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Abstract

Background

Mild cognitive impairment (MCI) is a heterogeneous diagnostic entity, without a clear prognosis, often accompanied by psychiatric symptomatology and physical frailty.

Objective

Understanding the heterogeneity within MCI is a critical step in improving the early detection of cognitive decline and developing effective interventions.

Methods

Cross-sectional multivariate latent mixture analyses of data from patients evaluated between 2015 and 2019, who were routinely entered into a multidisciplinary database for research purposes. A sample of 538 community-dwelling older adults drawn from a large academic medical center, referred from within the Department of Neurology (63.7% Female, M_age= 67.8, SD_age= 10.6). Participants completed comprehensive neuropsychological assessments, psychiatric symptom measures, and frailty evaluations.

Results

Latent profile analyses supported five profiles of cognitive impairment: At-Risk, Pre-MCI, Amnestic MCI, Multiple Domain MCI, and Major Cognitive Impairment. The inclusion of concomitant psychiatric symptoms and frailty criteria revealed two additional profiles: Psychiatric/Frail, without cognitive impairments, and Multiple Cognitive Domains/Psychiatric/Frail. Critically, 55% of those classified as Healthy based on cognitive data alone were reclassified. Significant profile-wise differences emerged across auxiliary variables of brief cognitive screening, sociodemographics, and medical and psychosocial risk.

Conclusions

Results highlight heterogeneity represented by neurologic patients referred for neuropsychological evaluation that include key physical and emotional symptoms known to increase the risk of cognitive decline. Findings are in alignment with more recent research suggesting that the traditional paradigm cognitive impairment may need to be expanded to improve diagnostic accuracy and to develop more tailored, precision-driven interventions.

Keywords

Alzheimer's disease dementia latent profile analysis mild cognitive impairment physical frailty psychiatric symptoms

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References

Roberts

Knopman

. Classification and epidemiology of MCI. Clin Geriatr Med 2013; 29: 753–772.

Lopez

Becker

Chang

Y-F

, et al. Incidence of mild cognitive impairment in the Pittsburgh cardiovascular health study–cognition study. Neurology 2012; 79: 1599–1606.

Thomas

Edmonds

Eppig

, et al. MCI-to-normal reversion using neuropsychological criteria in the Alzheimer’s disease neuroimaging initiative. Alzheimers Dement 2019; 15: 1322–1332.

Yaffe

. Modifiable risk factors and prevention of dementia: what is the latest evidence? JAMA Intern Med 2018; 178: 281–282.

Edmonds

Delano-Wood

Clark

, et al. Susceptibility of the conventional criteria for mild cognitive impairment to false-positive diagnostic errors. Alzheimers Dement 2015; 11: 415–424.

Clark

Delano-Wood

Libon

, et al.

Are empirically-derived subtypes of mild cognitive impairment consistent with conventional subtypes?

J Int Neuropsychol Soc 2013; 19: 635–645.

Dunne

Aarsland

Brien

, , et al. Mild cognitive impairment: the Manchester consensus. Age Ageing 2021; 50: 72–80.

Blanken

Dutt

, et al. Disentangling heterogeneity in Alzheimer’s disease: two empirically-derived subtypes. J Alzheimers Dis 2019; 70: 227–239.

Blanken

Jang

, et al. Distilling heterogeneity of mild cognitive impairment in the national Alzheimer coordinating center database using latent profile analysis. JAMA Netw Open 2020; 3: e200413.

10.

Libon

Xie

Eppig

, et al. The heterogeneity of mild cognitive impairment: a neuropsychological analysis. J Int Neuropsychol Soc 2010; 16: 84–93.

11.

Machulda

Lundt

Albertston

, et al. Neuropsychological subtypes of incident mild cognitive impairment in the Mayo Clinic study of aging. Alzheimers Dement 2019; 15: 878–887.

12.

Edmonds

Delano-Wood

Jak

, et al. “Missed” mild cognitive impairment: high false-negative error rate based on conventional diagnostic criteria. J Alzheimers Dis 2016; 52: 685–691.

