Table 2 Multi-variable statistical analysis was performed on the experimental data in which clot angulation (x1), clot length (x2), clot composition (x3), clot location in device (x4), and clot location in vasculature (x5) were allocated to be the model predictors. Regression coefficients, R2, adjusted R2, and an overall p-value were output from the model
From: Use of patient specific 3D printed neurovascular phantoms to simulate mechanical thrombectomy
Model: y = β0 + x1β1 + x2β2 + x3β3 + x4β4 + x5β5 | ||||
|---|---|---|---|---|
Predictor | Regression Coefficient | Estimate | P-Value | Odds Ratio (95% Confidence Intervals) |
Constant | β0 | 1.005 | 0.0002 |  |
Clot Angulation (x1) | β1 | −0.140 | 0.005 | 0.170 (0.032–0.905) |
Clot Length (x2) | β2 | 0.176 | 0.820 | 1.828 (0.457–7.315) |
Clot Composition (x3) | β3 | −0.183 | 0.369 | 1.300 (0.275–6.137) |
Clot Location in Device (x4) | β4 | −0.008 | 0.179 | 0.885 (0.232–3.380) |
Clot Location in Vasculature (x5) | β5 | −0.004 | 0.664 | 1.714 (0.452–6.506) |