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Validity of the Mindstreams™ computerized cognitive battery for mild cognitive impairment

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An Erratum to this article was published on 19 March 2008

Abstract

The NeuroTrax Mindstreams™ computerized cognitive assessment system was designed for widespread clinical and research use in detecting mild cognitive impairment (MCI). However, the capability of Mindstreams tests to discriminate the elderly with MCI from those who are cognitively healthy has yet to be evaluated. Moreover, the comparability between these tests and traditional neuropsychological tests in detecting MCI has not been examined. A two-center study was designed to assess the discriminant validity of tests in the Mindstreams Mild Impairment Battery. Participants were 30 individuals diagnosed with MCI, 29 with mild Alzheimer’s disease (AD), and 39 healthy elderly. Testing was with the Mindstreams battery and traditional neuropsychological tests. Receiver operating characteristic (ROC) analysis was used to examine the ability of Mindstreams and traditional measures to discriminate those with MCI from cognitively healthy elderly. Between-group comparisons were made (Mann-Whitney U test) between MCI and healthy elderly and between MCI and mild AD groups. Mindstreams outcome parameters across multiple cognitive domains significantly discriminated between MCI and healthy elders with considerable effect sizes (p<0.05). Measures of memory, executive function, visual spatial skills, and verbal fluency discriminated best, and discriminability was at least comparable to that of traditional neuropsychological tests in these domains. Mindstreams tests are effective in detecting MCI, providing a comprehensive profile of cognitive function. Further, the enhanced precision and ease of use of these computerized tests make the NeuroTrax system a valuable clinical tool in the identification of elders at high risk for dementia.

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References

  • Albert M. S., Moss M. B., Tanzi R., and Jones K. (2001) Preclinical prediction of AD using neuropsychological tests. J. Int. Neuropsychol. Soc. 7, 631–639.

    Article  PubMed  CAS  Google Scholar 

  • Bischkopf J., Busse A., and Angermeyer M. C. (2002) Mild cognitive impairment-a review of prevalence, incidence and outcome according to current approaches. Acta Psychiatr. Scand. 106, 403–414.

    Article  PubMed  CAS  Google Scholar 

  • Bozoki A., Giordani B., Heidebrink J. L., Berent S., and Foster N. L. (2001) Mild cognitive impairments predict dementia in nondemented elderly patients with memory loss. Arch. Neurol. 58, 411–416.

    Article  PubMed  CAS  Google Scholar 

  • Burns A. and Zaudig M. (2002) Mild cognitive impairment in older people. Lancet, 360, 1963–1965.

    Article  PubMed  Google Scholar 

  • Cauraugh J. H. (1990) Speed-accuracy tradeoff during response preparation. Res. Q. Exerc. Sport 61, 331–337.

    PubMed  CAS  Google Scholar 

  • Chen P., Ratcliff G., Belle S. H., Cauley J. A., DeKosky S. T., and Ganguli M. (2000) Cognitive tests that best discriminate between presymptomatic AD and those who remain nondemented. Neurology 55, 1847–1853.

    PubMed  CAS  Google Scholar 

  • Daly E., Zaitchik D., Copeland M., Schmahmann J., Gunther J., and Albert M. (2000) Predicting conversion to Alzheimer disease using standardized clinical information. Arch. Neurol. 57, 675–680.

    Article  PubMed  CAS  Google Scholar 

  • Darby D., Maruff P., Collie A., and McStephen M. (2002) Mild cognitive impairment can be detected by multiple assessments in a single day. Neurology 59, 1042–1046.

    Article  PubMed  CAS  Google Scholar 

  • Elwood R. W. (2001) MicroCog: assessment of cognitive functioning. Neuropsychol. Rev. 11, 89–100.

    Article  PubMed  CAS  Google Scholar 

  • Flicker C., Ferris S. H., and Reisberg B. (1991) Mild cognitive impairment in the elderly: predictors of dementia. Neurology 41, 1006–1009.

    PubMed  CAS  Google Scholar 

  • Folstein M. F., Folstein S. E., McHugh P. R. (1975) Minimental state: a practical method for grading the cognitive state of patients for the clinician. J. Psych. Res. 12, 189–198.

    Article  CAS  Google Scholar 

  • Fowler K. S., Saling M. M., Conway E. L., Semple J. M., and Louis W. J. (2002) Paired associate performance in the early detection of DAT. J. Int. Neuropsychol. Soc. 8, 58–71.

    Article  PubMed  Google Scholar 

  • Green R. C., Green J., Harrison J. M., and Kutner M. H. (1994) Screening for cognitive impairment in older individuals. Validation study of a computer-based test. Arch. Neurol. 51, 779–786.

    PubMed  CAS  Google Scholar 

  • Hanninen T., Hallikainen M., Koivisto K., Helkala E. L., Reinikainen K. J., Soininen H., et al. (1995) A follow-up study of age-associated memory impairment: neuropsychological predictors of dementia. J. Am. Geriatr. Soc. 43, 1007–1015.

    PubMed  CAS  Google Scholar 

  • Jacobs D. M., Sano M., Dooneief G., Marder K., Bell K. L., and Stern Y. (1995) Neuropsychological detection and characterization of preclinical Alzheimer’s disease. Neurology 45, 957–962.

