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Recognition Memory and Verbal Fluency Differentiate Probable Alzheimer Disease From Subcortical Ischemic Vascular Dementia
Mary C. Tierney, PhD;
Sandra E. Black, MD;
John P. Szalai, PhD;
W. Gary Snow, PhD;
Rory H. Fisher, MB;
Grant Nadon, MD;
Helena C. Chui, MD
Arch Neurol. 2001;58:1654-1659.
ABSTRACT
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Background Alzheimer disease (AD) and vascular dementia are among the most frequently
occurring causes of dementia in the world, and their accurate differentiation
is important because different pharmaceutical strategies may modify the course
of each disease.
Objective To determine which of 10 neuropsychological test scores can accurately
differentiate patients with probable AD from those with subcortical ischemic
vascular dementia (SIVD) for use in evidence-based clinical practice.
Design Patients with suspected dementia were referred to the study by family
physicians, geriatricians, and neurologists. All participants received a thorough
assessment according to standard diagnostic guidelines. Diagnoses of probable
AD (n = 31) and probable SIVD (n = 31) were made according to consensus criteria.
The diagnosticians were blind to the results of the 10 neuropsychological
test scores.
Results There were no significant differences between the groups in age or Mini-Mental
State Examination scores. Logistic regression analyses identified 2 neuropsychological
tests that best distinguished the groups (sensitivity = 81%; specificity =
84%; positive likelihood ratio = 5.1). These were the recognition memory subtest
of the Rey Auditory Verbal Learning Test and the Controlled Oral Word Association
Test. The AD group performed better on the oral association test, whereas
the SIVD group did better on the recognition memory test.
Conclusion Patients with probable AD and probable SIVD can be distinguished with
a high degree of accuracy using these 2 neuropsychological tests.
INTRODUCTION
ALZHEIMER disease (AD) and cerebrovascular disease (CVD) are the most
common causes of dementia in the world.1, 2
For several reasons, however, differential diagnosis of AD vs vascular dementia
(VaD) has proved difficult. First, there is still no specific biological marker
for AD.3 Second, although structural neuroimaging
studies (eg, computed tomography [CT] or magnetic resonance imaging) can detect
relatively small infarcts or hemorrhages—the most specific hallmarks
of CVD—they may be considered too expensive for epidemiological surveys4 or unnecessary for diagnosis in managed care settings.
Once dementia is identified, a short neuropsychological examination to determine
the likelihood of AD vs VaD or AD vs non-AD dementia would be useful. In this
study, we use evidence-based methods to assess the utility of neuropsychological
testing to differentiate dementia due to AD vs 1 subtype of VaD.
The impairment of memory and learning is one of the earliest signs of
AD. This is attributed to the selective vulnerability of medial temporal lobe
structures to neurofibrillary degeneration. The pattern of cognitive impairment
associated with VaD, on the other hand, is highly variable and depends on
the size and location of vascular brain injury. For example, occlusion of
the middle cerebral artery may be associated with aphasia if the left hemisphere
is involved or with inattention and neglect when the opposite hemisphere is
affected. Whereas reasonable success has been achieved in identifying characteristic
patterns of neuropsychological impairment in AD, this can be realized in VaD
only by confining study to more homogeneous subgroups. Small-artery disease
leads to lacunar infarcts in the subcortical gray and white matter. Although
the side of hemispheric involvement remains important, more consistent neurobehavioral
syndromes (eg, impaired executive function) emerge regardless of location,
possibly owing to a shared disruption of frontal subcortical circuits.5 For these reasons, this study focuses on the neuropsychological
differentiation of dementia associated with AD vs 1 subtype of VaD, namely
subcortical ischemic vascular dementia (SIVD).
