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Effects of Peripheral Arterial Disease on Outcomes in Advanced
Chronic Systolic Heart Failure: A Propensity-Matched Study
Mustafa I. Ahmed, MD,a Wilbert S. Aronow, MD,b Michael H. Criqui, MD, MPH,c
Inmaculada Aban, PhD,a Thomas E. Love, PhD,d Eric J. Eichhorn, MD,e Ali Ahmed, MD,
MPHa,f,*
a
University of Alabama at Birmingham, Birmingham, AL
b
New York Medical College, Valhalla, New York;
c
University of California, San Diego, La Jolla, CA
d
Case Western Reserve University, Cleveland, OH
e
Cardiopulmonary Research Science and Technology Institute, Dallas,
las, TX
f
Veterans Affairs Medical Center, Birmingham, AL
***
*Corresponding
onding author: Ali Ahmed, MD, MPH, University of Alabama at Birmingham,
Birmingham
m
1530 3rd Ave
A South, CH–19, Ste–219, Birmingham AL 35294–2041; Telephone: 1–205
1–205–
5
934–9632; Fax: 1–205–975–7099; Email: [email protected]
Running head: Peripheral arterial disease outcomes in heart failure
Word Count: 2453
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Page 2 of 24
Background– The effect of peripheral arterial disease (PAD) on outcomes in patients with
chronic heart failure (HF) has not been examined in propensity-matched studies.
Methods and Results–Of the 2689 patients with advanced chronic systolic HF in the BetaBlocker Evaluation of Survival Trial, 441 had a history of PAD. Propensity scores for a
history of PAD, calculated for each patient using a multivariable logistic regression model,
were used to assemble a matched cohort of 299 and 1015 patients respectively with and
without PAD who were well-balanced on 65 measured baseline characteristics. Cox
regression models were used to estimate hazard ratios (HR) and 95% confidence intervals
(CI) for associations between PAD and outcomes during 4.1 years of follow-up.
Patients
p Patie
ieent
n s had
a mean age of 63 (±11) years, 19% were women and 19% were African
Americans.
All-cause
ican A
meri
me
riica
cans
ns. Al
All
llmortality occurred
in 43% and 33% of patients with and without a history of PAD,
o
respectively
e (HR when PAD was compared with no-PAD, 1.40; 95% CI, 1.14–1.72;
ely
p=0.001). All-cause hospitalization occurred in 78% and 63% off patients with and witho
without
o
PAD, respectively
1.16–1.58;
p
pectively
(HR when PAD was compared with no-PAD, 1.36; 95% CI, 1.16–1.5
5
p<0.0001). PAD-associated HRs for cardiovascular mortality, HF mortality and HF
hospitalization were respectively 1.31 (95% CI, 1.04–1.63; p=0.019), 1.40 (95% CI, 0.97–
2.02; p=0.076) and 1.05 (95% CI, 0.86–1.29; p=0.635).
Conclusions– In a well-balanced propensity-matched population of chronic systolic HF
patients, a history of PAD was independently associated with increased mortality and
hospitalization.
Key Words: heart failure, peripheral artery disease, mortality, hospitalization
Word Count = 245
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Page 3 of 24
Peripheral arterial disease (PAD) is a manifestation of systemic atherosclerosis and
predicts adverse cardiovascular outcomes.1-7 In a propensity-matched cohort of communitydwelling older adults, we have previously demonstrated that the presence of PAD had an
independent association with increased all-cause and cardiovascular mortality.8 However, the
extent to which PAD may be independently associated with outcomes in heart failure (HF)
patients has not been previously examined in a propensity-matched study. In the current
study, we used a public-use copy of the Beta–Blocker Evaluation of Survival Trial (BEST)9
dataset to determine the association between a baseline history of PAD and long-term
outcomes in a propensity-matched population of advanced chronic systolic
sys
y tolic HF ppatients
atient
ntss iin
nt
which those with and without PAD were well-balanced in all measured
ured ba
bbaseline
seli
se
line
li
ne
characteristics.
stics.
