Carlos Fernández Baltar, María Elena Martínez Corral, Daniel Pérez Fentes
{"title":"个性化医疗时代经皮肾镜取石术并发症的预测与避免:范围综述》。","authors":"Carlos Fernández Baltar, María Elena Martínez Corral, Daniel Pérez Fentes","doi":"10.3390/jpm14090962","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>This scoping review highlights the potential of emerging technologies in reducing and predicting PCNL complications. However, larger prospective studies are required for validation.</p>","PeriodicalId":16722,"journal":{"name":"Journal of Personalized Medicine","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11432793/pdf/","citationCount":"0","resultStr":"{\"title\":\"Predicting and Avoiding Complications in Percutaneous Nephrolithotomy in the Era of Personalized Medicine: A Scoping Review.\",\"authors\":\"Carlos Fernández Baltar, María Elena Martínez Corral, Daniel Pérez Fentes\",\"doi\":\"10.3390/jpm14090962\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>This scoping review highlights the potential of emerging technologies in reducing and predicting PCNL complications. However, larger prospective studies are required for validation.</p>\",\"PeriodicalId\":16722,\"journal\":{\"name\":\"Journal of Personalized Medicine\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11432793/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Personalized Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3390/jpm14090962\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Personalized Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3390/jpm14090962","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
Predicting and Avoiding Complications in Percutaneous Nephrolithotomy in the Era of Personalized Medicine: A Scoping Review.
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.
期刊介绍:
Journal of Personalized Medicine (JPM; ISSN 2075-4426) is an international, open access journal aimed at bringing all aspects of personalized medicine to one platform. JPM publishes cutting edge, innovative preclinical and translational scientific research and technologies related to personalized medicine (e.g., pharmacogenomics/proteomics, systems biology). JPM recognizes that personalized medicine—the assessment of genetic, environmental and host factors that cause variability of individuals—is a challenging, transdisciplinary topic that requires discussions from a range of experts. For a comprehensive perspective of personalized medicine, JPM aims to integrate expertise from the molecular and translational sciences, therapeutics and diagnostics, as well as discussions of regulatory, social, ethical and policy aspects. We provide a forum to bring together academic and clinical researchers, biotechnology, diagnostic and pharmaceutical companies, health professionals, regulatory and ethical experts, and government and regulatory authorities.