The overall objective of the study is to identify prognostic predictors of cerebrovascular disease during various stages of the cerebrovascular disease itself, namely: hospitalization at the acute care facility, residential hospitalization at neurorehabilitation facilities, outpatient follow-up visits, and day hospital admissions at the various facilities. The aim is to obtain data on those factors that can influence the prognosis, thus the clinical outcome, of patients with cerebrovascular disease. Cerebrovascular diseases are defined by the World Health Organization (WHO) as all those disorders in which there is an area of the brain transiently or permanently affected by ischemia or bleeding or in which one or more cerebral blood vessels are primarily affected in a pathological process, or a combination of the two conditions mentioned above. These diseases include a wide range of conditions, of which ischemic stroke and cerebral hemorrhage are the most common. Given the high overall frequency of these diseases and, consequently, the high social and economic cost of them on the population, it is essential to recognize as soon as possible those factors capable of predicting the time course of patients affected, as you are, by these diseases, also with a view to identifying strategies to improve the prognosis of patients for whom an unfavorable outcome is predicted. In addition, given the high prevalence of cerebrovascular disease, it is necessary that an extremely large patient population be enrolled, and thus an enormous amount of data be collected, in order for meaningful results to be obtained. The primary objective of this study is, in fact, to collect a large amount of clinical data, i.e., to establish a national data registry, obtained from the records of patients with cerebrovascular diseases that began after January 1, 2016, in order to be able to identify and define the subtypes of each cerebrovascular disease associated with poor prognosis. The secondary objectives are to identify clinical, neurophysiological, radiological, and biomarker data that are able to predict the clinical course of cerebrovascular disease over time and to identify prognostic scores obtained from the combination of the variables first indicated. With this study, we also aim to identify those clinical, radiological, and neurophysiological data that are able to help the clinician in the early differential diagnosis of these diseases and that are able to predict the occurrence of spontaneous or procedure-related complications and the successful outcome of treatment. Finally, we aim to identify those clinical, radiological, and neurophysiological variables that are able to predict a good outcome of rehabilitation performed as a result of the onset of cerebrovascular disease.