Searchable abstracts of presentations at key conferences in endocrinology

ea0090p95 | Diabetes, Obesity, Metabolism and Nutrition | ECE2023

Machine learning-derived low density lipoprotein cholesterol (LDL-C) estimation agrees better with directly measured LDL-C than conventional equations in individuals with type 2 diabetes mellitus.

Sng Gerald , Khoo You Liang , Tan Hong Chang , Mong Bee Yong

Introduction: Elevated low-density lipoprotein cholesterol (LDL-C) is an important risk factor for atherosclerotic cardiovascular disease (ASCVD). Direct LDL-C measurement is not widely performed. LDL-C is typically estimated using the Friedewald (FLDL), Martin-Hopkins (MLDL) or Sampson (SLDL) equations, which may be inaccurate at high triglycerides (TG) or low LDL-C levels. We aimed to determine if machine learning (ML)-derived LDL-C levels agree better with direct LDL-C than...

ea0056gp151 | Obesity | ECE2018

Improvement in insulin-mediated suppression of branched-chain amino acid flux is responsible for the post-bariatric surgery decrease in plasma branched-chain amino acid levels

Yao Jie , Kovalik Jean-Paul , Tham Kwang Wei , Bee Yong Mong , Lee Phong Ching , Eng Alvin , Chan Weng Hoong , Lim Eugene , Lim Jeremy , Tan Hong Chang

Background: Branched-chain amino acids (BCAA) are elevated in morbid obesity and decreases significantly following bariatric surgery. This decrease is associated with the post-surgical improvement in insulin resistance (IR) and may be secondary to the reduction in BCAA flux from proteolysis or an increase in BCAA catabolism. Presently, the underlying mechanism is unclear.Aim: To investigate the changes in BCAA metabolism in morbidly obese individuals fol...