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Neuropsychological Differentiation of Alzheimer’s Disease and Vascular Dementia: A Meta-Analysis Jennifer Burke University of Adelaide Associate Professor.

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Presentation on theme: "Neuropsychological Differentiation of Alzheimer’s Disease and Vascular Dementia: A Meta-Analysis Jennifer Burke University of Adelaide Associate Professor."— Presentation transcript:

1 Neuropsychological Differentiation of Alzheimer’s Disease and Vascular Dementia: A Meta-Analysis Jennifer Burke University of Adelaide Associate Professor Jane Mathias University of Adelaide

2 Background The differential diagnosis of Alzheimer’s Disease (AD) and vascular dementia (VaD) is difficult Cognitive assessments play an important role in differential diagnosis There is a lack of clear evidence regarding which cognitive tests accurately discriminate between AD and VaD

3 Aim Undertake a meta-analytic review of research comparing the cognitive deficits of persons with AD and VaD

4 Literature search Comprehensive search: – PsycINFO and PubMed databases – January 1989 to September 2006.

5 Inclusion criteria 1. Examined groups with AD & VaD 2. Cognitive tests were administered to both groups 3. These tests were not used for diagnosis 4. Data enabling the calculation of effect sizes 5. Participants did not have any other neurological or psychiatric disorder 6. Was published in English

6 Data collection The data extracted from each study included: –study characteristics –participants characteristics –cognitive tests –test data for AD & VaD groups

7 Effect size calculations Cohen’s d effect sizes were calculated for every cognitive test in every study –d measures the standardised mean difference between two groups –small effect: d =.2 medium effect: d =.5 large effect: d =.8

8 Calculations Mean effect sizes were then calculated for all studies that used a given measure Mean effect sizes were then calculated for all studies that used a given measure Effect sizes were weighted to take into account sample size Effect sizes were weighted to take into account sample size

9 Calculations Percentage overlap in scores (%OL) 95% confidence intervals Fail-safe N – measures Fail-safe N – measures the number of studies with small effects that are required to overturn a finding Heterogeneity was tested

10 Data interpretation For a test to be useful for differential diagnosis, it had to: i.d >.8 (large effect) ii.95% CI ≠ 0 iii.a large Nfs score

11 Demographics N = 81 studies 119 cognitive tests were used Participant recruitment: hospital inpatient & outpatients (34%) AD: 68% females, VaD: 53% females AD and VaD groups were comparable: education, time since diagnosis, depression AD group was younger and had lower MMSE Majority of studies used published diagnostic criteria

12 Tests examined by > one study Test N Studies N Participants Mean d w SD95% CIN fs %OL Facial expression recognition task Story recall delayed

13 Results d ranged from 0 to 1.1 %OL ranged from 40 to 100 At best, cognitive tests are limited in their ability to discriminate between AD & VaD

14 Results Tests examined by one study –13 cognitive tests showed large group differences Commonly used tests did not effectively discriminate between AD and VaD patients

15 Conclusions Cognitive tests must be used cautiously and in conjunction with other diagnostic information –Inadequate diagnostic criteria –VaD is a heterogeneous disease –Overlapping aetiologies There are a number tests that may prove suitable for assisting with differential diagnosis


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