International Journal of General Medicine
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ORIGINAL RESEARCH
Open Access Full Text Article
Peak oxygen uptake and left ventricular ejection
fraction, but not depressive symptoms,
are associated with cognitive impairment
in patients with chronic heart failure
Gerrit Steinberg 1,2*
Nicole Lossnitzer 2*
Dieter Schellberg 2
Thomas Mueller-Tasch 2
Carsten Krueger 3
Markus Haass 4
Karl Heinz Ladwig 5
Wolfgang Herzog 2
Jana Juenger 2
1
University Hospital of Psychiatry,
University of Bern, Bern, Switzerland;
2
Department of Psychosomatic
and General Internal Medicine,
Medical Hospital, University of
Heidelberg, Heidelberg, 3Department
of Cardiology, Josefs Hospital,
Heidelberg, 4Department of
Cardiology, Theresien Hospital,
Mannheim, 5Institute of Epidemiology,
German Research Center for
Environmental Health, Munich,
Germany
*both authors contributed equally
to this paper
Background: The aim of the present study was to assess cognitive impairment in patients
with chronic heart failure (CHF) and its associations with depressive symptoms and somatic
indicators of illness severity, which is a matter of controversy.
Methods and results: Fifty-five patients with CHF (mean age 55.3 ± 7.8 years; 80% male;
New York Heart Association functional class I–III) underwent assessment with an expanded
neuropsychological test battery (eg, memory, complex attention, mental flexibility, psychomotor speed) to evaluate objective and subjective cognitive impairment. Depressive symptoms
were assessed using the Structured Clinical Interview for Diagnostic and Statistical Manual
of Mental Disorders, Fourth Edition (SCID) and a self-report inventory (Hospital Anxiety
and Depression Scale [HADS]). A comprehensive clinical dataset, including left ventricular
ejection fraction, peak oxygen uptake, and a 6-minute walk test, was obtained for all patients.
Neuropsychological functioning revealed impairment in 56% of patients in at least one measure
of our neuropsychological test battery. However, the Mini Mental State Examination (MMSE)
could only detect cognitive impairment in 1.8% of all patients, 24% had HADS scores indicating
depressive symptoms, and 11.1% met SCID criteria for a depressive disorder. No significant
association was found between depressive symptoms and cognitive impairment. Left ventricular
ejection fraction was related to subjective cognitive impairment, and peak oxygen uptake was
related to objective cognitive impairment.
Conclusion: Cognitive functioning was substantially reduced in patients with CHF and should
therefore be diagnosed and treated in routine clinical practice. Caution is advised when the
MMSE is used to identify cognitive impairment in patients with CHF.
Keywords: chronic heart failure, cognitive impairment, neuropsychological testing, depressive
symptoms, peak oxygen uptake, quality of life
Introduction
Correspondence: Jana Juenger
Department of Psychosomatic
and General Internal Medicine, Medical
Hospital, University of Heidelberg,
Im Neuenheimer Feld 410, 69120
Heidelberg, Germany
Tel +49 62 2156 8660
Fax +49 62 2156 1341
Email jana.juenger@med.uni-heidelberg.de
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http://dx.doi.org/10.2147/IJGM.S23841
Chronic heart failure (CHF) is a frequent complication of heart disease, and is one
of the main causes of hospitalization, morbidity, and mortality in Western society.1
Clinically, significant depression is present in at least one in five patients with heart
failure.2 Depression has high rates in both inpatient and outpatient settings, and
predicts mortality.3,4 Quality of life is often also impaired in patients with CHF.5,6
A frequently neglected aspect of the clinical picture in patients with CHF is their cognitive functioning.7,8 Not only does cognitive impairment interfere with the patient’s
performance of everyday activities, but also with the ability to adhere to a complex
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which permits unrestricted noncommercial use, provided the original work is properly cited.
