Table 4

Stepwise linear regression of SDMT in multiple sclerosis

Model summary+predictorsRegression
coefficient
95% CIP values
MRI metrics
SDMT scoreAdj.R2=0.361
DGM, cm3 1.61(0.79 to 2.43) < 0.001
Lesion load, mL−0.17(−0.34 to −0.0014) 0.048
Female12.16(5.51 to 18.82) < 0.001
MRI metrics+network measures
SDMT scoreAdj.R2=0.352
DGM, cm3 1.52(0.61 to 2.43) 0.001
Lesion load, mL−0.17(−0.34 to 0.0069)0.059
Edge density, (%)0.24(−0.75 to 1.23)0.624
Female11.94(5.18 to 18.70) < 0.001
Adj.R2=0.396
DGM, cm3 1.93(1.21 to 2.65) < 0.001
Global efficiency0.021(0.0055 to 0.035) 0.008
Female10.97(4.37 to 17.56) 0.002
Adj.R2=0.380
DGM, cm3 2.01(1.28 to 2.75) < 0.001
mLE0.015(0.0028 to 0.028) 0.018
Female11.43(4.79 to 18.06) 0.001
Adj.R2=0.387
DGM, cm3 1.45(0.63 to 2.28) < 0.001
mCC0.21(0.047 to 0.38) 0.013
Female9.92(2.98 to 16.85) 0.006
Final model
SDMT scoreAdj.R2=0.396
DGM, cm3 1.93(1.21 to 2.65) < 0.001
Global efficiency0.021(0.0055 to 0.035) 0.008
Female10.97(4.36 to 17.56) 0.002
  • P values in bold denote statistical significance at p<0.05.

  • DGM, deep grey matter; SDMT, Symbol Digit Modalities Test; mCC, mean clustering coefficient; mLE, mean local efficiency.