Objectives: This paper presents a reference data model for blood bank management to control blood inventories considering real-world uncertainties and constraints. It helps information systems identify blood product status for various critical decisions (such as replenishment, assignment, and issuing) instantly. Additionally, some significant optimization concepts of the inventory management literature for blood wastage and shortage reduction, such as clearance sale and substitution based on medical priorities, are applied in the model. Methods: The proposed model was constructed by object-oriented and ICAM (Integrated Computer Aided Manufacturing) definition ɸ (IDEF0) techniques for function modeling. Through semi-structured questionnaires and interviews, the research team elicited and classified user requirements. Then, the demand-centered sub-processes and comprehensive functions were mapped to manage the process. Results: The model captures and integrates the top-level features of the inventory system entities. It also provides insights into a developed data dictionary to understand the system’s elements and attributes, where a data item fits in the structure, and what values it may contain. For designing the system’s process and following-up data, the main relevant inputs are considered. Conclusions A flexible and applicable demand-centered framework for managing a typical blood bank’s inventory process was developed by focusing on user requirements. The proposed model can be applied to design and monitor inventory information and decision-support systems. The model provides real-time iterative dynamic process insights. It can also provide the data needed for logistic planning systems and the design of blood operational infrastructure.

No abstract available.
Insulin Resistance*

BACKGROUND: Previous studies evaluating the relationship between serum vaspin concentrations and metabolic syndrome (MetS) have yielded contrasting results. Additionally, contribution of general and abdominal obesity, chronic inflammation, and insulin resistance to this relationship remains unknown. METHODS: In a cross-sectional setting, we investigated the association between vaspin and MetS in 145 subjects ranging from normoglycemia to type 2 diabetes. Vaspin concentrations were measured using enzyme-linked immunosorbent assay. RESULTS: Women had 29% higher vaspin concentrations compared with men. Subjects with MetS (51% of all participants) had higher vaspin concentrations (P=0.019 in women and P<0.001 in men). In logistic regression, vaspin significantly predicted raised fasting plasma glucose (P<0.001), and raised triglycerides (P<0.001) after controlling for age in both sexes. Moreover, vaspin was the significant predictor for reduced high-density lipoprotein cholesterol and raised waist circumference in women and men, respectively. Considering MetS as a whole, vaspin predicted MetS even after adjustment for age, medications, diabetes, total cholesterol, and waist circumference in both sexes (odds ratio [OR], 3.88; 95% confidence interval [CI], 1.36 to 11.05; P=0.011 for women; OR, 3.16; 95% CI, 1.28 to 7.78; P=0.012 for men). However, this relationship rendered nonsignificant after introducing homeostasis model assessment of insulin resistance (HOMA-IR) in women (P=0.089) and high-sensitivity C-reactive protein (P=0.073) or HOMA-IR in men (P=0.095). CONCLUSION: Vaspin is associated with some but not all components of MetS. Vaspin is a predictor of MetS as a single entity, independent of obesity. This relationship is largely ascribed to the effects of insulin resistance and chronic inflammation.
Blood Glucose ; C-Reactive Protein ; Cholesterol ; Enzyme-Linked Immunosorbent Assay ; Fasting ; Female ; Homeostasis ; Humans ; Inflammation ; Insulin Resistance* ; Insulin* ; Lipoproteins ; Logistic Models ; Male ; Obesity ; Obesity, Abdominal ; Triglycerides ; Waist Circumference