Ultrasonography versus bioelectrical impedance analysis: which predicts muscle strength better?

ŞENGÜL AYÇİÇEK G. , ÖZSÜREKCİ C. , ÇALIŞKAN H. , Kizilarslanoglu M. C. , TUNA DOĞRUL R. , BALCI C. , ...More

ACTA CLINICA BELGICA, 2019 (Journal Indexed in SCI) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume:
  • Publication Date: 2019
  • Doi Number: 10.1080/17843286.2019.1704989
  • Title of Journal : ACTA CLINICA BELGICA


Background & Aim: Muscle strength seems to be more relevant to the functionality than muscle mass in sarcopenia. Different diagnostic techniques are available for the evaluation of muscle mass. Ultrasonography (USG) seems to have some advantages compared to other techniques especially bioelectrical impedance analysis (BIA) including being not affected of the results by the factors like extreme body mass indexes (BMI) or hypervolemia. The aim of the study is to determine and compare the muscle strength prediction value of muscle mass measured by using USG or BIA and determine the cut-off values for the Turkish population. Methods: One hundred and thirty six patients admitted to geriatrics outpatient clinic for comprehensive geriatric assessment were included in the study. Body composition was determined by BIA and skeletal muscle mass index (SMI) was measured. Thickness of the gastrocnemius muscle was measured via USG. Diagnosis of sarcopenia was made according to the EWSGOP 2 diagnostic criteria. Results: The best cut-off value for gastrocnemius muscle thickness to predict low HGS was <= 13.8 mm (AUC:0.690,p <0.001). SMI was not found to predict low HGS (AUC:0.573,p >0.05). Comparison of AUCs for gastrocnemius muscle thickness and SMI showed that gastrocnemius muscle thickness had higher AUC (p=0.008). For predicting sarcopenia, the best cut-off value of gastrocnemius muscle thickness was found to be <= 12.3 mm in women (AUC: 0.862,p <0.001) and <= 12.3 mm in men (AUC:0.900, p < 0.001). Conclusions: In this study, we found that gastrocnemius thickness measured by USG seems to predict low HGS better than SMI measured by BIA.