Journal of Clinical and Preventive Cardiology (Jan 2019)

Distribution of conventional lipids in Indians with premature coronary artery disease: A substudy of the premature coronary artery disease registry

  • Rahul S Patil,
  • T R Raghu,
  • C N Manjunath,
  • Santu Ghosh,
  • Laxmi H Shetty

DOI
https://doi.org/10.4103/JCPC.JCPC_33_18
Journal volume & issue
Vol. 8, no. 1
pp. 18 – 24

Abstract

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Context: Conventional lipids in young Indians with Coronary Artery Disease. Aims: To study distribution of conventional lipids and their quantification in demographic subgroups of Indians with Premature Coronary Artery Disease (PCAD). Settings and Design: PCAD Registry is a Prospective Multisite Descriptive Observational study of Indians aged below 40 years with Coronary Artery Disease. This Lipid sub study is based on preliminary data of first year of the PCAD registry. Methods and Material: Of 1380 patients registered in PCAD registry, 1061 satisfied entry criteria. Conventional lipids were estimated using commercially available kits. Each of risk factor subgroups were compared by statistical analysis of lipid values. Statistical significance was derived by independent t-test or one-way ANOVA wherever appropriate. The distribution of different lipid profile parameters was visualised by nonparametric density plot. The data was analysed by statistical software R version 3.5.0. Results: A total of 1380 patients were registered. of which 1061 patients satisfied the entry criteria and were enrolled for the lipid analysis study. The mean age of all patients registered was 34.27 (±4.30) years. Mean total cholesterol of entire study population was 171.95 ± 47.11, LDL was 116.39 ± 84.81 mg/dl, HDL was 34.50 ± 9.64, TG was 165.18 ± 87.11, non-HDL was 138.09 ± 46.18. Conclusions: Among all the conventional lipid parameters, low HDL-C along with high TGs seems to be more relevant for premature coronary artery in Indians. Primary cardiovascular disease prevention for Young Indians cannot be solely on the basis of LDL-C. All risk factors should be considered together. Larger sample population studies are needed to draw population specific cutoff values for risk factors and to discover novel risk factors (CTRI/2018/03/012544).

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