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A brief cognitive test battery to differentiate Alzheimer's disease and frontotemporal dementia
Abstract
OBJECTIVES: To validate a simple bedside test battery designed to detect mild dementia and differentiate AD from frontotemporal dementia (FTD). METHODS: Addenbrooke's Cognitive Examination (ACE) is a 100-point test battery that assesses six cognitive domains. Of 210 new patients attending a memory clinic, 139 fulfilled inclusion criteria and comprised dementia (n = 115) and nondementia (n = 24) groups. The composite and the component scores on the ACE for the two groups were compared with those of 127 age- and education-matched controls. Norms and the probability of diagnosing dementia at different prevalence rates were calculated. To evaluate the ACE's ability to differentiate early AD from FTD, scores of the cases diagnosed with dementia with a Clinical Dementia Rating < or = 1 (AD = 56, FTD = 24, others = 20) were compared. RESULTS: Two cut-off values for the ACE composite score (88 and 83) were of optimal utility depending on the target population. The ACE had high reliability, construct validity, and sensitivity (93%, using 88 as cut-off). Using the lower cut-off of 83, the ACE had a higher sensitivity (82%) and predictive value than the Mini-Mental State Examination for a wide range of dementia prevalence. The ACE differentiated AD from FTD, and the VLOM ratio (derived using component scores: [verbal fluency + language]/[orientation + memory]) of <2.2 for FTD and >3.2 for AD was highly discriminating. CONCLUSION: The ACE is a brief and reliable bedside instrument for early detection of dementia, and offers a simple objective index to differentiate AD and FTD in mildly demented patients.
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“Many studies have supported its use in differentiating between FTD and Alzheimer's disease, but it has been less studied for the differential with PPD (Mathuranath et al. , 2000; Dudas et al. , 2005; Hodges, 2012; Hsieh et al. , 2015).”
From Recommendations to distinguish behavioural variant frontotemporal dementia from psychiatric disorders (2020) · cites this paper as Mathuranath et al., 2000
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“In recent years, several new word embedding methods based on neural networks have gained popularity, such as word2vec [26] or GloVe [27], which have shown improved performance over LSA for semantic modeling when sufficient training data is available [84].”
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Metadata
- Authors
- Mathuranath, P. S., Nestor, P. J., Berrios, G. E., Rakowicz, W., & Hodges, J. R.
- Affiliations
- MRC Cognition and Brain Sciences Unit (GB)
- From the University of Cambridge Neurology Unit (Drs. Mathuranath, Nestor, and Hodges, and W. Rakowicz) and Department of Psychiatry (Dr. Berrios), University of Cambridge, Addenbrooke's Hospital; and MRC Cognition and Brain Sciences Unit (Dr. Hodges), Cambridge, UK.
- Venue
- Neurology
- Published
- 2000-12-12
- Volume
- 55
- Issue
- 11
- Pages
- 1613-1620
- ISSN
- 0028-3878 (ISSN-L)
- 1526-632X
- OpenAlex
- W1992661874
- Cited by
- 1,029
- References
- 48
- Citations by year
- 2026: 30 · 2025: 44 · 2024: 41 · 2023: 34 · 2022: 55 · 2021: 58 · 2020: 81 · 2019: 55 · 2018: 45 · 2017: 49 · 2016: 36 · 2015: 54 · 2014: 46 · 2013: 38 · 2012: 43
- FWCI
- 7.06
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Neurology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Social Sciences › Psychology › Clinical Psychology › Historical and Modern Theater Studies
- Social Sciences › Psychology › Applied Psychology › Psychological Testing and Assessment
- Keywords
- Alzheimer's disease, frontotemporal dementia, Addenbrooke's Cognitive Examination, cognitive test battery, differential diagnosis of dementia, mild dementia, early detection of dementia, bedside assessment, verbal fluency, language, memory, orientation, sensitivity and predictive value, dementia prevalence
- MeSH terms
- Aged, Alzheimer Disease, Dementia, Diagnosis, Differential, Female, Frontal Lobe, Humans, Male, Neuropsychological Tests, Temporal Lobe
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