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Steinberg et al
medication regimen and dietary therapies. Recent findings in
patients with CHF have suggested structural brain injury in
areas involved in cognitive, language, pain, and mood function.9
Although several reports10,11 indicate that a considerable
number of patients with CHF (20%–80%, depending on age)
display deficits in cognitive abilities, the determinants and
mechanisms of these deficits are not clear due to the paucity
of systematic investigations.12,13 Until now, most of the relevant studies have only included small or geriatric samples,
or focused on patients with end-stage heart failure in
New York Heart Association (NYHA) functional class IV.8,14
Furthermore, the findings remain controversial.8,15
Some of the controversies in this field pertain to a lack of
evidence as to the pathophysiology of cognitive impairment in
CHF. The current hypotheses for cognitive impairment in heart
failure include structural and functional changes in the brain
related to vascular events due to emboli, cerebral hypoperfusion,
and impaired cerebral vascular reactivity.16–18 Several groups,
including Woo et al, have reported that patients with heart
failure have significantly less gray matter volume than healthy
subjects in specific regions of the brain.19 Moreover, Siachos
et al reported that the prevalence of silent strokes in patients
with heart failure was 34%,20 and other investigators found
functional changes in patients showing significant reductions
in regional blood flow compared with healthy subjects.21
However, the associations of cognitive functioning with
cardiac output found in the literature are inconsistent. Whereas
several investigators11,22,23 have noted that neuropsychological
scores are not associated with cardiac output, other researchers
have reported a significant association between cognitive functioning and left ventricular ejection fraction (LVEF).24 Because
cognitive impairment may also occur secondary to depressive
symptoms or other psychiatric problems, the relationship
between depressive symptoms, cognitive functioning, and
somatic indicators of illness severity (ie, LVEF, peak oxygen
uptake, and walking distance) in patients with CHF is of utmost
importance in this area of research.8,15 However, only a few
investigators have directly assessed cognitive performance and
its association with depressive symptoms and somatic indicators of illness severity in patients with CHF.15 Trojano et al, for
example, demonstrated a predictive effect of depressive symptoms on neuropsychological performance in geriatric patients
using the Geriatric Depression Scale.10 In contrast, Strauss et al
did not find any associations between depressive symptoms
and cognitive impairment in older patients with CHF.25 Only
Bornstein et al, evaluating 62 patients with end-stage CHF,
noted a weak but significant association between depressive
symptoms and cognitive impairment (r = 0.29, P , 0.02).14
880
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In light of the important clinical relevance of this topic,
we assessed cognitive impairment in a sample of middleaged patients with CHF (NYHA functional class I–III) using
an expanded neuropsychological test battery and evaluated
the specific associations between cognitive impairment,
clinically significant depressive symptoms, and clinical
parameters of CHF. Our first hypothesis was that, compared
with standard indications derived from data in healthy controls, the performance of patients with CHF on neuropsychological tasks would be impaired. Our second hypothesis
was that cognitive impairment in patients with CHF would
be associated with depressive symptoms, clinical parameters
of CHF, and quality of life variables.
Materials and methods
Sample
The study was based on analysis of 55 patients (mean age
55.3 ± 7.8 years, 44 males, 11 females) with stable CHF,
ie, NYHA functional class I–III. Patients were recruited
consecutively. Inclusion criteria were stable documented
CHF and LVEF #45%. Patients who had neurological and
known psychiatric problems including overt dementia were
excluded, as were those who had orthopedic, peripheral vascular, renal, or severe pulmonary diseases which could impair
successful completion of submaximal or maximal exercise
tests. Of 885 screened patients, only 64 were recruited
because of a large majority of the patients being ineligible
due to LVEF .45% or unstable clinical status. The dropout
rate, which includes 4% of missing data, was 15% (patients
became clinically unstable or developed illnesses, or were
not available for complete testing). In the end, we had the
complete data of 55 patients for our analyses. To obtain an
estimate of the required sample size, we assumed that in a
full multiple regression model with independent variables of
LVEF, peak oxygen uptake, walk test, and HADS depression
score, an R2 of about 0.2 would be obtained. Additionally
we assumed a reduced model that contained three irrelevant
independent variables. With 80% power and an alpha of 0.05,
45 cases would be necessary to obtain a squared semipartial
correlation of the relevant independent variable of 0.2 with
the criterion, which is equivalent to the difference between
the full and reduced models. Sample size estimation was
performed using SAS (v 9.2; SAS Institute Inc, Cary, NC).
