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Comparing the predictive validity of four MCI definitions for incident dementia in demographically diverse community-dwelling individuals: Results from the Einstein Aging Study (EAS)

Published online by Cambridge University Press:  27 December 2024

Katherine H. Chang Open the ORCID record for Katherine H. Chang [Opens in a new window] ,
Cuiling Wang ,
Jiyue Qin ,
Mindy J. Katz ,
Desiree A. Byrd ,
Richard B. Lipton  and
Laura A. Rabin
Katherine H. Chang*
Affiliation:
Department of Psychology, Queens College, City University of New York (CUNY), Flushing, NY, USA Department of Psychology, The Graduate Center, City University of New York (CUNY), New York, NY, USA Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, USA
Cuiling Wang
Affiliation:
Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, USA Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
Jiyue Qin
Affiliation:
Division of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, La Jolla, CA, USA
Mindy J. Katz
Affiliation:
Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, USA
Desiree A. Byrd
Affiliation:
Department of Psychology, Queens College, City University of New York (CUNY), Flushing, NY, USA Department of Psychology, The Graduate Center, City University of New York (CUNY), New York, NY, USA
Richard B. Lipton
Affiliation:
Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, USA Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY, USA
Laura A. Rabin
Affiliation:
Department of Psychology, Queens College, City University of New York (CUNY), Flushing, NY, USA Department of Psychology, The Graduate Center, City University of New York (CUNY), New York, NY, USA Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, USA Department of Psychology, Brooklyn College, City University of New York (CUNY), Brooklyn, NY, USA
*
Corresponding author: Katherine H. Chang; Email: kchang@gradcenter.cuny.edu
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Abstract

Objective:

Research examining (MCI) criteria in diverse and/or health-disparate populations is limited. There is a critical need to investigate the predictive validity for incident dementia of widely used MCI definitions in diverse populations.

Method:

Eligible participants were non-Hispanic White or Black Bronx community residents, free of dementia at enrollment, with at least one annual follow-up visit after baseline. Participants completed annual neurological and neuropsychological evaluations to determine cognitive status. Dementia was defined based on DSM-IV criteria using case conferences. Cox proportional hazard models assessed predictive validity for incident dementia of four specific MCI definitions (Petersen, Jak/Bondi, number of impaired tests, Global Clinical Ratings) at baseline, controlling for age, sex, education, and race/ethnicity. Time-dependent sensitivity and specificity at 2–7 years for each definition, and Youden’s index were calculated as accuracy measures.

Results:

Participants (N = 1073) ranged in age from 70 to 100 (mean = 78.4 ± 5.3) years at baseline. The sample was 62.5% female, and educational achievement averaged 13.9 ± 3.5 years. Most participants identified as White (70.0%), though Black participants were well-represented (30.0%). In general, MCI definitions differed in sensitivity and specificity for incident dementia. However, there were no significant differences in Youden’s index for any definition, across all years of follow-up.

Conclusions:

This work provides an important step toward improving the generalizability of the MCI diagnosis to underrepresented/health-disparate populations. While our findings suggest the studied MCI classifications are comparable, researchers and clinicians may choose to consider one method over another depending on the rationale for evaluation or question of interest.

