OBJECTIVE: This study aimed to validate and optimize a machine learning algorithm for accurately predicting low-density lipoprotein cholesterol (LDL-C) levels, addressing limitations of traditional formulas, particularly in hypertriglyceridemia.
INTRODUCTION: Propofol is a widely used sedative-hypnotic agent for critically ill patients requiring invasive mechanical ventilation (IMV). Despite its clinical benefits, propofol is associated with increased risks of hypertriglyceridemia. Early ide...
AIM: To evaluate the association between high triglyceride/HDL-cholesterol (TG/HDL-C) ratio and insulin resistance (IR) or hyperinsulinemia after oral glucose tolerance test (OGTT) in normal-weight healthy adults.
BACKGROUND: Random forest (RF) is a machine-learning method that generally works well with high-dimensional problems and allows for nonlinear relationships between predictors; however, the presence of correlated predictors has been shown to impact it...
AIM: To assess the association between elevated triglycerides/glucose index (TGI) and insulin resistance (IR) or hyperinsulinemia after oral glucose tolerance test (OGTT) in a sample of healthy adults.
To develop and validate an explainable machine learning (ML) tool to help clinicians predict the risk of propofol-associated hypertriglyceridemia in critically ill patients receiving propofol sedation. Patients from 11 intensive care units (ICUs) a...
The Journal of clinical endocrinology and metabolism
Dec 18, 2024
CONTEXT: Metabolic dysfunction-associated steatotic liver disease (MASLD) is currently the most common chronic liver disease worldwide and is strongly associated with metabolic comorbidities, including dyslipidemia.
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