Summary of the best evidence for the prevention of deep vein thrombosis in patients with intracerebral hemorrhage - Xie, Wenguang; Xu, Qingxin; Zhang, Yangyang; Gong, Yanyan; Xiao, Wei; Zhang, Wenhao; Huang, Shuyuan; Li, Huan; Zhang, Chao (Frontiers in Neurology, 2026)
ObjectiveThis study aims to retrieve, evaluate, and summarize the existing evidence regarding the prevention of deep vein thrombosis (DVT) in patients with cerebral hemorrhage. The findings will provide a solid foundation for clinical nursing practice.DesignThis study presents a comprehensive evidence summary conducted in accordance with the standards set forth by the Evidence-Based Nursing Center at Fudan University. The adherence to these standards ensures the rigor and reliability of the findings presented herein.MethodsBased on the ‘5S’ evidence pyramid model, various evidence-based resources for the prevention of deep vein thrombosis in patients with cerebral hemorrhage were systematically retrieved. These resources include clinical decisions, best practices, guidelines, expert consensus, systematic reviews, and evidence summaries. The search period spans from January 2011 to April 2025.ResultsThis study included a total of 16 high-quality articles, comprising 2 clinical decisions, 7 guidelines, 4 expert consensuses, 2 systematic reviews, and 1 summary of evidence. In total, 38 pieces of evidence were synthesized across six dimensions: risk assessment, basic prevention, mechanical prevention, pharmacological prevention, nursing documentation, and informed consent.ConclusionThis study summarizes the 38 most compelling pieces of evidence for the prevention of DVT in patients with cerebral hemorrhage, providing an evidence-based foundation for clinical medical staff. It is recommended that healthcare professionals implement these evidence-based practices in clinical settings to effectively reduce the incidence of DVT among patients suffering from cerebral hemorrhage.Systematic review registrationhttp://ebn.nursing.fudan.edu.cn/registerResources, identifier ES2025786.