 000 km2 (http://nrco.
lanouvellerepublique.fr/dossiers/necro/index.php). In-hospital deaths
represented 65% of all deaths. The institution includes a total of
four hospitals covering all medical and surgical specialties, the only
public institution in an area of 4000 km2, serving 400 000
inhabitants.
Statistical analysis
The study population was stratified into four categories according to
EF, i.e. severe LV impairment (EF ,35%), moderate LV impairment
(EF 35 – 40%), mild LV impairment (EF 41– 49%), and normal LV function (EF ≥ 50%) (Figure 1). Baseline characteristics were determined
separately for the four EF strata, and differences were investigated
using x2 test for categorical covariates and Kruskal – Wallis test for
continuous covariates. To avoid any confusion, we defined HFPEF as
clinical HF with EF ≥ 50% in this study.
In each of the four EF categories, event rates of stroke/TE, bleeding,
and death were calculated for AF patients who were not receiving a
vitamin K antagonist (VKA). For all the following analyses, a composite
endpoint of stroke and TE was used. The x2 test was used to test for
differences between event rates, with patients with normal EF (EF ≥
50%) as the reference group. The risk associated with the individual
risk factors of the CHA2DS2-VASc score was estimated in Cox proportional hazard models. To increase the power of the analyses, the
Cox regression models included patients with and without a VKA;
this approach was appropriate since no interaction was found
between the effect of the individual risk factors and VKA treatment.
Both univariate (including the individual risk factors and VKA treatment
only) and multivariate (including all the CHA2DS2-VASc risk factors
and VKA treatment) Cox regression models were applied. Furthermore, the event rates of stroke/TE were calculated in patients with
and without each of the CHA2DS2-VASc risk factors. If appropriate,
Net Reclassification Improvement (NRI) and Integrated Discrimination
Improvement (IDI) indices were performed to test the additional
predictive value of EF.
A two-sided P-value ,0.05 was considered statistically significant.
All analyses were performed with SPSS statistical software version
18.0 (IBM, USA).
Ethics approval
The local ethics committee of our institution was consulted and
approved this study. The informed consent of patients was deemed
unnecessary for our analyses since this is a retrospective analysis of
a single centre cardiology department.
Results
Of 8962 patients with AF, 7156 had NVAF. Of these NVAF
patients, 1276 had measured EF data and were included in the analysis (Figure 1). Baseline characteristics are displayed in Table 1, and
patients with HFREF are stratified into severe LV impairment (EF
,35%), moderate LV impairment (EF 35 –40%), and mild LV
impairment (EF 41 –49%) in Supplementary material online,
Table S1. Patients with normal EF were older (P , 0.001) and,
after age adjustment, were more likely to be female (P , 0.001)
and hypertensive (P , 0.001), and less likely to have prior vascular
disease (P , 0.001). Patients with normal EF had higher CHADS2
(P , 0.001) and CHA2DS2-VASc scores (P , 0.001). As expected,
patients with low EF were more likely to be on treatment for HF
(P , 0.001).
There was no difference in type of NVAF (P ¼ 0.64) or bleeding
risk by HAS-BLED score (P ¼ 0.10), after adjustment for age or
antithrombotic medications (P ¼ 0.51) based on EF. As all patients
had a history of HF; no patient had a CHADS2 or CHA2DS2-VASc
score of 0. Supplementary material online, Table S2, shows that
patients with HF are older, and more likely to have other risk
factors (except dyslipidaemia and prior stroke) and to receive
antithrombotic and HF therapies when compared with patients
without HF, even after age adjustment.
