Sonographic methods to predict type 2 diabetes patients with sarcopenia: B mode ultrasound and shear wave elastography.

BACKGROUND: Type 2 diabetes accelerates the loss of muscle mass and strength. Sarcopenia is also one of the chronic complications of diabetes. OBJECTIVE: To investigate the clinical value of B mode ultrasound (BMUS) and shear wave elastography (SWE) for predicting type 2 diabetic sarcopenia. METHODS: We recorded Skeletal Muscle Mass Index (ASMI), grip strength, muscle thickness (MT), pinna angle (PA), fascicle length (FL), and the difference of Young's modulus in the relaxed states and tense states (ΔSWE). The correlations between clinical indicators and ultrasound characteristics were compared. A diagnostic model of sarcopenia was developed to assess the independent correlates and evaluate the diagnostic efficacy of sarcopenia. RESULTS: ASMI was significantly and positively correlated with MT and ΔSWE (r = 0.826, 0.765, P < 0.01), and grip strength was significantly and positively correlated with MT and ΔSWE (r = 0.797, 0.818, P < 0.01). MT was the most significant predictor of sarcopenia (OR = 4.576, P < 0.001), and the cut-off value of MT was 11.4 mm (AUC: 0.952). CONCLUSION: BMUS and SWE can quantitatively assess muscle mass and strength, and are effective methods to predict the occurrence of sarcopenia in elderly patients with type 2 diabetes.

Supply Chain Partner Communication in a Managed Programme in the UK Water Industry: A Case Study with Social Network Analysis.

The water industry in every country aims to effectively and efficiently provide water with satisfactory quality in a sustainable and environmentally friendly manner. To this end, it is critical to achieve effective communication among the partners in water supply chain networks. In this paper, we focus on one of the UK's largest water utility companies and its eight main contractors and analyze the factors influencing partner and network communication in a managed programme of their asset supply chain. We employ social network analysis to conduct the cross-sectional and longitudinal analysis of partner communication. Factors found to influence the communication network are grouping of projects within the programme, individual's organisational affiliation, status, tenure, elapsed time through the programme lifecycle, and co-location. Our contributions to practice include demonstrating water programme management factors that influence communication and trust and how social network analysis can better inform them about intra- and interorganisational relationships. Moreover, the methodology introduced in this study may be applied to water management in other parts of the world.