Prevalence and pattern of dyslipidemia in Nepalese individuals with type 2 diabetes

Abstract Background Atherogenic dyslipidemia is an important modifiable risk factor for cardiovascular disease among patients of type 2 diabetes mellitus. Timely detection and characterization of this condition help clinicians estimate future risk of cardiovascular disease and take appropriate preventive measures. The aim of this study was to determine the prevalence, pattern and predictors of dyslipidemia in a cohort of Nepalese patients with type 2 diabetes. Results We found mixed dyslipidemia as the most prevalent (88.1%) and isolated dyslipidemia (10.1%) as the least prevalent forms of dyslipidemia in our patients. The most prevalent form of single dyslipidemia was high LDL-C (73.8%) and combined dyslipidemia was high TG, high LDL-C and low HDL-C (44.7%). Prevalence of all single and mixed dyslipidemia was higher in patients with poor glycemic control and hypertension. The glycemic status of patients correlated with their fasting serum lipid profile. Dyslipidemia was associated mainly with male gender, poor glycemic control and hypertension. Conclusions Atherogenic dyslipidemia is associated mainly with male gender, poor glycemic control and hypertension. It is highly prevalent in Nepalese patients with type 2 diabetes. Urgent lifestyle modification, sustained glycemic control and aggressive lipid lowering treatment plans are necessary to minimize the future risk of cardiovascular disease in this population

Non-high density lipoprotein cholesterol versus low density lipoprotein cholesterol as a discriminating factor for myocardial infarction

Abstract Background Serum total cholesterol (TC) and LDL cholesterol (LDL-C) have been used as major laboratory measures in clinical practice to assess cardiovascular risk in the general population and disease management as well as prognosis in patients. However, some studies have also reported the use of non-HDL cholesterol (non-HDL-C). As non-HDL-C can be calculated by subtracting HDL-C from TC, both of which do not require fasting blood sample in contrast to LDL-C which requires fasting blood sample, we aimed to compare non-HDL-C with LDL-C as a predictor of myocardial infarction (MI). Methods This hospital based cross sectional study was undertaken among 51 cases of MI and equal number of controls. MI was diagnosed based on the clinical history, ECG changes and biochemical parameters. 5 mL of fasting blood sample was collected from each research participant for the analysis of lipid profile. Non-HDL-C was calculated by using the equation; Non-HDL-C = TC – HDL-C. Statistical analysis was performed using SPSS 14.0. Results 42 MI cases were dyslipidemic in contrast to 20 dyslipidemic subjects under control group. The differences in the median values of each lipid parameter were statistically significant between MI cases and controls. The lipid risk factors most strongly associated with MI were HDL-C (OR 5.85, 95% CI 2.41-14.23, P value = 0.000) followed by non-HDL-C (OR 3.77, 95% CI 1.64-8.66, P value = 0.002), LDL-C/HDL-C (OR 3.38, 95% CI 1.44-7.89, P value = 0.005), TC/HDL-C (OR 2.93, 95% CI 1.36-7.56, P value = 0.026), LDL-C (OR 2.70, 95% CI 1.20-6.10, P value = 0.017), TC (OR 2.68, 95% CI 1.04-6.97, P value = 0.042) and Tg (OR 2.54, 95% CI 1.01-6.39, P value = 0.047). Area under the receiver operating curve was greater for non-HDL-C than for LDL-C. Non-HDL-C was also found to be more sensitive and specific than LDL-C for MI. Conclusions HDL-C and non-HDL-C are better discriminating parameters than LDL-C for MI. Thus, we can simply perform test for HDL-C and non-HDL-C both of which do not require fasting blood sample rather than waiting for fasting blood sample to measure LDL-C.</p

MOESM1 of Prevalence and pattern of dyslipidemia in Nepalese individuals with type 2 diabetes

Additional file 1. Survey questionnaire and data collection form for screening dyslipidemia in Nepalese individuals with type 2 diabetes