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Estimation of 10-Year Risk of Coronary Heart Disease in Nepalese Patients with Type 2 Diabetes: Framingham Versus United Kingdom Prospective Diabetes Study.

Pokharel DR, Khadka D, Sigdel M, Yadav NK, Sapkota LB, Kafle R, Nepal S, Sapkota RM, Choudhary N - N Am J Med Sci (2015)

Bottom Line: The estimated CHD risks were compared using kappa statistics, Pearson's bivariate correlation, Bland-Altman plots, and multiple regression analysis.The Framingham equation predicted higher risk for patients usually below 70 years and showed better association with their current risk profile than the UKPDS risk engine.Based on the predicted risk, Nepalese diabetic patients, particularly those associated with increased numbers of risk factors, bear higher risk of future CHDs.

View Article: PubMed Central - PubMed

Affiliation: Department of Biochemistry, Manipal College of Medical Sciences, Pokhara, Kaski, Nepal.

ABSTRACT

Background: Predicting future coronary heart disease (CHD) risk with the help of a validated risk prediction function helps clinicians identify diabetic patients at high risk and provide them with appropriate preventive medicine.

Aim: The aim of this study is to estimate and compare 10-year CHD risks of Nepalese diabetic patients using two most common risk prediction functions: The Framingham risk equation and United Kingdom Prospective Diabetes Study (UKPDS) risk engine that are yet to be validated for Nepalese population.

Patients and methods: We conducted a hospital-based, cross-sectional study on 524 patients with type 2 diabetes. Baseline and biochemical variables of individual patients were recorded and CHD risks were estimated by the Framingham and UKPDS risk prediction functions. Estimated risks were categorized as low, medium, and high. The estimated CHD risks were compared using kappa statistics, Pearson's bivariate correlation, Bland-Altman plots, and multiple regression analysis.

Results: The mean 10-year CHD risks estimated by the Framingham and UKPDS risk functions were 17.7 ± 12.1 and 16.8 ± 15 (bias: 0.88, P > 0.05), respectively, and were always higher in males and older age groups (P < 0.001). The two risk functions showed moderate convergent validity in predicting CHD risks, but differed in stratifying them and explaining the patients' risk profile. The Framingham equation predicted higher risk for patients usually below 70 years and showed better association with their current risk profile than the UKPDS risk engine.

Conclusions: Based on the predicted risk, Nepalese diabetic patients, particularly those associated with increased numbers of risk factors, bear higher risk of future CHDs. Since this study is a cross-sectional one and uses externally validated risk functions, Nepalese clinicians should use them with caution, and preferably in combination with other guidelines, while making important medical decisions in preventive therapy of CHD.

No MeSH data available.


Related in: MedlinePlus

Distribution of 10-year CHD risks according to the age groups of diabetic patients
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Figure 1: Distribution of 10-year CHD risks according to the age groups of diabetic patients

Mentions: The 10-year CHD risks estimated by the Framingham and the UKPDS risk functions, their stratification into low, medium, and high risk groups and statistical agreement are shown in Table 2. The mean CHD risks estimated by the two risk prediction functions did not differ significantly (bias = 0.88, P = 0.16) and were always higher in males (P < 0.001). Both of the risk prediction functions showed fair agreement (κ = 0.39, 95% CI (0.33–0.45), P < 0.001) in classifying the patients into low, medium, and high risk groups. There were 166 (31.7%) patients at low, 167 (31.9%) at medium, and 191 (36.4%) at high risk according to the Framingham risk equation; while 224 (42.7%) patients were at low, 148 (28.2%) at medium, and 152 (29%) at high risk according to the UKPDS risk engine. They also identified more males than females (P < 0.05) at medium and high risk. Patients associated with obesity, poor glycemic control, longer duration of diabetes, dyslipidemia, HTN, and current smoking habit had higher CHD risk than those without [Table 3]. However, the CHD risk estimated for such patients by the UKPDS risk engine was significantly lower than the one estimated by the Framingham risk equation. Both the predicted 10-year CHD risks increased gradually with the age of the patients, although the overall increase was always higher in males [Figure 1]. Except for the age groups 40–44, and 70–74 years, both the predicted CHD risks showed substantial overlap with each other.