13.

Bondi

Smith

. Mild cognitive impairment: a concept and diagnostic entity in need of input from neuropsychology. J Int Neuropsychol Soc 2014; 20: 129–134.

14.

Bondi

Edmonds

Jak

, et al. Neuropsychological criteria for mild cognitive impairment improves diagnostic precision, biomarker associations, and progression rates. J Alzheimers Dis 2014; 42: 275–289.

15.

Edmonds

Smirnov

Thomas

, et al. Data-driven vs consensus diagnosis of MCI: enhanced sensitivity for detection of clinical, biomarker, and neuropathologic outcomes. Neurology 2021; 97: e1288–e1299.

16.

Petermann-Rocha

Lyall

Gray

, et al. Associations between physical frailty and dementia incidence: a prospective study from UK Biobank. Lancet Healthy Longev 2020; 1: e58–e68.

17.

Kim

Han

K-D

Baek

, et al. Association between physical activity and conversion from mild cognitive impairment to dementia. Alzheimers Res Ther 2020; 12: 136.

18.

. Depression, anxiety, and apathy in mild cognitive impairment: current perspectives. Front Aging Neurosci 2020; 12: 9.

19.

Delano-Wood

Bondi

Sacco

, et al. Heterogeneity in mild cognitive impairment: differences in neuropsychological profile and associated white matter lesion pathology. J Int Neuropsychol Soc 2009; 15: 906–914.

20.

Jak

Bondi

Delano-Wood

, et al. Quantification of five neuropsychological approaches to defining mild cognitive impairment. Am J Geriatr Psychiatry 2009; 17: 368–375.

21.

Lezak

Howieson

Bigler

, et al. Neuropsychological assessment, 5th ed. New York, NY, US: Oxford University Press, 2012.

22.

Nelson

Willison

. National Adult Reading Test (NART). Windsor, UK: NFER-Nelson, 1991.

23.

Del Ser

González-Montalvo

J-I

Martı´nez-Espinosa

, et al. Estimation of premorbid intelligence in Spanish people with the word accentuation test and its application to the diagnosis of dementia. Brain Cogn 1997; 33: 343–356.

24.

Kaplan

Goodglass

Weintraub

. Boston naming test. 2nd edition. Philadelphia: Lea & Febiger, 1983.

25.

Delis

Kaplan

Kramer

. Delis-Kaplan Executive Function System: Technical Manual. San Antonio, TX: The Psychological Corporation, 2001.

26.

Rey

Benton

. Multilingual Aphasia Examination-Spanish. Manual of Instructions. Iowa City: AJA Associates, 1991.

27.

Wechsler

. Wechsler Adult Intelligence Scale - Fourth Edition. San Antonio, TX: Pearson Assessments, 2008.

28.

Benton

Sivan

Hamsher

, et al. Contributions to neuropsychological assessment: A clinical manual. USA: Oxford University Press, 1994.

29.

Osterrieth

. Le test de copie d’une figure complexe; contribution à l’étude de la perception et de la mémoire. [Test of copying a complex figure; contribution to the study of perception and memory.]. Arch Psychol 1944; 30: 206–356.

30.

Rey

. L’examen psychologique dans les cas d’encéphalopathie traumatique. (Les problems.). [The psychological examination in cases of traumatic encepholopathy. Problems.]. Arch Psychol 1941; 28: 215–285.

31.

Wechsler

. Wechsler Memory Scale - Fourth Edition. San Antonio, TX: Pearson Assessments, 2009.

32.

Delis

Kramer

Kaplan

, et al. California Verbal Learning Test, Second Edition. San Antonio, TX: Pearson Assessments, 2000.

33.

Benedict

RHB

Schretlen

Groninger

, et al. Revision of the brief visuospatial memory test: studies of normal performance, reliability, and validity. Psychol Assess 1996; 8: 145–153.

34.

Matthews

Klove

. Instruction Manual for the Adult Neuropsychology Test Battery. Madison, WI: University of Wisconsin Medical School, 1964.

35.

