1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. References

Cardiac output and cerebral perfusion are reduced in patients with advanced stages of heart failure. Our aim was to determine whether cerebral blood flow velocity measured by transcranial Doppler ultrasonography was reduced in outpatients with mild heart failure in comparison to controls and, if so, whether this reduction was related to cognitive performance and abnormalities of the brain diagnosed by magnetic resonance imaging.

Cerebral blood flow velocity (CBF-V) was determined in 43 outpatients with heart failure (HF), 33 patients with cardiovascular disease but without evidence of HF, and 22 healthy controls. Neuropsychological assessment consisted of an extensive test battery. White matter hyperintensities and medial temporal lobe atrophy were assessed by magnetic resonance imaging (MRI) of the brain.

Mean middle cerebral artery (MCA) CBF-V was lower in patients with mild to moderate HF, as compared with healthy controls. No associations were found between the CBF-V parameters and the neuropsychological results or MRI abnormalities.

Cognitive impairment is common among patients with chronic heart failure (HF).1 It is associated with both diminished health-related quality of life2,3 and increased mortality.4 Reductions in cerebral blood flow as well as cardiogenic embolism have been held responsible for the observed cognitive deficits.5 Furthermore, hemodynamic changes in patients with HF and cardiovascular risk factors may contribute to morphologic cerebral abnormalities, in particular cerebral infarction and white matter hyperintensities (WMH).6,7 Recent studies indicate that brain perfusion is decreased and cerebral autoregulation fails in advanced stages of HF.8 Transcranial Doppler ultrasonography (TCDU) is an easy-to-administer and noninvasive tool for assessing CBF-V reductions in patients with HF. Low CBF-V measured by TCDU has already been described as a risk factor for WMH in the elderly.9 However, few data are available with regard to the relationship between decreased CBF-V and neuroimaging in outpatients with mild to moderate HF.10,11 Moreover, investigation of its possible relation to neuropsychological task performance may identify persons at increased risk for developing cognitive impairment and may provide an opportunity for intervention.

Because of the high prevalence of a variety of vascular risk factors (eg, hypertension and diabetes) and comorbidities that may contribute to the development of cognitive decline in HF patients, the underlying pathophysiologic mechanisms are difficult to identify and are as yet unknown. We therefore used a case-control design, including patients with cardiovascular disease but no evidence of HF (cardiac controls), to disentangle the specific effects of HF on the CBF-V.

We hypothesized that HF was associated with decreased CBF-V, measured by TCDU, compared with control participants. Moreover, we expected that diminished CBF-V in HF patients was related to both neuropsychological deficits and cerebrovascular abnormalities, such as WMH.


  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. References

Patients. Forty-nine patients living independently were recruited from a specialist HF outpatient clinic over a 12-month period. Patients were considered eligible to participate in the study if they fulfilled the following criteria: (1) they had clinically diagnosed chronic HF, functional class II or III according to the New York Heart Association (NYHA) classification12; (2) left ventricular ejection fraction (LVEF) was <45% on transthoracic echocardiography; and (3) they were aged 50 years or older. Criteria for exclusion were psychiatric illness or use of psychoactive drugs, serious or life-threatening diseases, prior diagnosis of dementia, history of stroke associated with the development of neurologic signs or symptoms, history of alcohol abuse (>4 units/d), myocardial infarction during the previous 3 months, and pacemaker implants.

In addition, we recruited 36 cardiac controls from the outpatient clinic of the cardiology department. All of the participants had a history of ischemic cardiac disease without a clinical diagnosis of HF and an LVEF >55%. We aimed to establish an equal distribution of cardiovascular risk factors in the 2 patient groups. Finally, a group of 25 healthy controls was studied. Healthy control participants were healthy spouses or neurologic outpatients visiting the same hospital for a peripheral nerve problem. The study was approved by both the institutional review board of the hospital and the local research ethics committee.

