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Clinical Dementia Rating independently predicted conversion to dementia in a cohort of urban elderly in Brazil

Published online by Cambridge University Press:  06 November 2012

Maria Beatriz Marcondes Macedo Montaño ,
Solange Andreoni  and
Luiz Roberto Ramos
Maria Beatriz Marcondes Macedo Montaño*
Affiliation:
Departamento de Medicina Preventiva, Universidade Federal de São Paulo, São Paulo, Brazil
Solange Andreoni
Affiliation:
Departamento de Medicina Preventiva, Universidade Federal de São Paulo, São Paulo, Brazil
Luiz Roberto Ramos
Affiliation:
Departamento de Medicina Preventiva, Universidade Federal de São Paulo, São Paulo, Brazil
*
Correspondence should be addressed to: Maria Beatriz Marcondes Macedo Montaño, MD, PhD, Departamento de Medicina Preventiva, Universidade Federal de São Paulo, Rua Luiz Marthe, 125/Sorocaba, 18017-204, São Paulo, Brazil. Phone: +55-15-32274851; Fax: +55-15-32274851. Email: [email protected].
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Abstract

Background: Dementia is a major public health problem in aging populations. The Clinical Dementia Rating (CDR) classifies the severity of dementia and identifies borderline cases that supposedly have higher rates of conversion to dementia. This study aims to verify the dementia conversion rate (CR) in a subsample of an elderly cohort (70+ free of the disease), and to identify risk factors, determining whether CDR is able to predict which individuals have high likelihood of converting.

Methods: A subsample of 156 participants was clinically evaluated for dementia at baseline in which 80 patients without dementia were reassessed after 2.6 years on average to verify the conversion. The CR was analyzed according to demographic, health variables, and CDR classification at baseline, using the Poisson regression method in univariate and multivariate analyses, with exposure time as an offset variable (person-years).

Results: From those re-evaluated, 50% had CDR = 0 and a CR of 38.1/1,000 person-years and the other 50%, CDR = 0.5 (70% with sum of boxes scores ≤1, CR = 145.4/1,000 person-years and 30% > 1, CR = 216.8/1,000 person-years). CR was 91.3/1,000 person-years on average. In the multivariate analysis, when compared with those with CDR = 0, the hazard ratio of those with CDR = 0.5 was 3.82; and for those with CDR = 0.5 and sum of boxes scores >1, 5.69.

Conclusions: Conversion rate to dementia was significantly higher among those with CDR = 0.5 and even higher for those whose sum of boxes scores was >1. Therefore, CDR was able to predict which individuals had a higher likelihood of converting to dementia.

Keywords

Alzheimer's diseaseclinical assessmentrisk factorsepidemiologyMCI
Type
Research Article
Information
International Psychogeriatrics , Volume 25 , Issue 2 , February 2013 , pp. 245 - 251
Copyright
Copyright © International Psychogeriatric Association 2012

