Hyperlipidemias subtypes association with different glycemic levels

Authors

  • Safia Fatima Department of Chemical Pathology and Endocrinology, AFIP, Rawalpindi-National University of Medical Sciences, Pakistan
  • Haseeba Nigarish Shabbir Armed Forces Post Graduate Medical Institute Rawalpindi (National University of Medical Sciences), Pakistan
  • Muhammad Aamir Armed Forces Institute of Pathology Rawalpindi (National University of Medical Sciences), Pakistan
  • Afshan Bibi Armed Forces Institute of Pathology Rawalpindi (National University of Medical Sciences), Pakistan
  • Sobia Irum Kirmani Armed Forces Institute of Pathology Rawalpindi (National University of Medical Sciences), Pakistan
  • Muhammad Tahir Khadim National Public Health Laboratory, Islamabad, Pakistan

Abstract

Objective: To compare lipid profile and glycemic profile in diabetic, pre-diabetic and biochemical healthy individuals.

Material and Methods: This cross-sectional study at Department of Chemical Pathology & Endocrinology, Armed Forces Institute of Pathology, Rawalpindi from July 2018 to March 2019. Samples of fasting lipid profile, fasting plasma glucose and HbA1c were collected by simple random technique. At 3000 RPM for 5 minutes, these samples were then centrifuged. Using the enzymatic colorimetric methods fasting plasma glucose, total cholesterol (TC), triglyceride (TG), low density lipoprotein cholesterol (LDL-C) and high density lipoprotein cholesterol (HDL-C) and very low density lipoprotein cholesterol (VLDL-C) were analyzed on ADVIA1800 and glycosylated hemoglobin (HbA1c) analysis was facilitated by turbidometry inhibition immunoassay (TINIA) using ADVIA1800. For the statistical analysis SPSS 22 was used.

Results: Out of 141 selected subjects 72 (51.1%) were males and 69 (48.9%) were females. On the basis of fasting plasma glucose and HbA1c values, outcome variable was divided into following three categories; healthy group 18 (12.8%), pre-diabetic 40 (28.4%) and diabetic 83 (58.9%). Mean age in healthy, prediabetic and diabetic groups were 45.9±18.3 years, 52.3±11.1 years, 55.4±10.2 years respectively. The results deducted from the lipid profile analysis suggest; out of these 141 patients 21 (14.9%) were healthy, 15(10.6%) with familial combined hyperlipidemias (FCH), 12(8.5%) had familial cholesterolemia (FH), 2(1.4%) were with hypertriglyceridemia, and 91(64.6%) were of nonspecific dyslipidemias. Different hyperlipidemia (according to Frederickson ‘s classification) and nonspecific dyslipidemia percentage distribution in three glycemic profile categories was; diabetic group included normal lipid profile = 9 (10.8%), FH = 8 (9.6%), FCH = 7 (8.4%), hypertriglyceridemia = 2 (2.4%) and nonspecific dyslipidemia = 57 (68.7%), pre-diabetic group included normal lipid profile =7 (17.5%), FH = 7 (17.5%), FCH = 5 (12.5%) and nonspecific dyslipidemia = 21 (52.5%) and healthy group included lipid profile within reference range= 5 (27.8%) and nonspecific  dyslipidemias = 13(72.2%). The non- specific dyslipidemias groups had been further divided into different groups; 1st group included only decrease HDL-C= 21(23%), 2nd group included increase VLDL-C and decrease HDL-C = 15 (17%), 3rd group included decrease HDL-C increase LDL-C and increase total cholesterol (TC) of 38 (42%) and 4th group included decrease HDL-C, increase Triglyceride (TG), increase VLDL-C with decrease HDL-C 16(18%).

Conclusion: Nonspecific dyslipidemia was found with highest frequency in healthy than pre-diabetic and diabetic population.

Key Words: Nonspecific dyslipidemias, HDL-C, LDL-C, VLDL-C.

Downloads

Published

07-07-2020

How to Cite

1.
Fatima S, Shabbir HN, Aamir M, Bibi A, Kirmani SI, Khadim MT. Hyperlipidemias subtypes association with different glycemic levels. Pak J Pathol [Internet]. 2020 Jul. 7 [cited 2024 Dec. 22];31(2):31-7. Available from: https://pakjpath.com/index.php/Pak-J-Pathol/article/view/564

Issue

Vol. 31 No. 2 (2020): Pakistan Journal of Pathology

Section

Articles

License

Copyright (c) 2020 Safia Fatima, Haseeba Nigarish Shabbir, Muhammad Aamir, Afshan Bibi, Sobia Irum Kirmani, Muhammad Tahir Khadim

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Readers may “Share-copy and redistribute the material in any medium or format” and “Adapt-remix, transform, and build upon the material”. The readers must give appropriate credit to the source of the material and indicate if changes were made to the material. Readers may not use the material for commercial purpose. The readers may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.