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Predicting and Avoiding Complications in Percutaneous Nephrolithotomy in the Era of Personalized Medicine: A Scoping
Carlos Fernández Baltar1, María Elena Martínez Corral2, Daniel Pérez Fentes2
1Department of Urology, University Hospital Complex of Pontevedra, 36071 Pontevedra, Spain.
Background:
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.
Methods:
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.
Results:
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.
Conclusion:
This scoping review highlights the potential of emerging technologies in reducing and predicting PCNL complications. However, larger prospective studies are required for validation.
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