Setting
The patients were referred to the Department of Cardiology
at the University Hospital of Heidelberg, Germany. Assessment and examination procedures were conducted within
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Heart failure and cognitive impairment
4 weeks of initial screening and assessment. Each patient’s
history, clinical status, sociodemographic variables, and the
etiology of heart failure were assessed. Cardiopulmonary
exercise testing (peak oxygen uptake), assessment of LVEF,
and a 6-minute walk test were conducted on the same day.
In order to avoid exhaustion, testing for cognitive functioning and depressive symptoms was either done on the
same day, before the clinical tests, or on another day. Short
Form (SF)-36 questionnaires were sent to the patients and
returned by mail. Recruitment, neuropsychological testing,
and assessment of depression were carried out by GS and
MB; 15% of the patients were retested separately by GS and
MB, and interrater reliability was satisfactory. Procedures
to assess indicators of illness severity (equilibrium radionuclide ventriculography, cardiopulmonary exercise testing,
6-minute walk test) were carried out by medical staff and
trained physicians in the department. Ethical approval for
the study was obtained from the institutional review board
at the Medical Faculty, University of Heidelberg. All the
patients gave their written informed consent.
symptoms.33 A total score $8 indicates clinically significant
depressive symptoms. This instrument was chosen over other
scales assessing depressive symptoms because of minimal
item overlap between items referring to somatic symptoms
and items referring to heart failure. The HADS scale is a well
established self-report inventory to assess depressive symptoms, and has proven to have good operating characteristics.34
The average time taken to assess cognitive functioning and
depressive symptoms was about 50 minutes.
Assessment of cognitive impairment
Assessment of somatic indicators
of illness severity
All participants were evaluated with a battery of neuropsychological tests designed to assess orientation, verbal and
digit memory, complex attention, visuomotor skills, concept
formation, language functioning, praxis, calculation, cognitive and motor speed, and mental flexibility. The German
versions of the battery of tests included the Trail Making
Test A,26 a Verbal Learning List,27 a digit symbol test,27 and a
digit recall procedure.28 The Trail Making Test A, the Verbal
Learning List, and the digit symbol test were administered in
two versions, one of them adapted to subjects aged 55 years
or older. Additionally, the Mini Mental State Examination
(MMSE) was administered to all participants.29 The Cerebral Insufficiency Self Report Inventory (CIS) was used to
assess subjective cognitive impairment (SCI) by 38 “yes or
no” items referring to difficulties in everyday activities.30
A score of 20 or more indicates cognitive impairment. All
tests produce valid and reliable measures of general cognitive abilities.26–30
Assessment of depression
The Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (SCID)31,32
served as the criterion for a depressive disorder. In addition,
depressive symptoms were evaluated by the German version
of the Hospital Anxiety and Depression Scale (HADS), a selfrating inventory using seven items to assess for depressive
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Assessment of health-related quality
of life
Patient self assessment of health-related quality of life was
measured by the German version of the SF-36.35 The SF-36
is a generic multidimensional instrument consisting of eight
scales representing physical functioning, role functioning
physical, bodily pain, general health perceptions, vitality,
social functioning, role functioning emotional, and mental
health. SF-36 scores are converted to a scale of 0–100, with
higher scores indicating a better quality of life.
To determine LVEF, equilibrium radionuclide ventriculography
was performed with a multicrystal gamma camera in the left
anterior oblique view. Cardiopulmonary exercise testing was
used to determine the functional capacity of the subjects.
Equipment included a metabolic cart with an interfaced
supine positioned bicycle ergometer. Peak oxygen uptake
was defined as the maximum oxygen consumption measured
during the last 30 seconds of symptom-limited exercise. Submaximal exercise capacity was evaluated with the 6-minute
walk test within 24 hours, and at least 4 hours before cardiopulmonary exercise.
