Li Pengcheng, Wang Yan, Zhao Runkai, Hao Lin, Chai Wei, Jiying Chen, Feng Zeyu, Ji Quanbo, Zhang Guoqiang
Department of Orthopaedics, General Hospital of Chinese People's Liberation Army, Beijing 100853, China.
Department of Orthopaedics, General Hospital of Chinese People's Liberation Army, Beijing 100853, China; Beijing National Research Center for Information Science and Technology (BNRist), Beijing, China; Department of Automation, Tsinghua University, Beijing, China.
J Adv Res. 2025 Mar 28. doi: 10.1016/j.jare.2025.03.039.
Periprosthetic joint infection (PJI) represents one of the most devastating complications following total joint arthroplasty, often necessitating additional surgeries and antimicrobial therapy, and potentially leading to disability. This significantly increases the burden on both patients and the healthcare system. Given the considerable suffering caused by PJI, its prevention and treatment have long been focal points of concern. However, challenges remain in accurately assessing individual risk, preventing the infection, improving diagnostic methods, and enhancing treatment outcomes. The development and application of artificial intelligence (AI) technologies have introduced new, more efficient possibilities for the management of many diseases. In this article, we review the applications of AI in the prevention, diagnosis, and treatment of PJI, and explore how AI methodologies might achieve individualized risk prediction, improve diagnostic algorithms through biomarkers and pathology, and enhance the efficacy of antimicrobial and surgical treatments. We hope that through multimodal AI applications, intelligent management of PJI can be realized in the future.
人工关节周围感染（PJI）是全关节置换术后最具破坏性的并发症之一，常常需要额外的手术和抗菌治疗，并可能导致残疾。这显著增加了患者和医疗系统的负担。鉴于PJI造成的巨大痛苦，其预防和治疗长期以来一直是关注的焦点。然而，在准确评估个体风险、预防感染、改进诊断方法以及提高治疗效果方面仍存在挑战。人工智能（AI）技术的发展和应用为许多疾病的管理带来了新的、更高效的可能性。在本文中，我们回顾了AI在PJI预防、诊断和治疗中的应用，并探讨AI方法如何实现个性化风险预测、通过生物标志物和病理学改进诊断算法，以及提高抗菌和手术治疗的疗效。我们希望通过多模式AI应用，未来能够实现PJI的智能管理。
