An intracerebral haemorrhage (ICH) is a general type of haemorrhage in the brain, which arises due to the rupture of cerebral blood vessels. Many molecules have been investigated for their potential ability to modify hemostasis and blood-brain barrier function in ICH. Vascular endothelial growth factor (VEGF) is highly expressed in some diseases and helps induce angiogenesis. VEGF serves as a key mediator of the angiogenic pathway and is now recognized as a major contributor to cerebrovascular diseases; many promising results have been obtained in animal therapeutic experiments. VEGF promotes blood vessel growth (angiogenesis) to increase oxygen and nutrient supply in damaged tissues, and exerts neuroprotective effects in processes including inflammation, apoptosis, neurotrophy, and protein clearance. This review examines the dual roles of VEGF in the pathology of ICH and explores therapeutic targets of VEGF pathways for this disease.

Database (DB) exploitation is an essential tool in medical and epidemiological research, enabling the extraction of hidden insights from large volumes of information through statistical analysis. This work provides a methodological reflection on two critical aspects of such studies, namely sample size and confounder detection via multivariate analysis. When working with databases, researchers must perform statistical inference based exclusively on the available data and therefore often ask whether the fixed sample size is sufficient to detect relationships of interest. In most cases, no threshold value separates valid sizes from invalid ones, as statistical power increases gradually and depends on multiple parameters, with no fixed cutoff points. Even when the results are inconclusive (high p-values), possibly because of limited sample size, their publication is essential to feed future meta-analyses that may provide more solid conclusions. DB analysis requires discriminating between general and circumstantial associations. Although the relationships revealed by univariate analysis maintain their descriptive value, the accuracy of their interpretation can be increased by identifying possible confounding factors.