4.7 Article

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

Journal

SCIENTIFIC REPORTS
Volume 8, Issue -, Pages -

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/s41598-018-28881-1

Keywords

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Funding

  1. National Research Foundation of Korea (NRF) - Ministry of Science, ICT & Future Planning [2016M3C7A1913844]
  2. NRF - Korean government [2015R1C1A2A01053281, 2017R1A2B2005081]
  3. Fire Fighting Safety & 119 Rescue Technology Research and Development Program - National Fire Agency [MPSS-2015-80]
  4. Korea Ministry of Environment (MOE) [2014001360002]
  5. National Research Foundation of Korea [2015R1C1A2A01053281] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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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.

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