In designing our study, several weaknesses encountered in previous comparison
studies were addressed. These measures included the following: (1) attention
to subtype of VaD; (2) controlling for group differences in dementia severity,
age, and level of education; (3) independence between neuropsychological testing
and group ascertainment; and (4) use of multivariate rather than multiple
univariate analyses. In the interest of developing cost-effective clinical
tools, we employed a battery reduction approach for distinguishing AD from
SIVD. Finally, the utility of this reduced set of tests is summarized using
evidence-based performance measures (eg, sensitivity, specificity, and likelihood
ratios) that are relevant for decision making among individual patients.6
PARTICIPANTS AND METHODS
Participants with suspected dementia were referred to the study by family
physicians, geriatricians, and neurologists. Figure 1 shows a flow diagram describing the number of participants
referred to the study and those meeting inclusion and exclusion criteria.
Physicians were asked to refer patients with suspected AD or VaD who did not
have any other medical conditions that would account for the cognitive impairment.
Informed consent was obtained after the nature of the procedures had been
fully explained. An experienced board-certified geriatrician (R.H.F. or G.N.)
saw the patients and their caregivers. A standardized interview was administered
inquiring about the history and course of cognitive problems as well as daily
functioning. A thorough physical examination, a head CT scan, and laboratory
tests including hematological, renal, hepatic, and metabolic function tests
were conducted. To be included in this study, participants were required to
be 60 years or older. The final study sample was selected according to the
fulfillment of (1) medical exclusion criteria; (2) dementia inclusion criteria;
and (3) dementia subtype inclusion criteria.
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Figure 1. Flow diagram of participants meeting
inclusion and exclusion criteria.
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MEDICAL EXCLUSION CRITERIA
We excluded patients with severe aphasia because of their inability
to complete neuropsychological testing. We also excluded subjects if any of
the following causes of memory impairment other than AD or VaD were present:
chronic alcohol abuse, hypoxia, metabolic disorders, intracranial mass lesions,
psychoses, brain trauma, or other neurological disorders including Parkinson
disease. Six patients were excluded because they met these medical exclusion
criteria.
CRITERIA FOR DEMENTIA
Patients who met the medical criteria for the study were administered
a neuropsychological test battery consisting of the Wechsler Memory Scale–Revised7: Information, Orientation, and Visual Reproduction,
immediate and delayed recall (we also had the patients copy the designs after
the delayed recall trials); California Verbal Learning Test8;
Boston Naming Test9 (odd-even version); Controlled
Oral Word Association Test (COWAT)10 (letters P, R, and W); Category Fluency (animal names); Wechsler Adult Intelligence Scale–Revised11: Digit Span, Similarities, and Digit Symbol subtests;
Read Perceptual Closure Test12; Finger Tapping
Test13; and Tokens Test.14
Diagnoses of dementia were made by an experienced board-certified psychologist
(W.G.S.) and were based on the criteria of the Diagnostic
and Statistical Manual of Mental Disorders, Revised Third Edition (DSM-III-R).15 Twelve subjects
were excluded because they did not meet the criteria for dementia.
DIAGNOSIS OF DEMENTIA SUBTYPE
Patients who met the criteria for dementia were further evaluated to
determine whether they met the criteria for AD or SIVD. Diagnosticians were
blind to the results of the neuropsychological evaluation. All CT scans (of
patients with either AD or VaD) were interpreted and reported by clinical
neuroradiologists in our institution who were blind to clinical status but
aware that patients were being evaluated for memory problems. The Hachinski
Ischemic Score16 was obtained for each subject
but was not used for diagnosis of subtype.
Probable AD Group
Patients were diagnosed as having AD if they met the criteria of the
National Institute of Neurological and Communicative Disorders and Stroke–Alzheimer's
Disease and Related Disorders Association (NINCDS-ADRDA) guidelines.17 Two patients who met these criteria were excluded
because of the presence of vascular lesions on the CT scan. Thirty-one patients
met the criteria of the NINCDS-ADRDA for probable AD.
