Table 2.
MRI outcomes among EDIC participants and control subjects without diabetes
| EDIC participants | Control subjects | P | Cohen d | Equivalent years of age | |
|---|---|---|---|---|---|
| N | 416 | 99 | |||
| TBV (cm3) | 1,206 ± 1.7 | 1,229 ± 3.5 | <0.0001 | −0.67 | 7.1 |
| GMV (cm3) | 647 ± 1.7 | 660 ± 3.4 | 0.0008 | −0.37 | 4.4 |
| WMV (cm3) | 538 ± 1.5 | 549 ± 2.8 | 0.0002 | −0.38 | — |
| Ventricle volume (cm3) | 34 ± 0.7 | 26 ± 1.5 | <0.0001 | 0.53 | 8.6 |
| Subarachnoid CSF volume (cm3) | 198 ± 1.6 | 182 ± 3.2 | <0.0001 | 0.47 | 6.4 |
| WMH volume (cm3)* | 2.68 ± 0.17 | 2.20 ± 0.27 | |||
| WMH asinh volume (cm3)* | 1.37 ± 0.04 | 1.03 ± 0.08 | 0.0003 | 0.46 | 7.9 |
| Total white matter mean FA† | 0.409 ± 0.001 | 0.414 ± 0.002 | 0.0579 | −0.22 | 6.2 |
Data are least squares means ± SE from linear mixed models with adjustment for ICV, age, and scanner. We calculated Cohen d effect size by taking the difference in means between EDIC participants and control subjects and dividing by the pooled SD. We estimated the additional number of years of age that would yield the same difference in each MRI outcome as the difference between control subjects without diabetes and T1DM participants by taking the ratio of the β-coefficient estimate for subject group (1 = participant, 0 = control) to that for age from a linear mixed model that included both factors. The equivalent years of aging is not presented for WMV, since age was not a significant factor in the model.
WMH was assessed in N = 381 EDIC participants and N = 82 control subjects; an inverse hyperbolic sine transformation was used to normalize the distribution (asinh).
Total white matter mean FA was assessed in N = 363 EDIC participants and N = 80 control subjects and was not adjusted for ICV.