Keywords

Mild cognitive impairmentcross-cultural neuropsychologycross-cultural issuesdiversitylongitudinalaging
Type
Research Article
Information
Journal of the International Neuropsychological Society , First View , pp. 1 - 10
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of International Neuropsychological Society

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References

Al-Qazzaz, N. K., Ali, S. H., Ahmad, S. A., Islam, S., & Mohamad, K. (2014). Cognitive impairment and memory dysfunction after a stroke diagnosis: A post-stroke memory assessment. Neuropsychiatric Disease and Treatment, 10, 1677–1691.CrossRefGoogle ScholarPubMed
Albert, M. S., DeKosky, S. T., Dickson, D., Dubois, B., Feldman, H. H., Fox, N. C., Gamst, A., Holtzman, D. M., Jagust, W. J., Petersen, R. C., Snyder, P. J., Carrillo, M. C., Thies, B., & Phelps, C. H. (2011). The diagnosis of mild cognitive impairment due to Alzheimer’s disease: Recommendations from the national institute on aging—Alzheimer’s association workgroups on diagnostic guidelines for alzheimer’s disease. Alzheimers & Dementia, 7, 270–279.CrossRefGoogle ScholarPubMed
Alfano, D. P., Grummisch, J. A., Gordon, J. L., & Hadjistavropoulos, T. (2022). A neuropsychological approach to mild cognitive impairment. Archives of Clinical Neuropsychology, 37, 873–890.CrossRefGoogle ScholarPubMed
American Psychiatric Association (APA). (1994). Diagnostic and statistical manual of mental disorders (4th ed.). American Psychiatric Publishing, Inc.Google Scholar
Angevaare, M. J., Vonk, J. M. J., Bertola, L., Zahodne, L., Watson, C. W..-M., Boehme, A., Schupf, N., Mayeux, R., Geerlings, M. I., & Manly, J. J. (2022). Predictors of incident mild cognitive impairment and its course in a diverse community-based population. Neurology, 98, e15–e26.CrossRefGoogle Scholar
Arosio, B., Ostan, R., Mari, D., Damanti, S., Ronchetti, F., Arcudi, S., Scurti, M., Franceschi, C., & Monti, D. (2017). Cognitive status in the oldest old and centenarians: A condition crucial for quality of life methodologically difficult to assess. Mechanisms of Ageing and Development, 165, 185–194.CrossRefGoogle ScholarPubMed
Artero, S., Petersen, R. C., Touchon, J., & Ritchie, K. (2006). Revised criteria for mild cognitive impairment: Validation within a longitudinal population study. Dementia and Geriatric Cognitive Disorders, 22, 465–470.CrossRefGoogle ScholarPubMed
Bigelow, R. T., Semenov, Y. R., Trevino, C., Ferrucci, L., Resnick, S. M., Simonsick, E. M., Xue, Q. L., & Agrawal, Y. (2015). Association between visuospatial ability and vestibular function in the Baltimore longitudinal study of aging. Journal of the American Geriatrics Society, 63, 1837–1844.CrossRefGoogle ScholarPubMed
Binder, L. M., Iverson, G. L., & Brooks, B. L. (2009). To err is human: “Abnormal” neuropsychological scores and variability are common in healthy adults. Archives of Clinical Neuropsychology, 24, 31–46.CrossRefGoogle Scholar
Blackford, R. C., & LaRue, A. (1989). Criteria for diagnosing age-associated memory impairment: Proposed improvements from the field. Developmental Neuropsychology, 5, 295–306.CrossRefGoogle Scholar
Blackstone, K., Moore, D. J., Franklin, D. R., Clifford, D. B., Collier, A. C., Marra, C. M., Gelman, B. B., McArthur, J. C., Morgello, S., Simpson, D. M., Ellis, R. J., Atkinson, J. H., Grant, I., & Heaton, R. K. (2012). Defining neurocognitive impairment in HIV: Deficit scores versus clinical ratings. The Clinical Neuropsychologist, 26, 894–908.CrossRefGoogle ScholarPubMed