SIVD Group
To be included in this group, participants had to meet National Institute
of Neurological Disorders and Stroke–Association Internationale pour
la Recherche et l'Enseignement en Neurosciences (NINDS-AIREN)18
criteria for probable VaD, modified for SIVD by restricting the group to patients
with evidence of lacunar infarct. Specifically, patients were included if
they had neuroimaging evidence of a subcortical ischemic infarct with a clear
temporal relationship between the stroke and the onset of dementia. Four patients
were excluded because there was no evidence of subcortical infarcts on the
CT scan. One participant was excluded because of the presence of a meningioma
on the CT scan. Patients were also restricted from participation if they had
experienced only hemorrhagic strokes or exhibited only periventricular white
matter disease on neuroimaging studies. Two subjects were excluded because
of brain hemorrhages. No patients in this sample had infarcts limited to the
cortical regions. In cases where there was a report of vascular lesions, the
film was independently reviewed by the study neurologist (S.E.B.), who was
experienced in clinical and research neuroimaging and had no knowledge of
the clinical histories or test performance of the patients. Lesions were classified
as subcortical or both subcortical and cortical (mixed), and the lobe or subcortical
location was documented noting particularly strategic locations in the thalamus,
angular gyrus, and medial temporal regions. Thirty-one patients met the criteria
for SIVD.
Neuropsychological Tests to Differentiate AD vs SIVD
After the administration of the dementia screen, another research battery
of neuropsychological tests, distinct from that used to diagnose dementia,
was given to participants. The psychometrists who administered the tests were
blind to the diagnoses of the participants. This battery was administered
to compare the 2 groups and was kept separate from any diagnostic decisions.
It consisted of the following 10 neuropsychological test scores: Wechsler
Memory Scale subtests19: Mental Control, Logical
Memory, and Paired Associates; the Rey Auditory Verbal Learning Test (RAVLT)20: number of words recalled after an interference list
(delayed recall), and percentage of true positives and true negatives from
a 30-item recognition list; COWAT10: total
number of words beginning with F, A, and S generated in 1 minute for each letter;
and the Trail Making Test13 (intermediate form):
time taken to complete parts A and B.
STATISTICAL ANALYSES
Logistic regression analysis was used to examine the significance of
the model, which included the 10 neuropsychological test scores and the covariate
of education, for the prediction of membership in the AD or SIVD group. The
intercorrelation matrix of these variables was examined to determine whether
any variables were highly correlated (r 0.80).
If this occurred, 1 variable would be selected from the correlated set to
avoid multicollinearity. The variables that significantly contributed to the
prediction of group membership were identified with forward stepwise regression
analysis where P<.05 was used to include variables
in the model.
RESULTS
STUDY SAMPLE
The demographic characteristics of patients in the AD and SIVD groups,
as well as their scores on the Mini-Mental State Examination (MMSE), the original
full-scale Hachinski Ischemic Scale, and the neuropsychological tests are
presented in Table 1. There were
no differences between the groups in age (t60 = 0.42; P = .68), level of education (t60 = 1.86; P = .07),
or MMSE score (t60 = 0.66; P = .51). However, because the educational differences between the
groups were marginally significant and because these differences are known
to influence cognitive performance, education was used as a covariate in all
subsequent analyses. As expected, the mean difference between the groups on
the Hachinski Ischemic Scale was significant (t38.1 = 13.99; P = .001).
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Table 1. Means and SDs of Selected Variables for the Probable Alzheimer
Disease and Vascular Dementia Groups*
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All patients in the SIVD group had subcortical involvement including
the basal ganglia (caudate or lenticular nucleus), thalamus, internal capsule,
and periventricular white matter region. Nineteen subjects had purely subcortical
infarcts (pure SIVD). Twelve had cortical lesions with involvement of the
adjacent white matter in addition to subcortical lesions (mixed SIVD). Of
the 31 patients in the SIVD group, 9 had unilateral lesions and 22 had bilateral
lesions.
