Identification of Mild Cognitive Impairment in ACTIVE: Algorithmic Classification and Stability

被引:10
|
作者
Cook, Sarah E. [1 ,2 ]
Marsiske, Michael [1 ]
Thomas, Kelsey R. [1 ]
Unverzagt, Frederick W. [3 ]
Wadley, Virginia G. [4 ]
Langbaum, Jessica B. S. [5 ]
Crowe, Michael [4 ]
机构
[1] Univ Florida, Dept Clin & Hlth Psychol, Gainesville, FL 32610 USA
[2] Duke Univ, Dept Psychiat, Durham, NC 27706 USA
[3] Indiana Univ Sch Med, Dept Psychiat, Indianapolis, IN USA
[4] Univ Alabama Birmingham, Dept Psychol, Birmingham, AL 35294 USA
[5] Banner Hlth, Banner Alzheimers Inst, Phoenix, AZ USA
关键词
Cognitive impairment; Research classification; Cognitive aging; Longitudinal follow-up; OLDER-ADULTS; DIAGNOSTIC-CRITERIA; MEMORY SCORES; PREVALENCE; DEMENTIA; POPULATION; DECLINE; HEALTH; PROGRESSION; FREQUENCY;
D O I
10.1017/S1355617712000938
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Rates of mild cognitive impairment (MCI) have varied substantially, depending on the criteria used and the samples surveyed. The present investigation used a psychometric algorithm for identifying MCI and its stability to determine if low cognitive functioning was related to poorer longitudinal outcomes. The Advanced Cognitive Training of Independent and Vital Elders (ACTIVE) study is a multi-site longitudinal investigation of long-term effects of cognitive training with older adults. ACTIVE exclusion criteria eliminated participants at highest risk for dementia (i.e., Mini-Mental State Examination, 23). Using composite normative for sample- and training-corrected psychometric data, 8.07% of the sample had amnestic impairment, while 25.09% had a non-amnestic impairment at baseline. Poorer baseline functional scores were observed in those with impairment at the first visit, including a higher rate of attrition, depressive symptoms, and self-reported physical functioning. Participants were then classified based upon the stability of their classification. Those who were stably impaired over the 5-year interval had the worst functional outcomes (e.g., Instrumental Activities of Daily Living performance), and inconsistency in classification over time also appeared to be associated increased risk. These findings suggest that there is prognostic value in assessing and tracking cognition to assist in identifying the critical baseline features associated with poorer outcomes. (JINS, 2013, 19, 73-87)
引用
收藏
页码:73 / 87
页数:15
相关论文
共 50 条
  • [1] Cognitive impairment in active: Stability of classification
    Cook, S
    Marsiske, M
    Unverzagt, F
    Wadley, V
    Doherty, M
    Langbaum, J
    [J]. GERONTOLOGIST, 2005, 45 : 507 - 508
  • [2] Sensory impairment and algorithmic classification of early cognitive impairment
    Cai, Yurun
    Schrack, Jennifer A. A.
    Gross, Alden L. L.
    Armstrong, Nicole M. M.
    Swenor, Bonnielin K. K.
    Deal, Jennifer A. A.
    Lin, Frank R. R.
    Wang, Hang
    Tian, Qu
    An, Yang
    Simonsick, Eleanor M. M.
    Ferrucci, Luigi
    Resnick, Susan M. M.
    Agrawal, Yuri
    [J]. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING, 2023, 15 (02)
  • [3] DERIVATION AND VALIDATION OF AN ALGORITHMIC CLASSIFICATION OF EARLY COGNITIVE IMPAIRMENT
    Gross, Alden
    An, Yang
    Lin, Frank
    Ferrucci, Luigi
    Schrack, Jennifer
    Agrawal, Yuri
    Resnick, Susan
    [J]. INNOVATION IN AGING, 2021, 5 : 436 - 436
  • [4] Olfactory identification and mild cognitive impairment
    Suwalska, Julia
    Lojko, Dorota
    Wieczorowska-Tobis, Katarzyna
    Suwalska, Aleksandra
    [J]. NEUROPSYCHIATRIA I NEUROPSYCHOLOGIA, 2015, 10 (02): : 69 - 77
  • [5] Classification of mild cognitive impairment in a population study
    López, OL
    [J]. REVISTA DE NEUROLOGIA, 2003, 37 (02) : 140 - 144
  • [6] Mild cognitive impairment: classification method and procedure
    Carlos Melendez-Moral, Juan
    Sanz-Alvarez, Teresa
    Navarro-Pardo, Esperanza
    [J]. ANALES DE PSICOLOGIA, 2012, 28 (02): : 604 - 610
  • [7] Application and validation of an algorithmic classification of early impairment in cognitive performance
    Cai, Yurun
    Schrack, Jennifer A.
    Agrawal, Yuri
    Armstrong, Nicole M.
    Wanigatunga, Amal
    Kitner-Triolo, Melissa
    Moghekar, Abhay
    Ferrucci, Luigi
    Simonsick, Eleanor M.
    Resnick, Susan M.
    Gross, Alden L.
    [J]. AGING & MENTAL HEALTH, 2023, 27 (11) : 2187 - 2192
  • [8] Stability of neurocognitive impairment in different subtypes of mild cognitive impairment
    Loewenstein, David A.
    Acevedo, Amarilis
    Agron, Joscelyn
    Duara, Ranjan
    [J]. DEMENTIA AND GERIATRIC COGNITIVE DISORDERS, 2007, 23 (02) : 82 - 86
  • [9] Odor identification in mild cognitive impairment subtypes
    Westervelt, Holly James
    Bruce, Jared M.
    Coon, William G.
    Tremont, Geoffrey
    [J]. JOURNAL OF CLINICAL AND EXPERIMENTAL NEUROPSYCHOLOGY, 2008, 30 (02) : 151 - 156
  • [10] The Role of PPG in Identification of Mild Cognitive Impairment
    Gwak, Migyeong
    Woo, Ellen
    Sarrafzadeh, Majid
    [J]. 12TH ACM INTERNATIONAL CONFERENCE ON PERVASIVE TECHNOLOGIES RELATED TO ASSISTIVE ENVIRONMENTS (PETRA 2019), 2019, : 32 - 35