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Year : 2019  |  Volume : 5  |  Issue : 2  |  Page : 94-99

Association of cardiovascular risk estimate with degree of atherosclerosis in patients with type 2 diabetes mellitus

1 Department of General Medicine, PIMS, Puducherry, India
2 Department of Radiology, PIMS, Puducherry, India

Correspondence Address:
Ali Hasan Faiz Karnam
Assistant Professor, Department of General Medicine, PIMS, Puducherry
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jcrsm.jcrsm_20_19

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Background: Type 2 diabetes mellitus is one of the leading causes for global public health crisis mainly affecting the Asian countries. Cardivascular disease (CVD) is one of the leading contributors to morbidity and mortality for type 2 diabetes mellitus patients. Assessment of the cardiovascular risk in asymptomatic patients and advising them for proper preventive measures will help to bring down the morbidity and mortality. In this study we aim to find the correlation of carotid intima thickness (CIMT) with different risk scores estimating 10 years risk of cardiovascular disease. Method: It is a cross sectional study involving type 2 diabetes mellitus patient of age between 20 years and 80 years, without having any previous history of cardiovascular disease, cerebrovascular accident, chronic kidney disease and connective tissue disorder. Detailed history and examination was done along with blood investigations like fasting lipid profile, HbA1c, fasting and post prandial blood glucose, blood urea and creatinine. All these data were used to estimate 10 years cardiovascular risk using different risk engines - United Kingdom Prospective Diabetes Study (UKPDS) risk engine, Framingham Risk Score (FRS), Q risk and Atherosclerotic cardio vascular disease (ASCVD). All the patients were subjected for measurement of carotid intima thickness (CIMT) by ultrasonography. Correlation coefficient was calculated using SPSS software version 18. Result: Total 59 patient (40 males and 19 females) were included in the study. Mean age, duration of diabetes, HbA1c and CIMT were 56.3 ± 10 years, 8.1 ± 6.9 years, 8.2 ± 1.2% and 0.8 ± 0.2 mm respectively. Age, duration of diabetes, HbA1c, total cholesterol, low density cholesterol and triglyceride had significant positive correlation with CIMT (P < 0.05). Among risk score ASCVD, Q risk and UKPDS risk score had positive and significant correlation with CIMT (P < 0.05). Although, FRS had positive correlation, it was not statistically significant. Conclusion: In the absence of South Asian specific risk estimate algorithm Q risk and UKPDS risk score can be used with caution. CIMT is well established indicator of atherosclerosis, hence it can be used to estimate cardiovascular risk and to advise preventive measures.

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