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Predictive Value of Updating te Score Cardiovascular Risk Assessment Engine with Novel Biomarkers in a Type 2 Diabetes Population

, Simmons RK, Sharp SJ, Griffin SJ, Wareham NJ. Cardiovascular risk assessment scores for people with diabetes: a systematic review. Diabetologia 52: 2001-2014, 2009. 9. Pearson TA, Mensah GA, Alexander RW et al. Markers of inflammation and cardiovascular disease: application to clinical public health practice: A statement for healthcare professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation 107: 499-511, 2003. 10. Sinderman AJ, Williams K, Contois JH et al. A metaanalysis of low

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Relations Between Diabetes, Kidney Disease and Metabolic Syndrome: Dangerous Liaisons

, Fitzgerald AP et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J 24: 987-1003, 2003. 6. D’Agostino RB Sr, Vasan RS, Pencina MJ et al. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation 117: 743-753, 2008. 7. Centers for Disease Control and Prevention . National diabetes fact sheet: National estimates and general information on diabetes and prediabetes in the United States, 2011. Atlanta, GA: U.S. Department of Health and Human Services, Centers for

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Increased Type 2 Diabetes Mellitus Risk (Assessed by Findrisc Score) is Associated with Subclinical Atherosclerotic Markers in Asymptomatic Adult Population

JW, Jang EH, Kim MK et al. Diabetic retinopathy is associated with subclinical atherosclerosis in newly diagnosed type 2 diabetes mellitus. Diabetes Res Clin Pract 91: 253-259, 2011. 5. Shah PK. Screening asymptomatic subjects for subclinical atherosclerosis: can we, does it matter, and should we? J Am Coll Cardiol 56: 98-105, 2010. 6. Lindström J, Tuomilehto J. The diabetes risk score: a practical tool to predict type 2 diabetes risk. Diabetes Care 26: 725-731, 2003. 7. Perk J, De Backer G, Gohlke H et al. European Guidelines on

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Evaluating the Direct and Indirect Effects of SF-36 Domains Score on Two Main Factors in Diabetic Patients with Path Analysis: Health-Related Quality of Life Study

depression in diabetes (EDID) research consortium. Curr Diabetes Rew 5(2): 112-119, 2009 20. Glasgow RE, Ruggiero L, Eakin EG, Dryfoos J, Chobanian L. Quality of life and associated characteristics in a large national sample of adults with diabetes. Diabetes Care 20(4): 562-567, 1997 21. Ware Jr JE. How to score the revised MOS short-form health scale (SF-36®). New Engl Med Centr Hosp 10: 17-18, 1988 22. Ware Jr JE Sherbourne CD . The MOS 36-item short-form health survey (SF-36): I. Conceptual framework and item selection. Med Care 30 (6): 473

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Assessment of Long Term Metabolic Effects of Atypical Antipsychotics in Schizophrenia Patients

schizophrenia and schizoaffective disorder post hoc analyses of 3 randomized, controlled clinical trials. J Clin Psychopharmacol 30(6): 656-660, 2010. 27. Schorr SG, Slooff CJ, Bruggeman R, Taxis K. The incidence of metabolic syndrome and its reversal in a cohort of schizophrenic patients followed for one year. J Psychiatr Res 43(13): 1106-1111, 2009. 28. Guo Y, Musani SK, Sims M, Pearson TA, DeBoer MD, Gurka MJ. Assessing the added predictive ability of a metabolic syndrome severity score in predicting incident cardiovascular disease and type 2 diabetes

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Assessment of Nutritional Status in Patients with Metabolic Syndrome and Chronic Hepatitis C

. Schneider SM, Hebuterne X. Use of nutritional scores to predict clinical outcomes in chronic diseases. Nutr Rev 58(2 Pt 1): 31-38, 2000.

