Literature DB >> 19784754

Prediction of Alzheimer dementia with short neuropsychological instruments.

Susanne Jungwirth1, Sonja Zehetmayer, Peter Bauer, Silvia Weissgram, Karl Heinz Tragl, Peter Fischer.   

Abstract

The aim of this study was to evaluate the neuropsychological instruments in predicting Alzheimer dementia after 5 years in the context of a longitudinal population-based cohort study. A total of 585 nondemented 75-year-old individuals completed neuropsychological examination at the baseline investigation; 479 subjects were followed after 30 months and 404 after 60 months. Cognition, depression and memory complaints were evaluated with psychometric instruments. Known risk factors for Alzheimer dementia were included in the analyses. Univariate logistic regression analyses and stepwise multiple models were calculated. A combination of reduced verbal memory, reduced visual motor speed, subjective memory complaints and the APOE epsilon4 carriage was best in predicting incident probable Alzheimer dementia (R(2) = 0.42, ROC curve = 0.91). The model achieved a positive predictive value of 23.3%, a negative predictive value of 98.7%, a sensitivity of 82.8% and a specificity of 82.4%. Alzheimer dementia can be predicted by neuropsychological instruments measuring episodic memory and motor speed. A high percentage of 98.7% subjects at age 75 years could be predicted as remaining non-demented at age 80 years. The prediction of those unlikely to develop AD would be more important in the future to spare further expensive diagnostic testing and protective therapies in individuals at low risk.

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Year:  2009        PMID: 19784754     DOI: 10.1007/s00702-009-0318-6

Source DB:  PubMed          Journal:  J Neural Transm (Vienna)        ISSN: 0300-9564            Impact factor:   3.575


  33 in total

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2.  Conversion from subtypes of mild cognitive impairment to Alzheimer dementia.

Authors:  P Fischer; S Jungwirth; S Zehetmayer; S Weissgram; S Hoenigschnabl; E Gelpi; W Krampla; K H Tragl
Journal:  Neurology       Date:  2007-01-23       Impact factor: 9.910

3.  The course of adult intellectual development.

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4.  The Seattle Longitudinal Study: a thirty-five-year inquiry of adult intellectual development.

Authors:  K W Schaie
Journal:  Z Gerontol       Date:  1993 May-Jun

5.  Normal ranges of neuropsychological tests for the diagnosis of Alzheimer's disease.

Authors:  M Berres; A U Monsch; F Bernasconi; B Thalmann; H B Stähelin
Journal:  Stud Health Technol Inform       Date:  2000

6.  Vienna Transdanube Aging "VITA": study design, recruitment strategies and level of participation.

Authors:  P Fischer; S Jungwirth; W Krampla; S Weissgram; W Kirchmeyr; W Schreiber; K Huber; M Rainer; P Bauer; K H Tragl
Journal:  J Neural Transm Suppl       Date:  2002

7.  The preclinical phase of alzheimer disease: A 22-year prospective study of the Framingham Cohort.

Authors:  M F Elias; A Beiser; P A Wolf; R Au; R F White; R B D'Agostino
Journal:  Arch Neurol       Date:  2000-06

8.  Neuropathology of cognitively normal elderly.

Authors:  D S Knopman; J E Parisi; A Salviati; M Floriach-Robert; B F Boeve; R J Ivnik; G E Smith; D W Dickson; K A Johnson; L E Petersen; W C McDonald; H Braak; R C Petersen
Journal:  J Neuropathol Exp Neurol       Date:  2003-11       Impact factor: 3.685

9.  The Consortium to Establish a Registry for Alzheimer's Disease (CERAD). Part I. Clinical and neuropsychological assessment of Alzheimer's disease.

Authors:  J C Morris; A Heyman; R C Mohs; J P Hughes; G van Belle; G Fillenbaum; E D Mellits; C Clark
Journal:  Neurology       Date:  1989-09       Impact factor: 9.910

10.  Risk factors for Alzheimer's disease: a prospective analysis from the Canadian Study of Health and Aging.

Authors:  Joan Lindsay; Danielle Laurin; René Verreault; Réjean Hébert; Barbara Helliwell; Gerry B Hill; Ian McDowell
Journal:  Am J Epidemiol       Date:  2002-09-01       Impact factor: 4.897

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  11 in total

1.  Alzheimer disease: are we intervening too late? Pro.

Authors:  Virginia Olga B Emery
Journal:  J Neural Transm (Vienna)       Date:  2011-06-07       Impact factor: 3.575

Review 2.  Dementia risk prediction in the population: are screening models accurate?

Authors:  Blossom C M Stephan; Tobias Kurth; Fiona E Matthews; Carol Brayne; Carole Dufouil
Journal:  Nat Rev Neurol       Date:  2010-05-25       Impact factor: 42.937

3.  Prediction of dementia in primary care patients.

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Journal:  PLoS One       Date:  2011-02-18       Impact factor: 3.240

4.  Molecular neuropsychology: creation of test-specific blood biomarker algorithms.

Authors:  Sid E O'Bryant; Guanghua Xiao; Robert Barber; C Munro Cullum; Myron Weiner; James Hall; Melissa Edwards; Paula Grammas; Kirk Wilhelmsen; Rachelle Doody; Ramon Diaz-Arrastia
Journal:  Dement Geriatr Cogn Disord       Date:  2013-01-03       Impact factor: 2.959

5.  Neuropsychological predictors of dementia in late-life major depressive disorder.

Authors:  Guy G Potter; H Ryan Wagner; James R Burke; Brenda L Plassman; Kathleen A Welsh-Bohmer; David C Steffens
Journal:  Am J Geriatr Psychiatry       Date:  2013-03       Impact factor: 4.105

6.  Comparison of brief cognitive tests and CSF biomarkers in predicting Alzheimer's disease in mild cognitive impairment: six-year follow-up study.

Authors:  Sebastian Palmqvist; Joakim Hertze; Lennart Minthon; Carina Wattmo; Henrik Zetterberg; Kaj Blennow; Elisabet Londos; Oskar Hansson
Journal:  PLoS One       Date:  2012-06-22       Impact factor: 3.240

Review 7.  Dementia risk estimates associated with measures of depression: a systematic review and meta-analysis.

Authors:  Nicolas Cherbuin; Sarang Kim; Kaarin J Anstey
Journal:  BMJ Open       Date:  2015-12-21       Impact factor: 2.692

8.  Combining Cognitive, Genetic, and Structural Neuroimaging Markers to Identify Individuals with Increased Dementia Risk.

Authors:  Nicola M Payton; Grégoria Kalpouzos; Debora Rizzuto; Laura Fratiglioni; Miia Kivipelto; Lars Bäckman; Erika J Laukka
Journal:  J Alzheimers Dis       Date:  2018       Impact factor: 4.472

9.  Influence of age and education on the processing of clustering and switching in verbal fluency tasks.

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10.  Prediction of dementia risk in low-income and middle-income countries (the 10/66 Study): an independent external validation of existing models.

Authors:  Blossom C M Stephan; Eduwin Pakpahan; Mario Siervo; Silvan Licher; Graciela Muniz-Terrera; Devi Mohan; Daisy Acosta; Guillermina Rodriguez Pichardo; Ana Luisa Sosa; Isaac Acosta; Juan J Llibre-Rodriguez; Martin Prince; Louise Robinson; Matthew Prina
Journal:  Lancet Glob Health       Date:  2020-04       Impact factor: 38.927

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