Hostname: page-component-78c5997874-xbtfd Total loading time: 0 Render date: 2024-11-16T18:21:15.120Z Has data issue: false hasContentIssue false
  • English
  • Français

Cognitive test performance predicts change in functional status at the population level: The MYHAT Project

Published online by Cambridge University Press:  08 July 2010

MARY GANGULI ,
JONI VANDER BILT ,
CHING-WEN LEE ,
BETH E. SNITZ ,
CHUNG-CHOU H. CHANG ,
DAVID A. LOEWENSTEIN  and
JUDITH A. SAXTON
MARY GANGULI*
Affiliation:
Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania Department of Epidemiology, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania
JONI VANDER BILT
Affiliation:
Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
CHING-WEN LEE
Affiliation:
Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
BETH E. SNITZ
Affiliation:
Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
CHUNG-CHOU H. CHANG
Affiliation:
Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania Department of Biostatistics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania
DAVID A. LOEWENSTEIN
Affiliation:
Department of Psychiatry, University of Miami Miller School of Medicine, Miami, Florida
JUDITH A. SAXTON
Affiliation:
Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
*
*Correspondence and reprint requests to: Mary Ganguli, Western Psychiatric Institute and Clinic, 3811 O’Hara Street, Pittsburgh, PA, 15213. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

In the community at large, many older adults with minimal cognitive and functional impairment remain stable or improve over time, unlike patients in clinical research settings, who typically progress to dementia. Within a prospective population-based study, we identified neuropsychological tests predicting improvement or worsening over 1 year in cognitively driven everyday functioning as measured by Clinical Dementia Rating (CDR). Participants were 1682 adults aged 65+ and dementia-free at baseline. CDR change was modeled as a function of baseline test scores, adjusting for demographics. Among those with baseline CDR = 0.5, 29.8% improved to CDR = 0; they had significantly better baseline scores on most tests. In a stepwise multiple logistic regression model, tests which remained independently associated with subsequent CDR improvement were Category Fluency, a modified Token Test, and the sum of learning trials on Object Memory Evaluation. In contrast, only 7.1% with baseline CDR = 0 worsened to CDR = 0.5. They had significantly lower baseline scores on most tests. In multiple regression analyses, only the Mini-Mental State Examination, delayed memory for visual reproduction, and recall susceptible to proactive interference, were independently associated with CDR worsening. At the population level, changes in both directions are observable in functional status, with different neuropsychological measures predicting the direction of change. (JINS, 2010, 16, 761–770.)

Keywords

EpidemiologyCommunityAgingClinical dementia ratingCognitionPrediction
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 16 , Issue 5 , September 2010 , pp. 761 - 770
Copyright
Copyright © The International Neuropsychological Society 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Benton, A.L., & Hamsher, K.D. (1989). Multilingual aphasia examination (3rd ed.). Iowa City: AJA Associates.Google Scholar
Bruscoli, M., & Lovestone, S. (2004). Is MCI really just early dementia? A systematic review of conversion studies. International Psychogeriatrics, 16, 129–140.CrossRefGoogle ScholarPubMed
Busse, A., Hensel, A., Guhne, U., Angermeyer, M.C., & Riedel-Heller, S.G. (2006). Mild cognitive impairment: Long-term course of four clinical subtypes. Neurology, 67, 2176–2185.CrossRefGoogle ScholarPubMed