Following the obtainment of informed consent, baseline data were collected by means of a structured interview including information on demographic characteristics, relevant medical history, alcohol consumption, current use of medication, and neurologic complaints. Presence of hypertension, diabetes mellitus, coronary artery bypass graft, atrial fibrillation, or hypercholesterolemia was derived either from medical files or from the laboratory test results. All participants underwent physical examination, laboratory blood tests, neuropsychologic testing, and MRI brain scanning.

Transcranial Doppler Ultrasonography. TCDU was performed using a standard protocol with a 2-Mhz pulsed-wave probe (Multidop X4 Doppler; DWL 2.5 software; Compumedics Germany GmbH, Singen, Germany). The study was performed with participants in a supine position without any visual or auditory stimulation. The MCA was insonated on both sides, and data were obtained from measurements at 3 incrementing depths. The highest mean and systolic CBF-Vs as well as the lowest pulsatility index (PI) were used in the analysis. TCDU data were missing in 7 participants (3 in the HF group, 2 in the cardiac control group, and 2 in the healthy control group) because of the bilateral absence of a temporal window.

Hemodynamic significant stenosis of the internal carotid artery (ICA) was estimated indirectly by means of asymmetric PI in both MCAs using the pulsatility transmission index (lowest PI divided by the highest PI should be between 0.92 and 1.08).13 Another 2 patients in the HF group and 1 patient in the cardiac control group with a transmission index <0.92 were hereby excluded from the analysis.

Magnetic Resonance Imaging. MRI of the brain was performed using a 1.5 Tesla scanner (GE-Signa Horizon LX, Milwaukee, WI). A standardized imaging protocol consisting of sagittal T1-weighted (repetition time [TR], 300 ms; echo time [TE], 4 ms) and axial T2-weighted (TR, 6500 ms; TE 105 ms) and fluid-attenuated inversion recovery (FLAIR)-weighted (TR, 10,000 ms; TE, 160 ms) as well as coronal FLAIR images was used. Scans were generated with a slice thickness of 5 mm with a 2-mm gap. MRI scans were read in a standard fashion by 2 experienced raters who were not provided with any clinical information. WMHs were rated according to the Scheltens scale.14 This scale scores the periventricular white matter hyperintensities (PWMH) and deep white matter hyperintensities (DWMH) according to size and number of lesions in different regions. The total WMH (range, 0–80) represented the sum of DWMH and PWMH subscores. In addition, we used visual rating scales to evaluate medial temporal lobe atrophy (MTA) (possible range of scores for each side, 0–4).15

Neuropsychological Assessment. Five cognitive domains were assessed by an extensive neuropsychological battery: (1) memory (by the Rey Auditory 15-Word Verbal Learning Test,16 the Digit Span,17 and pattern recognition memory testing, part of the Cambridge Neuropsychological Test Automated Battery [CANTAB]18); (2) executive functions (Intra-extra dimensional set shift [part of the CANTAB],18 Stockings of Cambridge [also part of the CANTAB], and the Trailmaking Test B19); (3) visuospatial functions (object recognition and fragmented line drawings); (4) language (letter fluency and categorical fluency20); (5) mental speed/attention (the Stroop Color-Word Test parts 2 and 321 and the Trailmaking test A19). In addition, the Mini Mental State Examination (MMSE) was administered.22 These tests were administered by a trained neuropsychologist who was blinded to the participant's group allocation. Neuropsychological data were missing for 2 patients who could not complete all tests.

Statistical Analysis. Data were collated on SPSS version 12.0 (SPSS, Inc, Chicago, IL). Analyses of variance (ANOVA) were performed to assess intergroup differences in baseline data. Categoric data (sex, cardiovascular risk factors) were compared with chi-square tests. Neuropsychological scores on the individual tests were transformed to Z-scores and composite Z-scores were defined for the 5 cognitive domains as described in the neuropsychological methods. To obtain an indication of overall cognitive performance, a mean Z-score was calculated. ANOVAs with post hoc Bonferroni tests were used to assess group differences with respect to the TCDU data, adjusting for age, sex, and hematocrit profile.

