Association of Risk Estimates of Three Different Cardiovascular Risk Assessment Tools with Carotid Intima Media Thickness
in Patients with Type 2 Diabetes
Published: July 1, 2016 | DOI: https://doi.org/10.7860/JCDR/2016/.8087
Herath Mudiyanselage Meththananda Herath, Thi lak Priyantha Weerarathna, Ranasinghe Bethmi Arachige Thilini Dulanjalee, Madumekala Rupasinghe Jayawardana, Udara Priyadarshani Edirisingha, Madush anka
1. Senior Lecturer, Department of Medicine, Faculty of Medicine, Galle University of Ruhuna, Srilanka.
2. Professor, Department of Medicine, Faculty of Medicine, Galle University of Ruhuna, Galle, Srilanka.
3. Demonstrator, Department of Medicine, Faculty of Medicine, Galle University of Ruhuna, Galle, Srilanka.
4. Demonstrator, Department of Medicine, Faculty of Medicine, Galle University of Ruhuna, Galle, Srilanka.
5. Demonstrator, Department of Medicine, Faculty of Medicine, Galle University of Ruhuna, Galle, Srilanka.
6. Demonstrator, Department of Medicine, Faculty of Medicine, Galle University of Ruhuna, Galle, Srilanka.
Correspondence Address :
Dr. Herath Mudiyanselage Meththananda Herath,
Senior Lecturer, Department of Medicine, Faculty of Medicine, PO Box 70, Galle, Srilanka.
E-mail: herathtp@gmail.com
Abstract
Introduction: Risk assessment tools used to calculate the Cardiovascular Disease (CVD) risk such as the Framingham Risk Score (FRS), United Kingdom Prospective Diabetes study (UKPDS) risk engine and the World Health Organization (WHO) risk score have not been tested on their ability to detect subclinical atherosclerosis in most developing countries.
Aim: To study the association between the calculated CVD risk scores using each of these tools and Carotid Intima Medial Thickness (CIMT), a surrogate marker of atherosclerosis, in a group of patients with Type 2 diabetes (T2DM) in Sri Lanka.
Materials and Methods: We calculated CVD risk scores of 68 randomly selected patients with T2DM with no history or symptoms of CVD and measured their CIMT using B-mode ultrasonography (USS). Carotid USS was considered positive when the maximum carotid IMT was 0.9mm or when arteriosclerotic plaques were detected. The 10-year CVD risk was calculated using the FRS, the UKPDS risk engine and the WHO risk score. Pearson correlation was used to study the association between CVD risk scores with CIMT.
Results: Of the 68 patients studied, 50% were males and their mean age (SD) was 56.9 (±9.6) years. The mean age at onset and duration of diabetes were 44.3(±9.1) and 12.2(±7.6) years respectively. Of the scoring methods, UKPDS tool had weak, but significantly positive (r = 0.26, p < 0.05) and FRS had positive but not significant association (r= 0. 21) with CIMT. There was a negative association between CIMT and WHO risk score (r= - 0.07).
Conclusion: Of the three CVD risk assessment tools, both UKPDS risk engine and FRS have almost equal ability (former being marginally superior) in predicting underlying atherosclerotic vascular disease in patients with T2DM. Negative association of the WHO risk score with CIMT argues against its utility for CVD screening. These findings highlight the need for developing more sensitive and reliable CVD risk assessment tools for developing countries.
Keywords
Cardiac risk prediction, Framingham risk score, United kingdom prospective diabetes study risk engine, World health organization risk score