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Showing 1 to 4 of 4 for “"Type 2 diabetes--Treatment"”.

  1. Grape Extracts for Type 2 Diabetes Treatment Through Specific Inhibition of α-Glucosidase and Antioxidant Protection

    … and inflammation associated with obesity-induced type 2 diabetes. Because intestinal α-glucosidase plays a key role in the digestion and absorption of complex carbohydrates, the inhibition of this enzyme is a metabolic target for managing diabetes by improving post-prandial blood glucose control. …

    vt Repository record for Grape Extracts for Type 2 Diabetes Treatment Through Specific Inhibition of α-Glucosidase and Antioxidant Protection (opens in a new tab)

  2. Implementing an Evidence Based Practice Guideline to Standardize the Care of Adults with Type 2 Diabetes

    … in standardizing the care for adults with type 2 diabetes. The goal was to improve patients’ glycosylated hemoglobin A1c (HbA1c) levels to less than 8% and Low Density Lipoprotein (LDL) levels to less than 100mg/dL. The Implementation Model, adapted by Titler (2010) and built on Rogers …

    hawaii Repository record for Implementing an Evidence Based Practice Guideline to Standardize the Care of Adults with Type 2 Diabetes (opens in a new tab)

  3. General Fatalism and Diabetes Fatalism as Predictors of Diabetes Treatment Adherence

    … as a predictor of health behaviors such as diabetes treatment adherence. We tested an integrated, theory-driven structural model of relationships among income, education, age, gender, general fatalism, diabetes fatalism, and type 2 diabetes treatment adherence, as measured by hemoglobin a1c …

    loma-linda Repository record for General Fatalism and Diabetes Fatalism as Predictors of Diabetes Treatment Adherence (opens in a new tab)

  4. Characterizing Variation in Healthcare across Time and Providers using Machine Learning

    … on when the patient is receiving care, and treatment decisions can vary depending on who makes the decisions. In this thesis, we consider two axes of variation in healthcare: over time and across providers. For both axes, we focus on identifying when variation exists, characterizing the …

    mit Repository record for Characterizing Variation in Healthcare across Time and Providers using Machine Learning (opens in a new tab)