High level of individual lipid profile and lipid ratio as a predictive marker of poor glycemic control in type-2 diabetes mellitus
Received 24 March 2019
Accepted for publication 3 May 2019
Published 5 June 2019 Volume 2019:15 Pages 149—157
Checked for plagiarism Yes
Review by Single-blind
Peer reviewer comments 2
Editor who approved publication: Dr Pietro Scicchitano
I Made Junior Rina Artha,1 Agha Bhargah,1,2 Nyoman Khrisna Dharmawan,2 Utami Wijayaswari Pande,2 Komang Agus Triyana,2 Pande Agung Mahariski,2 Jessica Yuwono,2 Varennia Bhargah,2 I Putu Yuda Prabawa,3 Ida Bagus Amertha Putra Manuaba,4,5 I Ketut Rina6
1Department of Cardiology and Vascular Medicine, Faculty of Medicine, Udayana University, Sanglah General Hospital, Denpasar, Bali, Indonesia; 2Faculty of Medicine, Udayana University, Denpasar, Bali, Indonesia; 3Clinical Pathology Department, Faculty of Medicine, Udayana University, Sanglah General Hospital, Denpasar, Bali, Indonesia; 4International Ph.D Program in Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan; 5Medical and Health Education Unit, Faculty of Medicine, Udayana University, Denpaser, Bali, Indonesia; 6Cardiology Department, Puri Raharja General Hospital, Denpasar, Bali, Indonesia
Introduction: Diabetes is often accompanied by undiagnosed dyslipidemia. The aim of the study is to investigate the clinical relevance of lipid profiles and lipid ratios as predictive biochemical models for glycemic control in patients with type 2 diabetes mellitus (T2DM).
Methods: This is a retrospective study recruiting 140 patients with T2DM during a one-year period, 2018–2019, at the Diabetic Center Sanglah General Hospital and Internal Medicine Polyclinic Puri Raharja General Hospital. Demographic characteristics, glycosylated hemoglobin (HBA1c) , and lipid profile were recorded and analyzed using SPSS version 25.0 for Windows. The sample is then classified into good (HBA1c≤7) and poor (HBA1c>7) glycemic control. Risk analysis model, receiver operator characteristics (ROC) analysis, and correlation test were used to evaluate the association of HBA1c level with lipid profile and lipid ratio parameters.
Result: Lipid profile findings such as total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) , triglycerides (TG), and lipid ratio parameter (LDL-C to high-density lipoprotein cholesterol (HDL-C) ratio) were higher in patients in the poor glycemic control group (p<0.05) and HDL-C was significantly lower in patients with poor glycemic control (p=0.001). There is a significant positive correlation between LDL, total cholesterol, LDL-C, TG, and TC to HDL-C ratio, triglycerides, and TC/HDL-C ratio with HBA1c level. Meanwhile, a negative correlation was observed on HDL-C with the HBA1c level. Only TC/HDL-C ratio and LDL-C/HDL-C ratio parameters may be used as predictive models (AUC>0.7), with cutoff point, sensitivity, and specificity of 4.68 (77%; 52%) and 3.06 (98%; 56%) respectively. A risk analysis model shows that the LDL-C/HDL-C ratio parameter is the most influential risk factor in the occurrence of poor glycemic control (adjusted OR =38.76; 95% CI: 27.32–56.64; p<0.001).
Conclusion: Lipid profiles (LDL-C) and lipid ratios (LDL-C/HDL-C and TC/HDL-C ratio) show potential markers that can be used in predicting glycemic control in patients with T2DM.
Keywords: dyslipidemia, glycemic, diabetes, risk
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