Methodss
Study Data
ta and Patients
h BEST was a multicenter randomized placebo-controlled clinical trial of
he
The
bucindolol, a beta-blocker, in advanced systolic HF, methods and results of which have been
previously published.9 Briefly, 2708 patients with advanced systolic HF were enrolled from
90 different sites across the United States and Canada between May 1995 and December
1998. At baseline, patients had a mean duration of 49 months of HF and had a mean left
ventricular ejection fraction of 23%. All patients had New York Heart Association class IIIIV symptoms and over 90% of all patients were receiving angiotensin-converting enzyme
(ACE) inhibitors, diuretics, and digitalis.
Study Exposure and Outcomes
The public-use copy of the BEST dataset included 2707 patients (one patient did not
consent to be included in the public-use copy). After excluding 18 patients without data on
smoking pack-years, a total of 2689 patients were included in the current analysis. Overall,
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Page 4 of 24
441 (16%) patients had a history of PAD at baseline. Data on a history of PAD were
collected by study investigators and were not centrally adjudicated. Data on sociodemographic, clinical, sub-clinical and laboratory variables were collected at baseline. BEST
participants were enrolled during a 3-year period and were followed up for a minimum of 18
months and a maximum of 4.5 years.9 Primary outcomes for the current analysis were allcause mortality and all-cause hospitalization during 4.1 years of follow-up (mean, 2 years;
range, 10 days to 4.14 years). Secondary outcomes were mortality due to cardiovascular
causes, heart failure and sudden cardiac death and hospitalizations due to HF.
Assembly of a Balanced Cohort of Patients with and without PAD
AD
tics bbetween
ettwe
ween
en ppatients
atie
at
ient
ie
ntss with
nt
As there were significant imbalances in baseline characteristics
ut PAD before matching (Table 1), we used propensity score matching to asse
e
and without
assemble
of patients whereby those with and without PAD would be well-balanced on alll
a cohort of
measured baseline covariates.10-12 Propensity score for PAD for a patient would be that
patient’s probability
p
of having PAD given his or her measured baseline characteristics.
Propensity scores for PAD were estimated for each of the 2689 patients using a nonparsimonious multivariable logistic regression model. In the model, PAD was the dependent
variable and 65 baseline characteristics displayed in Figure 1 were used as covariates in the
model. A number of clinically relevant interactions such as age by smoking, coronary artery
disease (CAD) by smoking etc were also were included in initial models but were excluded
from the final model due to lack of statistical significance. We used a greedy matching
protocol, described in detail elsewhere, to match one patient with PAD with up to 4 patients
without PAD. Using this approach, we were able to match 299 patients with PAD with 1015
patients without PAD.13-17
Because propensity score models are sample-specific adjusters and are not intended to
be used for out-of-sample prediction or estimation of coefficients, measures of fitness and
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Page 5 of 24
discrimination are not important for the assessment of the model's effectiveness. As such,
measures of fitness and discrimination are irrelevant for the assessment of the model's
effectiveness.13-17 We assessed propensity score models by estimating pre- and post-match
absolute standardized differences for measured baseline covariates between patients with and
without PAD. Absolute standardized differences directly quantify bias in the means (or
proportions) of covariates across the groups. They are expressed as a percentage of the
pooled standard deviation and are presented in Love plots.13-17 An absolute standardized
difference of 0% indicates no residual bias and differences <10% are considered
inconsequential.
Statistical Analysis
a
aplan-Meier
Kaplan-Meier
and Cox regression analyses were used to determine associations
durin 4.1 years
ars of follow-up.
follow- . Log-minus-log
Lo minus-lo scale survival
surviva
between PAD and outcomes during
plots weree used to check proportional hazards assumptions. Formal sensitivity analyses were
i
conductedd to quantify the degree off a hidden bias that would need to be present to invali
invalidate
our conclusions based on significant association between PAD and primary outcomes among
matched patients.18 Subgroup analyses were conducted to determine the homogeneity of
association between a history of PAD and all-cause mortality. All statistical tests were twotailed with a p-value <0.05 considered significant. All data analyses were performed using
SPSS for Windows version 15 (SPSS Inc., Chicago, IL).19
Results
Baseline Characteristics
Matched patients had a mean age of 63 (±11) years, 19% were women and 19% were
African Americans. Significant imbalances in several baseline characteristics before
matching and the balances achieved after matching are displayed in Table 1 and Figure 1.
