Table 1.
Patients’ demographics and dataset characteristics for the predictive modeling.
| Characteristics | Nimodipine Only (n = 232) |
Cilostazol and Nimodipine (n = 89) |
p-Value | Data Type | Value |
|---|---|---|---|---|---|
| Age, y, mean (SD) | 55.47 (12.756) | 55.37 (14.150) | 0.952 | Float | 21–94 |
| Sex, female, n (%) | 147 (63.4) | 51 (57.3) | 0.318 | Binary | 1: male; 2: female |
| GCS on admission, mean (SD) | 12.81 (3.248) | 13.25 (3.185) | 0.279 | Integer | 1–15 |
| Aneurysm size, mm, mean (SD) | 5.63 (3.016) | 6.55 (4.123) | 0.029 | Float | 0.6–27 |
| Hunt–Hess grade | N/A | N/A | 0.142 | Integer | 1–5 |
| 1 | 12 | 1 | |||
| 2 | 115 | 57 | |||
| 3 | 67 | 20 | |||
| 4 | 33 | 9 | |||
| 5 | 5 | 2 | |||
| Fisher grade | N/A | N/A | 0.068 | Integer | 1–4 |
| 1 | 14 | 6 | |||
| 2 | 18 | 12 | |||
| 3 | 103 | 26 | |||
| 4 | 97 | 45 | |||
| Location | N/A | N/A | 0.007 | Integer | 1: ACA; 2: MCA; 3: ICA; 4: VA or BA |
| ACA | 86 | 40 | |||
| MCA | 60 | 10 | |||
| ICA | 74 | 28 | |||
| VA or BA | 12 | 11 | |||
| HTN, n (%) | 95 (40.9) | 35 (39.3) | 0.791 | Binary | 0 or 1 |
| DM, n (%) | 25 (10.8) | 13 (14.6) | 0.342 | Binary | 0 or 1 |
| Hyperlipidemia, n (%) | 17 (7.3) | 12 (13.5) | 0.085 | Binary | 0 or 1 |
| Smoking, n (%) | 76 (32.8) | 37 (41.6) | 0.139 | Binary | 0 or 1 |
| Clip/coil, n (%) | 169 (72.8)/63 (27.2) | 16 (18.0)/73 (82.0) | 0 | Binary | 0 or 1 |
| ACV | 68 (29.3) | 12 (13.5) | 0.003 | Binary | 0 or 1 |
| DCI | 48 (20.7) | 7 (7.9) | 0.006 | Binary | 0 or 1 |
Note: GCS: Glasgow coma scale; ACA: anterior cerebral artery; MCA: middle cerebral artery; ICA: internal carotid artery; VA: vertebral artery; BA: basilar artery; HTN: hypertension; DM: diabetes mellitus; ACV: angiographic cerebral vasospasm; DCI: delayed cerebral infarction; N/A: not applicable.