Ms excel

Continuous variables are presented as mean ± standard deviation and categorical variables are presented as frequency and percent. Univariable analyses were carried out using binary logistic regression, Chi-square and Fisher’s exact tests, as appropriate. Post hoc testing for crosstabs exceeding 2×2 dimension was performed by calculating adjusted standardized residuals (z-scores) and associated p-values. Significance was evaluated after Bonferroni correction. Multivariable analysis was performed by integrating variables with a possible association (p < 0.15) with LVO. Stepwise backward elimination was performed and p-values of < 0.05 were considered statistically significant. Collinearity diagnostics were performed assessing correlation coefficients and variance inflation factors. Discrimination of predictive models was performed using the area under the receiver operating characteristic curve (AUC). Analysis of AUC, sensitivity/specificity criteria were calculated with MedCalc. Calibration of scores was tested using Hosmer and Lemeshow test. Comparison of receiver operating characteristic curves was performed using DeLong test. Statistical analyses, creation of figures and charts were performed using IBM SPSS version 22, MedCalc, MS Excel, and Adobe Photoshop CS5.

Data were shown as means ± standard deviations unless otherwise indicated. Graphs were obtained from GraphPad Prism6 or MS Excel and re-generated using Adobe Illustrator. Two-tailed Student’s t test was performed with GraphPad Prism6. *, p < 0.05 **, p < 0.01 ***, p < 0.001