Prediction Models of Cognitive Trajectories in Patients with Nonamnestic Mild Cognitive Impairment

被引:17
|
作者
Lee, Jin San [1 ,2 ,3 ]
Cho, Seong-Kyung [4 ]
Kim, Hee Jin [1 ,2 ]
Kim, Yeo Jin [5 ]
Park, Key-Chung [3 ]
Lockhart, Samuel N. [6 ]
Na, Duk L. [1 ,2 ,8 ]
Kim, Changsoo [7 ]
Seo, Sang Won [1 ,2 ,8 ,9 ]
机构
[1] Sungkyunkwan Univ, Sch Med, Samsung Med Ctr, Dept Neurol, Seoul 06351, South Korea
[2] Samsung Med Ctr, Neurosci Ctr, Seoul 06351, South Korea
[3] Kyung Hee Univ Hosp, Dept Neurol, Seoul, South Korea
[4] Yonsei Univ, Wonju Coll Med, Dept Prevent Med, Wonju, South Korea
[5] Hallym Univ, Chuncheon Sacred Heart Hosp, Dept Neurol, Coll Med, Chunchon, South Korea
[6] Wake Forest Sch Med, Dept Internal Med, Winston Salem, NC USA
[7] Yonsei Univ, Dept Prevent Med, Coll Med, Seoul, South Korea
[8] Sungkyunkwan Univ, Dept Hlth Sci & Technol, SAIHST, Seoul 06351, South Korea
[9] Sungkyunkwan Univ, Clin Res Design & Evaluat, SAIHST, Seoul 06351, South Korea
来源
SCIENTIFIC REPORTS | 2018年 / 8卷
基金
新加坡国家研究基金会;
关键词
ALZHEIMERS-DISEASE; DEMENTIA; PROGRESSION; DIAGNOSIS; CONVERSION; CRITERIA;
D O I
10.1038/s41598-018-28881-1
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
To evaluate prediction models of cognitive trajectories in patients with nonamnestic mild cognitive impairment (naMCI) using group-based trajectory analysis, we evaluated 121 patients with naMCI who underwent at least their first three yearly assessments. Group-based trajectory models were used to classify cognitive trajectories based on Clinical Dementia Rating Sum of Boxes scores over four years in patients with naMCI. A total of 22 patients (18.2%) were classified into the "fast-decliners" group, while 99 patients (81.8%) were classified into the "slow-decliners" group. The mean age was higher in the fast-decliners than in the slow-decliners (p = 0.037). Compared to the slow-decliners, the fast-decliners were more frequently impaired in the domains of language (p = 0.038) and frontal/executive functions (p = 0.042), and had more frequent multiple-domain cognitive impairment (p = 0.006) on baseline neuropsychological tests. The rate of conversion to dementia was significantly higher in the fast-decliners than in the slow-decliners (86.4% vs. 10.1%, p < 0.001). Our findings showed that there are indeed distinct patterns of cognitive trajectories in patients with naMCI. Close observation of naMCI patients' baseline demographic and clinical profiles in clinical settings may help identify individuals at greatest risk for dementia.
引用
收藏
页数:8
相关论文
共 50 条
  • [31] Prevalence of mild behavioral impairment in patients with mild cognitive impairment
    Kianimehr, Gilda
    Fatehi, Farzad
    Noroozian, Maryam
    ACTA NEUROLOGICA BELGICA, 2022, 122 (06) : 1493 - 1497
  • [32] Prediction of Clinical Scores for Subjective Cognitive Decline and Mild Cognitive Impairment
    Li, Aojie
    Yue, Ling
    Liu, Manhua
    Xiao, Shifu
    PREDICTIVE INTELLIGENCE IN MEDICINE (PRIME 2019), 2019, 11843 : 134 - 141
  • [33] Mild cognitive impairment and subjective cognitive impairment
    Takeda, Masatoshi
    Morihara, Takashi
    Okochi, Masayasu
    Sadik, Golam
    Tanaka, Toshihisa
    PSYCHOGERIATRICS, 2008, 8 (04) : 155 - 160
  • [34] Increased morning salivary cortisol levels in older adults with nonamnestic and multidomain mild cognitive impairment
    Venero, Cesar
    Diaz-Mardomingo, Carmen
    Pereda-Perez, Inmaculada
    Garcia-Herranz, Sara
    Utrera, Lucia
    Valencia, Azucena
    Peraita, Herminia
    PSYCHONEUROENDOCRINOLOGY, 2013, 38 (04) : 488 - 498
  • [35] Mild cognitive impairment in patients with epilepsy
    Korostiy, V.
    Blazhina, I.
    EUROPEAN PSYCHIATRY, 2019, 56 : S138 - S138
  • [36] Prediction Models of Mild Cognitive Impairment Using the Korea Longitudinal Study of Ageing
    Park, Hyojin
    Ha, Juyoung
    JOURNAL OF KOREAN ACADEMY OF NURSING, 2020, 50 (02) : 191 - 199
  • [37] Neuropsychological prediction of conversion to Alzheimer disease in patients with mild cognitive impairment
    Tabert, Matthias H.
    Manly, Jennifer J.
    Liu, Xinhua
    Pelton, Gregory H.
    Rosenblum, Sara
    Jacobs, Marni
    Zamora, Diana
    Goodkind, Madeleine
    Bell, Karen
    Stern, Yaakov
    Devanand, D. P.
    ARCHIVES OF GENERAL PSYCHIATRY, 2006, 63 (08) : 916 - 924
  • [38] CLINICAL FACTORS FOR PREDICTION OF MILD COGNITIVE IMPAIRMENT IN PATIENTS RECEIVING DIALYSIS
    Chen, Jin-Bor
    Lung-Chih, Li
    Wen-Chin, Lee
    Chiung-Chih, Chang
    Chen, Chiu-Hua
    NEPHROLOGY DIALYSIS TRANSPLANTATION, 2019, 34 : 389 - 389
  • [39] Trajectories of Occupational Cognitive Demands and Risk of Mild Cognitive Impairment and Dementia in Later Life
    Edwin, Trine H.
    Haberg, Asta K.
    Zotcheva, Ekaterina
    Bratsberg, Bernt
    Jugessur, Astanand
    Engdahl, Bo
    Bowen, Catherine
    Selbaek, Geir
    Kohler, Hans-Peter
    Harris, Jennifer R.
    Tom, Sarah E.
    Krokstad, Steinar
    Mekonnen, Teferi
    Stern, Yaakov
    Skirbekk, Vegard F.
    Strand, Bjorn H.
    NEUROLOGY, 2024, 102 (09) : e209353
  • [40] Uncovering heterogeneous cognitive trajectories in mild cognitive impairment: a data-driven approach
    Wang, Xiwu
    Ye, Teng
    Zhou, Wenjun
    Zhang, Jie
    Alzheimer's Disease Neuroimaging Initiative, Alzheimer's Disease Neuroimaging Initiative
    ALZHEIMERS RESEARCH & THERAPY, 2023, 15 (01)