Atherogenic Indices as Early Predictors of Cardiovascular Diseases among Patients with Subclinical and Overt Hypothyroidism in a Tertiary Care Hospital, Karnataka: A Cross-sectional Study

Abstract

Introduction: Hypothyroidism is a common health issue that decreases the functional ability of life. It is strongly associated with altered levels of serum lipids, leading to an increased risk of Cardiovascular Disease (CVD). Lipid profile and Atherogenic Indices (AIs) can serve as better markers for evaluating CVD risk. Aim: The aim of this cross-sectional study is to evaluate the role of dyslipidaemia and AIs as predictors of CVD risk among patients with Subclinical Hypothyroidism (SCH) and Overt Hypothyroidism (OH) compared to euthyroid controls. Materials and Methods: The present cross-sectional study was conducted at the Clinical Biochemistry Section of Mandya Institute of Medical Sciences in Mandya, Karnataka, India from August to September 2019. A total of 150 subjects aged between 25-60 years were enrolled. Fasting lipid profile and Thyroid Function Test (TFT) were analysed. Based on TFT results, subjects were categorised into SCH, OH, and euthyroid groups. Data on anthropometry {(height, weight, Body Mass Index (BMI), and Blood Pressure (BP)}, lipid profile, Atherogenic Index of Plasma (AIP), Castelli Risk Index-I (CRI-I), CRI-II, and Atherogenic Coefficient (AC) were collected. Statistical analysis was performed using Pearson’s correlation and Receiver Operating Characteristic (ROC) curve analysis. Results: Out of the 150 subjects, 104 (69.3%) were females and 46 (30.7%) were males, with a mean age of 41.08±11.24 years. Both the SCH and OH groups showed statistically significant dyslipidaemic changes and elevated AIs compared to euthyroid controls. Among OH patients, there was a statistically significant positive correlation between TSH and Total Cholesterol (TC) (r=0.463), Low-Density Lipoprotein cholesterol (LDL-c) (r=0.448), CRI-I (r=0.414), CRI-II (r=0.412), and AC (r=0.411). Conversely, there was a statistically significant negative correlation between fT3 and TC (r=-0.393), LDL-c (r=-0.363), CRI-I (r=-0.300), CRI-II (r=-0.301), and AC (r=-0.298). Among the AIs, AIP showed the maximum Area Under the Curve (AUC) in both the SCH (0.707) and OH (0.747) groups. Conclusion: AIs aid in the better assessment of dyslipidaemia and CVD risk compared to lipid profile alone in hypothyroid subjects. Incorporating AIs enables early prediction of high-risk individuals for CVD risk.

Keywords

• atherosclerosis
• blood pressure
• dyslipidaemia
• thyroid disorder