Statistical Analysis
Data analysis was performed by SPSS® Statistics software V. 21 (IBM®, Chicago, USA).
Mean and standard deviations were calculated for continuous variables (i.e. age, age at onset, duration of illness etc.) and percentages calculated for categorical values. Chi-square test for variance (χ2) was applied to categorical socio-demographic data, assumed to be normally distributed (i.e. gender/ age differences). Student’s t-test was used to analyze statistical significance of differences between the means of continuous variables (i.e. age/gender vs. medication usage, predictability of attacks etc.). Analysis of variance (ANOVA) and multivariate analysis of variance (MANOVA, unidirectional with repeated measurements) were used to assess differences between prodromes and attacks, as related to personal categorical values. Pearsons’ correlation coefficient was calculated for associations between continuous personal variables and scalable parameters. Stepwise Hierarchical Regression analysis was used to assess the contribution of health-related personal variables of prodromes to variables of attack, in which the personal health variables were forcedly introduced first, prodrome variables second, and thirdly- the interactions between personal and prodrome variables. Sensitivity and specificity computations assessed the clinical utility of the new instruments.