Objectives: To study the effect of providing tertiary (specialized) health care for type 2 diabetic patients to meet the WHO and ADA standards and glycemic targets.
Method: Six months, Jan. – Jun. 2010, cohort study was conducted on 600 adult diabetics who registered in the National Diabetes Center (NDC) / Al-Mustansiriya University, Baghdad – Iraq. They were followed for 3- 6 months; each time patients were examined physically and their blood pressure, height, weight and BMI were measured. Fasting blood samples were taken from all patients to test the FPG, HbA1c, T.Chol, TG, HDL and LDL.
Results: Patients’ age was 52.85±15.56 year and the male/female ratio was 1.01, the median duration of disease was 7 years and their BMI was 28.80 ± 13.02 kg/m2. Patients’ achievement during study period, of glycemic and cardiovascular risk factors, meet the targets of ADA, NHANES and NCEP/ATP III Guidelines of FPG, PPG, HbA1c, T.Chol, TG, LDL, HDL, systolic and diastolic blood pressure by 26.74%, 29.09%, 32.78%, 61.0%, 60.86%, 76.19%, 74.35%, 52.54% and 62.50% respectively.
Conclusions: We concluded that tertiary health service can help to meet the international guidelines and recommended targets for type 2 diabetes. Improving quality and coverage of tertiary health services may help in achieve and sustain targets; and afterward close adhering to the WHO and ADA standards and glycemic targets.
Abbreviations: BMI=Body Mass Index, FPG= Fasting Plasma Glucose, PPG = post prandial plasma glucose, HbA1c =glycated hemoglobin, T.Chol. = total cholesterol, TG = Triglyceride, LDL = low-density lipoprotein, HDL = high-density lipoprotein, ADA= American Diabetes Association, NHANES = National Health and Nutrition Examination Survey, NCEP/ATP III = National Cholesterol Education Program/Adult Treatment Panel
Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica
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