Estimation of 10-Year Risk of Coronary Heart Disease in Nepalese Patients with Type 2 Diabetes: Framingham Versus United Kingdom Prospective Diabetes Study.

Pokharel DR, Khadka D, Sigdel M, Yadav NK, Sapkota LB, Kafle R, Nepal S, Sapkota RM, Choudhary N - N Am J Med Sci (2015)

Distribution of 10-year CHD risks according to the age groups of diabetic patients
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4561440&req=5

Figure 1: Distribution of 10-year CHD risks according to the age groups of diabetic patients
Mentions: The 10-year CHD risks estimated by the Framingham and the UKPDS risk functions, their stratification into low, medium, and high risk groups and statistical agreement are shown in Table 2. The mean CHD risks estimated by the two risk prediction functions did not differ significantly (bias = 0.88, P = 0.16) and were always higher in males (P < 0.001). Both of the risk prediction functions showed fair agreement (κ = 0.39, 95% CI (0.33–0.45), P < 0.001) in classifying the patients into low, medium, and high risk groups. There were 166 (31.7%) patients at low, 167 (31.9%) at medium, and 191 (36.4%) at high risk according to the Framingham risk equation; while 224 (42.7%) patients were at low, 148 (28.2%) at medium, and 152 (29%) at high risk according to the UKPDS risk engine. They also identified more males than females (P < 0.05) at medium and high risk. Patients associated with obesity, poor glycemic control, longer duration of diabetes, dyslipidemia, HTN, and current smoking habit had higher CHD risk than those without [Table 3]. However, the CHD risk estimated for such patients by the UKPDS risk engine was significantly lower than the one estimated by the Framingham risk equation. Both the predicted 10-year CHD risks increased gradually with the age of the patients, although the overall increase was always higher in males [Figure 1]. Except for the age groups 40–44, and 70–74 years, both the predicted CHD risks showed substantial overlap with each other.

Bottom Line: The estimated CHD risks were compared using kappa statistics, Pearson's bivariate correlation, Bland-Altman plots, and multiple regression analysis.The Framingham equation predicted higher risk for patients usually below 70 years and showed better association with their current risk profile than the UKPDS risk engine.Based on the predicted risk, Nepalese diabetic patients, particularly those associated with increased numbers of risk factors, bear higher risk of future CHDs.

View Article: PubMed Central - PubMed

Affiliation: Department of Biochemistry, Manipal College of Medical Sciences, Pokhara, Kaski, Nepal.

ABSTRACT

Background: Predicting future coronary heart disease (CHD) risk with the help of a validated risk prediction function helps clinicians identify diabetic patients at high risk and provide them with appropriate preventive medicine.

Aim: The aim of this study is to estimate and compare 10-year CHD risks of Nepalese diabetic patients using two most common risk prediction functions: The Framingham risk equation and United Kingdom Prospective Diabetes Study (UKPDS) risk engine that are yet to be validated for Nepalese population.

Patients and methods: We conducted a hospital-based, cross-sectional study on 524 patients with type 2 diabetes. Baseline and biochemical variables of individual patients were recorded and CHD risks were estimated by the Framingham and UKPDS risk prediction functions. Estimated risks were categorized as low, medium, and high. The estimated CHD risks were compared using kappa statistics, Pearson's bivariate correlation, Bland-Altman plots, and multiple regression analysis.

Results: The mean 10-year CHD risks estimated by the Framingham and UKPDS risk functions were 17.7 ± 12.1 and 16.8 ± 15 (bias: 0.88, P > 0.05), respectively, and were always higher in males and older age groups (P < 0.001). The two risk functions showed moderate convergent validity in predicting CHD risks, but differed in stratifying them and explaining the patients' risk profile. The Framingham equation predicted higher risk for patients usually below 70 years and showed better association with their current risk profile than the UKPDS risk engine.

Conclusions: Based on the predicted risk, Nepalese diabetic patients, particularly those associated with increased numbers of risk factors, bear higher risk of future CHDs. Since this study is a cross-sectional one and uses externally validated risk functions, Nepalese clinicians should use them with caution, and preferably in combination with other guidelines, while making important medical decisions in preventive therapy of CHD.

No MeSH data available.


Related in: MedlinePlus