Bondi, M. W., Edmonds, E. C., Jak, A. J., Clark, L. R., Delano-Wood, L., McDonald, C. R., Nation, D. A., Libon, D. J., Au, R., Galasko, D., & Salmon, D. P. (2014). Neuropsychological criteria for mild cognitive impairment improves diagnostic precision, biomarker associations, and progression rates. Journal of Alzheimer’s Disease, 42, 275–289.CrossRefGoogle ScholarPubMed
Bondi, M. W., & Smith, G. E. (2014). Mild cognitive impairment: A concept and diagnostic entity in need of input from neuropsychology. Journal of the International Neuropsychological Society, 20, 129–134.CrossRefGoogle ScholarPubMed
Boone, K. B., Victor, T. L., Wen, J., Razani, J., & Pontón, M. (2007). The association between neuropsychological scores and ethnicity, language, and acculturation variables in a large patient population. Archives of Clinical Neuropsychology, 22, 355–365.CrossRefGoogle ScholarPubMed
Brooks, B. L., Iverson, G. L., Holdnack, J. A., & Feldman, H. H. (2008). Potential for misclassification of mild cognitive impairment: A study of memory scores on the Wechsler memory scale-III in healthy older adults. Journal of the International Neuropsychological Society, 14, 463–478.CrossRefGoogle ScholarPubMed
Brooks, B. L., Iverson, G. L., & White, T. (2007). Substantial risk of “accidental MCI” in healthy older adults: Base rates of low memory scores in neuropsychological assessment. Journal of the International Neuropsychological Society, 13, 490–500.CrossRefGoogle ScholarPubMed
Brose, A., Schmiedek, F., Lövdén, M., & Lindenberger, U. (2012). Daily variability in working memory is coupled with negative affect: The role of attention and motivation. Emotion, 12, 605–617.CrossRefGoogle ScholarPubMed
Buschke, H. (1984). Cued recall in Amnesia. Journal of Clinical Neuropsychology, 6, 433–440.CrossRefGoogle ScholarPubMed
Byrd, D. A., Walden Miller, S., Reilly, J., Weber, S., Wall, T. L., & Heaton, R. K. (2006). Early environmental factors, ethnicity, and adult cognitive test performance. The Clinical Neuropsychologist, 20, 243–260.CrossRefGoogle ScholarPubMed
Calvillo, M., & Irimia, A. (2020). Neuroimaging and psychometric assessment of mild cognitive impairment after traumatic brain injury. Frontiers in Psychology, 11, 1423.CrossRefGoogle ScholarPubMed
Chang, K. H., Wang, C., Nester, C. O., Katz, M. J., Byrd, D. A., Lipton, R. B., & Rabin, L. A. (2023). Examining the role of participant and study partner report in widely-used classification approaches of mild cognitive impairment in demographically-diverse community dwelling individuals: Results from the Einstein Aging Study (EAS). Frontiers in Aging Neuroscience, 15, 1221768. doi: 10.3389/fnagi.2023.1221768 CrossRefGoogle Scholar
Chen, Y., Liang, N., Li, X., Yang, S., Wang, Y., & Shi, N. (2021). Diagnosis and treatment for mild cognitive impairment: A systematic review of clinical practice guidelines and consensus statements. Frontiers in Neurology, 12, 719849.CrossRefGoogle ScholarPubMed
Crowe, S. F., Benedict, T., Enrico, J., Mancuso, N., Matthews, C., & Wallace, J. (1999). Cognitive determinants of performance on the digit-symbol coding test, and the symbol search test of the WAIS-III and the symbol digit modalities test: An analysis in a healthy sample. Australian Psychologist, 34, 204–210.CrossRefGoogle Scholar
de Vent, N. R., Agelink van Rentergem, J. A., Huizenga, H. M., van der Flier, W. M., Sikkes, S. A. M., Murre, J. M. J., van den Bosch, K. A., Scheltens, P., & Schmand, B. A. (2020). An operational definition of abnormal cognition to optimize the prediction of progression to dementia: What are optimal cut-off points for univariate and multivariate normative comparisons? Journal of Alzheimer’s Disease, 77, 1693–1703.CrossRefGoogle ScholarPubMed
