Abstract
Early detection of Alzheimer's disease and related disorders in Japan is increasingly important. The Mild Cognitive Impairment Screen (MCIS)—derived from the National Institute of Aging CERAD neuropsychologic battery—differentiates normal aging from MCI and mild dementia with 97.3% and 99% accuracy, respectively. The Japanese MCIS (JMCIS), Mini-Mental State Examination (MMSE), quantitative SPECT (qSP), and quantitative MRI (qMRI) were used to classify 63 outpatients at Fukuoka University Hospital who were either normal or had MCI based on Clinical Dementia Rating scores of 0 and 0.5, respectively. Performance statistics for the JMCIS, MMSE, qSP, and qMRI were, respectively: (1) accuracy = 0.964, 0.768, 0.722, 0.733; (2) sensitivity = 0.958, 0.792, 0.688, 0.700; (3) specificity = 1.000, 0.625, 1.000, 1.000; and (4) κ validity = 0.813, 0.420, 0.296, 0.308. This initial study shows negligible differences between the English and Japanese MCIS, supporting its potential use for early detection in Japan.
Keywords: MCI Screen, MMSE, Neuroimaging, early detection, mild cognitive impairment, Alzheimer's disease and related disorders
Full Text
The Full Text of this article is available as a PDF (63.2 KB).
Contributor Information
Ai Cho, Department of Neurology, Fukuoka University School of Medicine, Fukuoka, Japan.
Mika Sugimura, Department of Neurology, Fukuoka University School of Medicine, Fukuoka, Japan.
Seigo Nakano, Department of Neurology, Fukuoka University School of Medicine, Fukuoka, Japan.
Tatsuo Yamada, Department of Neurology, Fukuoka University School of Medicine, Fukuoka, Japan, tyamada@fukuoka-u.ac.jp .
References
- Life Expectancies at Specified Ages, Abridged Life Tables for Japan 2006. Japanese Ministry of Health, Labor and Welfare. [Google Scholar]
- Population Statistics 2006. Japanese Ministry of Health, Labor and Welfare. [Google Scholar]
- Population Statistics of Japan 2006. National Institute of Population and Social Security Research, March 2006. [Google Scholar]
- Shankle WR, Romney AK, Hara J., et al. Method to improve the detection of mild cognitive impairment . Proc Natl Acad Sci USA. 2005;102:4919-4924. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Trenkle D., Shankle WR, Azen SP Detecting cognitive impairment in primary care: performance assessment of three screening instruments. J Alzheimers Dis. 2007;11: 323-335. [DOI] [PubMed] [Google Scholar]
- Morris JC Clinical dementia rating: a reliable and valid diagnostic and staging measure for dementia of the Alzheimer type. Int Psychogeriatr. 1997;9(suppl 1): S173-S176; discussion 177-178. [DOI] [PubMed] [Google Scholar]
- Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E. Mild cognitive impairment: clinical characterization and outcome. Arch Neurol. 1999;56: 303-308. [DOI] [PubMed] [Google Scholar]
- Beinhoff U., Hilbert V., Bittner D., Gron G., Riepe MW Screening for cognitive impairment: a triage for outpatient care. Dement Geriatr Cogn Disord. 2005;20:278-285. [DOI] [PubMed] [Google Scholar]
- Matsuda H., Mizumura S., Nagao T., et al. Automated discrimination between very early Alzheimer's disease and controls using an easy Z-score imaging system for multi-center brain perfusion single-photon emission tomography. AJNR Am J Neuroradiol. 2007;28:731-736. [PMC free article] [PubMed] [Google Scholar]
- Hirata Y., Matsuda H., Nemoto K., et al. Voxel-based morphometry to discriminate early Alzheimer's disease from controls. Neurosci Lett. 2005;382:269-274. [DOI] [PubMed] [Google Scholar]
- Dubois B., Feldman HH, Jacova C., et al. Research criteria for the diagnosis of Alzheimer's disease: revising the NINDCS-ADRDA criteria. Lancet Neurol. 2007;6: 734-746. [DOI] [PubMed] [Google Scholar]