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Global Journal of Obesity, Diabetes and Metabolic Syndrome

ISSN: 2455-8583

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Abstract Open Access
Research Article PTZAID: GJODMS-1-104

Coronary Risk Estimation according to the Framingham-Wilson Score and Impaired Fasting Glucose in Adult Subjects from Maracaibo city, Venezuela

Valmore Bermúdez*, Joselyn Rojas, Juan Salazar, Robys González, María Sofía Martínez, Carmen Chávez, Marcos Palacio, Edward Rojas, Mayela Cabrera and José López Miranda

Introduction: Type 2 Diabetes Mellitus (T2DM) is an independent risk factor for coronary artery disease. Nevertheless, the coronary risk rendered by pre-diabetes states such as Impaired Fasting Glucose (IFG) has not been thoroughly explored. The purpose of this study was to evaluate the influence of glycemic status on coronary risk estimated by the recalibrated Framingham-Wilson equation in our population. 

Materials and Methods: A total 1,378 of subjects were selected from the Maracaibo City Metabolic Syndrome Prevalence Study. A complete medical history was taken, next to laboratory workup and anthropometric measurement. All subjects were classified according to glycemic status in normal fasting glucose (NG), impaired fasting glucose (IFG), and T2DM. Coronary risk estimation was calculated using the Framingham-Wilson equation recalibrated for our population. 

Results: An increase in coronary risk was observed in IFG (p=3.78x10-6) and DM (p=4.34x10-13) when compared to NG; pattern also observed within genders: men (p=1.57x10-4) and women (p=2.37x10-4). Coronary risk also increased according to age in all categories of glycemic status. Within the IFG group, occupational status (p=0.004), smoking (p=2.29x10-5) and alcohol consumption (p=0.013) were associated with higher coronary risk. Finally, subjects with IFG exhibited greater probability for allocation in high coronary risk categories [OR: 1.46 (1.06 - 2.14); p=0.05].

Conclusions: Coronary risk scores from the recalibrated Framingham-Wilson equation were significantly higher in subjects with IFG. In our population, this increase may be influenced by sociodemographic and psychobiological traits, such as marital and occupational status, smoking and alcohol consumption.

Published on: Oct 24, 2014 Pages: 20-29

Full Text PDF Full Text HTML DOI: 10.17352/2455-8583.000004

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