NEUROPSYCHOLOGICAL DIFFERENCES BETWEEN PARTICIPANTS WITH VAD AND AD
Logistic regression analysis (forward stepwise procedure) was used to
determine which of the tests in the full neuropsychology battery (10 neuropsychological
test scores and the covariate of education) significantly (P<.05) predicted diagnostic classification. Only 3 variables met
the criteria for entry into the model: COWAT ( 21
= 12.22; P<.001), RAVLT recognition (21 = 9.77; P = .002), and educational
level (21 = 4.31; P =
.04). The direction of the coefficients suggested that poor recognition memory,
higher oral fluency scores, and higher education were associated with an increased
probability of having AD.
We used the receiver operating characteristic (ROC) curve to determine
the optimal combination of sensitivity and specificity for this 3-variable
model. The optimal combination simultaneously maximizes both sensitivity and
specificity. This analysis yielded a sensitivity of 81% and a specificity
of 84% when the cutoff value of the predicted probability of AD was 0.54.
The area under the ROC curve for the reduced model was 0.89 (95% confidence
limits, 0.85-0.93). The ROC curve for the 3-variable model with associated
predicted probabilities of having AD is provided in Figure 2.
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Figure 2. Receiver operating characteristic
curve for the 3-variable model with associated predicted probabilities of
having Alzheimer disease.
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The likelihood ratio of a positive test (LR+) for AD can be calculated
from these results and is the quotient of 2 measures: (1) the likelihood of
obtaining a given test result among people with the target disorder (sensitivity);
and (2) the likelihood of obtaining the same test result among people without
the target disorder (1 – specificity). The LR determines the extent
to which a test result will raise or lower the pretest probability that a
target disorder is present. The pretest probability refers to the diagnostician's
judgment about the presence of the disease in a patient before seeing the
results of the test. The posttest probability is the diagnostician's judgment
about the presence of the disease after knowing the test results. If the test
does not appreciably raise or lower the pretest probability, it is not useful
diagnostically. The reader is urged to consult Sackett et al6
for a more detailed description of how to evaluate the usefulness of diagnostic
tests. The LR+ for AD on these 2 tests (including the education covariate)
is 5.1. Following the guide provided by Jaeschke et al,21
this LR would generate a moderate change in the pretest-to-posttest probability
of AD.
We repeated these analyses with the subsample of 19 participants who
had pure SIVD. The same pattern emerged: COWAT, RAVLT recognition, and level
of education were included as significant variables in the forward-stepping
regression model. The classification accuracy of this model was also similar
to the model with patients who had mixed SIVD, with a sensitivity of 81% and
a specificity of 79% (LR+ = 3.9) when the cutoff value for the predicted probability
of having AD was 0.66.
COMMENT
In this study we found that 2 tests, one a measure of verbal recognition
memory and the other a measure of verbal fluency, distinguished accurately
between patients with AD and those with SIVD. A double dissociation was found.
The patients with AD performed worse on a recognition memory test than the
patients with SIVD, whereas the SIVD group performed worse on the COWAT. Receiver
operating characteristic curves were used to identify the optimal cutoff points
for each test. The combination of poor recognition and preserved verbal fluency
was associated with an LR+ of 5.1 when the cutoff value of the predicted probability
of having AD was 0.54. This would generate a moderate change in the pretest-to-posttest
likelihood of AD.
The participants in the SIVD subgroup all had subcortical lacunes. However,
because 12 of these 31 participants also had cortical infarcts, we replicated
the analysis in the smaller group (n = 19) with only subcortical lacunes.
In addition to the same 3 variables emerging from the forward logistic analyses,
the ß coefficients were of a similar magnitude and in the same direction,
allowing us to derive the same conclusions from both analyses. However, to
further strengthen our findings, cross-validation of the discriminatory variables
should be performed in a completely independent sample. In such a study, the ß
coefficients would be applied to the confirmatory data set, and the predicted
probabilities would be correlated with the actual outcomes.
The literature comparing AD with SIVD is limited. In many studies of
VaD, patients are not identified by subtype, and group differences in dementia
severity, age, and level of education are not adequately controlled. In our
study we focused on SIVD, a more homogeneous subgroup of VaD. The 2 groups
of patients were similar in age and dementia severity as measured by the MMSE.