DeCarli, C., Mungas, D., Harvey, D., Reed, B., Weiner, M., Chui, H., et al. . (2004). Memory impairment, but not cerebrovascular disease, predicts progression of MCI to dementia. Neurology, 63, 220–227.CrossRefGoogle Scholar
Farias, S.T., Mungas, D., Reed, B.R., Harvey, D., & DeCarli, C. (2009). Progression of mild cognitive impairment to dementia in clinic- vs. community-based cohorts. Archives of Neurology, 66, 1151–1157.CrossRefGoogle ScholarPubMed
Fleisher, A.S., Sowell, B.B., Taylor, C., Gamst, A.C., Petersen, R.C., Thal, L.J., et al. . (2007). Clinical predictors of progression to Alzheimer disease in amnestic mild cognitive impairment. Neurology, 68, 1588–1595.CrossRefGoogle ScholarPubMed
Folstein, M.F., Folstein, S.E., & McHugh, P.R. (1975). Mini-mental state: A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–198.CrossRefGoogle Scholar
Freedman, M., Leach, L., Kaplan, E., Winocur, G., Shulman, K.I., & Delis, D. (1994). Clock drawing: A neuropsychological analysis. New York: Oxford University Press.Google Scholar
Fuld, P.A. (1981). Fuld object-memory evaluation. Woodale, IL: Stoelting Company.Google Scholar
Ganguli, M., Chang, C.-C.H., Snitz, B.E., Saxton, J.A., Vander Bilt, J., & Lee, C.-W. (2010). Prevalence of mild cognitive impairment by multiple classifications: The MYHAT project. American Journal of Geriatric Psychiatry, [Epub ahead of print].CrossRefGoogle ScholarPubMed
Ganguli, M., Dodge, H.H., Chen, P., Belle, S., & DeKosky, S.T. (2000). Ten-year incidence of dementia in a rural elderly US community population: The MoVIES Project. Neurology, 54, 1109–1116.CrossRefGoogle Scholar
Ganguli, M., Dodge, H.H., Shen, C., & DeKosky, S.T. (2004). Mild cognitive impairment, amnestic type: An epidemiologic study. Neurology, 63, 115–121.CrossRefGoogle ScholarPubMed
Ganguli, M., Snitz, B., Vander Bilt, J., & Chang, C.C. (2009). How much do depressive symptoms affect cognition at the population level? The Monongahela-Youghiogheny Healthy Aging Team (MYHAT) study. International Journal of Geriatric Psychiatry, 24, 1277–1284.CrossRefGoogle ScholarPubMed
Ganguli, M., Snitz, B.E., Lee, C.-W., Vander Bilt, J., Saxton, J.A., & Chang, C.-C.H. (2010). Age and education effects and norms on a cognitive test battery from a population-based cohort: The Monongahela -Youghiogheny Healthy Aging Team (MYHAT). Aging and Mental Health, 14, 109–116.CrossRefGoogle Scholar
Grober, E., Hall, C.B., Lipton, R.B., Zonderman, A.B., Resnick, S.M., & Kawas, C. (2008). Memory impairment, executive dysfunction, and intellectual decline in preclinical Alzheimer’s disease. Journal of the International Neuropsychological Society, 14, 266–278.CrossRefGoogle ScholarPubMed
Howieson, D.B., Carlson, N.E., Moore, M.M., Wasserman, D., Abendroth, C.D., Payne-Murphy, J., et al. . (2008). Trajectory of mild cognitive impairment onset. Journal of the International Neuropsychological Society, 14, 192–198.CrossRefGoogle ScholarPubMed
Hughes, C.P., Berg, L., Danziger, W.L., Coben, L.A., & Martin, R.L. (1982). A new clinical scale for the staging of dementia. British Journal of Psychiatry, 140, 566–572.CrossRefGoogle ScholarPubMed
Iwasa, H., Gondo, Y., Yoshida, Y., Kwon, J., Inagaki, H., Kawaai, C., et al. . (2008). Cognitive performance as a predictor of functional decline among the non-disabled elderly dwelling in a Japanese community: A 4-year population-based prospective cohort study. Archives of Gerontology & Geriatrics, 47, 139–149.CrossRefGoogle Scholar
Jack, C.R. Jr., Shiung, M.M., Weigand, S.D., O’Brien, P.C., Gunter, J.L., Boeve, B.F., et al. . (2005). Brain atrophy rates predict subsequent clinical conversion in normal elderly and amnestic MCI. Neurology, 65, 1227–1231.CrossRefGoogle ScholarPubMed
Kaplan, E.F., Goodglass, H., & Weintraub, S. (1978). The Boston naming test. Boston: E. Kaplan & H. Goodglass.Google Scholar
Kluger, A., Ferris, S.H., Golomb, J., Mittelman, M.S., & Reisberg, B. (1999). Neuropsychological prediction of decline to dementia in nondemented elderly. Journal of Geriatric Psychiatry & Neurology, 12, 168–179.CrossRefGoogle ScholarPubMed
