Support for the development of this risk calculator was provided by Alberta Health Services (Cardiovascular Health and Stroke Strategic Clinical Network) and Merck Canada. Tsuyuki, BSc(Pharm), PharmD, MSc, FCSHP, FACC Charlotte A Jones, MD, PhD, FRCHP(C) Brenda R. While the authors have tested the tool and used it in the R 圎ACH study, the authors take no responsibility for results or outcomes resulting from your use of it. This tool is provided for educational purposes and should not replace sound clinical judgment. General cardiovascular risk profile for use in primary care: The Framingham heart study. Heart 2013 99:866-872.ĭ’Agostino RB, Vasan RS, Pencina MJ et al. Source: Indian Journal of Pharmaceutical Sciences Document Type: Article Keywords: cardiovascular complications metabolic syndrome. Development and validation of a prediction rule for recurrent vascular events based on a cohort study in patients with arterial disease: the SMART risk score. Methods: The UKPDS risk engine 2.0 was applied to data collected in the ABCD liraglutide audit database before and at the earliest return to clinic between. Clin Sci 2001 101: 671-9.ĭorresteijn JAN, Visseren FLJ, Wassink AMJ et al. The UKPDS risk engine: a model for the risk of coronary heart disease in type 2 diabetes (UKPDS 56). Stevens RJ, Kothari V, Adler AI, Stratton IM, Holman RR. Effectiveness of Community Pharmacist Prescribing and Care on Cardiovascular Risk Reduction: Randomized Controlled R 圎ACH Trial. Cardiovascular risk is best evaluated with an estimation that takes into account the individuals characteristics and risk factors.Tsuyuki RT, Al Hamarneh YN, Jones CA, Hemmelgarn BR. Nevertheless, the American Diabetes Association has recognized that absolute risk for cardiovascular disease varies among individuals with diabetes and has recommended the use of designed models and algorithms to estimate risk, especially in younger patients ( < 40 years). Diabetes itself has been considered a cardiovascular disease equivalent. The presence of traditional and nontraditional risk factors that frequently coexist with type 2 diabetes are associated with this higher cardiovascular risk. Mexico DF, Mexico.,IranĪbstract: Individuals with type 2 diabetes have a two to four fold increased risk for developing cardiovascular disease than persons without diabetes. Endocrinology and Metabolism Department, Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Vasco de Quiroga No.Title: UKPDS Risk Engine, Decode and Diabetes PHD Models for the Estimation of Cardiovascular Risk in Patients with DiabetesĪuthor(s): Paloma Almeda-Valdes, Daniel Cuevas-Ramos, Roopa Mehta, Francisco J. Keywords: Cardiovascular risk, Diabetes mellitus, UKPDS risk engine, Diabetes PHD, DECODE In this review we will discuss the pros and cons of each model, their use in clinical practice and the application of the UKPDS risk engine and PHD model in a Mexican population. Specifically, the DECODE (Diabetes Epidemiology: Collaborative analysis of Diagnostic criteria in Europe) equation has been shown to have discriminative capacity of 0.67 the UKPDS Risk Engine model is reported to have a sensitivity of around 90% and specificity of 33% and the Diabetes Personal Health Decisions (PHD) in our study had a sensitivity of 67% and specificity of 41%. The algorithms and models that have been designed specifically for the assessment of cardiovascular risk in individuals with diabetes will be the subject of this review. Cardiovascular risk is best evaluated with an estimation that takes into account the individuals characteristics and risk factors. Individuals with type 2 diabetes have a two to four fold increased risk for developing cardiovascular disease than persons without diabetes.
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