Nutrition Department, Alfred Health, Melbourne, Australia.
Department of Dietetics, Nutrition and Sport, La Trobe University, Melbourne, Australia.
JPEN J Parenter Enteral Nutr. 2021 Jan;45(1):136-145. doi: 10.1002/jpen.1822. Epub 2020 Apr 15.
The development of bedside methods to assess muscularity is an essential critical care nutrition research priority. We aimed to compare ultrasound-derived muscle thickness at 5 landmarks with computed tomography (CT) muscle area at intensive care unit (ICU) admission. Secondary aims were to (1) combine muscle thicknesses and baseline covariates to evaluate correlation with CT muscle area and (2) assess the ability of the best-performing ultrasound model to identify patients with low CT muscle area.
Adult patients who underwent CT scanning at the third lumbar area <72 hours after ICU admission were prospectively recruited. Muscle thickness was measured at mid-upper arm, forearm, abdomen, and thighs. Low CT muscle area was determined using published cutoffs. Pearson correlation compared ultrasound-derived muscle thickness and CT muscle area. Linear regression was used to develop ultrasound prediction models. Bland-Altman analyses compared ultrasound-predicted and CT-measured muscle area.
Fifty ICU patients were enrolled, aged 52 ± 20 years. Ultrasound-derived muscle thickness at each landmark correlated with CT muscle area (P < .001). The sum of muscle thickness at mid-upper arm and bilateral thighs, including age, sex, and the Charlson Comorbidity Index, improved the correlation with CT muscle area (r = 0.85; P < .001). Mean difference between ultrasound-predicted and CT-measured muscle area was -2 cm (95% limits of agreement, -40 cm to +36 cm ). The best-performing ultrasound model demonstrated good ability to identify 14 patients with low CT muscle area (area under curve = 0.79).
Ultrasound shows potential for assessing muscularity at ICU admission (Clinicaltrials.gov NCT03019913).
开发床边方法来评估肌肉量是重症监护营养研究的一个重要优先事项。我们旨在比较重症监护病房(ICU)入院时 5 个标志点的超声测量肌肉厚度与计算机断层扫描(CT)肌肉面积。次要目标是(1)结合肌肉厚度和基线协变量来评估与 CT 肌肉面积的相关性,以及(2)评估表现最佳的超声模型识别 CT 肌肉面积低的患者的能力。
前瞻性招募了 ICU 入院后 72 小时内第三腰椎区进行 CT 扫描的成年患者。在中上臂、前臂、腹部和大腿处测量肌肉厚度。使用已发表的截断值确定低 CT 肌肉面积。Pearson 相关性比较了超声测量的肌肉厚度和 CT 肌肉面积。线性回归用于开发超声预测模型。Bland-Altman 分析比较了超声预测和 CT 测量的肌肉面积。
共纳入 50 例 ICU 患者,年龄 52 ± 20 岁。每个标志点的超声测量肌肉厚度与 CT 肌肉面积相关(P <.001)。中上臂和双侧大腿的肌肉厚度总和,包括年龄、性别和 Charlson 合并症指数,可改善与 CT 肌肉面积的相关性(r = 0.85;P <.001)。超声预测与 CT 测量的肌肉面积之间的平均差异为-2 cm(95%一致性界限,-40 cm 至+36 cm)。表现最佳的超声模型具有良好的能力来识别 14 例 CT 肌肉面积低的患者(曲线下面积= 0.79)。
超声在 ICU 入院时评估肌肉量具有潜力(Clinicaltrials.gov NCT03019913)。