The total WMH score and the MTA score underwent square root transformation before statistical analysis. In HF patients (n=46), a linear regression analysis was performed, controlling for age and sex, to examine the association between TCDU variables (dependent) and both neuropsychological performance (composite cognitive Z-score and MMSE) and MRI parameters (WMH and MTA).


  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. References

TCDU data were available for 76 patients and 22 healthy controls (Table I). The healthy control group was relatively younger and contained more female participants, although these differences did not reach statistical significance. Cardiovascular risk factors were equally distributed between the 2 patient groups. Significant baseline differences were found for LVEF, brain natriuretic peptide (BNP), diastolic and systolic blood pressure, and smoking habits. HF patients had lower blood pressure values, lower LVEFs, and higher BNP plasma levels. There were differences between groups in terms of the number of antihypertensive medications used. These medications included angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, diuretics, β-blockers, and calcium channel blockers. The etiology of cardiomyopathy in HF patients was ischemic in 29 (65%) patients, dilated in 8 (20%), hypertrophic in 4 (11%), and idiopathic in 2 (4%). HF in 22 patients was classified as NYHA class II and in 21 as class III, with the duration of heart disease ranging from 1 to 12 years.

Table I.  Baseline Characteristics of HF Patients, Cardiac Controls and Healthy Controls
VariablesHF (n=43)Cardiac Controls (n=33)Healthy Controls (n=22)P Value
Agea68.0 (8.9)67.8 (9.7)64.1 (8.3).093
Female8 (19)6 (21)10 (45).082
Diabetes mellitus11 (26)7 (22)0.941
Atrial fibrillation7 (16)4 (11)0.387
Hypercholesterolemia20 (47)21 (64)0.103
Hypertension20 (47)16 (47)0.901
CABG11 (26)12 (36)0.414
Occlusive artery disease7 (16)7 (22)0.372
Smoking17 (40)15 (44)4 (18).015b
LVEFa27 (7.4)63 (8.2)-.000c
BNPa262.3 (399.2)93.4 (145.5)24.7 (19.9).001b,c
Systolic blood pressurea125.8 (15.6)140.2 (15.4)133.4 (16.4).000c
Diastolic blood pressurea76.7 (9.1)83.3 (7.7)83.2 (9.3).001b,c
Pulsea69.7 (10.8)67.6 (10.7)68.2 (12.4).798
Hematocrita0.40 (0.04)0.41 (0.03)0.40 (0.03).128
Abbreviations: BNP, brain natriuretic peptide; CABG, coronary artery bypass graft; HF, heart failure; LVEF, left ventricular ejection fraction; values are frequency (%) unless otherwise indicated. P values for univariate analysis of variance F or chi-square test. aMean (SD). bP<.05 for comparisons between HF and healthy controls. cP<.05 for comparisons between HF and cardiac controls.

Table II represents the composite domain scores of the 3 groups, adjusted for age, sex, and education. Results indicate a significant overall group effect on the cognitive domains memory, executive functions, mental speed/attention, and the overall cognitive Z-score. Mean MMSE scores were similar in the 3 groups.

Table II.  Neuropsychological Data in the 3 Study Groups
Neuropsychological DomainHF (n=43)Cardiac Controls (n=33)Healthy Controls (n=22)P Value
Memory−0.23 (0.60)0.10 (0.53)0.27 (0.93).014
Executive function−0.16 (0.56)0.05 (0.54)0.33 (0.64).029
Language−0.11 (0.77)−0.04 (0.77)0.35 (0.71).212
Visuospatial function−0.10 (0.52)0.15 (0.37)0.25 (0.70).050
Mental speed/attention−0.12 (0.59)0.08 (0.52)0.24 (0.75).044
Overall cognitive score−0.14 (0.44)0.05 (0.38)0.29 (0.60).003
MMSE27.6 (2.1)27.5 (1.97)28.1 (1.91).361
Abbreviations: HF, heart failure; MMSE, Mini-Mental State Examination. Results are mean (SD). P value for univariate analysis of variance F; data corrected for age, sex, and education level.

