College of Medicine, University of Florida, Gainesville, FL 32610, USA.
College of Medicine, University of Miami-Miller School of Medicine, Miami, FL 33136, USA.
Medicina (Kaunas). 2023 Sep 25;59(10):1714. doi: 10.3390/medicina59101714.
Platelets play a critical role in blood clotting and the development of arterial blockages. Antiplatelet therapy is vital for preventing recurring events in conditions like coronary artery disease and strokes. However, there is a lack of comprehensive guidelines for using antiplatelet agents in elective neurosurgery. Continuing therapy during surgery poses a bleeding risk, while discontinuing it before surgery increases the risk of thrombosis. Discontinuation is recommended in neurosurgical settings but carries an elevated risk of ischemic events. Conversely, maintaining antithrombotic therapy may increase bleeding and the need for transfusions, leading to a poor prognosis. Artificial intelligence (AI) holds promise in making difficult decisions regarding antiplatelet therapy. This paper discusses current clinical guidelines and supported regimens for antiplatelet therapy in neurosurgery. It also explores methodologies like P2Y12 reaction units (PRU) monitoring and thromboelastography (TEG) mapping for monitoring the use of antiplatelet regimens as well as their limitations. The paper explores the potential of AI to overcome such limitations associated with PRU monitoring and TEG mapping. It highlights various studies in the field of cardiovascular and neuroendovascular surgery which use AI prediction models to forecast adverse outcomes such as ischemia and bleeding, offering assistance in decision-making for antiplatelet therapy. In addition, the use of AI to improve patient adherence to antiplatelet regimens is also considered. Overall, this research aims to provide insights into the use of antiplatelet therapy and the role of AI in optimizing treatment plans in neurosurgical settings.
血小板在血液凝固和动脉阻塞的发展中起着关键作用。抗血小板治疗对于预防冠心病和中风等疾病的复发事件至关重要。然而，在择期神经外科手术中使用抗血小板药物缺乏全面的指南。手术期间继续治疗会增加出血风险，而手术前停止治疗会增加血栓形成的风险。神经外科手术中推荐停药，但会增加缺血事件的风险。相反，维持抗血栓治疗可能会增加出血和输血的需求，导致预后不良。人工智能（AI）在做出抗血小板治疗的困难决策方面具有很大的潜力。本文讨论了目前神经外科抗血小板治疗的临床指南和支持方案。还探讨了监测抗血小板方案使用的 P2Y12 反应单位（PRU）监测和血栓弹力图（TEG）图谱等方法，以及它们的局限性。本文探讨了 AI 克服与 PRU 监测和 TEG 图谱相关的局限性的潜力。它强调了心血管和神经血管外科学领域的各种研究，这些研究使用 AI 预测模型来预测缺血和出血等不良后果，为抗血小板治疗的决策提供帮助。此外，还考虑了使用 AI 提高患者对抗血小板治疗方案的依从性。总的来说，这项研究旨在深入了解抗血小板治疗的使用情况以及 AI 在优化神经外科治疗方案中的作用。