Devlin, K. N., Brennan, L., Saad, L., Giovannetti, T., Hamilton, R. H., Wolk, D. A., Xie, S. X., Mechanic-Hamilton, D., & Okonkwo, O. (2022). Diagnosing mild cognitive impairment among racially diverse older adults: Comparison of consensus, actuarial, and statistical methods. Journal of Alzheimer’s Disease, 85, 627–644.CrossRefGoogle ScholarPubMed
Díaz-Venegas, C., Downer, B., Langa, K. M., & Wong, R. (2016). Racial and ethnic differences in cognitive function among older adults in the USA. International Journal of Geriatric Psychiatry, 31, 1004–1012.CrossRefGoogle ScholarPubMed
Donders, J. (2020). The incremental value of neuropsychological assessment: A critical review. The Clinical Neuropsychologist, 34, 56–87.CrossRefGoogle ScholarPubMed
Dubois, B., Villain, N., Frisoni, G. B., Rabinovici, G. D., Sabbagh, M., Cappa, S., Bejanin, A., Bombois, S., Epelbaum, S., Teichmann, M., Habert, M.-O., Nordberg, A., Blennow, K., Galasko, D., Stern, Y., Rowe, C. C., Salloway, S., Schneider, L. S., Cummings, J. L., & Feldman, H. H. (2021). Clinical diagnosis of Alzheimer2019’s disease: Recommendations of the international working group. The Lancet Neurology, 20, 484–496.CrossRefGoogle ScholarPubMed
Dunne, R. A., Aarsland, D., O’Brien, J. T., Ballard, C., Banerjee, S., Fox, N. C., Isaacs, J. D., Underwood, B. R., Perry, R. J., Chan, D., Dening, T., Thomas, A. J., Schryer, J., Jones, A.-M., Evans, A. R., Alessi, C., Coulthard, E. J., Pickett, J., Elton, P., …, Burns, A. (2021). Mild cognitive impairment: The Manchester consensus. Age and Ageing, 50, 72–80.CrossRefGoogle ScholarPubMed
Edmonds, E. C., Delano‐Wood, L., Clark, L. R., Jak, A. J., Nation, D. A., McDonald, C. R., Libon, D. J., Au, R., Galasko, D., Salmon, D. P., Bondi, M. W., & Alzheimer’s Disease Neuroimaging Imitative (2015a). Susceptibility of the conventional criteria for mild cognitive impairment to false‐positive diagnostic errors. Alzheimer’s & Dementia, 11, 415–424.CrossRefGoogle ScholarPubMed
Edmonds, E. C., Smirnov, D. S., Thomas, K. R., Graves, L. V., Bangen, K. J., Delano-Wood, L., Galasko, D. R., Salmon, D. P., & Bondi, M. W. (2021). Data-driven vs consensus diagnosis of MCI: Enhanced sensitivity for detection of clinical, biomarker, and neuropathologic outcomes. Neurology, 97, e1288–e1299.CrossRefGoogle ScholarPubMed
Edmonds, E. C., Weigand, A. J., Thomas, K. R., Eppig, J., Delano-Wood, L., Galasko, D. R., Salmon, D. P., & Bondi, M. W. (2018). Increasing inaccuracy of self-reported subjective cognitive complaints over 24 months in empirically derived subtypes of mild cognitive impairment. Journal of the International Neuropsychological Society, 24, 842–853.CrossRefGoogle Scholar
Facer-Childs, E., Boiling, S., & Balanos. G. (2018). The effects of time of day and chronotype on cognitive and physical performance in healthy volunteers. Sports Medicine, 4, 47. doi: 10.1186/s40798-018-0162-z Google ScholarPubMed
Ganguli, M., Snitz, B. E., Saxton, J. A., Chang, C.-C. H., Lee, C.-W., Vander Bilt, J., Hughes, T. F., Loewenstein, D. A., Unverzagt, F. W., & Petersen, R. C. (2011). Outcomes of mild cognitive impairment by definition: A population study. Archives of Neurology, 68, 761–767.CrossRefGoogle ScholarPubMed
Gasquoine, P. G. (2009). Race-norming of neuropsychological tests. Neuropsychology Review, 19, 250–262.CrossRefGoogle ScholarPubMed
Giau, V. V., Bagyinszky, E., & An, S. S. (2019). Potential fluid biomarkers for the diagnosis of mild cognitive impairment. International Journal of Molecular Sciences, 20, 4149.CrossRefGoogle ScholarPubMed
