Skip to main content
. 2020 Jun 23;162(9):2295–2301. doi: 10.1007/s00701-020-04455-x

Table 3.

Logistic regression and fitted model of possible predictors of deep-vein thrombosis linked to subarachnoid hemorrhage.

Logistic regression Fitted model
OR 95% CI p value OR 95% CI p value
ICA (%) 6.26 * 10−8 3.5.83 * 10−50–2.68 * 1024 0.990
MCA(%) 0.99 0.18–6.35 0.997
ACA(%) 1.15 0.34–4.32 0.935
ACoA(%) 1.40 0.29–8.49 0.688
CP(%) 1.25 0.23–8.32 0.802
SM(%) 0.65 0.02–9.61 0.769
ICH(%) 2.59 0.81–8.39 0.106 2.78 1.07–7.12 0.032*
IVH(%) 0.99 0.33–2.99 0.986
Vasospasm (%) 1.11 0.38–3.05 0.840
Surgical clipping (%) 0.49 0.16–1.42 0.194
Dec craniectomy (%) 1.65 0.34.-7.75 0.520
WFNS scale 0.71 0.43–1.10 0.147 0.73 0.50–1.02 0.086
Fisher 0.97 0.001–1.11 0.819
D-dimer at hosp (mcg/L) 1.003 1.001–1.005 0.028* 1.002 1.001–1.003 0.042*
PT start (days) 1.16 0.90–1.05 0.226
Ventilation days (days) 1.004 0.95–1.05 0.864
Infection (%) 0.71 0.20–2.44 0.597
Motor deficit (%) 6.3 1.77–24.2 0.005* 3.46 1.37–9.31 0.010*

ICA internal carotid artery, MCA middle cerebral artery, ACA anterior cerebral artery, ACoA anterior communicating artery, CP posterior cerebral artery, SM sine materia, ICH intraparenchymal cerebral hemorrhage, IVH intraventricular hemorrhage, WFNS World Federation of Neurological Surgeons, PT pharmacologic thromboprophylaxis

*Statistically significant results