Gao Ming, Tan Li, Zhou Yingli, Peng Wei, Xu Yuan, Zhou Hua, van Zanten Arthur Raymond Huber, Zhu Yan
Department of Critical Care Medicine, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua Medicine, Tsinghua University, Beijing, China.
Department of Intensive Care Medicine, Gelderse Vallei Hospital, Ede, The Netherlands.
PLoS One. 2025 Jun 18;20(6):e0325751. doi: 10.1371/journal.pone.0325751. eCollection 2025.
This study aimed to assess the accuracy of bedside ultrasound in predicting resting energy expenditure (REE) in critically ill patients.
We studied critically ill patients admitted to our hospital's ICU between November 2021 and March 2023 who underwent REE, cardiac ultrasound, and muscle ultrasound evaluations. General demographic information and ultrasound data (including cardiac output, biceps brachii and quadriceps femoris thickness) were collected to estimate REE (REE-US). Simultaneously, REE was measured using indirect calorimetry (REE-IC). Correlations between REE-US and established equations (Harris-Benedict, Penn State University (PSU), Mifflin, ASPEN standard) as well as REE-IC were evaluated. Additionally, the feasibility and application of ultrasound for REE prediction across different disease conditions in critically ill patients were analysed.
Ninety-seven critically ill patients with 124 ultrasound measurements were included. The Penn State University formula showed the highest correlation with REE-IC (r = 0.779, p < 0.001), followed by ultrasound estimation (r = 0.668, p < 0.001). Correlation between the PSU formula and REE-IC remained robust across subgroups. However, REE-US correlation was weaker in patients with low BMI (BMI < 20 kg/m2) (r = 0.521, p = 0.009) but comparable to the PSU formula in normal and high BMI groups (BMI 20-30 kg/m2: r = 0.682 vs. r = 0.714, p = 0.5743; BMI > 30 kg/m2: r = 0.712 vs. r = 0.882, p = 0.1294). In subgroup analysis, REE-US performed similarly to the PSU formula in the sepsis subgroup (r = 0.612 vs r = 0.661, p = 0.6852) and ICU patients in the late period of the acute phase (r = 0.675 vs r = 0.751, p = 0.2762).
The Penn State University formula demonstrated the strongest correlation with REE-IC in critically ill patients. Ultrasound may replace the PSU formula in non-mechanically ventilated patients with unavailable gas measurement parameters. However, ultrasound-derived REE is less predictive in patients with low BMI or during the early acute phase of critical illness. Further research is warranted to refine ultrasound application in these populations.
本研究旨在评估床旁超声预测危重症患者静息能量消耗(REE)的准确性。
我们研究了2021年11月至2023年3月期间入住我院重症监护病房(ICU)并接受REE、心脏超声和肌肉超声评估的危重症患者。收集一般人口统计学信息和超声数据(包括心输出量、肱二头肌和股四头肌厚度)以估算REE(REE-US)。同时,使用间接测热法测量REE(REE-IC)。评估REE-US与既定公式(Harris-Benedict、宾夕法尼亚州立大学(PSU)、Mifflin、ASPEN标准)以及REE-IC之间的相关性。此外,分析了超声在危重症患者不同疾病状态下预测REE的可行性和应用情况。
纳入了97例危重症患者,进行了124次超声测量。宾夕法尼亚州立大学公式与REE-IC的相关性最高(r = 0.779,p < 0.001),其次是超声估计值(r = 0.668,p < 0.001)。PSU公式与REE-IC之间的相关性在各亚组中均保持强劲。然而,BMI较低(BMI < 20 kg/m²)的患者中REE-US的相关性较弱(r = 0.521,p = 0.009),但在正常和高BMI组(BMI 20 - 30 kg/m²:r = 0.682 vs. r = 0.714,p = 0.5743;BMI > 30 kg/m²:r = 0.712 vs. r = 0.882,p = 0.1294)中与PSU公式相当。在亚组分析中,REE-US在脓毒症亚组(r = 0.612 vs r = 0.661,p = 0.6852)和急性期后期的ICU患者中(r = 0.675 vs r = 0.751,p = 0.2762)与PSU公式表现相似。
宾夕法尼亚州立大学公式在危重症患者中与REE-IC的相关性最强。在无法获得气体测量参数的非机械通气患者中,超声可能取代PSU公式。然而,超声得出的REE在BMI较低的患者或危重症早期阶段预测性较差。有必要进一步研究以优化超声在这些人群中的应用。