Glosser, G., Butters, N., & Kaplan, E. (1977). Visuoperceptual processes in brain damaged patients on the digit symbol substitution test. International Journal of Neuroscience, 7, 59–66.CrossRefGoogle ScholarPubMed
Gomersall, T., Astell, A., Nygard, L., Sixsmith, A., Milhailidis, A., & Hwang, A. (2015). Living with ambiguity: A metasynthesis of qualitative research on mild cognitive impairment. The Gerontologist, 55, 892–912.CrossRefGoogle ScholarPubMed
Graves, L. V., Edmonds, E. C., Thomas, K. R., Weigand, A. J., Cooper, S., & Bondi, M. W. (2020). Evidence for the utility of actuarial neuropsychological criteria across the continuum of normal aging, mild cognitive impairment, and dementia. Journal of Alzheimer’s Disease, 371–385.CrossRefGoogle ScholarPubMed
Graves, L. V., Edmonds, E. C., Thomas, K. R., Weigand, A. J., Cooper, S., Stickel, A. M., Zlatar, Z. Z., Clark, A. L., & Bondi, M. W. (2022). Diagnostic accuracy and differential associations between ratings of functioning and neuropsychological performance in non-hispanic Black and White older adults. The Clinical Neuropsychologist, 36, 287–310.CrossRefGoogle ScholarPubMed
Hackett, K., Mis, R., Drabick, D. A., & Giovannetti, T. (2020). Informant reporting in mild cognitive impairment: Sources of discrepancy on the functional activities questionnaire. Journal of the International Neuropsychological Society, 26, 503–514.CrossRefGoogle ScholarPubMed
Hansson, O., Edelmayer, R. M., Boxer, A. L., Carrillo, M. C., Mielke, M. M., Rabinovici, G. D., Salloway, S., Sperling, R., Zetterberg, H., & Teunissen, C. E. (2022). The Alzheimer’s association appropriate use recommendations for blood biomarkers in Alzheimer’s disease. Alzheimer’s & Dementia, 18, 2669–2686.CrossRefGoogle ScholarPubMed
Heaton, R. K., Grant, I., Butters, N., White, Dé A., Kirson, D., Atkinson, J. H., McCutchan, J. A., Taylor, M. J., Kelly, M. D., Ellis, R. J., Wolfson, T., Velin, R., Marcotte, T. D., Hesselink, J. R., Jernigan, T. L., Chandler, J., Wallace, M., Abramson, I., & The HNRC group (1995). The HNRC 500-Neuropsychology of HIV infection at different disease stages. Journal of the International Neuropsychological Society, 1, 231–251.CrossRefGoogle ScholarPubMed
Hong, T. B., Zarit, S. H., & Johansson, B. (2003). Mild cognitive impairment in the oldest old: A comparison of two approaches. Aging & Mental Health, 7, 271–276.CrossRefGoogle ScholarPubMed
Ilardi, C. R., Chieffi, S., Iachini, T., & Iavarone, A. (2021). Neuropsychology of posteromedial parietal cortex and conversion factors from mild cognitive impairment to Alzheimer’s disease: Systematic search and state-of-the-art review. Aging Clinical and Experimental Research, 34, 289–307.CrossRefGoogle ScholarPubMed
Jack, C. R., Bennett, D. A., Blennow, K., Carrillo, M. C., Dunn, B., Haeberlein, S. B., Holtzman, D. M., Jagust, W., Jessen, F., Karlawish, J., Liu, E., Molinuevo, J. L., Montine, T., Phelps, C., Rankin, K. P., Rowe, C. C., Scheltens, P., Siemers, E., Snyder, H. M., …, Silverberg, N. (2018). NIA-AA research framework: Toward a biological definition of Alzheimer’s disease. Alzheimer’s & Dementia, 14, 535–562.CrossRefGoogle Scholar
Jak, A. J., Bondi, M. W., Delano-Wood, L., Wierenga, C., Corey-Bloom, J., Salmon, D. P., & Delis, D. C. (2009). Quantification of five neuropsychological approaches to defining mild cognitive impairment. The American Journal of Geriatric Psychiatry, 17, 368–375.CrossRefGoogle ScholarPubMed
Jak, A. J., Preis, S. R., Beiser, A. S., Seshadri, S., Wolf, P. A., Bondi, M. W., & Au, R. (2016). Neuropsychological criteria for mild cognitive impairment and dementia risk in the Framingham heart study. Journal of the International Neuropsychological Society, 22, 937–943.CrossRefGoogle ScholarPubMed
