Table 2.

Multivariate analysis for predictors of mortality in patients with severe anterior circulation stroke

	Odds ratio	95% Confidence interval	p value
Age (years)	1.08	(0.99, 1.19)	0.09
NIHSS score	1.06	(0.85, 1.34)	0.59
Infarct volume (ml)	1.01	(0.98, 1.01)	0.31
Hyperosmolar therapy	3.11	(0.42, 23.3)	0.72
Bolus ICP treatment	0.66	(0.07, 6.58)	0.27
ACA involvement	9.78	(1.15, 82.8)	0.04*

^*significant

A multivariate logistic regression analysis was used to determine predictors of mortality in patients with severe anterior circulation stroke. A multivariate model was constructed using the least squares approach. Models were created including various predictors allowing for determination of individual regression coefficients and R-squared values. An analysis of variance was used to compare different models. Visual regression diagnostics were performed by plotting residual versus fitted values, standardized residuals versus theoretical quantiles, square root of standardized residuals versus fitted values, and standardized residuals versus leverage. In a multivariate model, only anterior cerebral artery involvement was predictive of mortality (p=0.04).

Abbreviations: NIHSS= National Institutes of Health stroke scale; ICP= Intracranial pressure; ACA= Anterior cerebral artery