Statistical analyses
In a first step, neuropsychological test battery scores were transformed into z values adapted for age and education. All z scores
#−0.8 were classified as cognitive impairments. Pearson’s
correlation coefficients were computed for the relationship
between neuropsychological scores, clinical variables (LVEF,
peak oxygen uptake, walking distance in the 6-minute walk
test), depression (HADS), and quality of life scores (SF-36).
Additionally, 95% confidence intervals were estimated for the
mean. Chi-square tests (HADS, total score $ 8 as cutoff) with
Bonferroni’s correction for multiple comparisons and t-tests
(SCID) were used to compare the neuropsychological data of
depressed and nondepressed patients.
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Steinberg et al
In a second step, two regression analyses were conducted,
with the dependent variables being objective and subjective
cognitive impairment. Depression (HADS), peak oxygen
uptake, LVEF, and walking distance were used as independent variables.
The objective cognitive impairment variable was generated by a factor analysis of all scores from the neuropsychological battery of tests. Factor analysis was computed with
varimax rotation, and the factors could easily be interpreted as
reflecting the Verbal Learning List, Trail Making Test A, and
Digit Symbol Test. We used principal component analysis.
Two factors were retained by the Eigenvalues .1 criterion.
Varimax rotation showed a factor with high loadings on
the Verbal Learning List, Trail Making Test A, and Digit
Symbol Test. Because completion of the Digit Symbol Test
did not always correspond to completion of the Trail Making
Test A and Verbal Learning List, we decided to compute
the unweighted sum of the Verbal Learning List and Trail
Making Test A as a summary measure for objective cognitive impairment (OCI). The CIS summary score was used
for the subjective cognitive impairment variable. Statistical
analyses were performed using SAS (v 6.0).
Results
Demographic data and clinical parameters for all patients are
shown in Table 1. Eighty percent of the patients were male
and had a cardiological diagnosis of dilated cardiomyopathy
(60.0%) or coronary artery disease (23.6%). Their mean
LVEF was 22.4% ± 12.8%, and 61.8% had NYHA class II,
35.5% had NYHA class III, and 7.3% had NYHA class I
symptoms. None of the patients was in NYHA class IV. Mean
peak oxygen uptake was 14.3 ± 5.2 mL/min/kg.
The prevalence of cognitive impairment (as defined
by the tests) in at least one measure of the objective
neuropsychological battery of tests (OCI) was 43.6% compared with normative values reported for healthy adults.26–30
Forty percent of the patients reported SCI. Altogether, 56%
of the patients showed deficits in their cognitive capacity
in at least one objective or subjective measure (OCI and/
or SCI), 31% in at least two instruments, and 11% in three
instruments. Thirteen percent showed subjective deficits but
no objective impairment. Most deficits occurred in the Verbal
Learning List and the Trail Making Test A, indicating impairment in complex attention, verbal memory, and cognitive and
psychomotor speed. Single test measures and prevalences of
cognitive impairment are shown in Tables 2 and 3.
In contrast with the other measures of our neuropsychological test battery, the MMSE detected cognitive deficits in
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Table 1 Demographic and clinical characteristics of patients
n
Age (years)
Males/females (%)
Education $8 years (%)
Body mass index (kg/m2, SD)
Cardiological diagnosis (%)
Dilated cardiomyopathy
Coronary artery disease
Others
NYHA functional class (%)
Class I
Class II
Class III
Class IV
pVO2 (mL/min/kg; mean, SD)
LVEF (%; mean, SD)
6-minute walk test (mean, SD)
SCID, current depressive disorder (%)
HADS $8 (%)
SF-36 (%, SD)
Role functioning physical
General health perceptions
Vitality
Physical functioning
Role functioning emotional
Mental health
Bodily pain
Social functioning
Total score
55
55.3 ± 7.8
80.0/20.0
54.5
23.8 ± 8.6
60.0
23.6
16.4
7.3
61.8
35.5
0.0
14.3 ± 5.2
22.4 ± 12.8
473.4 ± 122.3
11.1
25.0
37.2 ± 42.3
39.5 ± 17.3
41.5 ± 20.4
48.1 ± 24.5
54.6 ± 45.3
60.2 ± 19.6
64.4 ± 29.2
71.0 ± 23.9
52.1 ± 21.0
Abbreviations: LVEF, left ventricular ejection fraction; pVO2, peak oxygen uptake;
NYHA, New York Heart Association; SCID, Structured Clinical Interview for
Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition; HADS, Hospital
Anxiety and Depression Scale; SD, standard deviation; SF-36, Short Form 36.
