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Research Article

Machine Learning for the Preliminary Diagnosis of Dementia

Table 1

Comparison of demographic data among the groups with different stages of cognitive impairment.

GroupCDR 0CDR 0.5 (MCI)CDR 0.5 (VMD)CDR ≥ 1F/x2

N5111398265
Age, year (mean (SD))68.1 (10.7)71.8 (9.3)76.1 (8.9)78.9 (9.5)30.772<0.001
Female, N (%)24 (47.1)55 (48.7)59 (60.2)156 (58.9)5.6890.128
Education, year (mean (SD))6.9 (5.1)6.4 (4.5)4.4 (4.0)4.5 (4.5)8.452<0.001
MoCA, mean (SD)21.1 (7.1)18.0 (5.6)11.1 (5.1)7.2 (3.9)202.176<0.001
CASI, mean (SD)85.5 (11.3)78.3 (10.1)63.5 (14.0)47.7 (15.1)202.478<0.001
IADL, mean (SD)8.0 (0.0)7.3 (1.2)6.0 (1.5)2.7 (2.0)314.797<0.001
NPI-sum, mean (SD)3.0 (4.1)5.6 (6.8)6.1 (7.3)9.7 (10.5)12.386<0.001

CDR: Clinical Dementia Rating Scale; MCI: mild cognitive impairment; VMD: very mild dementia; N: number of participants; MoCA: Montreal Cognitive Assessment; IADL: Instrumental Activities of Daily Living; NPI-sum: sum score of Neuropsychiatric Inventory. Post hoc analysis showed CDR 0 < MCI < VMD < CDR≧1; post hoc analysis showed CDR 0 = MCI > VMD = CDR≧1; post hoc analysis showed CDR 0 = MCI = VMD < CDR ≥ 1.

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