Milner

. Effects of different brain lesions on card sorting: the role of the frontal lobes. Arch Neurol 1963; 9: 90–100.

36.

Beck

Steer

Brown

. Manual for the Beck Depression Inventory-II. San Antonio, TX: Psychological Corporation, 1996.

37.

Beck

Steer

. Beck Anxiety Inventory Manual. San Antonio, TX: The Psychological Corporation Harcourt Brace & Company, 1993.

38.

Marin

Biedrzycki

Firinciogullari

. Reliability and validity of the apathy evaluation scale. Psychiatry Res 1991; 38: 143–162.

39.

Hann

Jacobsen

Azzarello

, et al. Measurement of fatigue in cancer patients: development and validation of the fatigue symptom inventory. Qual Life Res 1998; 7: 301–310.

40.

von Glischinski

von Brachel

Hirschfeld

. How depressed is “depressed”? A systematic review and diagnostic meta-analysis of optimal cut points for the Beck depression inventory revised (BDI-II). Qual Life Res 2019; 28: 1111–1118.

41.

Fried

Tangen

Walston

, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001; 56: M146–M156.

42.

Stewart

Mills

King

, et al. CHAMPS Physical activity questionnaire for older adults: outcomes for interventions. Med Sci Sports Exerc 2001; 33: 1126–1141.

43.

Radloff

. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas 1977; 1: 385–401.

44.

Peugh

Fan

. Modeling unobserved heterogeneity using latent profile analysis: a Monte Carlo simulation. Struct Equ Model Multidiscip J 2013; 20: 616–639.

45.

Pastor

Gagné

. Mean and covariance structure mixture models. In: Structural equation modeling: a second course, 2nd ed. Charlotte, NC, US: IAP Information Age Publishing, 2013, pp.343–393.

46.

Dempster

Laird

Rubin

. Maximum likelihood from incomplete data via the EM algorithm. J R Stat Soc Ser B Methodol 1977; 39: 1–22.

47.

Nylund

Asparouhov

Muthén

. Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo simulation study. Struct Equ Model Multidiscip J 2007; 14: 535–569.

48.

Mendell

Rubin

. Testing the number of components in a normal mixture. Biometrika 2001; 88: 767–778.

49.

Wang

M-C

Deng

, et al. Performance of the entropy as an index of classification accuracy in latent profile analysis: a Monte Carlo simulation study. Acta Psychol Sin 2017; 49: 1473–1482.

50.

Woo

Jebb

Tay

, et al. Putting the “person” in the center: review and synthesis of person-centered approaches and methods in organizational science. Organ Res Methods 2018; 21: 814–845.

51.

Lubke

Neale

. Distinguishing between latent classes and continuous factors: resolution by maximum likelihood? Multivar Behav Res 2006; 41: 499–532.

52.

Spurk

Hirschi

Wang

, et al. Latent profile analysis: a review and “how to” guide of its application within vocational behavior research. J Vocat Behav 2020; 120: 103445.

53.

Jak

Urban

McCauley

, et al. Profile of hippocampal volumes and stroke risk varies by neuropsychological definition of mild cognitive impairment. J Int Neuropsychol Soc 2009; 15: 890–897.

54.

Bakk

Vermunt

. Robustness of stepwise latent class modeling with continuous distal outcomes. Struct Equ Model Multidiscip J 2016; 23: 20–31.

55.

Asparouhov

Muthén

. Auxiliary variables in mixture modeling: three-step approaches using Mplus. Struct Equ Model 2014; 21: 329–341.

56.

Kapasi

DeCarli

Schneider

. Impact of multiple pathologies on the threshold for clinically overt dementia. Acta Neuropathol (Berl) 2017; 134: 171–186.

57.

Kawas

Kim

Sonnen

, et al. Multiple pathologies are common and related to dementia in the oldest-old. Neurology 2015; 85: 535–542.

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Exploring heterogeneity in mild cognitive impairment

Abstract

Background

Objective

Methods

Results

Conclusions

Keywords

Get full access to this article

References

Supplementary Material