Education was used as a covariate in all analyses to statistically remove
its effects on test scores. Finally, the study was designed to separate the
assignment of the target reference groups from the neuropsychological tests,
in keeping with evidence-based guidelines for diagnostic tests.21, 22
Our results are consistent with previous patterns noted in the literature.
Patients with subcortical ischemic vascular disease tend to show greater impairment
in executive function and relatively better preservation of recognition memory.23, 24 The COWAT is a widely used test of
executive function25 and is considered to measure
impairment in the dorsolateral prefrontal system, which is interconnected
with the basal ganglia and thalamus in a frontal subcortical loop.5 The specific nuclei include the dorsolateral caudate
nucleus, lateral dorsomedial globus pallidus internus, and anterior and dorsomedial
nuclei of the thalamus.5, 26 Our
finding that letter fluency was one of the most critical tests in the battery
may indicate that this circuit is frequently disrupted in SIVD at 1 or more
of these subcortical loci or in the white matter tracts that interconnect
them with the dorsolateral prefrontal lobe. Thus, the results of our study
are consistent with earlier findings27, 28
that the deficits found in patients with SIVD are primarily due to changes
in subcortical structures and in the white matter of the frontal lobe.
It is not surprising that the patients with AD in this study were characterized
by deficits in recognition memory. This pattern is well established in the
AD literature. Poor recognition memory is considered to reflect deficits in
storage caused by deficient consolidation of new memory traces.29
This, in turn, is most often linked to the degeneration of the mesial temporal
areas, namely the hippocampus and amygdala. These areas are highly vulnerable
to neurofibrillary degeneration, one of the classic neuropathological hallmarks
of AD.30, 31 Thus, poor recognition
memory among patients with AD is likely due to neurofibrillary degeneration
in the mesial temporal lobes, including the hippocampus.
This study focuses on a highly selected group of subjects. All patients
met either NINCDS-ADRDA criteria for probable AD or NINDS-AIREN criteria for
probable VaD modified for SIVD. The latter requires a history of a temporal
relationship between a clinical stroke and cognitive decline. Among various
available clinical criteria for VaD (Hachinski Ischemic Score, California
Alzheimer Disease Diagnostic and Treatment Center criteria, DSM-III-R, and International Classification of Diseases,
Ninth Revision), the NINDS-AIREN criteria are the most conservative.32, 33, 34 In addition, attempts
were made to exclude subjects with mixed AD and VaD. This was done by restricting
anyone with vascular lesions on a CT scan from the AD group and excluding
stroke subjects without a clearly defined temporal relationship to the onset
of dementia from the SIVD group. This selectivity limits the generalizability
of our results to typical clinical practice settings where mixed, possible,
and other subtypes of VaD are likely to be seen.
How can the results of this study be used to assess the relative likelihood
of AD vs SIVD in a clinical setting? After administering the 2 neuropsychological
tests, the regression coefficients provided in Table 2 can be used to calculate the probability of having AD. For
example, patient A had a grade 12 education, a RAVLT recognition memory score
of 60%, and a mean COWAT score of 13 for the 3 trials. The linear combination
[X] of the products of the regression coefficients using this patient's values
for educational level, RAVLT recognition, and COWAT would be as follows:
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Table 2. Probability of Alzheimer Disease: Results of Logistic Linear
Regression Analyses of the Relationship Between Diagnostic Classification
and Variables in the Reduced Model*
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.
Using the equation
,
the predicted probability of AD for patient A would be 0.99.
We would like to caution physicians and neuropsychologists in the appropriate
application of this procedure to their patients. First, it should be applied
only to those patients who have undergone a thorough clinical workup (apart
from a CT scan) to exclude other causes of cognitive impairment and for whom
there are only 2 reasonable alternative diagnoses: AD or SIVD. A second caution
in the application of these results is that this procedure should be applied
only to patients who are similar to the study sample (ie, similar age and
educational level, mild to moderate impairment, fluency in English, and the
ability to hear normal speech with or without auditory aids). Finally, these
tests should be conducted in a controlled, quiet environment by someone trained
in their administration and who is skillful with the patient population. Adherence
to these 3 recommendations is critical for the proper application of the procedures
described in this article.