Of our cohort, 747/1276 (58.5%) patients were on VKAs. The
overall stroke/TE event rate per 100 person-years was 1.05
[95% confidence interval (CI) 0.87 – 1.25]. Corresponding rates
in patients with and without VKA therapy were 1.06 (0.84 –
1.32) and 1.03 (0.76 – 1.38), respectively. Table 2 displays event
rates per 100 person-years in patients with AF and HF, and
Supplementary material online, Table S3, shows the same data
by EF ranges: ,35%, 35 – 40%, 41 – 49%, and ≥50%. Comparing
HFPEF and HFREF patients, there were no statistical differences
in stroke, stroke/TE, all-cause death, or bleeding. The rates of
stroke (P ¼ 0.02) and stroke/TE (P ¼ 0.02) were significantly different between patients with EF ,35% and patients with EF ≥
50%, but bleeding (P ¼ 0.63), all-cause death (P ¼ 0.10), and
the composite outcome of stroke/TE and death (P ¼ 0.82)
were not (Supplementary material online, Table S3). The observed
rates of the composite endpoint of ‘stroke/TE/death and all-cause
mortality’ were highest in patients with severe LV impairment (EF
,35%); these patients also had lower rates of stroke/TE and
bleeding compared with patients with HFPEF. Overall, patients
with mild LV impairment (EF 41 –49%) had the highest rates of
stroke/TE.
Cox regression analyses for all AF patients with HF are presented in Table 3. On univariate analyses, age ≥ 75 years [hazard
ratio (HR) 1.72, 95% CI 1.10–2.70], previous stroke (2.56, 1.59–
4.14), vascular disease (1.43, 1.01–2.03), and female gender
(1.49, 1.05– 2.13) significantly increased the risk of stroke and
TE, although on multivariate analysis the associations with age
≥75 and female gender were not significant. The risks associated
with age 65–74, hypertension, diabetes, EF (whether defined as
EF ,35%, EF ¼ 35 –49%, or EF ≥ 50%, or as a continuous variable) were not statistically significant. Given this non-significant
result on multivariate analysis, further calculations using the NRI
and IDI indices were not performed.
298
A. Banerjee et al.
Table 1 Characteristics of patients with heart failure by left ventricular ejection fraction
n (%)
HFREF (EF <50%), n 5 691
HFPEF (EF ≥50%), n 5 585
Mean age (SD)
70.7 (12.0)
74.7 (12.5)
,0.001
Female sex
Type of AF
155 (22.4)
294 (50.3)
,0.001
0.53
,0.001
0.64
Paroxysmal
337 (48.8)
295 (50.4)
Permanent
Persistent
305 (44.1)
49 (7.1)
242 (41.4)
48 (8.2)
298 (43.1)
164 (23.7)
363 (62.1)
150 (25.6)
,0.001
0.44
,0.001
0.36
P-value
Age-adjusted P-value
...............................................................................................................................................................................
–
Co-morbidities
Hypertension
Diabetes
Previous stroke
45 (6.5)
40 (6.8)
0.82
0.97
Any vascular disease
Renal failure
365 (52.8)
116 (16.8)
205 (35.0)
90 (15.4)
,0.001
0.54
,0.001
0.83
Dyslipidaemia
157 (22.7)
153 (26.2)
0.17
0.08
Smoking
Pacemaker/ICD
142 (20.5)
204 (29.5)
97 (16.6)
111 (19.0)
0.07
,0.001
0.85
,0.001
39 (5.6)
21 (3.0)
35 (6.0)
23 (3.9)
0.81
0.24
0.90
0.37
Vitamin K antagonist
Antiplatelet
412 (59.6)
231 (33.4)
335 (61.4)
199 (37.3)
0.44
0.81
0.83
0.44
Any antithrombotic
529 (76.6)
458 (78.3)
0.33
0.51
Bleeding risk factors
Previous bleeding
Labile INR
Antithrombotic agents
Heart failure therapy
ACEI/ARB
391 (56.6)
180 (38.1)
,0.001
,0.001
Beta-blocker
345 (49.9)
237 (50.1)
,0.001
,0.001
Digoxin
Diuretic
213 (30.8)
397 (57.5)
128 (27.1)
259 (54.8)
0.001
,0.001
0.001
,0.001
Antiarrhythmic agent
280 (40.5)
290 (49.6)
0.06
,0.001
Calcium channel blocker
CHADS2
40 (5.8)
54 (23.3)
0.11
0.07
198 (28.7)
88 (15.0)
,0.001
,0.001
493 (71.3)
497 (85.0)
,0.001
,0.001
0.07
0.10
Intermediate (score ¼ 1)
High (score ≥2)
CHA2DS2-VASc
Intermediate (score ¼ 1)
High (score ≥2)
HAS-BLED
66 (9.6)
22 (3.8)
625 (90.4)
563 (96.2)
Low (score ¼ 0– 2)
508 (73.5)
413 (70.6)
High (score ≥3)
183 (26.5)
172 (29.4)