    PubMed  CAS  Google Scholar 

  • Kabani N. J., Sled J. G., Shuper A., and Chertkow H. (2002) Regional magnetization transfer ratio changes in mild cognitive impairment. Magn. Reson. Med. 47, 143–148.

    Article  PubMed  Google Scholar 

  • Kawas C. H., Corrada M. M., Brookmeyer R., Morrison A., Resnick S. M., Zonderman A. B., and Arenberg D. (2003) Visual memory predicts Alzheimer’s disease more than a decade before diagnosis. Neurology 60, 1089–1093.

    Article  PubMed  CAS  Google Scholar 

  • Levy R. (1994) Aging-associated cognitive decline. Working Party of the International Psychogeriatric Association in collaboration with the World Health Organization. Int. Psychogeriatr. 6, 63–68.

    Article  PubMed  CAS  Google Scholar 

  • MacLeod C. M. (1991) Half a century of research on the Stroop effect: an integrative review. Psychol. Bull. 109, 163–203.

    Article  PubMed  CAS  Google Scholar 

  • Mapstone M., Steffenella T. M., and Duffy C. J. (2003) A visuospatial variant of mild cognitive impairment: getting lost between aging and AD. Neurology 60, 802–808.

    Article  PubMed  Google Scholar 

  • Massoud F., Chertkow H., Whitehead V., Overbury O., and Bergman H. (2002) Word-reading thresholds in Alzheimer disease and mild memory loss: a pilot study. Alzheimer Dis. Assoc. Disord. 16, 31–39.

    Article  PubMed  Google Scholar 

  • Mohs R., Rosen W., Davis K. (1983) The Alzheimers disease assessment scale: an instrument for assessing treatment efficacy. Psychopharm. Bull. 19, 448–450.

    CAS  Google Scholar 

  • NeuroTrax Corporation (2003) Mindstreams cognitive health assessment. http://www.mindstreamshealth.com/content/mssupmat.pdf (electronic citation).

  • Olichney J. M., Morris S. K., Ochoa C., Salmon D. P., Thal L. J., Kutas M., and Iragui V. J. (2002) Abnormal verbal event related potentials in mild cognitive impairment and incipient Alzheimer’s disease. J. Neurol. Neurosurg. Psychiatry 73, 377–384.

    Article  PubMed  CAS  Google Scholar 

  • Petersen R. C., Doody R., Kurz A., Mohs R. C., Morris J. C., Rabins P. V., et al. (2001) Current concepts in mild cognitive impairment. Arch. Neurol. 58, 1985–1992.

    Article  PubMed  CAS  Google Scholar 

  • Petersen R. C., Smith G. E., Waring S. C., Ivnik R. J., Tangalos E. G., and Kokmen E. (1999) Mild cognitive impairment: clinical characterization and outcome. Arch. Neurol. 56, 303–308.

    Article  PubMed  CAS  Google Scholar 

  • Petersen R. C., Stevens J. C., Ganguli M., Tangalos E. G., Cummings J. L., and DeKosky S. T. (2001) Practice parameter: early detection of dementia: mild cognitive impairment (an evidence-based review). Report of the Quality Standards Subcommittee of the American Academy of Neurology. Neurology 56, 1133–1142.

    PubMed  CAS  Google Scholar 

  • Powell D. H., Kaplan E. F., Whitla D., Weintraub S., Catlin R., and Funkenstein H. H. (1993) Microcog: assessment of cognitive functioning [2.1] (computer program). The Psychological Corporation, San Antonio, TX.

    Google Scholar 

  • Reid W., Broe G., Creasey H., Grayson D., McCusker E., Bennett H., et al. (1996) Age at onset and pattern of neuropsychological impairment in mild early-stage Alzheimer disease. A study of a community-based population. Arch. Neurol. 53, 1056–1061.

    PubMed  CAS  Google Scholar 

  • Ritchie K., Artero S., and Touchon J. (2001) Classification criteria for mild cognitive impairment: a population-based validation study. Neurology 56, 37–42.

    PubMed  CAS  Google Scholar 

  • Tierney M. C., Szalai J. P., Snow W. G., Fisher R. H., Nores A., Nadon G., et al. (1996) Prediction of probable Alzheimer’s disease in memory-impaired patients: A prospective longitudinal study. Neurology 46, 661–665.

    PubMed  CAS  Google Scholar 

  • Xu G., Meyer J. S., Thornby J., Chowdhury M., and Quach M. (2002) Screening for mild cognitive impairment (MCI) utilizing combined mini-mental-cognitive capacity examinations for identifying dementia prodromes. Int. J. Geriatr. Psychiatry 17, 1027–1033.

    Article  PubMed  Google Scholar 

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Correspondence to Howard Chertkow.

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An erratum to this article is available at http://dx.doi.org/10.1007/s12031-007-9031-9.

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Dwolatzky, T., Whitehead, V., Doniger, G.M. et al. Validity of the Mindstreams™ computerized cognitive battery for mild cognitive impairment. J Mol Neurosci 24, 33–44 (2004). https://doi.org/10.1385/JMN:24:1:033

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