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
Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca
... Show MoreUrinary tract infection is a bacterial infection that often affects the bladder and thus the urinary system. E. coli is one of the leading uropathogenic bacteria that cause urinary tract infections. Uropathogenic E. coli is highly effective and successful in causing urinary tract infections through biofilm formation and urothelial cell invasion mechanisms. Other organisms that cause urinary tract infections include members of the Enterobacteriaceae family, streptococci and staphylococci species and perch. In addition, K.penumoniae is another important gram-negative bacterium that causes urinary tract infections. With the PCR technique, unseen bacterial species can be detected using standard clinical microbiology methods. In this study, the
... Show MoreAccording to the famous saying of the medieval physician Paracelsus, "There is no substance without poison. Only the dose determines the extent of the toxic effect." Here, the effect of monosodium glutamate (MSG) on human health and the risks to the health of its frequent use in the short term was addressed and the long term was evaluated according to the studies of several researchers specializing in this regard. Monosodium glutamate (MSG) is known as one of the most popular food additives that classified as a flavor enhancer. Parts of the evidence were reviewed from the literature explaining its effect on immune system cells in addition to metabolic disorders by exposing individuals to obesity and what is known as metabolic syndrome, as w
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... Show MoreIn this paper, a new technique is offered for solving three types of linear integral equations of the 2nd kind including Volterra-Fredholm integral equations (LVFIE) (as a general case), Volterra integral equations (LVIE) and Fredholm integral equations (LFIE) (as special cases). The new technique depends on approximating the solution to a polynomial of degree and therefore reducing the problem to a linear programming problem(LPP), which will be solved to find the approximate solution of LVFIE. Moreover, quadrature methods including trapezoidal rule (TR), Simpson 1/3 rule (SR), Boole rule (BR), and Romberg integration formula (RI) are used to approximate the integrals that exist in LVFIE. Also, a comparison between those
... Show MoreIn this paper, a new technique is offered for solving three types of linear integral equations of the 2nd kind including Volterra-Fredholm integral equations (LVFIE) (as a general case), Volterra integral equations (LVIE) and Fredholm integral equations (LFIE) (as special cases). The new technique depends on approximating the solution to a polynomial of degree and therefore reducing the problem to a linear programming problem(LPP), which will be solved to find the approximate solution of LVFIE. Moreover, quadrature methods including trapezoidal rule (TR), Simpson 1/3 rule (SR), Boole rule (BR), and Romberg integration formula (RI) are used to approximate the integrals that exist in LVFIE. Also, a comparison between those methods i
... Show MoreKE Sharquie, AA Noaimi, MS Younis, BS Al-Sultani, Journal of Cosmetics, Dermatological Sciences and Applications, 2015 - Cited by 8
Background: The influence of glucose metabolism is seen in many infectious diseases, making diabetic patients more vulnerable to sepsis and other serious sequelae of bacterial invasion such as UTI and vaginitis.Patients and method: sixty two patients (women) were suffering from GUTIs consulting Al-Elwya hospital from November- 2009 to March -2010. Two samples were taken from those patients (urine samples and vaginal swabs); these samples were cultured on Blood, Chocolate, and MacConkey's agar for isolation of bacteria.Results: The study group consists of sixty two women suffering from (GUTI), their ages range from 18-55 years. Thirty eight of them were diabetic women and twenty four of them were non- diabetic women. Twenty t
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