title: Estimation of 10-Year Risk of Coronary Heart Disease in Nepalese Patients with Type 2 Diabetes: Framingham Versus United Kingdom Prospective Diabetes Study.
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.
  
  
  OBJECTIVE
  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.
  
  
  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.
authors.affiliation: Department of Biochemistry, Manipal College of Medical Sciences, Pokhara, Kaski, Nepal.
authors.forename: Daya Ram
authors.initials: DR
authors.lastname: Pokharel
authors.affiliation: Department of Laboratory Science, School of Health and Allied Sciences, Pokhara University, Lekhnath, Kaski, Nepal.
authors.forename: Dipendra
authors.initials: D
authors.lastname: Khadka
authors.affiliation: Department of Biochemistry, Manipal College of Medical Sciences, Pokhara, Kaski, Nepal.
authors.forename: Manoj
authors.initials: M
authors.lastname: Sigdel
authors.affiliation: Department of Biochemistry, Manipal College of Medical Sciences, Pokhara, Kaski, Nepal.
authors.forename: Naval Kishor
authors.initials: NK
authors.lastname: Yadav
authors.affiliation: Department of Biochemistry, Manipal College of Medical Sciences, Pokhara, Kaski, Nepal.
authors.forename: Lokendra Bahadur
authors.initials: LB
authors.lastname: Sapkota
authors.affiliation: Department of Internal Medicine, Manipal College of Medical Sciences and Teaching Hospital, Phoolbari, Pokhara, Kaski, Nepal.
authors.forename: Ramchandra
authors.initials: R
authors.lastname: Kafle
authors.affiliation: Department of Internal Medicine, Manipal College of Medical Sciences and Teaching Hospital, Phoolbari, Pokhara, Kaski, Nepal.
authors.forename: Sarthak
authors.initials: S
authors.lastname: Nepal
authors.affiliation: Institute of Microbiology, Immunology and Hygiene, Technical University Munich, Trogerstrasse, Munich, Germany.
authors.forename: Ravindra Mohan
authors.initials: RM
authors.lastname: Sapkota
authors.affiliation: Department of Laboratory Science, School of Health and Allied Sciences, Pokhara University, Lekhnath, Kaski, Nepal.
authors.forename: Niraj
authors.initials: N
authors.lastname: Choudhary
keywords: Convergent validity; Nepal; UKPDS risk engine; coronary heart disease; framingham risk equation; risk prediction; type 2 diabetes