only 1.8% of the patients. There was no significant difference
between neuropsychological outcomes in patients with
dilated cardiomyopathy, coronary artery disease, and other
etiologies of CHF (all P $ 0.05).
Using the DSM IV criteria for depressive disorders,
11.1% of the interviewed patients met the criteria for a current
depressive disorder, 20% for a former depressive episode,
and 25% met the diagnostic criteria for clinically significant depressive symptoms according to the HADS (total
score $8 as cutoff).
Correlation analyses revealed that higher subjective
cognitive impairment was associated with lower scores on
the SF-36 subscale of General Health Perceptions (r = −0.44;
P , 0.01). No other significant correlations were found
between the SF-36 subscales and the neuropsychological
tests. High and significant correlations (P , 0.001) were
found between depressive symptoms (HADS) and quality
of life variables (SF-36), ie, mental health (r = −0.74), total
score (r = −0.70), social functioning (r = −0.68), general
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Heart failure and cognitive impairment
Table 2 Prevalence in cognitive impairment
Deicits in
One test of 5 (OCI or SCI)
Two tests out of 5 (OCI and/or SCI)
Three tests out of 5 (OCI and/or SCI)
One test out of 4 (OCI)
SCI, no OCI
56.0%
31.0%
11.0%
43.6%
13.0%
Deicits in
Verbal Learning List (OCI)
TMT-A (OCI)
Digit Symbol Test (OCI)
Digit Recall (OCI)
CI Self Inventory (SCI)
MMSE
23.6%a
20.0%a
9.1%a
5.6%a
40.1%b
1.8%c
Notes: az value #−0.8; btotal score $20; ctotal score ,24.
Abbreviations: OCI, objective cognitive impairment; SCI, subjective cognitive
impairment; MMSE, Mini Mental State Examination; CI Self Inventory, Cerebral
Insuficiency Self Inventory.
health perceptions (r = −0.65), vitality (r = −0.62), physical
functioning (r = −0.51), bodily pain (r = −0.47), role functioning emotional (r = −0.44) and role functioning physical
(r = −0,38) (all P , 0.05). Regarding neuropsychological
performance, depressed and nondepressed patients did not
differ significantly (according to SCID diagnosis and HADS
score, t-tests and Chi-square tests, see Tables 3 and 4).
Regression analyses for OCI
Univariate analyses revealed that none of the independent variables were significantly associated with OCI (all
P $ 0.05, see Table 5). In the multivariate regression model,
only peak oxygen uptake was significantly associated with
OCI (P = 0.04, β = 0.39). The depression variable (HADS)
was not significantly related to OCI in the univariate or
multivariate analyses (P = 0.60 and 0.94, respectively).
Regression analyses for SCI
Univariate analyses revealed that none of the independent variables were significantly associated with SCI (all
P $ 0.05). The multivariate regression model revealed LVEF
as being significantly associated with SCI (P = 0.04, β = 0.33).
The depression variable (HADS) was not significantly related
to SCI in the univariate or multivariate analyses (P = 0.71
and 0.69, respectively). Altogether, neither the correlation,
t-tests, Chi-square procedures, nor the univariate or multivariate analyses revealed significant associations between
cognitive status and depressive symptoms.