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Page 6 of 24
After matching, standardized differences for all measured covariates were <10% (most were
<5%), suggesting substantial covariate balance across the groups (Figure 1).
PAD and Mortality
All-cause mortality occurred in 43% and 33% of patients with and without PAD
respectively (hazard ratio, 1.40; 95% confidence interval, 1.14–1.72; p=0.001; Figure 2a and
Table 2). In the absence of hidden bias, a sign-score test for matched data with censoring
provides relatively strong evidence (p=0.035) that patients without PAD clearly outlived
those with PAD. A hidden covariate that is a near-perfect predictor of mortality may
potentially explain away the association between PAD and all-causee mortality
would
y if thatt wo
w
increase the odds of PAD by only 1. 3% No heterogeneity of association
PAD
ation
n bbetween
ettwe
ween
en P
AD aand
all-cause mortality
Associations
m
was detected in any of the subgroups of patients (Figure 3). Associat
t
of PAD with
w mortality due to cardiovascular causes, HF, and sudden cardiac death are
displayed in Table 2.
PAD and Hospitalization
All-cause hospitalization occurred in 78% and 63% patients with and without PAD
respectively (HR, 1.36; 95% CI, 1.16–1.58; p<0.0001; Figure 2b and Table 2). In the
absence of hidden bias, a sign-score test for matched data with censoring provides strong
evidence (p=0.001) that patients without PAD clearly had fewer hospitalizations due to all
causes than those with PAD. A hidden covariate that is a near-perfect predictor of
hospitalization, could potentially explain away our observed association between PAD and
all-cause hospitalization, should it increase the odds of PAD by 9.4%. Other pre- and postmatch associations of PAD with hospitalizations are displayed in Table 2.
Discussion
Findings from the current study demonstrate that the prevalence and the burden of
CAD was high among systolic HF patients with a history of PAD, and a history of PAD was
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Page 7 of 24
associated with increased risk of mortality and hospitalization in these patients. Significant
strong bivariate associations of PAD with major natural history endpoints suggest that the
presence of PAD may be used to identify advanced systolic HF patients who are at an
increased risk for poor outcomes. The significant associations of PAD with all-cause
mortality and all-cause hospitalization after propensity score matching suggest that the effect
of PAD was independent of the 65 measured baseline characteristics that included major
cardiovascular risk factors. These findings are important as PAD is common in patients with
advanced systolic HF.20
Strong bivariate associations between PAD and outcomes aree likelyy due to
ell
llit
itus
it
us, th
thee pr
pprevalence
eval
ev
al
confounding by covariates such as age, smoking, CAD, and diabetess me
mellitus,
of which was
w higher in those with PAD than in those without PAD. However, associatio
associations
o
P
between PAD
and all-cause mortality and all-cause hospitalization persisted despite riskk
adjustments
n using multiple approaches including propensity matching. This suggests an
nts
intrinsic association
a
between PAD and outcomes in HF that was independent of the measured
meaa
covariates in our study. However, we are not aware of any mechanistic pathway of a direct
and intrinsic effect of PAD on death or hospitalization. One possible explanation is that
atherosclerotic diseases in PAD patients are of a greater severity and more advanced or
widespread.1, 21, 22 This is evident from the higher prevalence and burden of CAD and other
morbidities in pre-match patients with PAD. While these and other measured confounders
were well-balanced after matching, it is possible that atherosclerosis progressed at a faster
rate during follow-up in patients with PAD than in those without PAD. Findings from our
subgroup analysis also suggest a significant PAD-associated increase in mortality among
those with CAD. It is also possible that HF patients with clinical PAD may restrict their
physical activity to avoid claudication pain, potentially leading to deconditioning and
deterioration of cardiovascular fitness and poor outcomes.23
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Page 8 of 24
Findings from population-based studies suggest that age, smoking, systolic blood
pressure, and serum glucose are significantly associated with large vessel PAD.24 Before
matching patients with PAD in our study were older, with a significantly higher prevalence of
current smokers and higher pack-years of smoking, higher systolic blood pressure and higher
serum glucose, all indicating the presence of large vessel PAD. Large vessel PAD has been
shown to be independently associated with increased mortality.4 Smoking is one of the
strongest predictors for progression of large vessel PAD.6, 25 Although our matched patients
were balanced on pack-years of smoking and prevalence of current smokers, it is possible
d in the ppresence
resencee of
that the deleterious effects of continued smoking was more profound
PAD.26, 27
An
n examination of the associations between PAD and cause-specific mortalities
u
urther
patiee
provide further
insight into how PAD may affect mortality in advanced systolic HF patients.
