Anticoagulant-associated Intracranial Hemorrhage

Study observational. The total number of subjects for this study will be determined by the number of patients with intracranial bleeding associated with anticoagulant therapy on the clinical records. Primary objective: To identify the incidence and prevalence of intracranial bleeding events associated to oral anticoagulant therapy including vitamin k antagonists, factor Xa inhibitors and factor 2a inhibitors. Secondary objective: * To identify mortality related to intracranial bleeding associated with oral anticoagulant therapy, including vitamin K antagonists, factor Xa inhibitors and factor 2a inhibitors. * To identify patients´ characteristics correlated with intracranial hemorrhage associated with oral anticoagulants. * To identify treatment patterns: anticoagulant-associated intracranial bleeding management, including clinical, pharmacological, surgical, and interventional treatments, as well as procoagulant therapies. Sample size Justification / Statistical Analysis: Non probabilistic, incidental reasoned selection. The sample size will be determined by the number of patients with intracranial hemorrhage associated with anticoagulation in the clinical records. All electronic medical records that meet the inclusion criteria will be included in the analysis. Descriptive analysis: Descriptive statistics will be used for demographic and clinical characteristics of the study sample. This will include measures of central tendency (mean, median) and measures of dispersion (standard deviation, range). Analytic (Inferential) analysis: A univariate analysis will take place in order to examine the relationship between demographic and clinical variables with anticoagulation-associated intracranial hemorrhage This will include chi-squared tests for categorical data and T-tests or Mann-Whitney U Tests for continuous data. A multivariable logistic regression analysis will be done to identify independent predictors of intracranial bleeding associated with anticoagulant therapy. The variables to include in the model will be determined by de univariate analysis results. The investigators will consider a p-value under 0.05 for statistical significance.