Clinical Decision Support System to Optimize Neonatal Nutrition and Growth

项目摘要/摘要：优化新生儿营养和营养的临床决策支持系统 生长 营养，定义为能量、大量营养素(蛋白质、脂肪和碳水化合物)和微量营养素(例如， 电解质)是新生儿重症监护室(NICU)中早产儿护理的一个重要特征。不足之处 营养与生长和神经发育障碍有关，并且两者的发生率都增加。 早产儿视网膜病变和支气管肺发育不良。尽管人们认识到营养的重要性 和增长，临床医生经常无法提供建议的摄入量，在 住院治疗。事实上，50%的极低出生体重(VLBW，出生体重和1500克)婴儿在1岁时离开NICU 排出体重&lt；10%的校正后的出生年龄。我们已经确定，大多数 隶属于儿童医院新生儿联盟的NICU，这是一个由美国和加拿大儿童组成的组织 医院缺乏临床决策支持系统(CDSS)来计算营养摄入量。此外， 机构有任何CDSS来计算收到的卡路里摄入量，很少有人能自动计算营养 从肠外和肠内来源摄取，无需额外复制数据。临床医生需要以下数据 营养和液体摄入，以考虑与各种营养提供做法相关的权衡 (例如，肠外营养、静脉注射脂肪乳剂、肠内强化和中线放置)和 在明智的液体管理和最佳的营养提供之间取得平衡。这个项目的目标是开发一部小说 生长和营养仪表板，以及基于营养摄入量和生理数据的预测生长模型 从多参数监护仪。我们假设呈现实时、全面的营养和液体 来自肠外和肠内来源的摄取数据以及生长模型将提高临床医生的能力 提供高质量的新生儿营养，实现最佳生长。营养状况有望改善 通过增强对婴儿已经接受的摄入量的情景意识，累积 婴儿将从各种营养实践中获得的摄入量，以及考虑心率的模型 活动，能量消耗的替代品。

Project Summary/Abstract: Clinical Decision Support System to Optimize Neonatal Nutrition and Growth Nutrition, defined as energy, macronutrients (protein, fat, and carbohydrates), and micronutrients (e.g., electrolytes), is a critical feature of care for preterm infants in the neonatal intensive unit (NICU). Inadequate nutrition is associated with growth and neurodevelopmental impairment, and increased rates of both retinopathy of prematurity and bronchopulmonary dysplasia. Despite the recognized importance of nutrition and growth, clinicians often fail to deliver the recommended intake with large deficits accruing during hospitalization. Indeed, 50% of very low birth weight (VLBW, birth weight <1500g) infants leave the NICU at a discharge weight <10th percentile for their corrected, postnatal age. We have determined that the majority of NICUs affiliated with the Children’s Hospital Neonatal Consortium, a group of US and Canadian children’s hospitals, lack Clinical Decision Support Systems (CDSS) to calculate nutrition intake. Moreover, of the institutions with any CDSS to calculate caloric intake received, few could automatically calculate nutrition intake from both parenteral and enteral sources without additional copying of data. Clinicians need data on both nutrition and fluid intake to consider the trade-offs associated with various nutrition delivery practices (e.g., parenteral nutrition, intravenous lipid emulsions, enteral fortification, and central line placement) and balance judicious fluid management with optimal nutrition delivery. The goal of this project is to develop a novel growth and nutrition dashboard, and model projected growth based on nutrition intake and physiologic data from the multiparameter monitor. We hypothesize that presenting real-time, comprehensive nutrition and fluid intake data from both parenteral and enteral sources alongside growth modelling will improve clinicians’ ability to deliver high quality neonatal nutrition and achieve optimal growth. Improvements in nutrition are expected from an enhanced situational awareness of the intake that an infant has already received, the cumulative intake that an infant will receive from various nutrition practices, and modelling that accounts for heart rate activity, a surrogate of energy expenditure.