Mean MCA CBF-V differed significantly between HF patients and healthy controls, but not between the HF patients and the cardiac controls (Table III). The MCA PI was significantly higher in the 2 patient groups relative to the healthy control group. After additional correction for age, sex, and hematocrit profile, this group effect remained significant for HF patients and healthy controls.

Table III.  Comparisons of TCDU Data of the Study Groups
TCDU VariablesHFCardiac ControlsHealthy ControlsP1 ValueP2 Value
Mean MCA CBF-V, cm/s47.3 (10.7)49.8 (11.2)56.1 (10.9)P1=.011bP2=.034b
Systolic MCA CBF-V, cm/s80.6 (17.9)82.7 (19.2)86.1 (15.5)P1=.463P2=.611
MCA pulsatility index, cm/s0.93 (0.19)0.95 (0.16)0.79 (0.13)P1=.003b,cP2=.046b
Abbreviations: CBF-V, cerebral blood flow velocity; HF, heart failure; MCA, middle cerebral artery; TCDU, Transcranial Doppler ultrasonography. Results are mean (SD). P1, P value for univariate analysis of variance F; uncorrected data. P2, P value for univariate analysis of variance F; data corrected for age, sex, and hematocrit profile. aP<.05 for comparisons between HF and cardiac controls. bP<.05 for comparisons between HF and healthy controls. cP<.05 for comparisons between cardiac controls and healthy controls.

Linear regression analyses in the sample of HF patients showed that CBF-V variables were not correlated to any of the MRI measures or the total cognitive domain Z-score and MMSE (Table IV), nor were the CBF-V parameters correlated to the LVEF or systolic and diastolic blood pressure.

Table IV.  Linear Regression Coefficients of CBF-V Parameters on MRI Measures and Cognitive Performance in Heart Failure Patients
Dependent VariablesMean CBF-VSystolic CBF-VPulsatility Index
Total WMH−0.0020.018−0.0040.110−0.0710.912
Total cognitive Z-score−0.0280.016−0.0260.011−0.8670.928
Abbreviations: CBF-V, cerebral blood flow velocity; MMSE, Mini Mental State Examination; MRI, magnetic resonance imaging; MTA, medial temporal lobe atrophy; WMH, white matter hyperintensities. Results are given as β coefficients and standardized error (SE). Results were not significant.


  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. References

We found that patients with mild to moderate HF (NYHA class II or III) had a lower mean CBF-V of the MCA compared with healthy participants. In contrast to what we expected, this CBF-V reduction was not related to cognitive performance or brain abnormalities as observed on MRI.

The CBF-V measured by TCDU is an indirect estimate of actual cerebral perfusion. Equivalence between both variables has been suggested by some studies but challenged by others.23,24 It can be assumed, however, that in a large sample of participants with TCDU performed under the same conditions, CBF-V is a good surrogate of cerebral blood flow and that the observed group differences actually reflect differences in cerebral blood flow.

Cross-sectional studies have shown that patients with HF have a decreased cerebral blood flow and impaired cerebral autoregulation.8,10,25,26 The present series is distinct from previous studies in that it includes outpatients with HF living independently and a cardiac control group with a comparable cardiovascular risk profile but no evidence of HF. These cardiac controls also showed a reduction in CBF-V compared with healthy controls; however, this difference did not reach statistical significance. CBF-V reductions in HF can therefore not be exclusively attributed to systolic dysfunction of the heart leading to low cardiac output. Cardiovascular risk factors that were highly prevalent in the 2 patients groups may also play a role.