Jessen, F., Amariglio, R. E., van Boxtel, M., Breteler, M., Ceccaldi, M., Chételat, G., Dubois, B., Dufouil, C., Ellis, K. A., van der Flier, W. M., Glodzik, L., van Harten, A. C., de Leon, M. J., McHugh, P., Mielke, M. M., Molinuevo, J. L., Mosconi, L., Osorio, R. S., Perrotin, A., …, Subjective Cognitive Decline Initiative (SCD-I) Working Group (2014). A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer’s disease. Alzheimer’s & Dementia, 10, 844–852.CrossRefGoogle ScholarPubMed
Kaduszkiewicz, H., Eisele, M., Wiese, B., Prokein, J., Luppa, M., Luck, T., Jessen, F., Bickel, H., Mosch, E., Pentzek, M., Fuchs, A., Eifflaender-Gorfer, S., Weyerer, S., Konig, H.-H., Brettschneider, C., van den Bussche, H., Maier, W., Scherer, M., Riedel-Heller, S. G., & Study on Aging, Cognition, and Dementia in Primary Care Patients (AgeCoDe) Study Group (2014). Prognosis of mild cognitive impairment in general practice: Results of the German AgeCoDe study. The Annals of Family Medicine, 12, 158–165.CrossRefGoogle ScholarPubMed
Kaplan, E. F., Goodglass, H., & Weintraub, S. (1983). The Boston Naming Test (2nd ed.). Lea & Febiger.Google Scholar
Katz, M. J., Lipton, R. B., Hall, C. B., Zimmerman, M. E., Sanders, A. E., Verghese, J., Dickson, D. W., & Derby, C. A. (2012). Age-specific and sex-specific prevalence and incidence of mild cognitive impairment, dementia, and Alzheimer dementia in Blacks and Whites. Alzheimer Disease & Associated Disorders, 26, 335–343.CrossRefGoogle ScholarPubMed
Kravitz, E., Schmeidler, J., & Schnaider Beeri, M. (2012). Cognitive decline and dementia in the oldest-old. Rambam Maimonides Medical Journal, 3, e0026.CrossRefGoogle ScholarPubMed
Lawton, M. P., & Brody, E. M. (1969). Assessment of older people: Self-maintaining and instrumental activities of daily living. The Gerontologist, 9, 179–186.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 and Geriatric Cognitive Disorders, 27, 418–423.CrossRefGoogle Scholar
Malaspina, L., Woods, S. P., Moore, D. J., Depp, C., Letendre, S. L., Jeste, D., Grant, I., & HIV Neurobehavioral Research Programs (HNRP) Group. (2011). Successful cognitive aging in persons living with HIV infection. Journal of NeuroVirology, 17, 110–119.CrossRefGoogle ScholarPubMed
Manly, J. J. (2005). Advantages and disadvantages of separate norms for African Americans. The Clinical Neuropsychologist, 19, 270–275.CrossRefGoogle ScholarPubMed
Manly, J. J., & Echemendia, R. J. (2007). Race-specific norms: Using the model of hypertension to understand issues of race, culture, and education in neuropsychology. Archives of Clinical Neuropsychology, 22, 319–325.CrossRefGoogle ScholarPubMed
Manly, J. J., Tang, M. X., Schupf, N., Stern, Y., Vonsattel, J. G., & Mayeux, R. (2008). Frequency and course of mild cognitive impairment in a multiethnic community. Annals of Neurology, 63, 494–506.CrossRefGoogle Scholar
Marvanova, M. (2016). Drug-induced cognitive impairment: Effect of cardiovascular agents. Mental Health Clinician, 6, 201–206.CrossRefGoogle ScholarPubMed
Moore, E., Mander, A., Ames, D., Carne, R., Sanders, K., & Watters, D. (2012). Cognitive impairment and vitamin B12: A review. International Psychogeriatrics, 24, 541–556.CrossRefGoogle ScholarPubMed
Mormino, E. C., Papp, K. V., Perry, G., Avila, J., Moreira, P. I., Sorensen, A. A., & Tabaton, M. (2018). Amyloid accumulation and cognitive decline in clinically normal older adults: Implications for aging and early Alzheimer’s disease. Journal of Alzheimer’s Disease, 64, S633–S646.CrossRefGoogle Scholar