Discussion
The objectives of this study were to assess cognitive
impairment in middle-aged patients with CHF (mean age
55.3 ± 7.8 years) using an expanded neuropsychological
test battery and to analyze the specific associations between
cognitive impairment, depressive symptoms, and clinical
variables in these patients. First of all, we found substantially
reduced neuropsychological performance in our patients
(56% were impaired in at least one objective or subjective
measure compared with normative values for healthy adults)
regarding a variety of cognitive domains, such as memory,
complex attention, and psychomotor speed. Furthermore,
these impairments seem to be independent of CHF etiology,
Table 3 Neuropsychological battery of tests
Test
(German version)
Domain
Total group
deicient
test scores
(%)
Non-depressed (SCID)
z-value/score
M (SD)
n = 39
Depressed (SCID)
z-value/score
M (SD)
n = 10
t
df
P valuea
Trail Making Test A
(Zahlen-Verbindungs-Test)
Verbal Learning List
(Wortliste)
Digit Symbol Test
(Zahlen-Symbol-Test)
Digit Recall
(Zahlennachsprechen)
Cerebral Insuficiency Self
Inventory (CerebraleInsufizienz-Skala)
Mini Mental State
(Mini-Mental-Status-Test)
Attention, cognitive
and motor speed
Immediate and
delayed recall
Complex attention
visuo-motor skills
Memory, concentration
concept formation
Subjective cognitive
impairment
20.0b
−0.25 (0.71)
−0.84 (0.80)
2.29
47
0.03
23.6b
0.244 (1.04)
0.239 (0.93)
0.02
47
0.98
9.1b
0.46 (0.73)
−0.07 (0.84)
1.98
48
0.05
5.6b
0.43 (0.93)
0.24 (1.05)
0.56
46
0.58
40.1c
16.31 (7.53)
19.8 (5.59)
−1.37
47
0.18
Orientation, attention
immediate and delayed
recall, calculation
1.8d
Notes: aCorrected by Bonferroni procedure: 0.01; SCID = Structured Clinical Interview DSM IV; bz-value #−0.8; ctotal score $ 20; dtotal score , 24.
Abbreviations: SCID, Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition; SD, standard deviation.
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Steinberg et al
Table 4 Neuropsychological battery of tests
Test
(German version)
Domain
Non-depressed (HADS)
z-value/score
M (SD)
n = 33
Depressed (HADS)
z-value/score
M (SD)
n = 13
χ2
df
P valuea
Trail Making Test A
(Zahlen-Verbindungs-Test)
Verbal Learning List
(Wortliste)
Digit Symbol Test
(Zahlen-Symbol-Test)
Digit Recall
(Zahlennachsprechen)
Cerebral Insuficiency Self Inventory
(Cerebrale-Insufizienz-Skala)
Attention, cognitive
and motor speed
Immediate and
delayed recall
Complex attention,
visuo-motor skills
Memory, concentration,
concept formation
Subjective cognitive
impairment
−0.26 (0.62)
−0.83 (0.91)
3.29
1
0.07
0.07 (1.01)
0.42 (0.80)
0.98
1
0.32
0.42 (0.73)
0.12 (0.85)
0.00
1
0.99
0.43 (0.87)
0.31 (1.22)
0.96
1
0.33
16.8 (7.68)
18.3 (6.64)
0.10
1
0.75
Note: aCorrected by Bonferroni procedure: 0.01.
Abbreviations: HADS, Hospital Anxiety and Depression Scale; SD, standard deviation.
in that our study revealed no significant differences regarding
cognitive performance between patients with different CHF
etiologies, such as dilated cardiomyopathy or coronary artery
disease. Therefore, our first hypothesis was confirmed.
