IMITA Score: distinguishing between ischemic stroke and stroke mimics (P3.3-065)

Abstract

Objective: We developed a score to distinguish ischemic strokes (IS) from stroke mimics (SM) and identify patients that could benefit from undergoing brain MRI to confirm or reject the diagnosis of IS.

Background: Stroke mimics represent 25–30% of probable ischemic strokes. Fibrinolysis in these patients seems to be safe but carries high economical cost.

Design/Methods: There were 1314 patients with diagnosis of probable IS between january 2012 and july 2018. Univariate analysis of demographic and clinical variables was performed. Variables with a p<0.25 were entered into a multiple logistic regression model, obtaining adjusted odds ratios (OR) and their beta coefficients. The model was fitted comparing patients that had events of interest and the corresponding model prediction. Precision was tested by Hosmer-Lemeshow Χ2 and the goodness of fit with C-statistic. Finally, the IMITA score was developed, assigning points for each variable based on the regression coefficient. The total score was calculated with the sum of all scores. Internal validity was tested with bootstrapping. Fisher’s exact test and chi square was used for categorical variables and t-test/Mann-Whitney for continuous variables according to distribution assumptions. A p-value of <0.05 was considered statistically significant.

Results: The IMITA score is composed of 4 variables (1 point for each one): male gender (OR 3.6), age > 50 years (OR 6.7), pure motor symptoms (OR 4.4) and absence of pure sensory symptoms (OR 3.3). The ROC curve analysis showed that a IMITA score ≥ 2 has sensitivity of 96%, specificity of 57%, being that the best performance of the score.

Conclusions: A IMITA score ≥ 2 predicts with acceptable sensitivity and specificity patients with IS. A process of external validation will be performed.