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The Prevalence of Diabetogenic Risk Factors in Newly Diagnosed Diabetic Patients

, Cheța D, Popa E, Mincu I. Le rôle de l'obesité dans l'etiopathogenie du diabète sucré. Medicine et Nutrition 12: 97-106, 1976. 18. Gale EAM. Drug-induced diabetes 2014 Aug 13; Diapedia 41040851133 rev. no. 22. Accessed at: http://dx.doi.org/1014496/dia.4104851133.22 19. Noble D, Mathur R, Dent T, Meads C, Greenhalgh T. Risk models and scores for type 2 diabetes: systematic review. BMJ 343: d7163, 2011. 20. Saaristo T, Peltonen M, Lindström J et al. Cross-sectional evaluation of the Finnish Diabetes Risk Score: a tool to

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Advanced Glycation End Products Measured by Age Reader in a Group of Patients with Obesity

Gallefoss , Effects of Lifestyle Intervention in Persons at Risk for Type 2 Diabetes Mellitus, BMC Public Health 11(893), 2011. Lutgers H. et al. Skin autofluorescence provides additional information to the UK Prospective Diabetes Study (UKPDS) risk score for the estimation of cardiovascular prognosis in type 2 diabetes mellitus. Diabetologia 52(5): 789-797, 2009. Ranitz-Greven WL et al. Advanced Glycation End Products, Measured as Skin Autofluorescence, at Diagnosis in Gestational Diabetes Mellitus Compared with

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Multifactorial Analysis of a Group of Prediabetes Patients in Terms of Cardiovascular Risk

Abstract

Background and Aims: “Prediabetes” is defined by Impaired Fasting Glucose (IFG) or Impaired Glucose Tolerance (IGT), both states associated with increased risk for diabetes and high cardiovascular (CV) risk. The aim of our study was to investigate a population with prediabetes compared to a group from the general population in respect with the risk for progression to diabetes and CV risk parameters. Materials and Methods: We investigated 124 ambulatory patients with prediabetes and 98 persons without any known metabolic disorders (control group), for CV risk parameters and risk of developing diabetes. Results: We found statistically significant differences (p <0.05) for average weight, waist, BMI and lipids between the two groups. We also found a double risk score of developing diabetes in prediabetes patients compared to the control group. No significant differences were found in terms of anthropometric parameters, lipid values, cardiovascular disease and diabetes risk score for the IFG, IGT and IFG + IGT subgroups. Conclusions: People with prediabetes have features that differentiate them from the general population, both in terms of the history, anthropometric and biochemical characteristics. Increased risk for progression to diabetes, but also highly increased CV risk makes very useful the prevention efforts focused on this population group.

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Evaluation of Cognitive Function in Patients with Type 2 Diabetes and Overt Hypothyroidism

Abstract

Background and Aims. Previous studies report the presence of cognitive impairment in patients with overt hypothyroidism. The thyroid hormones are essential for neurological and intellectual functions. Type 2 diabetes mellitus (T2DM) subjects are exposed to higher risk of cognitive function alteration compared to nondiabetic subjects. The aim of the present study was to analyze the cognitive function of T2DM subjects with overt hypothyroidism.

Materials and Methods. We performed an observational study between 2015-2017. A total of 12 patients (11 women and 1 men) with overt hypothyroidism and T2DM were recruited for this study. Their cognitive function was compared with that of subjects of a control group (16 patients - 12 women and 4 men with T2DM but without overt hypothyroidism). Cognitive function was evaluated using the Mini Mental State Examination (MMSE) test. Serum thyroid stimulating hormone (TSH) levels were measured by immunoradiometric assay, free thyroxine (FT4) by radioimmunoassay while fasting plasma glucose (FPG) levels were evaluated using automated devices.

Results. There were no significant differences between the two groups in respect of age and FPG. In the study group, mean TSH and FT4 levels were 11.76±4.43 mIU/L, resepectively 0.53±0.08 ng/dL while in the control group these were 2.60±0.40 mIU/L, respectively 1.12±0.19 ng/dL (p<0.001). Moderate cognitive impairment was present in 3 patients of the study group (25.00%) and in 2 subjects from the control group (12.50%). Mild cognitive impairment was present in 4 patients (33.33%) of the study group and in 2 subjects from the control group (12.50%).

Conclusion. This study showed that MMSE scores are significantly reduced in subjects with T2DM and hypothyroidism compared to subjects with T2DM without hypothyroidism (p<0.004). The study revealed a negative correlation between TSH and MMSE score in the study group.

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