{"title":"评估营养支持团队的影响和人工智能在机械通气ICU患者临床结果中的作用:一项全面的综述","authors":"Yasamin Mohammadi","doi":"10.1016/j.nutos.2025.08.002","DOIUrl":null,"url":null,"abstract":"<div><div>This review examines the critical role of nutrition support teams (NSTs) in managing nutrition for mechanically ventilated patients in the intensive care unit (ICU). Nutritional support is essential for improving clinical outcomes in critically ill patients, with enteral nutrition (EN) being the preferred method. Early enteral nutrition (EEN) has demonstrated significant benefits, reducing complications such as infections, multi-organ failure, and prolonged mechanical ventilation. The review emphasizes the importance of a multidisciplinary approach, with NSTs playing a vital role in ensuring early and adequate nutritional support, which improves recovery outcomes. Additionally, the integration of artificial intelligence (AI) and machine learning (ML) in ICU nutrition management is explored, focusing on how these technologies can enhance decision-making and optimize nutrition strategies. AI's potential to predict feeding regimens and improve the precision of care is discussed, illustrating how NSTs can leverage these advancements to tailor nutrition interventions. The review also addresses the challenges associated with implementing AI in ICU settings, including barriers to integration and the need for infrastructure improvements. By evaluating both the impact of NSTs and the potential of AI, this review highlights the multifaceted approaches that can significantly improve clinical outcomes for mechanically ventilated ICU patients through effective nutrition support.</div></div>","PeriodicalId":36134,"journal":{"name":"Clinical Nutrition Open Science","volume":"63 ","pages":"Pages 288-303"},"PeriodicalIF":0.0000,"publicationDate":"2025-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluating the impact of nutrition support teams and the role of artificial intelligence in clinical outcomes for mechanically ventilated ICU patients: A comprehensive review\",\"authors\":\"Yasamin Mohammadi\",\"doi\":\"10.1016/j.nutos.2025.08.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This review examines the critical role of nutrition support teams (NSTs) in managing nutrition for mechanically ventilated patients in the intensive care unit (ICU). Nutritional support is essential for improving clinical outcomes in critically ill patients, with enteral nutrition (EN) being the preferred method. Early enteral nutrition (EEN) has demonstrated significant benefits, reducing complications such as infections, multi-organ failure, and prolonged mechanical ventilation. The review emphasizes the importance of a multidisciplinary approach, with NSTs playing a vital role in ensuring early and adequate nutritional support, which improves recovery outcomes. Additionally, the integration of artificial intelligence (AI) and machine learning (ML) in ICU nutrition management is explored, focusing on how these technologies can enhance decision-making and optimize nutrition strategies. AI's potential to predict feeding regimens and improve the precision of care is discussed, illustrating how NSTs can leverage these advancements to tailor nutrition interventions. The review also addresses the challenges associated with implementing AI in ICU settings, including barriers to integration and the need for infrastructure improvements. By evaluating both the impact of NSTs and the potential of AI, this review highlights the multifaceted approaches that can significantly improve clinical outcomes for mechanically ventilated ICU patients through effective nutrition support.</div></div>\",\"PeriodicalId\":36134,\"journal\":{\"name\":\"Clinical Nutrition Open Science\",\"volume\":\"63 \",\"pages\":\"Pages 288-303\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-08-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical Nutrition Open Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2667268525000889\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Nursing\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Nutrition Open Science","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2667268525000889","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Nursing","Score":null,"Total":0}
Evaluating the impact of nutrition support teams and the role of artificial intelligence in clinical outcomes for mechanically ventilated ICU patients: A comprehensive review
This review examines the critical role of nutrition support teams (NSTs) in managing nutrition for mechanically ventilated patients in the intensive care unit (ICU). Nutritional support is essential for improving clinical outcomes in critically ill patients, with enteral nutrition (EN) being the preferred method. Early enteral nutrition (EEN) has demonstrated significant benefits, reducing complications such as infections, multi-organ failure, and prolonged mechanical ventilation. The review emphasizes the importance of a multidisciplinary approach, with NSTs playing a vital role in ensuring early and adequate nutritional support, which improves recovery outcomes. Additionally, the integration of artificial intelligence (AI) and machine learning (ML) in ICU nutrition management is explored, focusing on how these technologies can enhance decision-making and optimize nutrition strategies. AI's potential to predict feeding regimens and improve the precision of care is discussed, illustrating how NSTs can leverage these advancements to tailor nutrition interventions. The review also addresses the challenges associated with implementing AI in ICU settings, including barriers to integration and the need for infrastructure improvements. By evaluating both the impact of NSTs and the potential of AI, this review highlights the multifaceted approaches that can significantly improve clinical outcomes for mechanically ventilated ICU patients through effective nutrition support.