Table 1.
Multivariable polynomial regression of CNN derived lesion volumes to biomarker levels.
| Lesion Type (n) | Biomarker | Coefficient (SE) | 95% Confidence Interval | P-value |
|---|---|---|---|---|
| Total EAH (n=1294) | GFAP | -3.65 (2.68) | -8.91, 1.6 | 0.172 |
| NFL | 0.1 (0.06) | -0.02, 0.22 | 0.094 | |
| NSE | 0.13 (0.12) | -0.1, 0.36 | 0.279 | |
| S100B | 0.12 (0.08) | -0.04, 0.27 | 0.135 | |
| t-tau | 0.1 (0.06) | -0.01, 0.21 | 0.090 | |
| UCH-L1 | 0.49 (2.79) | -4.99, 5.97 | 0.861 | |
| Oedema (n=934) | GFAP | 8.66 (2.28) | 4.19, 13.12 | 0.000*** |
| NFL | 0.22 (0.06) | 0.11, 0.33 | 0.000*** | |
| NSE | 0.28 (0.12) | 0.05, 0.52 | 0.017* | |
| S100B | 1.94 (2.52) | -3, 6.88 | 0.440 | |
| t-tau | 0.17 (0.06) | 0.06, 0.28 | 0.003** | |
| UCH-L1 | 0.16 (0.06) | 0.04, 0.27 | 0.008** | |
| IVH (n=212) | GFAP | 0.16 (0.1) | -0.04, 0.37 | 0.117 |
| NFL | 0.03 (0.12) | -0.21, 0.27 | 0.809 | |
| NSE | -0.08 (0.25) | -0.56, 0.41 | 0.760 | |
| S100B | 0.32 (0.16) | 0.01, 0.64 | 0.042* | |
| t-tau | 0.12 (0.11) | -0.1, 0.34 | 0.293 | |
| UCH-L1 | 0.22 (0.13) | -0.04, 0.48 | 0.090 | |
| IPH (n=659) | GFAP | 5.55 (1.95) | 1.73, 9.38 | 0.004** |
| NFL | 0.1 (0.06) | -0.02, 0.22 | 0.114 | |
| NSE | 0.02 (0.13) | -0.23, 0.28 | 0.853 | |
| S100B | 0.21 (0.09) | 0.04, 0.38 | 0.013* | |
| t-tau | 0.13 (0.06) | 0, 0.25 | 0.044* | |
| UCH-L1 | 0.12 (0.07) | -0.02, 0.25 | 0.082 |
Results of multivariable polynomial regression of the natural log of lesion volume to biomarker level. Adjustment for time to biomarker, time to scan, age, sex, Glasgow Coma Score (GCS), extracranial abbreviated injury score, volume of other lesion types and calculated total brain volume with polynomial terms of non-linear variables. *** p<0·001, ** p<0·01, * p<0·05.