Sudden cardiac
a
ardiac
death was a major mode of death in our study, accounting for over half of
o all
deaths. However,
o
owever,
PAD apparently was not associated with fatal cardiac arrhythmias
underlying sudden deaths. This lack of a statistically significant association between PAD
and sudden death suggests that the effect of PAD in HF may be predominantly non-sudden in
nature. PAD, however, had significant associations with cardiovascular death, and its
association with HF death was of borderline significance. PAD has also been shown to be
associated with increased risk of fatal acute myocardial infarction (AMI).5 However, only
<5% of all deaths in our study were due to AMI, which may explain the non-significant
association between PAD and AMI death. PAD-associated increase in the risk of other
cardiovascular mortality highlights its impact on vascular deaths such as those due to stroke.
Unfortunately, we had limited data on cause-specific hospitalizations with which to gain
insights into the PAD-associated increase in all-cause hospitalization in advanced systolic HF
patients. Extrapolating from cause-specific mortality data, it may be suggested that PAD-
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Page 9 of 24
associated increase in hospitalization was primarily due to cardiovascular causes. However,
recent reports have suggested an association between PAD and non-cardiovascular
morbidities.28, 29
To the best of our knowledge this is the first report of an association of PAD with
mortality and hospitalization in a propensity matched population of advanced chronic systolic
HF patients. Our findings of increased mortality and morbidity in chronic HF patients with
PAD have important clinical and public health implications. PAD may be a manifestation of
more severe and/or advanced systemic atherosclerosis, and thus its presence can be used to
identify HF patients with poorer prognosis. This may be useful as ann inexpensive
inexpe
p nsive clinical
clin
in
nic
ica tool
fte
t n be
be
in developing nations to risk stratify HF patients. Importantly PAD mayy of
often
m
matic
and hence under-diagnosed. It is relatively easy, however, to accurately
asymptomatic
t presence and severity PAD by measures such as the ankle-brachial pressuree
diagnose the
h
index. Ourr findings of independent associations of PAD with poor outcomes highlight th
the
c of prevention and timely detection of PAD, and aggressive treatment of
ce
importance
atherosclerotic risk factors in HF patients.
Management of PAD in HF is similar to that in the general population with a few
exceptions. Current recommendations for management of PAD patients are mainly based on
reduction of systemic cardiovascular risk, which include smoking cessation, exercise,
treatment of hypertension and diabetes, and the use of antiplatelet agents and statins.30
Walking and physical training have been shown to improve claudication distance in patients
with PAD.31, 32 Cilostazol, a phosphodiesterase-3 inhibitor approved for use in symptomatic
PAD, is contraindicated in HF (a black-box warning). Pentoxifylline, a phosphodiesterase-4
inhibitor, also approved for use in symptomatic PAD, may be safe in HF.33 However, its
efficacy in improving walking distance is very limited.32 Statins and ACE inhibitors have
shown some efficacy for walking distance, however there is no labeled indication for these
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Page 10 of 24
drugs.34-37 Despite concerns that beta-blockers may cause or worsen claudication in patients
with PAD these drugs are not contraindicated in these patients.30 We observed that the effect
of PAD on mortality appeared to be heterogeneous between patients receiving and not
receiving bucindolol, a beta-blocker. However, the lack of a significant interaction (p=0.140:
Figure 3) precludes any inference of heterogeneity. It is possible that the non-significant
interaction may be due to inadequate power. Considering the potential clinical importance of
these findings, future studies with adequate sample sizes are needed to examine the
heterogeneity of the effect of PAD on outcomes in HF patients receiving and not receiving
beta-blockers.