In conclusion, we illustrate how this type of study may be useful in
deciding whether to order a neuroimaging study. In epidemiological studies35 or in managed care settings, neuroimaging may be
considered an unnecessary expense.36 It would
be useful if neuropsychological test results could identify patients for whom
the addition of a neuroimaging study would significantly change the diagnosis
or treatment.37 The utility of a diagnostic
test (eg, a CT scan) depends not only on its sensitivity and specificity but
also on the prior probability of disease.6
A test is less useful if the prior probability is either very low or very
high. The results of neuropsychological testing may help to inform ascertainment
of this prior probability.
For example, if a patient obtains a low predicted probability of AD
after the regression coefficients are applied to his or her test scores and
educational level, the patient is likely to have SIVD, and a CT scan should
be ordered. If a patient obtains a high predicted probability of AD, the decision
to order a CT scan will depend on the magnitude of the probability as well
as the prevalence of the disease in the clinic (pretest probability). If the
pretest probability of AD is high, one might decide to forgo the CT scan.
If it is low, the test results will have less of an effect on the posttest
probability,6 and the physician may still decide
to order a CT scan. Future study is required to evaluate (1) the utility of
using neuropsychological test performance to inform the physician about the
prior probability of a disease; and (2) if more accurate assessment of prior
probability will provide a cost-effective basis for deciding whether to order
a neuroimaging study.
AUTHOR INFORMATION
Accepted for publication July 18, 2001.
This research was supported by the Ontario Ministry of Health, Toronto,
and by grant P01-AG 12435 from the National Institute on Aging, Bethesda,
Md.
From Geriatric Research (Drs Tierney and Snow) and the Department of
Family and Community Medicine (Dr Tierney), the Department of Medicine (Neurology)
(Dr Black), Clinical Epidemiology and Health Services Research (Dr Szalai),
and the Department of Medicine (Geriatric Medicine) (Drs Fisher and Nadon),
Sunnybrook and Women's College Health Sciences Center, University of Toronto,
Toronto, Ontario; and the Department of Neurology (Dr Chui), University of
Southern California, Los Angeles.
Corresponding author and reprints: Mary C. Tierney, Geriatric Research,
A145, Sunnybrook and Women's Health Sciences Center, 2075 Bayview Ave, Toronto,
Ontario, Canada M4N 3M5 (e-mail: mary.tierney{at}swchsc.on.ca).
REFERENCES
| |
1. Hebert R, Brayne C. Epidemiology of vascular dementia. Neuroepidemiology. 1995;14:240-257.
FULL TEXT
|
ISI
| PUBMED
2. Canadian Study of Health and Aging Workgroup. Canadian Study of Health and Aging: study methods and prevalence of
dementia. CMAJ. 1994;150:899-913.
ABSTRACT
3. Consensus report of the Working Group on Molecular and Biochemical
Markers of Alzheimer's disease: the Ronald and Nancy Reagan Research Institute
of the Alzheimer's Association and the National Institute on Aging Working
Group. Neurobiol Aging. 1998;19:109-116.
FULL TEXT
|
ISI
| PUBMED
4. Rocca W, Hofman A, Brayne C, et al. The prevalence of vascular dementia in Europe: facts and fragments
from 1980-1990 studies. Ann Neurol. 1991;30:817-824.
FULL TEXT
|
ISI
| PUBMED
5. Cummings JL. Frontal-subcortical circuits and human behavior. Arch Neurol. 1993;50:873-880.
ABSTRACT
6. Sackett DL, Haynes RB, Guyatt GH, Tugwell P. Clinical Epidemiology: A Basic Science for Clinical
Medicine. 2nd ed. Toronto, Ontario: Little Brown & Co; 1991.