ACEI/ARB, angiotensin-converting enzyme inhibitor/angiotensin receptor blocker; AF, atrial fibrillation; CHADS2 (one point each for congestive heart failure, hypertension, age
≥75, and diabetes, and two points for previous stroke or thrombo-embolism); CHA2DS2-VASc (one point for congestive heart failure, hypertension, diabetes, vascular disease,
age 65 –74, and female sex, and two points for previous stroke or thrombo-embolism and age ≥75); HAS-BLED [Hypertension, Abnormal renal and/or liver function,
Stroke, Bleeding history or predisposition, Labile INR, Elderly (.65 years)]; HFPEF, heart failure with preserved ejection fraction; HFREF, heart failure with reduced ejection
fraction; ICD, implantable cardiac defibrillator; INR, international normalized ratio; SD, standard deviation.
Table 4 displays event rates for patients with and without each of
the individual risk factors in patients with AF and HF who were not
receiving a VKA.
Discussion
In this large ‘real world’ cohort of patients with NVAF and HF, our
analyses revealed the following findings. Firstly, AF patients with
HFPEF had a risk factor profile different from that of patients
with HFREF in that they were more likely to be female and hypertensive, but less likely to have prior vascular disease, or be on HF
therapy. Secondly, there were no statistically significant differences
in rates of stroke and stroke/TE between HFPEF and HFREF.
Thirdly, EF does not provide additional value in risk prediction
for stroke/TE or bleeding in NVAF patients with HF. Finally,
among NVAF patients with HF, previous stroke and vascular
299
Ejection fraction in patients with AF and heart failure
Table 2 Event rates (95% confidence interval) per 100 person-years in patients with heart failure and measured ejection
fraction
HFREF (EF <50%)
.......................................................................
Events
Event rate
P*
HFPEF (EF ≥ 50%)
...............................................
Events
Event rate
...............................................................................................................................................................................
Stroke
Stroke/TE
Stroke/TE/death
Bleeding
All-cause death
46
0.67 (0.49–0.89)
0.17
51
0.87 (0.65–1.15)
65
175
0.94 (0.73–1.20)
2.53 (2.17–2.94)
0.11
0.85
68
151
1.16 (0.90–1.47)
2.58 (2.19–3.03)
78
1.13 (0.89–1.41)
0.06
88
1.50 (1.21–1.85)
139
2.01 (1.69–2.38)
0.43
107
1.83 (1.50–2.21)
HFPEF, heart failure with preserved ejection fraction; HFREF, heart failure with reduced ejection fraction; TE, thrombo-embolism.
*P-value for two-sided x2 test using Fisher’s exact test using patients with normal ejection fraction (EF ≥50%) as the reference group.
Table 3 Hazard ratio (95% confidence interval) of
stroke and thrombo-embolism in patients with heart
failure and measured ejection fraction
Univariate
HR (95% CI)
Table 4 Event rates (95% confidence interval) per
100 person-years in patients with heart failure and
measured ejection fraction and not receiving a vitamin
K antagonist
Multivariate
HR (95% CI)
Without risk factor
With risk factor
Hypertension
Age ≥75
1.46 (1.10– 1.91)
1.66 (1.28– 2.11)
1.99 (1.58– 2.48)
1.82 (1.41– 2.31)
Diabetes
1.70 (1.38– 2.07)
1.86 (1.29– 2.58)
1.57 (1.07–2.30)
Previous stroke
Vascular disease
1.58 (1.30– 1.90)
1.51 (1.16– 1.93)
3.92 (2.40– 6.06)
2.02 (1.57– 2.55)
1.15 (0.71– 1.89)
1.49 (1.05– 2.13)
1.06 (0.64–1.74 )
1.43 (0.96–2.13)
Age 65– 74
1.66 (1.28– 2.11)
1.77 (1.21– 2.49)
Ejection fraction ,35%*
0.72 (0.45– 1.15)
0.75 (0.44–1.30)
Female sex
Ejection fraction ,35%
1.55 (1.22– 1.94)
1.95 (1.61– 2.36)
2.08 (1.57– 2.70)
1.13 (0.72– 1.70)
Ejection fraction 35– 49%*
Ejection fraction†
1.14 (0.77– 1.71)
1.04 (0.96– 1.12)
1.27 (0.83–1.93)
1.05 (0.97–1.13)
Ejection fraction ≥50%
1.57 (1.21– 2.00)
1.94 (1.50– 2.46)
................................................................................
