Loredana Mӑdӑlina Popa, Bogdan Timar, Amorin Remus Popa and Mircea Ioachim Popescu
, 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
Alin Albai, Mirela Frandeș, Ramona Luminița Sandu, Gabriel Spoială, Flavia Hristodorescu, Bogdan Timar and Romulus Timar
, 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
Ovidiu Mitu, Florin Mitu, Maria-Magdalena Leon, Mihai Roca, Andreea Gherasim and Mariana Graur
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
Paria Dehesh, Tania Dehesh and Mohammad Hossein Gozashti
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
Nicolae-Marius Cason, Petru Aurel Babeş, Enikő Béres and Katalin Babeş
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
Marilena Mitrache, Robert Ancuceanu and Constantin Ionescu-Tîrgoviște
, 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
Raluca Dina, Iulia Vladu, Ciprian Dina and Adina Mitrea
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
Eduard Adamescu, Cătălina Niculescu and Carmen Dobjanschi
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.
Deniz Korkut, Gul Ergor, Gulsah Kaner and Nilgun Seremet Kurklu
Background and Aims: Diabetes is increasing rapidly in Turkey as most countries in the world. The prevention of complications which is the main aim in the treatment of diabetes can be accomplished partly with nutrition education. The aim of this study was to assess the relationship between nutrition knowledge (NK) and complications in patients with type 2 diabetes. Materials and Methods: 280 patients with 8-20 years of diabetes duration who applied to diet outpatient clinic were recruited. The questionnaire was prepared by the investigators to assess the NK. A score was calculated on the scale of 100. The complications were determined based on hospital records and patients’ selfreport. Results: 63.2% of participants were female and 36.8% were male. The most common complications in participants were retinopathy (56.1%) and neuropathy (42.9%). The mean NK score was 80.2±11.7. At least one complication was seen in 85.0% of the participants. There was no significant difference for having any complication in patients with adequate and inadequate NK. However the risk of diabetic foot, and coronary artery disease was significantly higher in women with inadequate NK. Conclusion: NK is quite high in long term diabetic patients. However no effect of the NK on the development of complications could be shown. The difference of effect between men and women could be due to the fact that food is mostly prepared by women thus not much chance of the knowledge of men to be reflected on his eating habits. The knowledge difference among female patients was seen in the results as; in women with inadequate NK, the prevalence of diabetic foot and CAD was significantly higher.