Sharma Vaibhav, Sharma Vishakha, Khan Ayesha, Wassmer David J, Schoenholtz Matthew D, Hontecillas Raquel, Bassaganya-Riera Josep, Zand Ramin, Abedi Vida
Geisinger Commonwealth School of Medicine, Scranton, PA, United States.
Neuroscience Institute, Geisinger Health System, Danville, PA, United States.
Front Nutr. 2020 Apr 15;7:44. doi: 10.3389/fnut.2020.00044. eCollection 2020.
Nutrition plays a vital role in health and the recovery process. Deficiencies in macronutrients and micronutrients can impact the development and progression of various disorders. However, malnutrition screening tools and their utility in the clinical setting remain largely understudied. In this study, we summarize the importance of nutritional adequacy and its association with neurological, cardiovascular, and immune-related disorders. We also examine general and specific malnutrition assessment tools utilized in healthcare settings. Since the implementation of the screening process in 2016, malnutrition data from hospitalized patients in the Geisinger Health System is presented and discussed as a case study. Clinical data from five Geisinger hospitals shows that ~10% of all admitted patients are acknowledged for having some form of nutritional deficiency, from which about 60-80% of the patients are targeted for a more comprehensive assessment. Finally, we conclude that with a reflection on how technological advances, specifically machine learning-based algorithms, can be integrated into electronic health records to provide decision support system to care providers in the identification and management of patients at higher risk of malnutrition.
营养在健康和康复过程中起着至关重要的作用。宏量营养素和微量营养素的缺乏会影响各种疾病的发展和进程。然而，营养不良筛查工具及其在临床环境中的效用在很大程度上仍未得到充分研究。在本研究中，我们总结了营养充足的重要性及其与神经、心血管和免疫相关疾病的关联。我们还研究了医疗环境中使用的一般和特定营养不良评估工具。自2016年实施筛查流程以来，作为案例研究，我们展示并讨论了盖辛格医疗系统中住院患者的营养不良数据。来自盖辛格五家医院的临床数据显示，所有入院患者中约10%被确认存在某种形式的营养缺乏，其中约60 - 80%的患者被列为更全面评估的对象。最后，我们得出结论，反思如何将技术进步，特别是基于机器学习的算法，整合到电子健康记录中，以便为护理人员提供决策支持系统，用于识别和管理营养不良风险较高的患者。