................................................................................
Hypertension
1.14 (0.80– 1.63)
0.91 (0.62–1.43)
Age ≥75
1.72 (1.10– 2.70)
1.37 (0.85–2.20)
Diabetes
Previous stroke
1.05 (0.70– 1.57)
2.56 (1.59– 4.14)
0.94 (0.62–1.34)
2.36 (1.45–3.86)
Vascular disease
1.43 (1.01– 2.03)
Age 65–74
Female sex
CI, confidence interval; HR, hazard ratio.
*Hazard ratio calculated with the patients with normal ejection fraction, i.e. EF
≥50%, as the reference category
†
Ejection fraction as a continuous variable with the hazard ratio representing the
risk associated with a 1% drop in ejection fraction.
disease were the strongest independent predictors of stroke
and TE.
Our observations suggest that HFPEF and HFREF in the setting
of NVAF have broadly similar risk factor profiles to HF in patients
without NVAF.17220 Patients with HFPEF had higher scores in
existing risk stratification systems for stroke/TE and bleeding
than patients with HFREF, but there were no differences in the
rates of oral anticoagulation across all categories of EF.
Few studies have considered the impact of EF on progression or
pattern of NVAF in a ‘real world’ population setting, although small
studies have suggested the predictive value of EF for NVAF in particular patient groups.29 A recent study of patients with HF found
that EF had no additional predictive value for the development of
persistent NVAF.30
Previous studies have highlighted the considerable burden of
HFPEF among HF patients, and several studies show that HFPEF
carries similar mortality and morbidity to HFREF.22,23,31 An increasingly important patient group appears to be those patients
with HF with recovered EF, who are reported to have milder
symptoms and fewer HF hospitalizations than both HFREF and
HFPEF.32 No study to date has considered this patient population
with respect to NVAF. Indeed, EF does not remain constant over
time, and future research is needed to assess the effect of change in
EF over time on adverse outcomes in patients with NVAF and HF.
Although there were differences between stroke/TE outcomes
by EF category in our study (Supplementary material online,
Table S3), Cox regression models suggested that the addition of
EF will not improve stroke/TE risk prediction and, therefore,
further calculations using the NRI and IDI indices were unwarranted. We have previously reported that HF is independently associated with stroke and TE in our NVAF cohort,7 although other
studies have been unconvincing.33234 However, although previous
studies support moderate–severe LV impairment as an independent risk predictor of outcomes in NVAF patients,25,26,28 – 35 EF was
not a risk predictor of stroke/TE or bleeding in the present study
population. Nonetheless, a previous analysis has shown that
reduced EF as a continuous variable was an independent predictor
300
of all-cause mortality in NVAF patients.36 A recent study showed
that AF and EF predicted mortality in HF patients receiving
cardiac resynchronization therapy.37 Since HFPEF and HFREF are
becoming a focus of both pathophysiological and echocardiographic studies of HF,38,39 future studies must include patients with
NVAF in order to better understand these interlinked disease
processes.