Larrieu, S., Letenneur, L., Orgogozo, J.M., Fabrigoule, C., Amieva, H., Le Carret, N., et al. . (2002). Incidence and outcome of mild cognitive impairment in a population-based prospective cohort. Neurology, 59, 1594–1599.CrossRefGoogle Scholar
Loewenstein, D.A., Acevedo, A., Agron, J., & Duara, R. (2007). Stability of neurocognitive impairment in different subtypes of mild cognitive impairment. Dementia & Geriatric Cognitive Disorders, 23, 82–86.CrossRefGoogle ScholarPubMed
Loewenstein, D.A., Acevedo, A., Luis, C., Crum, T., Barker, W.W., & Duara, R. (2004). Semantic interference deficits and the detection of mild Alzheimer’s disease and mild cognitive impairment without dementia. Journal of the International Neuropsychological Society, 10, 91–100.CrossRefGoogle ScholarPubMed
Loewenstein, D.A., Acevedo, A., Schram, L., Ownby, R., White, G., Mogosky, B., et al. . (2003). Semantic interference in mild Alzheimer disease: Preliminary findings. American Journal of Geriatric Psychiatry, 11, 252–255.CrossRefGoogle ScholarPubMed
Loewenstein, D.A., Acevedo, A., Small, B.J., Agron, J., Crocco, E., & Duara, R. (2009). Stability of different subtypes of mild cognitive impairment among the elderly over a 2- to 3-year follow-up period. Dementia & Geriatric Cognitive Disorders, 27, 418–423.CrossRefGoogle Scholar
Manly, J.J., Jacobs, D.M., Touradji, P., Small, S.A., & Stern, Y. (2002). Reading level attenuates differences in neuropsychological test performance between African American and White elders. Journal of the International Neuropsychological Society, 8, 341–348.CrossRefGoogle ScholarPubMed
Manly, J.J., Tang, M.X., Schupf, N., Stern, Y., Vonsattel, J.P., & Mayeux, R. (2008). Frequency and course of mild cognitive impairment in a multiethnic community. Annals of Neurology, 63, 494–506.CrossRefGoogle Scholar
Marquis, S., Moore, M.M., Howieson, D.B., Sexton, G., Payami, H., Kaye, J.A., et al. . (2002). Independent predictors of cognitive decline in healthy elderly persons. Archives of Neurology, 59, 601–606.CrossRefGoogle ScholarPubMed
Mitchell, A.J., & Shiri-Feshki, M. (2009). Rate of progression of mild cognitive impairment to dementia–meta-analysis of 41 robust inception cohort studies. Acta Psychiatrica Scandinavica, 119, 252–265.CrossRefGoogle ScholarPubMed
Morris, J.C. (1993). The Clinical Dementia Rating (CDR): Current version and scoring rules. Neurology, 43, 2412–2414.CrossRefGoogle ScholarPubMed
Morris, J.C. (2006). Mild cognitive impairment is early-stage Alzheimer disease: Time to revise diagnostic criteria. Archives of Neurology, 63, 15–16.CrossRefGoogle ScholarPubMed
Mungas, D., Marshall, S.C., Weldon, M., Haan, M., & Reed, B.R. (1996). Age and education correction of Mini-Mental State Examination for English and Spanish-speaking elderly. Neurology, 46, 700–706.CrossRefGoogle ScholarPubMed
Ott, A., Breteler, M.M., van Harskamp, F., Claus, J.J., van der Cammen, T.J., Grobbee, D.E., et al. . (1995). Prevalence of Alzheimer’s disease and vascular dementia: Association with education. The Rotterdam study. BMJ, 310, 970–973.CrossRefGoogle ScholarPubMed
Palmer, K., Berger, A.K., Monastero, R., Winblad, B., Backman, L., & Fratiglioni, L. (2007). Predictors of progression from mild cognitive impairment to Alzheimer disease. Neurology, 68, 1596–1602.CrossRefGoogle ScholarPubMed
Palmer, K., Wang, H.X., Backman, L., Winblad, B., & Fratiglioni, L. (2002). Differential evolution of cognitive impairment in nondemented older persons: Results from the Kungsholmen Project. American Journal of Psychiatry, 159, 436–442.CrossRefGoogle ScholarPubMed
Petersen, R.C., Smith, G.E., Waring, S.C., Ivnik, R.J., Tangalos, E.G., & Kokmen, E. (1999). Mild cognitive impairment: Clinical characterization and outcome. Archives of Neurology, 56, 303–308.CrossRefGoogle ScholarPubMed
