Fernández Baltar Carlos, Martínez Corral María Elena, Pérez Fentes Daniel
Department of Urology, University Hospital Complex of Pontevedra, 36071 Pontevedra, Spain.
Department of Urology, University Hospital Complex of Santiago de Compostela, 15706 Santiago de Compostela, Spain.
J Pers Med. 2024 Sep 10;14(9):962. doi: 10.3390/jpm14090962.
Percutaneous nephrolithotomy (PCNL) is associated with a wide range of complications. This review aims to explore how recent technological advancements and personalized medicine can help prevent or predict these complications.
A scoping review was conducted according to the PRISMA-SCR guidelines and registered on the Open Science Framework in April 2024. A literature search was performed on PUBMED, Web of Science, and Scopus databases. This review focused on predictive AI models, 3D surgical models, intrasurgical image guidance, and biomarkers. Articles meeting the following criteria were included: publication between 2019 and 2024, written in English, involving human participants, and discussing technological advancements or personalized medicine in the context of complications in PCNL.
Of the 11,098 articles searched, 35 new studies were included. We identified a few articles on predictive AI models. Several studies demonstrated that 3D presurgical models and virtual models could enhance surgical planning and reduce complications. New intrasurgical image and guidance systems showed the potential in reducing bleeding and radiation exposure. Finally, several biomarkers were identified as predictors of sepsis and other complications.
This scoping review highlights the potential of emerging technologies in reducing and predicting PCNL complications. However, larger prospective studies are required for validation.
经皮肾镜取石术（PCNL）会引发多种并发症。本综述旨在探讨近期的技术进步和个性化医疗如何有助于预防或预测这些并发症。
根据PRISMA - SCR指南进行了一项范围综述，并于2024年4月在开放科学框架上注册。在PUBMED、科学网和Scopus数据库上进行了文献检索。本综述聚焦于预测性人工智能模型、3D手术模型、术中图像引导和生物标志物。纳入符合以下标准的文章：2019年至2024年发表、英文撰写、涉及人类参与者且在PCNL并发症背景下讨论技术进步或个性化医疗。
在检索的11,098篇文章中，纳入了35项新研究。我们找到了几篇关于预测性人工智能模型的文章。多项研究表明，3D术前模型和虚拟模型可改善手术规划并减少并发症。新的术中图像和引导系统显示出在减少出血和辐射暴露方面的潜力。最后，几种生物标志物被确定为脓毒症和其他并发症的预测指标。
本范围综述突出了新兴技术在减少和预测PCNL并发症方面的潜力。然而，需要更大规模的前瞻性研究进行验证。
