Table 4.
Linear regression model to explore baseline variables with statistically significant associations with ICA Calcification in baseline
| Presence vs. absence of ICA calcification §§ | ||||
| Univariable | Multivariable | |||
| p-value § | OR (95% CI) | p-value § | OR (95% CI) b | |
| Age (years) | <0.001 | 1.136 (1.08–1.195) | <0.001 | 1.11 (1.05–1.175) |
| Sex (male versus female) | <0.001 | 2.82 (1.54–5.14) | 0.078 | 1.9 (1.03–2.8) |
| WMH volume (1000 mm3)a | 0.058 | 1.025 (1.002–1.049) | - | - |
| Total hippocampal volume (100 mm3)a | 0.489 | 0.989 (0.958–1.02) | - | - |
| AD cortical signature thickness (mm) | 0.022 | 0.053 (0.006–0.480) | 0.582 | 0.499 (0.042–5.92) |
| Centiloid (5 units)a | 0.49 | 0.985 (0.952–1.02) | - | - |
| High vs. low ICA calcification §§ | ||||
| Univariable | Multivariable | |||
| p-value § | OR (95%CI) | p-value § | OR (95%CI) b | |
| Age (years) | <0.001 | 1.11 (1.06–1.164) | 0.048 | 1.085 (1.015–1.159) |
| Sex (male versus female) | 0.005 | 2.4 (1.40–4.16) | 0.168 | 1.6 (0.807–3.42) |
| WMH volume (1000 mm3)a | 0.005 | 1.030 (1.011–1.048) | 0.163 | 1.012 (0.991–1.033) |
| Total hippocampal volume (100 mm3)a | 0.277 | 0.984 (0.956–1.012) | - | - |
| AD cortical signature thickness (mm) | 0.006 | 0.056 (0.008–0.397) | 0.262 | 0.964 (0.921–1.0080) |
| Centiloid (5 units)a | 0.277 | 0.982 (0.950–1.015) | - | - |
Abbreviations: ICA, internal carotid artery, WMH volume, white matter hyperintensities volume, Centiloid, measure of global amyloid disposition based on conversion of PIB or AV45 PET SUVRs to a standardized scale, AD cortical signature thickness, cortical thickness in signature regions affected in Alzheimer disease (see Dincer et al. 2020), OR (95% CI), odds ratio and 95% confidence interval; the presence or absence of ICA calcification was determined based on natural log transformation of ICA calcium score/volume
aCoefficients are demonstrated for 1000-mm3 increments in WMH volume, 100-mm3 increments in total hippocampal volume, and 5-unit increments in Centiloid scale
bSignificant variables from the univariable model were entered into a stepwise multivariable model where a probability of 0.3 was set to enter the variables into the model and a probability of 0.1 to remove variables from the model
§ p-values were corrected for multiple comparisons through estimation of the false discovery rate via the Benjamini and Hochberg method. Tests with a p-value of 0.05 were considered statistically significant in both regression models (denoted in bold).
§§Presence of ICA calcification was defined based on Agatston ICA calcium score/volume using a cut-off of 0. High versus low ICA calcification was determined using the median value for natural log transformation of ICA calcium score/volume as cut-off