Univariate logistic regression model for prediction of aneurysm rupture
| Characteristic | Odds ratio | p Value | 95% CI |
| Age ≤60 yr | 1.523 | 0.845 | 0.99 to 3.25 |
| Sex: Female | 1.426 | 0.174 | 0.855 to 2.379 |
| Hypertension | 1.938 | 0.009 | 1.179 to 3.186 |
| Diabetes mellitus | 0.828 | 0.758 | 0.250 to 2.743 |
| Smoking history | 1.000 | 1.000 | 0.475 to 2.104 |
| Alcohol history | 1.212 | 0.622 | 0.565 to 2.599 |
| Family history | 6.513 | <0.001 | 2.597 to 16.329 |
| Location | |||
| MCA | 1.619 | 0.081 | 0.942 to 2.781 |
| PCoA | 1.750 | 0.379 | 0.382 to 1.442 |
| Shape | |||
| Lobulated | 0.624 | 0.103 | 0.353 to 1.100 |
| Fusiform | NC | 0.998 | 0.000 |
| Nmax ≤3 mm | 2.54 | <0.001 | 1.57 to 4.09 |
| Dmax | 0.965 | 0.291 | 0.904 to 1.031 |
| Bottleneck factor | 1.445 | 0.026 | 1.044 to 2.001 |
| Aspect ratio | 1.973 | <0.001 | 1.485 to 2.622 |
Aspect ratio, Depth/Nmax; Bottleneck factor, Dmax/Nmax; Dmax, maximum diameter of aneurysmal dome; MCA, middle cerebral artery; Nmax, maximum diameter of aneurysmal neck; PCoA, posterior communicating artery.