Ultrasound Assessment of the Rectus Femoris in Patients with Chronic Obstructive Pulmonary Disease Predicts Sarcopenia

Concordance between muscle mass assessed by bioelectrical impedance analysis and by muscle ultrasound: a cross-sectional study in a cohort of patients on chronic hemodialysis

BACKGROUND

Sarcopenia is a common problem in hemodialysis (HD) patients, and it is diagnosed by low muscle mass, strength and/or low physical performance. Muscle ultrasound (US) is a non-invasive portable tool that might be used for assessment of muscle mass. The aim of the current study was to investigate the concordance between muscle US and bioelectrical impedance analysis (BIA) in diagnosis of sarcopenia in HD patients.

METHODS

This cross-sectional study included 41 HD patients. Sarcopenia was diagnosed according to the European Working Group on Sarcopenia in Older People (EWGSOP). The skeletal mass index was measured by BIA and the muscle strength was measured by handgrip strength. Muscle US was used to measure cross-sectional area (CSA) and thickness of quadriceps and biceps muscles.

RESULTS

The current study included 41 patients on HD (25 males), with a mean (SD) age of 44.18 (13.11) years and a median HD duration of 48 months. Sarcopenia was diagnosed in 58.5% of the patients. Patients with sarcopenia had significantly lower quadriceps muscle CSA than those without sarcopenia. The optimal cut-offs of quadriceps muscle CSA for both males and females for the diagnosis of sarcopenia were 2.96 and 2.92 cm2, respectively.

CONCLUSION

Sarcopenia is prevalent among Egyptian HD patients. US on quadriceps muscle CSA could be used for diagnosis of sarcopenia in these patients.

A Multivariable Model Based on Ultrasound Imaging Features of Gastrocnemius Muscle to Identify Patients With Sarcopenia

OBJECTIVES

Low skeletal muscle mass, strength, or somatic function are used to diagnose sarcopenia; however, effective assessment methods are still lacking. Therefore, we evaluated the effectiveness of ultrasound in identifying patients with sarcopenia.

METHODS

This study included 167 patients, 78 with sarcopenia and 89 healthy participants, from two hospitals. We evaluated clinical factors and five ultrasound imaging features, of which three ultrasound imaging features were used to create the model. In both the training and validation datasets, the sarcopenia detection performances of chosen ultrasonic characteristics and the constructed model were evaluated using receiver operating characteristic (ROC) curves. The predictive performance was evaluated by area under the ROC (AUROC), calibration, and decision curves.

RESULTS

There were statistically significant differences in muscle thickness (MT) of gastrocnemius medialis muscle (GM), flaky myosteatosis echo (FE), pennation angle (PA), average shear wave velocity (SWV) in the relaxed state (RASWV), and average SWV in the passive stretched state (PASWV) between sarcopenic and normal subjects. PA, RASWV, and PASWV were effective predictors of sarcopenia. The AUROC (95% confidence interval) for these three parameters were 0.930 (0.882-0.978), 0.865 (0.791-0.940), and 0.849 (0.770-0.928), respectively, in the training set, and 0.873 (0.777-0.969), 0.936 (0.878-0.993), and 0.826 (0.716-0.935), respectively, in the validation set. The combined model had better detection power. Finally, the calibration curve showed that the combined model had good prediction accuracy.

CONCLUSION

Our model can be used to identify sarcopenia in primary medical institutions, which is valuable for the early recognition and management of sarcopenia patients.