间接测热法确定重症机械通气成人能量需求低估或高估的发生情况：文献系统回顾
背景：喂养不足或喂养过量都与患者的不良预后相关。静息时能量消耗可以通过间接测热法来检测。在没有间接能量测定仪的情况下，使用预测方程进行计算。以下通过与预测方程对比，对间接测热法低估或高估机械通气的重症患者能量需求的发生情况进行系统回顾。
方法：在2013年5月在Ovid、MEDLINE、CINAHL Plus、Scopus以及EMBASE数据库中对同事应用预测方程和间接测热法确定需求的文献进行检索，同时对出版文章中的相关参考文献进行检索。无论在个体水平还是群体水平，记录所有预测方程与间接测热法相比，低估或高估能量需求±10%的数量。
结果：总共回顾了2349篇已出版的文章，其中包括18篇原始研究。在群体水平观察的13个预测方程中，160篇的差异超过了10%，其中38%低估了能量需求，12%高估了能量需求。剩余50%间接测热法预测的能量需求在方程预测的±10%内。在个体水平，预测方程低估和高估能量需求的比率分别为13～90%和0～80%。间接测热法的最大差异为低估了43%和高估了66%。
结论：无论在个体水平还是群体水平，预测方程和间接测热法估计能量需求均存在较大的差异。针对观察到的差异，还需要进一步的研究来明确间接测热法和预测方程的局限性。
JPEN J Parenter Enteral Nutr. 2016;40(2):212-25.
Prevalence of Underprescription or Overprescription of Energy Needs in Critically Ill Mechanically Ventilated Adults as Determined by Indirect Calorimetry: A Systematic Literature Review.
Tatucu-Babet OA, Ridley EJ, Tierney AC.
Nutrition and Dietetics Department, The Alfred, Melbourne Victoria, Australia; Department of Nutrition and Dietetics, Monash University, Notting Hill Victoria, Australia; Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), Department of Epidemiology and Preventive Medicine, Monash University, Melbourne Victoria, Australia; Department of Dietetics and Human Nutrition, La Trobe University, Bundoora Victoria, Australia.
BACKGROUND: Underfeeding and overfeeding has been associated with adverse patient outcomes. Resting energy expenditure can be measured using indirect calorimetry. In its absence, predictive equations are used. A systematic literature review was conducted to determine the prevalence of underprescription and overprescription of energy needs in adult mechanically ventilated critically ill patients by comparing predictive equations to indirect calorimetry measurements.
METHODS: Ovid MEDLINE, CINAHL Plus, Scopus, and EMBASE databases were searched in May 2013 to identify studies that used both predictive equations and indirect calorimetry to determine energy expenditure. Reference lists of included publications were also searched. The number of predictive equations that underestimated or overestimated energy expenditure by ±10% when compared to indirect calorimetry measurements were noted at both an individual and group level.
RESULTS: In total, 2349 publications were retrieved, with 18 studies included. Of the 160 variations of 13 predictive equations reviewed at a group level, 38% underestimated and 12% overestimated energy expenditure by more than 10%. The remaining 50% of equations estimated energy expenditure to within ±10 of indirect calorimetry measurements. On an individual patient level, predictive equations underestimated and overestimated energy expenditure in 13-90% and 0-88% of patients, respectively. Differences of up to 43% below and 66% above indirect calorimetry values were observed.
CONCLUSIONS: Large discrepancies exist between predictive equation estimates and indirect calorimetry measurements in individuals and groups. Further research is needed to determine the influence of indirect calorimetry and predictive equation limitations in contributing to these observed differences.
KEYWORDS: critically ill, nutrition; indirect calorimetry; intensive care unit; predictive equations; resting energy expenditure
PMID: 25605706
DOI: 10.1177/0148607114567898
