Palomares Sara Morales, Ferrara Gaetano, Sguanci Marco, Gazineo Domenica, Godino Lea, Palmisano Addolorata, Paderno Alberto, Vrenna Giada, Faraglia Eleonora, Petrelli Fabio, Cangelosi Giovanni, Gravante Francesco, Mancin Stefano
Department of Pharmacy, Health and Nutritional Sciences (DFSSN), University of Calabria, Rende, Italy; Gruppo Formazione e Ricerca Società Infermieri di Area Nefrologica (SIAN), Olbia, Italy.
Gruppo Formazione e Ricerca Società Infermieri di Area Nefrologica (SIAN), Olbia, Italy.
J Ren Nutr. 2025 Jun 28. doi: 10.1053/j.jrn.2025.06.002.
Chronic kidney disease is a global health challenge, and effective, individualized nutritional management is crucial for slowing progression and improving quality of life. Artificial intelligence (AI) offers innovative tools to optimize and personalize nutritional care. This review explores AI applications in nutritional management, assessing their impact on clinical outcomes, quality of life, and care efficiency.
A systematic review was conducted, reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Searches were performed on 5 databases, namely MEDLINE, Embase, Cochrane Library, Cumulative Index to Nursing and Allied Health Literature, and integrated with gray literature sources between September and November 2024. The methodological quality assessment was conducted independently by 2 researchers using the Joanna Briggs Institute methodology.
Of 2,053 initial records, 7 studies met inclusion criteria. AI showed significant potential in personalizing dietary recommendations using machine learning, clinical decision support systems, and generative AI tools. These systems tailored nutritional advice based on patient-specific clinical data, reducing complications such as hyperkalemia and improving adherence. AI also facilitated early risk detection and proactive care by monitoring nutritional parameters and predicting complications. In addition, AI-powered platforms enhanced patient education through culturally relevant, intuitive dietary plans and multilingual materials, increasing engagement. AI also improved health care efficiency by automating tasks and integrating with electronic health records.
AI technologies show promise in enhancing nutritional care for patients with chronic kidney disease. Evidence supports their role in improving care quality and dietary adherence. Further research is needed to validate these technologies in clinical practice and ensure integration into routine care pathways.
慢性肾脏病是一项全球性的健康挑战，有效的个体化营养管理对于减缓疾病进展和提高生活质量至关重要。人工智能（AI）提供了创新工具，可优化和个性化营养护理。本综述探讨了AI在营养管理中的应用，评估其对临床结局、生活质量和护理效率的影响。
按照系统评价和Meta分析的首选报告项目指南进行了一项系统评价。于2024年9月至11月在5个数据库（即MEDLINE、Embase、Cochrane图书馆、护理学与健康相关文献累积索引）中进行检索，并与灰色文献来源相结合。由2名研究人员使用乔安娜·布里格斯研究所的方法独立进行方法学质量评估。
在2053条初始记录中，有7项研究符合纳入标准。AI在使用机器学习、临床决策支持系统和生成式AI工具来个性化饮食建议方面显示出巨大潜力。这些系统根据患者特定的临床数据量身定制营养建议，减少了高钾血症等并发症并提高了依从性。AI还通过监测营养参数和预测并发症促进了早期风险检测和积极护理。此外，由AI驱动的平台通过提供与文化相关、直观的饮食计划和多语言材料加强了患者教育，提高了参与度。AI还通过自动化任务和与电子健康记录集成提高了医疗保健效率。
AI技术在加强慢性肾脏病患者的营养护理方面显示出前景。有证据支持它们在改善护理质量和饮食依从性方面的作用。需要进一步研究以在临床实践中验证这些技术，并确保将其纳入常规护理路径。