7. Wechsler D. Wechsler Memory Scale-Revised. San Antonio, Tex: Psychological Corp; 1987.
8. Delis DC, Kramer JH, Kaplan E, Ober BA. CVLT: California Verbal Learning Test: Research Edition,
Adult Version, Manual. San Antonio, Tex: Psychological Corp, 1987.
9. Kaplan E, Goodglass H, Weintraub S. Boston Naming Test. Philadelphia, Pa: Lea & Febiger; 1983.
10. Spreen O, Benton AL. Neurosensory Center Comprehensive Examination for
Aphasia. Victoria, British Columbia: Neuropsychology Laboratory; 1969.
11. Wechsler D. Wechsler Adult Intelligence Scale-Revised. New York, NY: Psychological Corp; 1981.
12. Read DE. Age-related changes in performance on a visual-closure test. J Clin Exp Neuropsychol. 1988;10:451-466.
ISI
| PUBMED
13. Reitan RM. Manual of Administration of Neuropsychological Test
Batteries for Adults and Children. Tucson, Ariz: Neuropsychology Laboratories; 1977.
14. Benton A, Hamsher K. Multilingual Aphasia Examination. Iowa City, Iowa: AJA Associates Inc; 1983.
15. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders,
Revised Third Edition. Washington, DC: American Psychiatric Association; 1987.
16. Hachinski VC, Iliff LD, Zilhka E, et al. Cerebral blood flow in dementia. Arch Neurol. 1975;32:632-637.
ABSTRACT
17. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA
Work Group under the auspices of Department of Health and Human Services Task
Force on Alzheimer's disease. Neurology. 1984;34:939-944.
FREE FULL TEXT
18. Roman GC, Tatemichi TK, Erkinjuntti T, et al. Vascular dementia: diagnostic criteria for research studies: report
of the NINDS-AIREN International Workshop. Neurology. 1993;43:250-260.
FREE FULL TEXT
19. Wechsler D, Stone CP. Wechsler Memory Scale. New York, NY: Psychological Corporation; 1973.
20. Lezak MD. Neuropsychological Assessment. 3rd ed. New York, NY: Oxford University Press; 1995.
21. Jaeschke R, Guyatt G, Sackett DL. Users' guides to the medical literature, III: how to use an article
about a diagnostic test, A: are the results of the study valid? JAMA. 1994;271:389-391.
FULL TEXT
|
ISI
| PUBMED
22. Jaeschke R, Guyatt GH, Sackett DL. Users' guides to the medical literature, III: how to use an article
about a diagnostic test, B: what are the results and will they help me in
caring for my patients? JAMA. 1994;271:703-707.
FULL TEXT
|
ISI
| PUBMED
23. Tei H, Miyazaki A, Iwata M, Osawa M, Nagata Y, Maruyama S. Early-stage Alzheimer's disease and multiple subcortical infarction
with mild cognitive impairment: neuropsychological comparison using and easily
applicable test battery. Dement Geriatr Cogn Disord. 1997;8:355-358.
ISI
| PUBMED
24. Lafosse J, Reed B, Mungas D, Sterling S, Wahbeh H, Jagust W. Fluency and memory differences between ischemic vascular dementia and
Alzheimer's disease. Neuropsychology. 1997;11:514-522.
FULL TEXT
|
ISI
| PUBMED
25. Malloy PF, Richardson ED. Assessment of frontal lobe functions. J Neuropsychiatry Clin Neurosci. 1994;6:399-410.
FREE FULL TEXT
26. Chui H, Willis L. Vascular diseases of the frontal lobes. In: Miller B, Cummings J, eds. The Human Frontal
Lobes. New York, NY: Guilford Press; 1999:370-401.
27. Almkvist O. Neuropsychological deficits in vascular dementia in relation to Alzheimer's
disease: reviewing evidence for functional similarity or divergence. Dementia. 1994;5:203-209.
28. Libon D, Bogdanoff B, Bonavita J, Skalina S. Dementia associated with periventricular and deep white matter alterations:
a subtype of subcortical dementia. Arch Clin Neuropsychol. 1997;12:239-250.
