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. 2018 Dec 10;4(4):2055217318815513. doi: 10.1177/2055217318815513

Table 1.

Demographics at baseline.

MS patientsn=66 Non-MS controlsn=40
Age in years (SD) 47.5 (12.4) 35.2 (14.7)
Gender
 Male 14 (21%) 12 (30%)
 Female 52 (79%) 28 (70%)
MS characteristics
 RRMS 51 (73%) -
 EDSS (median, IQR) 2.5 (1.25, 4.0) -
 Disease duration (years, (SD)) 14.0 (10.8) -
Baseline data (mean, SD)
 PASAT (n=56) 46.37 (11.83) 55.63 (5.95)
CBB (n=66)
Detection (DET)a
 Speed 2.56 (0.11) 2.51 (0.07)
 Accuracy 1.47 (0.11) 1.50 (0.09)
Identification (IDN)a
 Speed 2.75 (0.09) 2.69 (0.08)
 Accuracy 1.43 (0.13) 1.43 (0.15)
One card back (ONB)a
 Speed 2.91 (0.09) 2.84 (0.11)
 Accuracy 1.36 (0.15) 1.42 (0.17)
One card learning (OCL)a
 Speed 3.01 (0.27) 2.99 (0.10)
 Accuracy 0.99 (0.10) 1.05 (0.10)
Continuous paired associate learning (CPAL)
 Errors 30.89 (32.17) 12.23 (15.21)
Groton maze learning (GML)
 Errors 46.45 (16.22) 36.90 (12.88)

CBB: CogState Brief Battery; EDSS: Expanded Disability Status Scale; IQR: interquartile range; MS: multiple sclerosis; PASAT: Paced Auditory Serial Addition Test; RRMS: relapsing–remitting multiple sclerosis; SD: standard deviation.

aValues shown after base 10 logarithmic transformation.