Finally, among our NVAF patients with HF, previous stroke and
vascular disease were the strongest independent predictors of outcomes. Age, which was a strong predictor of stroke/TE in our previous analysis of this cohort, was not significantly associated with
outcomes in NVAF patients with HF.7 Nonetheless, AF patients
with HFREF were more likely to be on HF medications than
patients with HFPEF, and this may at least partially explain the
fact that reduced EF did not predict stroke/TE or bleeding in
NVAF patients with HF. Although atrial structural remodelling is increasingly recognized in the development and progression of
NVAF,40 the role of EF in pathogenesis of NVAF is still unclear.
For example, maintenance of sinus rhythm in patients with NVAF
can improve EF.41 Future clinical trials and prospective epidemiological studies involving NVAF patients should be statistically
powered to consider subgroups by risk factor, including HF.
Study limitations
The limitations of this ‘real world’ registry have been previously
reported.6 Briefly, there are inherent limitations of diagnostic
coding and case ascertainment, particularly if an enrolled patient
moved away from the area or had an outcome event in another
area. Despite adjustment for several risk factors, the nonrandomized design does not exclude the possibility of residual confounding factors. Oral anticoagulation therapy was determined at
baseline, and not adjusted for changes in treatment status during
follow-up; however, this limitation did not have an effect on the
results in a similar Danish cohort study.36 Despite inclusion of .
1200 patients with NVAF, analyses in specific subgroups had
reduced statistical power. Of 3630 patients with HF, only 1276
had echocardiographic assessment of EF, either because echocardiography was not performed or because EF could not be accurately measured from available data, which is a major limitation of
this analysis. Supplementary material online, Table S4, shows the
characteristics of patients with and without measured EF, and
patients without measured EF were older and, even after age adjustment, they were more likely to have hypertension and less
likely to have previous vascular disease (including stroke), previous
bleeding, and smoking history. EF assessment was only undertaken
at baseline and therefore the effect of changes in EF cannot be analysed in this data set. In addition, no data regarding duration of AF
or burden of AF were available. New data suggest that duration of
HF and/or AF36,37 may add important information to risk stratification, and future cohorts must include these data to assess these
potential associations. Data regarding cause of death were not
available for analysis and, therefore, some deaths could be attributable to stroke, which would influence the study conclusions
regarding stroke outcomes. Finally, we have refrained from speculations on the possible pathophysiological explanations for our
observations, given the multifactorial and complex pathogenesis
of AF influencing stroke, HFPEF, and HFREF.
A. Banerjee et al.
Conclusions
In this large ‘real world’ cohort of NVAF patients with HF, rates of
stroke, stroke/TE, death, and bleeding are similar in HFPEF and
HFREF. Only previous stroke and vascular disease independently
increased the risk of stroke/TE in these patients. Thus, EF may
not provide additional value to stroke risk prediction in patients
with NVAF and HF, and the increased risk of adverse outcomes
associated with clinical HF in patients with NVAF was not
significantly influenced by EF measurement.
Supplementary material
Supplementary material is available at European Journal of Heart
Failure online.
Conflicts of interest: J.B.O has received travel grants from
AstraZeneca and Boehringer Ingelheim. S.T. has received funding
for research from Sanofi Aventis. D.A.L has received funding for
research, conference travel, and educational symposia from
Bayer Healthcare and Boehringer Ingelheim, and is a member of
the ACCP9 Writing Committee. G.Y.H.L. has served as a consultant for Bayer, Astellas, Merck, AstraZeneca, Sanofi Aventis, Biotronik, BMS/Pfizer, and Boehringher Ingelheim, and has been on the
speakers bureau for Bayer, BMS/Pfizer, Boehringher Ingelheim,
and Sanofi Aventis. L.F. has served as a consultant for Bayer,
Medtronic, and Sanofi Aventis, and has received funding for conference travel and educational symposia from Boehringher Ingelheim,
Bayer, Medtronic, and Sanofi Aventis. A.B. and B.L. report no
conflicts of interest.
Authors’ contributions: L.F., B.L., and S.T. made the primary
contribution to data collection. A.B., J.B.O., G.Y.H.L., D.A.L., and
L.F. contributed to the study conception and design. A.B. performed the analyses. All authors contributed to interpretation of
results, revising the manuscript critically for important intellectual
content, and all approved the final manuscript.
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