Petersen, R.C. (2004). Mild cognitive impairment as a diagnostic entity. Journal of Internal Medicine, 256, 183–194.CrossRefGoogle ScholarPubMed
Petersen, R.C., Roberts, R.O., Knopman, D.S., Boeve, B.F., Geda, Y.E., Ivnik, R.J., et al. . (2009). Mild cognitive impairment: Ten years later. Archives of Neurology. 66, 1447–1455.CrossRefGoogle ScholarPubMed
Prince, M. (2000). Methodological issues for population-based research into dementia in developing countries. A position paper from the 10/66 Dementia Research Group. International Journal of Geriatric Psychiatry, 15, 21–30.3.0.CO;2-5>CrossRefGoogle ScholarPubMed
Reitan, R.M. (1955). The relation of the Trailmaking Test to organic brain damage. Journal of Consulting Psychology, 19, 393–394.CrossRefGoogle Scholar
Ritchie, K., Artero, S., & Touchon, J. (2001). Classification criteria for mild cognitive impairment: A population-based validation study. Neurology, 56, 37–42.CrossRefGoogle ScholarPubMed
SAS Institute. (2002). SAS v. 9.2. Cary, North Carolina.Google Scholar
Saxton, J., Snitz, B.E., Lopez, O.L., Ives, D.G., Dunn, L.O., Fitzpatrick, A., et al. . (2009). Functional and cognitive criteria produce different rates of mild cognitive impairment and conversion to dementia. Journal of Neurology, Neurosurgery, & Psychiatry, 80, 737–743.CrossRefGoogle ScholarPubMed
Snitz, B.E., Loewenstein, D.A., Chang, C.-C.H., Lee, C.-W., Vander Bilt, J., Saxton, J.A., et al. . (2010). A novel approach to assessing memory at the population level: Vulnerability to semantic interference. International Psychogeriatrics, [Epub ahead of print].CrossRefGoogle ScholarPubMed
Snitz, B.E., Unverzagt, F.W., Chang, C.-C.H., Vander Bilt, J., Gao, S., Saxton, J., et al. . (2009). Effects of age, gender, education, and race on two language tests of language ability in community-based older adults. International Psychogeriatrics, 21, 1051–1062.CrossRefGoogle ScholarPubMed
Solfrizzi, V., Panza, F., Colacicco, A.M., D’Introno, A., Capurso, C., Torres, F., et al. . (2004). Vascular risk factors, incidence of MCI, and rates of progression to dementia. Neurology, 63, 1882–1891.CrossRefGoogle ScholarPubMed
Tabert, M.H., Manly, J.J., Liu, X., Pelton, G.H., Rosenblum, S., Jacobs, M., et al. . (2006). Neuropsychological prediction of conversion to Alzheimer disease in patients with mild cognitive impairment. Archives of General Psychiatry, 63, 916–924.CrossRefGoogle ScholarPubMed
Teng, E., Lu, P.H., & Cummings, J.L. (2007). Neuropsychiatric symptoms are associated with progression from mild cognitive impairment to Alzheimer’s disease. Dementia & Geriatric Cognitive Disorders, 24, 253–259.CrossRefGoogle ScholarPubMed
Unverzagt, F.W., Farlow, M.R., & Hendrie, H.C. (1999). Clinical utility of new visual learning memory and language subtests for use in the CERAD neuropsychological battery. Journal of the International Neuropsychological Society, 5, 129.CrossRefGoogle Scholar
Washington University in St. Louis. (2006). Alzheimer’s Disease Research Center. Clinical dementia rating, on-line training. Retrieved from http://alzheimer.wustl.edu/cdr/default.htm (accessed March 10, 2006).Google Scholar
Wechsler, D. (1987). Wechsler Memory Scale Revised. San Antonio, TX: The Psychological Corporation.Google Scholar
Wechsler, D. (1997). Wechsler Adult Intelligence Scale - Third Edition. San Antonio, TX: The Psychological Corporation.Google Scholar
Wilkinson, G.S. (1993). Wide Range Achievement Test–Revision 3. Wilmington, DE: Jastak Association.Google Scholar
Winblad, B., Palmer, K., Kivipelto, M., Jelic, V., Fratiglioni, L., Wahlund, L.-O., et al. . (2004). Mild cognitive impairment: Beyond controversies, towards a consensus: Report of the International Working Group on Mild Cognitive Impairment. Journal of Internal Medicine, 256, 240–246.CrossRefGoogle Scholar