The relationship between sarcopenic obesity and changes in quadriceps muscle thickness and echo intensity in patients with stroke.

BACKGROUND: Research findings on skeletal muscle degeneration in post-stroke sarcopenic obesity are limited. Thus, this study aimed to investigate the association between post-stroke sarcopenic obesity and quantitative and qualitative changes in skeletal muscles. METHODS: This was a cross-sectional study conducted on patients with stroke admitted to the convalescent rehabilitation ward. For skeletal muscle assessment, an ultrasound system was used to measure quadriceps muscle thickness and echo intensity (QMT and QEI) on the paretic and non-paretic sides. Sarcopenic obesity was defined as the presence of both sarcopenia and obesity. Multiple regression analysis was performed to determine the relationships between sarcopenic obesity and QMT and QEI. RESULTS: A total of 130 patients with stroke were included in this study (mean age: 69.4 ± 12.7 years). The prevalence of sarcopenic obesity was 23.1%. The multiple regression analysis showed that sarcopenic obesity was significantly negatively associated with QMT on both the paretic and non-paretic sides (paretic side: ß = -0.28, p < 0.001; non-paretic side: ß = -0.37, p < 0.001) and significantly positively associated with QEI (paretic side ß = 0.21, p = 0.034; non-paretic side: ß = 0.20, p = 0.029). CONCLUSIONS: Post-stroke sarcopenic obesity was independently associated with quantitative and qualitative changes in skeletal muscles on both the paretic and non-paretic sides.

The Validity of Quadriceps Muscle Thickness as a Nutritional Risk Indicator in Patients with Stroke.

This study aimed to investigate whether quadriceps muscle thickness (QMT) is useful for nutritional assessment in patients with stroke. This was a retrospective cohort study. Nutritional risk was assessed using the Geriatric Nutritional Risk Index (GNRI), with GNRI < 92 indicating a risk of malnutrition and GNRI ≥ 92 indicating normal conditions. Muscle mass was assessed using QMT and calf circumference (CC). The outcome was Functional Independence Measure (FIM) effectiveness. The cutoff values of QMT and CC for discriminating between high and low GNRI were determined using the receiver operating characteristic curve. The accuracy of the nutritional risk discrimination model was evaluated using the Matthews correlation coefficient (MCC). Multiple regression analysis was performed to assess the relationship between nutritional risk, as defined by QMT and CC, and FIM effectiveness. A total of 113 patients were included in the analysis. The cutoff values of QMT and CC for determining nutritional risk were 49.630 mm and 32.0 cm for men (MCC: 0.576; 0.553) and 41.185 mm and 31.0 cm for women (MCC: 0.611; 0.530). Multiple regression analysis showed that only nutritional risk defined by QMT was associated with FIM effectiveness. These findings indicate that QMT is valid for assessing nutritional risk in patients with stroke.