ed. Findings
Fin
i di
ding
ngss off this
thi
thi
hiss sstudy
Several limitations of the current study must be acknowledged.
a
systolic HF patients enrolled in
n a clinical trial may nott be generalizab
b to
based on advanced
generalizable
w mild-moderate systolic HF or diastolic HF. Data on ankle-brachial pressuree
patients with
r not available and diagnosis of PAD was based on patient past medical histor
re
r as
index were
history
b study investigators. This may have misclassified some PAD patients and
assessed by
underestimated the true prevalence of PAD. Data were not available on the extent and
severity of PAD. It is possible that patients without PAD at baseline may have developed
PAD during follow-up, thus resulting in regression dilution bias, which is another potential
source of underestimation of the true association between PAD and outcomes38. Finally, the
findings of our sensitivity analyses suggest that our conclusions were rather sensitive to an
unmeasured confounder. However, sensitivity analysis cannot determine if an unmeasured
confounder exists or not. To be a confounder, an unmeasured covariate, in addition to being
associated with PAD, would also need to have a near-perfect association with outcomes,
without any strong association with any of the 65 measured baseline covariates used in our
study, a possibility which seems highly unlikely.
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Page 11 of 24
In conclusion, PAD in advanced chronic systolic HF patients was associated with
increased risk of death and hospitalization, which was independent of 65 baseline
characteristics including major cardiovascular risk factors. PAD-associated poor outcomes in
HF patients are likely non-sudden in nature and likely to be predominantly atherosclerotic in
origin. PAD may be useful as an inexpensive screening tool to risk stratify HF patients.
Acknowledgement: “The Beta–Blocker Evaluation of Survival Trial (BEST) is conducted
and supported by the NHLBI in collaboration with the BEST Study Investigators. This
Manuscript was prepared using a limited access dataset obtained from
and
om the NHLBI an
nd ddoes
not necessarily reflect the opinions or views of the BEST or the NHLBI.”
LBI.
I”
Funding/Support:
Dr. Ahmed is supported by the National Institutes of Health throughh
S
Support:
grants (R01-HL085561
0
01-HL085561
and R01-HL097047) from the National Heart, Lung, and Blood
Institute and
a a generous gift from Ms. Jean B. Morris of Birmingham, Alabama
Conflict of Interest Disclosures: None
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Page 12 of 24
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of Cardiovascular and Pulmonary Rehabilitation; National Heart, Lung, and Blood
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Figure Legends
Figure 1. Love plot displaying absolute standardized differences in baseline covariates
between patients with and without peripheral arterial disease, before and after propensity
score matching (ACE=angiotensin-converting enzyme; ARB=angiotensin receptor blocker)
Figure 2. Kaplan-Meier plots for (a) all-cause mortality and (b) all-cause hospitalization