In contrast with the high overall rate of cognitive impairment in our sample, the MMSE could detect cognitive
impairment in only 1.8% of the patients. This finding suggests
that the MMSE might not be sensitive enough to diagnose
minor or even moderate forms of cognitive impairment in
patients with CHF. Altogether, our results are in line with
earlier studies, which also found high rates of cognitive
impairment in patients with CHF. Since these studies investigated mostly cognitive functioning in end-stage geriatric
patients, they often reported even higher rates of cognitive
Table 5 Univariate and multivariate regression analysis: physical
variables and depressive symptoms as predictors for objective
and subjective cognitive impairment
Variable
Subjective
cognitive
impairment
Objective
cognitive
impairment
β value
P value
β value
P value
Univariate
pVO2 (mL/min/kg)
LVEF (%)
6-minute walk test (m)
Depressive symptoms
(HADS)
−0.19
0.24
0.01
0.27
0.41
0.11
0.95
0.71
0.20
−0.17
0.069
0.01
0.16
0.25
0.64
0.94
Multivariate
pVO2 (mL/min/kg)
LVEF (%)
6-minute walk test (m)
Depressive symptoms
(HADS)
−0.25
0.33
0.13
0.28
0.15
0.04
0.44
0.069
0.39
−0.13
−0.12
0.08
0.04
0.45
0.51
0.60
Abbreviations: pVO2, peak oxygen uptake; LVEF, left ventricular ejection fraction;
HADS, Hospital Anxiety and Depression Scale.
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impairment.15–17,36 In contrast with other studies, we investigated a middle-aged sample, and 56% of the patients were
found to have objective or subjective impairment. This is
quite surprising, given that we associate CHF mainly with
elderly people.
Our study confirms the evidence of high prevalence
rates of depressive symptoms in patients with CHF.2,5 Using
DSM IV criteria, the prevalence of current depression or
dysthymia was 11.1%. The self-report inventory, HADS,
revealed a prevalence of clinically significant depressive
symptoms of 25%. These differences in prevalence rates are
most likely due to depression assessment by either interview
or self-report inventory. Assessing depressive symptoms by
interview usually leads to lower prevalence rates compared
with self-report inventories.2
Contrary to our expectation of a linkage between cognitive impairment and depressive symptoms in patients with
CHF, there was no significant association between OCI or
SCI and depressive symptoms (SCID, HADS). Similar results
were found regarding quality of life. Because depressive
symptoms and quality of life are overlapping variables, both
were significantly related to each other, but neither depression nor quality of life was related to cognitive impairment,
except for the correlation between SCI and the SF-36 subscale of General Health Perception. This finding is rather
surprising, given that reciprocal enhancement could have
been assumed.
Whereas the present pattern of results matches the
results of previous studies, 15,19,23,37 that is, depressive
symptoms are unrelated to cognitive impairment in
patients suffering from heart failure, the present data are
also in conflict with those publications which found an
association between depressive symptoms and cognitive
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impairment.14,38–41 It is conceivable that these conflicting
findings are due to different samples (recruitment, sample
size, age of patients) and to the different instruments to
assess cognitive impairment, as well as due to the different
methods used to evaluate depressive symptoms. For instance,
in the investigation of Pullicino et al,38 the cognitive status
of an older sample (mean age 64.7 years) was assessed only
by one measure, ie, the six-item screener derived from the
MMSE. In this population, there was a considerable rate of
prior stroke compared with our study population which did
not have a main diagnosis of vascular etiology. Lopez et al39
investigated a sample of older adults with mild cognitive
impairment (mean age at least 74.0 years), of whom a significantly high percentage suffered from depression and had
poor neuroradiological results, such as white matter lesions,
cortical atrophy, and infarcts identified by magnetic resonance imaging. These vascular and neurodegenerative factors
may have contributed to cognitive impairment in the sample
reported by Lopez et al. As a consequence, it is difficult to
compare this sample with our sample. Likewise, Thomas and
O’Brien40 focused in their review mainly on depression in
later life and mentioned the conflicting literature on whether
depression is a risk factor for cognitive decline or not. Next,
in their prospective longitudinal study, Barnes et al41 investigated a random sample of adults aged 65 years and older.
Their results showed that worse depressive symptoms were
associated with an increased risk of cognitive decline and
dementia. These findings suggest that depressive symptoms
in the absence of overt cognitive impairment may reflect
early signs of neurodegenerative disease in older patients.
