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Diagnosing Alzheimer's disease
 — non-clinicians and computerised algorithms together are as accurate as the best clinical practice
Author(s)Catherine M L Foy, Helen Nicholas, Paul Hollingworth
Journal titleInternational Journal of Geriatric Psychiatry, vol 22, no 11, November 2007
Pagespp 1154-1163
Sourcehttp://www.interscience.wiley.com
KeywordsDementia ; Diagnosis ; Computers ; Screening ; Postmortems ; Evaluation.
AnnotationAn accurate diagnosis of Alzheimer's disease (AD) and an exclusion of other dementias is important in many clinical studies. Obtaining such a clinical diagnosis in epidemiological studies and clinical trials that recruit large numbers of patients is time-consuming. The authors constructed a computerised algorithm to generate diagnosis of Alzheimer's disease, dementia with Lewy body (DLB), frontotemporal dementia (FTD), vascular dementia or to flag the case as needing a clinical review based on a limited number of data points taken from a largely structured interview using widely used scales. The diagnosis generated in life by the algorithm in a prospective, longitudinal study was compared to definitive diagnosis at post mortem. Post mortem diagnoses were available for 43 cases. The positive predictive value of the algorithm was greater than 95%. AD was diagnosed by the algorithm at post mortem in 36 of the cases. Two cases with FTD were wrongly diagnosed as having AD by the algorithm, 5 cases were flagged as needing a clinical review due to concomitant medical conditions of whom 4 had AD and one, who had been diagnosed clinically as having AD, was diagnosed post mortem with corticobasal degeneration. A combination of non-clinical researchers, a structured interview and a computerised algorithm is as effective at identifying AD as highly trained and skilled clinicians. (RH).
Accession NumberCPA-071206224 A
ClassmarkEA: LK7 3O: 3V: JVP: 4C

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