by a history of peripheral arterial disease (PAD)
Figure 3. Association between peripheral arterial disease (PAD) and
all-cause
mortality
nd al
lll ca
caus
usee mo
mort
rttal
alit
ity in
it
subgroupss of propensity score-matched patients in the BEST trial (CI=confidence interv
interval)
v
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Table 1 Baseline patient characteristics by history of peripheral artery disease (PAD) before and after propensity matching
Before propensity matching
No history
of PAD
(n=2248)
60 (r13)
History
of PAD
(n=441)
64 (r10)
Female
497 (22)
African American
After propensity matching
<0.0001
No history
of PAD
(n=1015)
63 (r11)
History
of PAD
(n=299)
64 (r10)
86 (20)
0.224
196 (19)
58 (19)
0.973
530 (24)
89 (20)
0.121
204 (20)
54 (18)
0.435
Duration of heart failure, months
49 (r48)
53 (r49)
0.087
51 (r51)
51 (r49)
0.655
Left ventricular ejection fraction, %
23 (±7)
24 (±7)
0.118
23 (±7)
24 (±7)
0.629
Right ventricular ejection fraction, %
35 (r12)
35 (r11)
0.215
35 (±12.0)
35 (±11)
0.920
New York Heart Association class III
2077 (92)
386 (87)
0.001
914 (90)
272 (91)
0.637
Coronary artery disease
1231 (55)
353 (80)
<0.0001
739 (73)
222 (74)
4)
0.622
Angina pectoris
1107 (49)
284 (64)
<0.0001
616
61
6 (6
(61)
1)
181
18
1 (6
(61))
(61)
0.962
Coronary artery stenosis >70%
946 (42)
289 (66)
<0.0001
584 (5
(58)
8
8)
180
18
0 (6
((60)
0)
0.412
Stress perfusion
n test positive
426 (19)
114 (26)
0.001
249 (25)
73 (24)
0.967
Left bundle branch
a
anch
block
589 (26)
85 (19)
0.002
222 (22)
64 (21)
0.863
Coronary artery
y bypass graft surgery
585 (26)
192 (44)
<0.0001
369 (36)
124 (42)
0.108
Percutaneous coronary
c
intervention
329 (15)
89 (20)
0.003
186 (18)
50 (17)
0.526
n (%) or mean (rSD)
Age, years
P value
P value
0.122
Coronary artery disease-related history
Current smoker
e
er
377 (17)
94 (21)
0.022
203 (20)
56 (19)
0.627
Smoking , pack-years
k
k-years
20 (r17)
29 (r18)
<0.0001
25 (r17)
26 (r18)
0.921
1282 (57)
301 (68)
<0.0001
635 (63)
191 (64)
0.678
Other medical history
t
tory
Hypertension
Diabetes mellitus
723 (32)
237 (54)
<0.0001
442 (44)
142 (48)
0.228
Hyperlipidemia
909 (40)
255 (58)
<0.0001
524 (52)
167 (56)
0.198
Atrial fibrillation
542 (24)
107 (24)
0.945
250 (25)
67 (22)
0.430
Medications
Angiotensin-converting enzyme inhibitors
2175 (97)
416 (94)
0.013
983 (97)
290 (97)
0.901
Digitalis
2073 (92)
403 (91)
0.554
914 (90)
275 (92)
0.319
Diuretics
2084 (93)
422 (96)
0.023
957 (94)
284(95)
0.644
Vasodilators
925 (41)
249 (57)
<0.0001
519 (51)
153 (51)
0.991
Anti-arrhythmic drugs
Anti-coagulants
66 (3)
8 (2)
0.188
23 (2)
6 (2)
0.789
1274 (57)
283 (64)
0.004
631 (62)
184 (62)
0.844
37 (±8.5)
35 (±7.5)
<0.0001
36 (±7.6)
35 (±8.0)
0.700
Clinical findings
Body mass index, kg/m2
Heart rate, beats per minute
82 (±13)
81 (±13)
0.285
81 (±13)
81 (±13)
0.774
Systolic blood pressure, mm Hg
117 (±18)
120 (±18)
<0.0001
119 (±18)
119 (±18)
0.988
Diastolic blood pressure, mm Hg
71 (±11)
70 (±11)
0.002
70 (±11)
70 (±11)
0.415
Jugular venous distension
1035 (46)
193 (44)
0.380
452 (45)
129 (43)
0.671
S3 gallop
986 (44)
181 (41)
0.275
428 (42)