Furthermore, an item overlap, eg, in the CES-D scale (statements that reflect aspects both of mood and cognition) has to
be considered. To avoid item overlap with physical fatigue,
for instance, which occurs due to heart failure, we used the
HADS instrument. Because our sample consisted of middleaged patients diagnosed with dilated cardiomyopathy in 60%
of cases, neurodegenerative and cerebrovascular aspects as a
possible link between cognitive impairment and depression
seem to play a less important role than in a sample of elderly
patients. Regarding the somatic indicators of illness severity,
our results revealed that cognitive impairment is more associated with reduced functional capacity than depression. In the
final regression model, peak oxygen uptake was significantly
related to OCI. Furthermore, SCI was related to LVEF. These
results suggest that cognitive impairment might be secondary to deficits in blood supply in our sample. However, data
concerning a relationship between LVEF and cognitive
impairment are inconsistent. Whereas some studies22,23 found
International Journal of General Medicine 2011:4
Heart failure and cognitive impairment
that neuropsychological scores were not related to cardiac
output, others did find a relationship with LVEF.24
In summary, our data indicate that depression and
cognitive impairment are independent comorbidities in
middle-aged patients with CHF. Further studies which also
differentiate between OCI and SCI could be promising in
clarifying this specific relationship and its underlying mechanisms. Our investigation has limitations that need to be taken
into account, so the present pattern of results should not be
overinterpreted. First, impaired cognitive functioning was
classified as at least one cognitive measure out of the battery
of neuropsychological tests falling below z scores #−0.8
(OCI), or/and showing a total score beyond the cutoff value
of the Cerebral Insufficiency Self Report Inventory (SCI).
Other researchers might apply different algorithms. Second,
it is important to mention that, to the best of our knowledge,
it is still a matter of debate as to which z score best reflects
the onset of cognitive impairment. Third, it remains unclear
which of the numerous instruments and measures reliably
reflects cognitive impairment in this specific sample of
middle-aged patients suffering from heart failure. As a consequence, future research should use alternative instruments
to assess executive function.
Furthermore, the study was performed at a tertiary referral center. Therefore, the sample of patients with CHF as the
main etiology does not represent typical patients with CHF
seen by a general practitioner. These patients might show less
impairment of LVEF and demonstrate a higher prevalence
of coronary artery disease.42 Hence, our data may not be
representative of patients in primary care or in the general
population. It must also be pointed out that the cross-sectional
design of the present study does not permit conclusions to
be drawn concerning causality. However, the present data
show a clear association between cognitive impairment and
indicators of illness severity, whereas depressive symptoms
and cognitive deficits do not show any association.
Conclusion
In this study, we found that CHF was associated with significant levels of cognitive impairment and depressive symptoms
in a middle-aged sample of patients with NYHA functional
class I–III disease, and whereas cognitive scores were significantly associated with peak oxygen uptake and LVEF,
no significant association was found between cognitive
impairment and depressive symptoms. Successful therapeutic
management of CHF often depends heavily on the patient’s
understanding of and adherence to a complex medication
regimen and a strict diet. Cognitive impairment, such as
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Steinberg et al
memory and attention difficulties, can be very problematic
in this context because they might interfere with the patient’s
ability to adhere to medication and dietary therapies. Thus,
cognitive impairment could possibly contribute to weakened
compliance of patients with CHF with prescribed therapy
and, as a consequence, increase the rate of hospital readmission. In light of the results of this study, reduced compliance
in patients with depressive symptoms because of cognitive
impairment seems highly unlikely. Physicians should be
aware of these associations and be prepared to assess both
the cognitive and affective state of patients in addition to
physical parameters. However, even if the MMSE is largely
applied in many clinical settings as the only instrument to
assess cognition, it is not sensitive enough to identify mild or
even moderate cognitive impairment in patients with CHF.
Therefore caution is advised when the MMSE is applied
as the sole measure to identify cognitive impairment in
patients with CHF. Properly designed training programs to
prevent, slow down, or cope with cognitive impairment, as
well as implementation of depression screening programs in
routine clinical practice could help to improve the treatment
of patients with CHF and to prevent a progressive course
of disease.
Acknowledgment
We thank Mark Brandes for data gathering and data entry.
Moreover, we thank Anne-Louise Bornstein for proofreading
the manuscript.
Disclosure
The authors report no conflicts of interest in this work.
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