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References

Ames, D.et al. (2006). For debate: is mild cognitive impairment a clinically useful concept? Internacional Psychogeriatrics, 18, 393–414. doi:10.1017/S1041610206003929.CrossRefGoogle Scholar
Blay, S., Ramos, L. R. and Mari, J. (1988). Validity of a Brazilian Version of the Older Americans Resources and Services (OARS) Mental Health Screening Questionnaire. Journal of the American Geriatric Society, 36, 687–692.CrossRefGoogle ScholarPubMed
Breteler, M. M. (2000). Vascular risk factors for Alzheimer's disease: an epidemiologic perspective. Neurobiology of Aging, 21, 153–160. doi:10.1016/S0197-4580(99)00110-4.CrossRefGoogle ScholarPubMed
Callahan, C. M., Kathleen, S. H., Hui, S. I., Musick, B. S., Unverzagt, F. W. and Hendrie, H. C. (1996). Relationship of age, education, and occupation with dementia among a community-based sample of African Americans. Archives of Neurology, 53, 134–140.CrossRefGoogle ScholarPubMed
Cameron, A. C. and Trivedi, P. K. (1998). Regression Analysis of Count Data. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Daly, E., Zaitchik, D., Copeland, M., Schmahmann, J., Gunther, J. and Albert, M. (2000). Predicting conversion to Alzheimer disease using standardized clinical information. Archives of Neurology, 57, 675–680.CrossRefGoogle ScholarPubMed
Dickerson, B. C.et al. (2007). Clinical prediction of Alzheimer disease dementia across the spectrum of mild cognitive impairment. Archives of General Psychiatry, 64, 1443–1450.CrossRefGoogle ScholarPubMed
Farias, S. T., Mungas, D., Reed, B. R., Harvey, D. and DeCarli, C. (2009). Progression of Mild Cognitive Impairment to dementia in clinic- vs community-based cohorts. Archives of Neurology, 66, 1151–1157.CrossRefGoogle ScholarPubMed
Folstein, M. F., Folstein, S. E. and Mchugh, P. R. (1975). Mini-Mental State: a practical method for grading the cognitive state of patients for the clinicians. Journal of Psychiatric Research, 12, 189–198.CrossRefGoogle Scholar
Ganguli, M., Dodge, H. H., Chen, P., Belle, S. and Dekosky, S. T. (2000). Ten-year incidence of dementia in a rural elderly US community population (MOVIES Project). Neurology, 54, 1109–1116.CrossRefGoogle Scholar
Ganguli, M.et al. (2011). Outcomes of mild cognitive impairment by definition. Archives of Neurology, 68, 761–767. doi:10.1001/archneurol.2011.101.CrossRefGoogle ScholarPubMed
Hilbe, J. M. (2007). Negative Binomial Regression. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Hughes, C. P., Berg, L., Danziger, W. L., Coben, L. A. and Martin, R. L. A. (1982). A new clinical scale for the staging of dementia. British Journal of Psychiatry, 140, 566–572.CrossRefGoogle ScholarPubMed
Jager, C. A., Hogervorst, E., Combrinck, M. and Budge, M. M. (2003). Sensitivity and specificity of neuropsychological tests for mild cognitive impairment, vascular cognitive impairment and Alzheimer's disease. Psychological Medicine, 33, 1039–1050. doi:10.1017/S00332917033291703008031.CrossRefGoogle ScholarPubMed
Kukull, W. A.et al. (2002). Dementia and Alzheimer disease incidence, a prospective cohort study. Archives of Neurology, 59, 1737–1746.CrossRefGoogle ScholarPubMed
Lam, L.et al. (2008). Use of Clinical Dementia Rating in detecting early cognitive deficits in a community-based sample of Chinese older person in Hong Kong. Alzheimer Disease and Associated Disorders, 22, 153–157.CrossRefGoogle Scholar
Lindsay, J.et al. (2002). Risk factors for Alzheimer's disease: a prospective analysis from the Canadian Study of Health and Aging. American Journal of Epidemiology, 156, 445–453. doi:10.1093/aje/kwf074.CrossRefGoogle ScholarPubMed
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D. and Stadian, E. M. (1984). Clinical diagnosis of Alzheimer's disease: report of the NINCDS–ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's disease. Neurology, 34, 939–944.CrossRefGoogle ScholarPubMed
Montaño, M. B. M. M. and Ramos, L. R. (2005). Validade da versão em português da Clinical Dementia Rating. Revista de Saúde Pública, 39, 912–917.CrossRefGoogle ScholarPubMed
Morris, J. (1993). The clinical dementia rating: current version and scoring rules. Neurology, 43, 2412–2414.CrossRefGoogle ScholarPubMed
Nitrini, R.et al. (2004). Incidence of dementia in a community-dwelling Brazilian population. Alzheimer Disease and Associated Disorders, 18, 241–246.Google Scholar
O'Bryant, S. E.et al. (2008). Staging dementia using clinical dementia rating scale sum of boxes scores. Archives of Neurology, 65, 1091–1095.CrossRefGoogle ScholarPubMed
Petersen, R. C. (2007). Mild cognitive impairment: current research and clinical implications. Seminars in Neurology, 27, 22–31.CrossRefGoogle ScholarPubMed
Qiu, C. X., De Ronchi, D. and Fratiglioni, L. (2007). The epidemiology of the dementias: an update. Current Opinion in Psychiatry, 20, 380–385.CrossRefGoogle ScholarPubMed
Ramos, L. R.et al. (1998) Two-year follow-up study of elderly residents in S. Paulo, Brazil: methodology and preliminary results. Revista de Saúde Pública, 32, 397–407.CrossRefGoogle Scholar
Ramos, L. R., Simões, E. J. and Albert, M. S. (2001). Dependence in activities of daily living and cognitive impairment strongly predicted mortality in older urban residents in Brazil: a 2-year follow-up. Journal of the American Geriatrics Society, 49, 1168–1175.CrossRefGoogle ScholarPubMed
Ravaglia, G.et al. (2005). Incidence and etiology of dementia in a large elderly Italian population. Neurology, 64, 1525–1530. doi:10.1212/01.WNL.0000160107.02316.CrossRefGoogle Scholar
Rosen, W. G. (1980). Verbal fluency in aging and dementia. Journal of Clinical Neuropsychology, 2, 135–146.CrossRefGoogle Scholar
Ruff, R. M., Light, R. H. and Quayhagen, M. (1989). Selective reminding test: a normative study of verbal learning in adults. Journal of Clinical and Experimental Neuropsychology, 11, 539–550.CrossRefGoogle Scholar
Shulman, K., Shedletsky, R. and Silver, I. L. (1986). The challenge of time: clock drawing and cognitive functioning in the elderly. International Journal of Geriatric Psychiatry, 1, 135–140.CrossRefGoogle Scholar