In contrast with patients with advanced stages of HF, our sample of outpatients had relatively mild cerebral blood flow reductions. In the early stages of heart disease, the effect of left ventricular dysfunction may still be compensated by cerebral autoregulatory mechanisms that are intact, and as a consequence left ventricular dysfunction may not lead to permanent cerebral hypoperfusion that can be detected by TCDU. This may be an explanation for the fact that we were unable to demonstrate a correlation between the changes in CBF-V parameters and the cognitive performance or neuroimaging abnormalities. This finding contrasts with the few studies on this topic that have yielded conflicting results: one suggested that both low mean CBF-V of the MCA and high PI were correlated with the MMSE score.10 The median MMSE score of the population in that study was 23, and patients were younger (mean age, 55 years) than our patients. Alves and colleagues27 used a voxel-based image analysis method to investigate the presence of regional cerebral blood flow abnormalities in patients with HF compared with healthy controls. They found a direct relationship between cerebral blood flow and degree of cognitive impairment. Others have shown low mean CBF-V in HF patients that improved after cardiac transplantation, but unfortunately no cognitive data were reported.11,28 In these studies, sample size was limited and selection bias was likely because of the complex methods used (single-photon emission computed tomography or positron emission tomography).

The existence of cerebrovascular autoregulatory mechanisms, ensuring cerebral perfusion when systemic blood pressure falls, gave rise to the hypothesis of a nonlinear relationship between low CBF-V values and MRI brain abnormalities. Therefore, we performed an additional analysis and found that only a small sample of 9 HF patients with a systolic CBF-V below a cutoff of 62.5 cm/s had a higher total WMH score compared with the 37 patients with higher systolic CBF-V values. This finding is an association of which the direction remains speculative. A plausible explanation is that microangiopathy caused by multiple cardiovascular risk factors, such as hypertension and diabetes mellitus, causes a decrease in CBF-V and cerebral perfusion, which would contribute to the occurrence of WMH. Another explanation considered is that, in addition to microangiopathy, cerebral hypoperfusion due to left ventricular systolic dysfunction leads to incomplete white matter ischemia, lacunar strokes, and areas of microinfarction. Our results, however, have shown that the observed reductions in CBF-V did not relate to the LVEF. As a consequence, one may hypothesize that assessment of the CBF-V in the large cerebral arteries does not reflect the capillary perfusion in the deep white matter that is thought to be affected by chronic hypoperfusion. Apart from pathophysiologic considerations, our study has shown that although patients with mild to moderate HF have a lower CBF-V compared with healthy persons, this reduction was not yet related to cognitive performance or neuroimaging abnormalities in this stage of heart disease.

Some methodologic limitations of our study need to be addressed. First, the relatively small number of patients inevitably leads to limitation of the statistical power of the data. Second, the recruitment of patients from a specialist HF service may have led to selection bias, as 18% of the screened patients refused informed consent because of fatigue or claustrophobia. Nevertheless, we believe that our sample is representative of an outpatient HF population. Third, the study was essentially correlational, which limits interpretations about causal mechanisms underlying cognitive impairment associated with brain perfusion. Fourth, medication-related effects on the cardiovascular parameters and transcranial analysis (eg, blood pressure fluctuations and variable cerebral perfusion over time) were not registered during the specific time of data collection. Finally, we intended to exclude patients with hemodynamically significant ICA stenosis by using the pulsatility transmission index, but no actual duplex of the carotids was performed. We believe, however, that this index is a reliable estimate of actual severe ICA stenosis.13

Patients with mild to moderate HF have a lower mean CBF-V of the MCA measured by TCDU compared with healthy persons. In the investigated population, these reductions were not associated with WMH, MTA, or cognitive performance. Longitudinal studies are needed to help further elucidate the relationship between cerebral hemodynamic disturbances in patients with refractory HF and cognitive impairment.


  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. References
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