Participants
Among participants attending a memory clinic at a university hospital in Japan, those with a Clinical Dementia Rating (CDR) score of 0.5 (12) were included. A CDR score of 0.5 has been used as a criterion for diagnosing MCI (13). All participants were Japanese. The exclusion criteria were current serious medical or psychiatric disorder, history of symptomatic cerebrovascular disease, and gait disturbance or needing an assistive device to walk. The study protocol was approved by the Ethics Committee of the Graduate School of Medicine, Nagoya University (2015-04356977). Written informed consent was obtained from all participants. All methods were performed in accordance with the relevant guidelines and regulations.
CDR
The CDR is widely used to determine the clinical stage of cognitive impairment (12;13). Ratings are assigned based on information received from the subject and an accompanying informant on six subscales (memory, orientation, home and hobbies, judgement and problem solving, community affairs, and personal care). Each subscale is rated on a scale of 0–3 (0 = no impairment, 3 = need for maximal assistance), with a global CDR range of 0–3 (0 = a normal healthy individual with no cognitive or functional deficits; 0.5 = a normal healthy individual but with questionable cognitive and/or functional abilities indicating MCI; 1 = mild dementia; 2 = moderate dementia; and 3 = severe dementia). Participants in this study had global CDR scores of either 0 or 0.5.
Neuropsychological assessments
Three experienced clinical neuropsychologists administered the Mini Mental State Examination (MMSE) (14) and the Alzheimer's Disease Assessment Scale (ADAS) for general cognitive function (15).
Clock Drawing Test
The neuropsychologists administered the CDT. Participants were given a blank piece of paper and instructed to draw a clock face measuring 10 cm in diameter, write all the numbers on it, and then draw hands indicating a time of 10 past 11. The neuropsychologists then independently scored the drawn clocks using the method of Cahn et al. (2), whereby both quantitative and qualitative scores are assessed independently. Quantitative scores were determined for three components—integrity of the clock face (0–2 points), absence and sequencing of the numbers (0–4 points), and presence and sequencing of the hands (0–4 points)—and qualitative scores were determined for the eight error types: 1) stimulus-bound response (SB); 2) conceptual deficit (CD), where the error reflects a loss or deficit in accessing knowledge about the attributes, features, and meaning of a clock; 3) perseveration (PR), where the activity continues or recurs without an appropriate stimulus; 4) neglect of left hemi-space (NL), where the clock’s attributes are written only on the right half of the clock face; 5) planning deficit (PD), where there are gaps before the numbers 12, 3, 6 or 9; 6) nonspecific spatial error (NS), where there is no specific pattern in the disorganization of the spatial layout of numbers; 7) numbers written outside of the clock (OC), where the numbers are written either on or around the perimeter; and 8) numbers written counterclockwise (CC), where the numbers are arranged with 12 at the top and then continuing counterclockwise (2). Total CDT score was calculated by subtracting the sum of qualitative scores from the sum of quantitative scores, with a maximum score of 10. The higher the score, the better the performance on the CDT. Cronbach’ alpha for the three raters was 0.980.
Physical assessments
Grip strength in the participant's dominant hand was measured using a portable grip strength dynamometer (GRIP-D; Takei, Niigata, Japan). Gait speed (m/s) was measured using a stopwatch. Participants were instructed to walk 5 m on a flat, straight path twice at their preferred speed and twice at maximum speed, with the average times calculated for each. Two markers were used to indicate the start and end of the walking path. Participants walked a 1-m section in advance of the start marker to ensure that they were walking at a comfortable pace by the time they reached it and the stopwatch was started.
Body composition analysis
The amounts of extracellular and intracellular water in the body were directly measured using electrical current generated at three frequencies (5, 50, and 250 kHz) using a bioelectrical impedance data acquisition system (Inbody 430; Biospace Co., Seoul, South Korea). The system determines appendicular skeletal muscle mass from the segmental body composition and muscle mass. The skeletal muscle mass index (SMI) was calculated by dividing participants’ muscle mass by their height in meters squared (kg/m2).
Brain MRI
T2-weighted and axial FLAIR sequence images were obtained for all participants by head MRI using a 1.5-T MR scanner (either a Vantage system [Toshiba Medical Systems Corporation, Otawara, Japan] or an Avanto system [Siemens, Munich, Germany]). The slice settings were as follows: 20 slices with 6.0-mm thickness and an interslice gap of 7.2-7.5 mm obtained in parallel with the anterior commissure-posterior commissure line, covering a maximum of 144-150 mm and ranging from the vertex to the lower end of the pons. Eight-channel head coils were used for MR signal acquisition and transmission. The parameters of the T2-weighted sequence were as follows: repetition time, 4000-4500 ms; echo time, 91-105 ms; echo train, 13; and number of excitations, 1. The parameters of the FLAIR sequence were as follows: repetition time, 8000 ms; echo time, 100 ms; and inversion time, 2500 ms.
Evaluation of WMLs
In this study, the severity of cerebral WMLs was evaluated using the Fazekas scale, the most widely used method for visually assessing the severity of age-related WMLs. There are four stages of severity (grades 0–3) (16). WMLs were divided into 2 groups: paraventricular hyperintensities (PVH) and deep white matter hyperintensities (DWMH).
Statistical analysis
Continuous variables were compared using Student’s T test, and categorical variables were compared using the chi-square test, between groups with or without each CDT error type. Multiple logistic regression analysis adjusted for age and sex was performed to examine the association of CDT errors with the lowest tertiles of normal and maximum gait speeds.