121 (41)
0.601
Pulmonary râles
282 (13)
76 (17)
0.008
152 (15)
43 (14)
0.800
Lower extremity edema
590 (26)
136 (31)
0.047
287 (28)
83 (28)
0.861
Pulmonary edema by chest x-ray
238 (11)
68 (15)
0.003
125 (12)
39 (13)
0.738
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Table 1 Baseline patient characteristics by history of peripheral artery disease (PAD) before and after propensity matching
Before propensity matching
No history
of PAD
(n=2248)
History
of PAD
(n=441)
Hemoglobin, g/dl
14.0 (±1.6)
White blood cells, 103/μL
7.4 (±2.2)
Creatinine, mg/dl
Glucose, mg/dl
n (%) or mean (rSD)
After propensity matching
P value
No history
of PAD
(n=1015)
History
of PAD
(n=299)
13.8 (±1.7)
0.050
13.9 (r1.7)
13.8 (r1.7)
0.885
7.8 (±2.1)
0.003
7.6 (r2.3)
7.7 (r2.1)
0.661
1.2 (±0.4)
1.4 (±0.5)
<0.0001
1.3 (r0.4)
1.3 (r0.4)
0.239
129 (±69)
162 (±94)
<0.0001
144 (r79)
151 (r86)
0.186
P value
Laboratory findings
Sodium, mEq/L
139 (r3)
138 (r4)
0.001
139 (r3)
138 (r4)
0.626
Potassium, mEq/L
4.3 (±0.5)
4.4 (±0.5)
0.052
4.3 (r0.5)
4.4 (r0.5)
0.338
Magnesium, mg/dl
1.7 (±0.3)
1.8 (±0.3)
0.021
1.8 (r0.3)
1.8 (r0.3)
0.135
Norepinephrine, pg/ml
510 (r308)
537 (r296)
0.101
525 (±327)
520 (±270)
0.837
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Table 2. Peripheral artery disease (PAD) and outcomes in the matched cohort
% events
(total number of event / total duration of
follow-up in years)
Outcomes
Hazard ratio
(95% confidence
interval)
P value
No history of PAD
(n=1015)
History of PAD
(n=299)
All-cause
33%
(331/2020)
44%
(130/568)
1.40 (1.14–1.72)
0.001
Cardiovascular
28%
(287 / 2020)
35%
(105 / 568)
1.31 (1.04–1.63)
0.019
Heart failure
10%
(100 / 2020)
13%
(39 / 568)
1.40 (0.97–2.02)
0.076
Sudden cardiac death
15%
(155 / 2020)
16%
(48 / 568)
1.10 (0.80–1.53)
0.552
Myocardial infarction
1%
(11 / 2020)
2%
(5 / 568)
1.62
1.62 (0.56–4.65)
(0.
0 56
56–4
–4.665)
0.374
Other cardiovascular
2%
(21
( / 2020))
4%
(13
( / 568))
2.20
2 200 (1.10–4.39)
(1 10
10–4
–4 39)
0.026
Non-cardiovascular
u
ular
3%
(34 / 2020)
6%
(17 / 568)
1.78 (0.99–3.20)
0.076
Unknown
1%
(10 / 2020)
3%
(8 / 568)
2.89 (1.14–7.32)
0.025
63%
(640 / 1186)
39%
(400 / 1563)
75%
(223 / 294)
41%
(121 / 444)
1.36 (1.16–1.58)
<0.0001
1.05 (0.86–1.29)
(
)
0.635
Mortality
Hospitalization
All-cause
Heart failure
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Effects of Peripheral Arterial Disease on Outcomes in Advanced Chronic Systolic Heart
Failure: A Propensity-Matched Study
Mustafa I. Ahmed, Wilbert S. Aronow, Michael H. Criqui, Inmaculada Aban, Thomas E. Love,
Eric J. Eichhorn and Ali Ahmed
Circ Heart Fail. published online October 27, 2009;
Circulation: Heart Failure is published by the American Heart Association, 7272 Greenville Avenue, Dallas, TX
75231
Copyright © 2009 American Heart Association, Inc. All rights reserved.
Print ISSN: 1941-3289. Online ISSN: 1941-3297
The online version of this article, along with updated information and services, is located on the
World Wide Web at:
http://circheartfailure.ahajournals.org/content/early/2009/10/28/CIRCHEARTFAILURE.109.866558
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