Oltra‐Cucarella, J., Sánchez‐SanSegundo, M., Lipnicki, D. M., Sachdev, P. S., Crawford, J. D., Pérez‐Vicente, Jé A., Cabello‐Rodríguez, L., Ferrer‐Cascales, R., & Alzheimer’s Disease Neuroimaging Initiative (2018). Using base rate of low scores to identify progression from amnestic mild cognitive impairment to Alzheimer’s disease. Journal of the American Geriatrics Society, 66, 1360–1366.CrossRefGoogle ScholarPubMed
Pandya, S. Y., Lacrtiz, L. H., Weiner, M. F., Deschner, M., & Woon, F. L. (2017). Predictors of reversion from mild cognitive impairment to normal cognition. Dementia and Geriatric Cognitive Disorders, 43, 204–214.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., Aisen, P. S., Beckett, L. A., Donohue, M. C., Gamst, A. C., Harvey, D. J., Jack, C. R., Jagust, W. J., Shaw, L. M., Toga, A. W., Trojanowski, J. Q., & Weiner, M. W. (2010). Alzheimer’s disease neuroimaging initiative (ADNI): Clinical characterization. Neurology, 74, 201–209.CrossRefGoogle Scholar
Petersen, R. C., Caracciolo, B., Brayne, C., Gauthier, S., Jelic, V., & Fratiglioni, L. (2014). Mild cognitive impairment: A concept in evolution. Journal of Internal Medicine, 275, 214–228.CrossRefGoogle ScholarPubMed
Petersen, R. C., Doody, R., Kurz, A., Mohs, R. C., Morris, J. C., Rabins, P. V., Ritchie, K., Rossor, M., Thal, L., & Winblad, B. (2001). Current concepts in mild cognitive impairment. Archives of Neurology, 58, 1985–1992.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
Pfeffer, R. I., Kurosaki, T. T., Harrah, C. H., Chance, J. M., & Filos, S. (1982). Measurement of functional activities in older adults in the community. Journal of Gerontology, 37, 323–329.CrossRefGoogle ScholarPubMed
Reitan, R. M. (1958). Validity of the trail making test as an indicator of organic brain damage. Perceptual and Motor Skills, 8, 271–276.CrossRefGoogle Scholar
Ritchie, K., Artero, S., & Touchon, J. (2001). Classification criteria for mild cognitive impairment. Neurology, 56, 37–42.CrossRefGoogle ScholarPubMed
Rosen, W. G. (1980). Verbal fluency in aging and dementia. Journal of Clinical Neuropsychology, 2, 135–146.CrossRefGoogle Scholar
Scharre, D. W. (2019). Preclinical, prodromal, and dementia stages of Alzheimer’s Disease. Practical Neurology, 36–47.Google Scholar
Shao, X., Wang, K., Zhang, Y., Zhen, X., Dong, F., Tian, H., & Yu, Y. (2023). Outcome of visuospatial dysfunction assessment in patients with Parkinson’s disease using mobile application software. Frontiers in Aging Neuroscience, 15, 1108166.CrossRefGoogle ScholarPubMed
Sheikh, J. I., & Yesavage, J. A. (1986). Geriatric depression scale (GDS): Recent evidence and development of a shorter version. Clinical Gerontologist, 5, 165–173.Google Scholar
Spreen, O., & Strauss, E. (2006). A compendium of neuropsychological tests: Administration, norms, and commentary. Oxford University Press.Google Scholar
Thomas, K. R., Cook, S. E., Bondi, M. W., Unverzagt, F. W., Gross, A. L., Willis, S. L., & Marsiske, M. (2020). Application of neuropsychological criteria to classify mild cognitive impairment in the ACTIVE study. Neuropsychology, 34, 862–873.CrossRefGoogle ScholarPubMed
Thomas, K. R., Eppig, J. S., Weigand, A. J., Edmonds, E. C., Wong, C. G., Jak, A. J., Delano‐Wood, L., Galasko, D. R., Salmon, D. P., Edland, S. D., Bondi, M. W., & Alzheimer’s Disease Neuroimaging Initiative. (2019). MCI-to-normal reversion using neuropsychological criteria in the Alzheimer’s disease neuroimaging initiative. Alzheimer’s & Dementia, 15, 561–569.CrossRefGoogle ScholarPubMed
