验证重症患者四头肌床边超声肌肉层厚度（VALIDUM研究）的初步结果

　　在重症患者中，肌肉萎缩与患者的预后显著相关。计算机断层扫描（CT）能准确定量肌肉的质量，但其临床适用性欠佳。加拿大滑铁卢大学、加拿大金斯顿总医院、美国马里兰大学、美国明尼苏达大学、美国宾夕法尼亚大学、美国犹他州山间医疗中心、美国拉什大学医疗中心为验证超声评估肌肉厚度的可行性，对10个重症监护病房（ICU）进行了多中心的前瞻性观察性研究，发现超声下股四头肌厚度（QMLT）与腹部CT第三腰椎平面的骨骼肌横断面积（CSA）显著正相关。此外，超声QMLT联合其他预测因子，如年龄、性别、体质指数（BMI）等，对预测ICU患者的肌肉发达程度有较好的实用价值。

JPEN J Parenter Enteral Nutr. 2016;40(4):117-118.

Validation of Bedside Ultrasound of Muscle Layer Thickness of the Quadriceps in the Critically Ill Patient (VALIDUM Study): Preliminary Results.

Michael Paris; Marina Mourtzakis; Andrew Day; Roger Leung; Snehal Watharkar; Rosemary Kozar; Carrie Earthman; Adam Kuchnia; Rupinder Dhaliwal; Lesley Moisey; Charlene Compher; Niels Martin; Michele Nicolo; Thomas White; Hannah Roosevelt; Sarah Peterson; Daren Heyland.

University of Waterloo, Waterloo, Ontario, Canada; Kingston General Hospital, Kingston, Ontario, Canada; University of Maryland, Baltimore, MD, USA; University of Minnesota, St Paul, MN, USA; University of Pennsylvania, Philadelphia, PA, USA; Hospital of the University of Pennsylvania, Philadelphia, PA, USA; Intermountain Medical Center, Murray, UT, USA; Rush University Medical Center, Chicago, IL, USA.

Purpose: In critically ill patients, muscle atrophy is a strong predictor of morbidity, mortality, and long-term disability. While body mass index (BMI) has been commonly used to identify malnourished individuals, it cannot quantify specific lean tissues, such as skeletal muscle. Computed tomography (CT) can precisely quantify muscle mass; however, it may not be practical or expedient. Ultrasound, which is available in most intensive care units (ICUs), is a potential tool to assess muscle atrophy. Comprehensive ultrasound protocols that assess multiple landmarks (ie, 9 sites) have been validated to quantify lean tissue in healthy individuals. These types of protocols are not feasible or practical in an ICU environment. While a quadriceps muscle layer thickness (QMLT) protocol may be easily applied at the ICU bedside, it has not been evaluated for its ability to identify ICU patients with low muscle mass. Thus, our objective was to validate QMLT derived by ultrasound by comparing with CT-based measures of muscle tissue.

Methods: In this multicenter (10 ICUs) prospective observational study, all patients were >18 years of age and had abdominal CT scans performed for clinical reasons <24 hours before or <72 hours after ICU admission. Moribund patients who were not expected to survive were excluded. CT scans were landmarked at the third lumbar vertebra and were analyzed for skeletal muscle cross-sectional area (CSA). Previously established cut points for identifying individuals with lower-than-normal muscularity were applied (<110 cm² for females and <170 cm² for males). The ultrasound assessment occurred <72 hours of the CT scan. The QMLT protocol for ultrasound assessed 2 sites on each quadriceps with maximal compression (depressing the underlying soft tissues by applying maximum force of the ultrasound probe against the landmarked sites).

Results: Of the 149 patients, 42% were females. Overall, patients were (mean ± SD) 50 ± 19 years old and had a BMI of 29 ± 8 kg/m². Mean APACHE II and SOFA scores were 17 ± 8 and 5 ± 4, respectively. Median (Q1-Q3) Charlson Comorbidity Index was 1 (0-3) and ICU and hospital length of stay were 3 (2-7) and 8 (5-17) days, respectively, with 9% and 11% rates of mortality. Based on BMI, 3% of patients were classified as underweight and 68% overweight or obese, whereas CT data revealed that 57% of patients had lower-than-normal muscularity. Mean abdominal skeletal muscle CSA was 109 ± 25 cm² for females and 168 ± 37 cm² for males, suggesting that, on average, patients had low muscularity. Average ultrasound QMLT was significantly different between males (1.5 ± 0.6 cm) and females (1.1 ± 0.6 cm; P < .001). A significant positive correlation (r = 0.45) was found between QMLT and CSA (P < .0001). Area under the curve was 0.67 for an receiver operating characteristic curve that was created to predict CT-derived low-muscularity cut points based on QMLT (Figure 3-1). Notably, the area under the curve of the logistic model based on age, sex, BMI, Charlson Comorbidity Index, and admission type (surgical vs medical) as predictors was 0.72, and if ultrasound QMLT was added to the model, this increased to 0.76 (Table 3-1).

Conclusions: Although 68% of the patients in this study were overweight or obese and only 3% were underweight, more than half of the patients had lower-than-normal muscularity. CT imaging has been an important measure in identifying patients with low muscularity. Here, our preliminary results suggest that QMLT obtained from ultrasound along with additional predictors, including age, BMI, sex, Charlson Comorbidity index, and admission type, were valuable in predicting muscularity in this group of ICU patients.

Financial support: Government of Ontario Ministry of Research and Innovation Early Researcher Award.