Liang Chenglong, Pan Shuo, Wu Wei, Chen Fanxuan, Zhang Chengxi, Zhou Chen, Gao Yifan, Ruan Xiangyuan, Quan Shichao, Zhao Qi, Pan Jingye
The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China.
Wenzhou Medical University, Wenzhou 325000, China.
Comput Struct Biotechnol J. 2024 Apr 12;24:292-305. doi: 10.1016/j.csbj.2024.04.020. eCollection 2024 Dec.
Sepsis, a life-threatening medical condition, manifests as new or worsening organ failures due to a dysregulated host response to infection. Many patients with sepsis have manifested a hyperinflammatory phenotype leading to the identification of inflammatory modulation by corticosteroids as a key treatment modality. However, the optimal use of corticosteroids in sepsis treatment remains a contentious subject, necessitating a deeper understanding of their physiological and pharmacological effects. Our study conducts a comprehensive review of randomized controlled trials (RCTs) focusing on traditional corticosteroid treatment in sepsis, alongside an analysis of evolving clinical guidelines. Additionally, we explore the emerging role of artificial intelligence (AI) in medicine, particularly in diagnosing, prognosticating, and treating sepsis. AI's advanced data processing capabilities reveal new avenues for enhancing corticosteroid therapeutic strategies in sepsis. The integration of AI in sepsis treatment has the potential to address existing gaps in knowledge, especially in the application of corticosteroids. Our findings suggest that combining corticosteroid therapy with AI-driven insights could lead to more personalized and effective sepsis treatments. This approach holds promise for improving clinical outcomes and presents a significant advancement in the management of this complex and often fatal condition.
脓毒症是一种危及生命的医学状况,表现为由于宿主对感染的反应失调而导致新的或恶化的器官功能衰竭。许多脓毒症患者表现出高炎症表型,这使得将皮质类固醇的炎症调节作为一种关键治疗方式得以确定。然而,皮质类固醇在脓毒症治疗中的最佳使用仍然是一个有争议的话题,需要更深入地了解它们的生理和药理作用。我们的研究对关注脓毒症传统皮质类固醇治疗的随机对照试验(RCT)进行了全面综述,并对不断演变的临床指南进行了分析。此外,我们探讨了人工智能(AI)在医学中的新兴作用,特别是在脓毒症的诊断、预后和治疗方面。人工智能先进的数据处理能力为加强脓毒症中皮质类固醇治疗策略开辟了新途径。将人工智能整合到脓毒症治疗中有可能弥补现有知识空白,特别是在皮质类固醇的应用方面。我们的研究结果表明,将皮质类固醇治疗与人工智能驱动的见解相结合可能会带来更个性化、更有效的脓毒症治疗。这种方法有望改善临床结果,并在这种复杂且往往致命的疾病管理方面取得重大进展。