Tibhirani, R. J., & Efron, B. (1993). An introduction to the bootstrap. Chapman and Hall/CRC.Google Scholar
Trittschuh, E. H., Crane, P. K., Larson, E. B., Cholerton, B., McCormick, W. C., McCurry, S. M., Bowen, J. D., Baker, L. D., & Craft, S. (2011). Effects of varying diagnostic criteria on prevalence of mild cognitive impairment in a community sample. Journal of Alzheimer’s Disease, 25, 163–173.CrossRefGoogle Scholar
Visser, L. N. C., van Maurik, I. S., Bouwman, F. H., Staekenborg, S., Vreeswijk, R., Hempenius, L., de Beer, M. H., Roks, G., Boelaarts, L., Kleijer, M., van der Flier, W. M., Smets, E. M. A., & Ginsberg, S. D. (2020). Clinicians’ communication with patients receiving a MCI diagnosis: The ABIDE project. PLOS ONE, 15, e0227282.CrossRefGoogle ScholarPubMed
von Stumm, S. (2016). Is day-to-day variability in cognitive function coupled with day-to-day variability in affect? Intelligence, 55, 1–6.CrossRefGoogle Scholar
Vuoksimaa, E., McEvoy, L. K., Holland, D., Franz, C. E., Kremen, W. S., & Alzheimer’s Disease Neuroimaging Initiative (2020). Modifying the minimum criteria for diagnosing amnestic MCI to improve prediction of brain atrophy and progression to Alzheimer’s disease. Brain Imaging and Behavior, 14, 787–796.CrossRefGoogle ScholarPubMed
Wang, C., Katz, M. J., Chang, K. H., Qin, J., Lipton, R. B., Zwerling, J. L., Sliwinski, M. J., Derby, C. A., Rabin, L. A., & Abner, E. (2021). UDSNB 3.0 neuropsychological test norms in older adults from a diverse community: Results from the Einstein Aging Study (EAS). Journal of Alzheimer’s Disease, 83, 1665–1678.CrossRefGoogle ScholarPubMed
Wechsler, D. (1987). WMS-R: Wechsler memory scale-revised. Psychological Corporation.Google Scholar
Wechsler, D. (1997). WAIS-III: Administration and scoring manual: Wechsler Adult Intelligence Scale. Psychological Corporation.Google Scholar
Wei, E. X., Anson, E. R., Resnick, S. M., & Agrawal, Y. (2020). Psychometric tests and spatial navigation: Data from the Baltimore longitudinal study of aging. Frontiers in Neurology, 11, 484.CrossRefGoogle ScholarPubMed
Werry, A. E., Daniel, M., & Bergström, B. (2019). Group differences in normal neuropsychological test performance for older non-Hispanic White and Black/African American adults.. Neuropsychology, 33, 1089–1100.CrossRefGoogle ScholarPubMed
Winblad, B., Palmer, K., Kivipelto, M., Jelic, V., Fratiglioni, L., Wahlund, L‐O., Nordberg, A., Bäckman, L., Albert, M., Almkvist, O., Arai, H., Basun, H., Blennow, K., De Leon, M., DeCarli, C., Erkinjuntti, T., Giacobini, E., Graff, C., Hardy, J., & Petersen, R. C. (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
Wong, C G., Thomas, K R., Edmonds, E C., Weigand, A J., Bangen, K J., Eppig, J S., Jak, A J., Devine, S A., Delano-Wood, L., Libon, D J., Edland, S D., Au, R., & Bondi, M W. (2018). Neuropsychological criteria for mild cognitive impairment in the Framingham heart study’s old-old. Dementia and Geriatric Cognitive Disorders, 46, 253–265.CrossRefGoogle ScholarPubMed
Zahodne, L. B., Manly, J. J., Azar, M., Brickman, A. M., & Glymour, M. M. (2016). Racial disparities in cognitive performance in mid- and late adulthood: Analyses of two cohort studies. Journal of the American Geriatrics Society, 64, 959–964.CrossRefGoogle ScholarPubMed
Zahodne, L. B., Sharifian, N., Kraal, A. Z., Zaheed, A. B., Sol, K., Morris, E. P., Schupf, N., Manly, J. J., & Brickman, A. M. (2021). Socioeconomic and psychosocial mechanisms underlying racial/ethnic disparities in cognition among older adults. Neuropsychology, 35, 265–275.CrossRefGoogle ScholarPubMed
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