FULL TEXT
|
ISI
| PUBMED
29. Branconnier RJ, Cole JO, Spera KF, Devitt DR. Recall and recognition as diagnostic indices of malignant memory loss
in senile dementia: a Bayesian analysis. Exp Aging Res. 1982;8:189-193.
ISI
| PUBMED
30. Braak H, Braak E. Neuropathological staging of Alzheimer-related changes. Acta Neuropathol (Berl). 1991;82:239-259.
FULL TEXT
| PUBMED
31. Hyman BT, VanHoesen GW, Damasio AR. Memory-related neural systems in Alzheimer's disease: an anatomic study. Neurology. 1990;40:1721-1730.
FREE FULL TEXT
32. Verhey F, Lodder J, Rozendaal N, Jolles J. Comparison of seven sets of criteria used for the diagnosis of Alzheimer's
disease and ischemic vascular dementia. Neuroepidemiology. 1996;15:166-172.
ISI
| PUBMED
33. Wetterling T, Kanitz R, Borgis K. Comparison of different diagnostic criteria for vascular dementia (ADDTC,
DSM-IV, ICD-10, NINCDS-AIREN). Stroke. 1996;27:30-36.
FREE FULL TEXT
34. Chui HC, Mack W, Jackson JE, et al. Clinical criteria for the diagnosis of vascular dementia: a multicenter
study of comparability and interrater reliability. Arch Neurol. 2000;57:191-196.
FREE FULL TEXT
35. Rocca W, Kokmen E. Frequency and distribution of vascular dementia. Alzheimer Dis Assoc Disord. 1999;13(suppl 3):S9-S14.
36. Practice parameter for diagnosis and evaluation of dementia (summary
statement): report of the Quality Standards Subcommittee of the American Academy
of Neurology. Neurology. 1994;44:2203-2206.
FREE FULL TEXT
37. Chui H, Zhang Q. Evaluation of dementia: a systematic study of the usefulness of the
American Academy of Neurology's practice parameters. Neurology. 1997;49:925-935.
FREE FULL TEXT
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Ingles et al.
Stroke 2007;38:1148-1153.
ABSTRACT
| FULL TEXT
National Institute of Neurological Disorders and Stroke-Canadian Stroke Network Vascular Cognitive Impairment Harmonization Standards
Hachinski et al.
Stroke 2006;37:2220-2241.
ABSTRACT
| FULL TEXT
Cognitive profile in CADASIL
Buffon et al.
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ABSTRACT
| FULL TEXT
Cognitive profile of subcortical ischaemic vascular disease
Jokinen et al.
J. Neurol. Neurosurg. Psychiatry 2006;77:28-33.
ABSTRACT
| FULL TEXT
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Leblanc et al.
Stroke 2006;37:248-255.
ABSTRACT
| FULL TEXT
The Pattern of Cognitive Performance in CADASIL: A Monogenic Condition Leading to Subcortical Ischemic Vascular Dementia
Peters et al.
Am. J. Psychiatry 2005;162:2078-2085.
ABSTRACT
| FULL TEXT
Driver landmark and traffic sign identification in early Alzheimer's disease
Uc et al.
J. Neurol. Neurosurg. Psychiatry 2005;76:764-768.
ABSTRACT
| FULL TEXT
Effects of White Matter Lesions and Lacunes on Cortical Function
Reed et al.
Arch Neurol 2004;61:1545-1550.
ABSTRACT
| FULL TEXT
Evaluation of visual recognition memory in MCI patients
Barbeau et al.
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ABSTRACT
| FULL TEXT
Diagnostic utility of abbreviated fluency measures in Alzheimer disease and vascular dementia
Canning et al.
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ABSTRACT
| FULL TEXT
Effects of subcortical ischemic vascular dementia and AD on entorhinal cortex and hippocampus
Du et al.
Neurology 2002;58:1635-1641.
ABSTRACT
| FULL TEXT
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