AIMC Topic: Triglycerides

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Machine learning-based prediction of LDL cholesterol: performance evaluation and validation.

PeerJ Apr 9, 2025
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.
Hypertriglyceridemia Humans Machine Learning Algorithms Female Aged Adult Male Middle Aged Risk Assessment Cholesterol, LDL Triglycerides
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Surrogate markers of insulin resistance and coronary artery disease in type 2 diabetes: U-shaped TyG association and insights from machine learning integration.

Lipids in health and disease Mar 15, 2025
BACKGROUND: Surrogate insulin resistance (IR) indices are simpler and more practical alternatives to insulin-based IR indicators for clinical use. This study explored the association between surrogate IR indices, including triglyceride-glucose index ...
Humans Machine Learning Biomarkers Logistic Models Female Male Body Mass Index Aged Middle Aged Coronary Artery Disease Blood Glucose Waist Circumference ROC Curve Cholesterol, HDL Diabetes Mellitus, Type 2 Triglycerides Insulin Resistance
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Relationship between atherogenic index of plasma and length of stay in critically ill patients with atherosclerotic cardiovascular disease: a retrospective cohort study and predictive modeling based on machine learning.

Cardiovascular diabetology Feb 28, 2025
BACKGROUND: The atherogenic index of plasma (AIP) is considered an important marker of atherosclerosis and cardiovascular risk. However, its potential role in predicting length of stay (LOS), especially in patients with atherosclerotic cardiovascular...
Triglycerides Length of Stay Time Factors Predictive Value of Tests Atherosclerosis Cholesterol, HDL Databases, Factual Biomarkers Prognosis Humans Retrospective Studies Female Machine Learning Critical Illness Risk Factors Decision Support Techniques Intensive Care Units Aged Male Middle Aged Risk Assessment
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Prediction of insulin resistance using multiple adaptive regression spline in Chinese women.

Endocrine journal Feb 1, 2025
Insulin resistance (IR) is the core for type 2 diabetes and metabolic syndrome. The homeostasis assessment model is a straightforward and practical tool for quantifying insulin resistance (HOMA-IR). Multiple adaptive regression spline (MARS) is a mac...
Blood Pressure Uric Acid Asian People Cholesterol, HDL Middle Aged Bilirubin China Humans Triglycerides Blood Glucose Machine Learning Waist-Hip Ratio Insulin Resistance Female East Asian People Young Adult C-Reactive Protein Adult
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The triglyceride-glucose index and its obesity-related derivatives as predictors of all-cause and cardiovascular mortality in hypertensive patients: insights from NHANES data with machine learning analysis.

Cardiovascular diabetology Jan 29, 2025
BACKGROUND: Hypertension (HTN) is a global public health concern and a major risk factor for cardiovascular disease (CVD) and mortality. Insulin resistance (IR) plays a crucial role in HTN-related metabolic dysfunction, but its assessment remains cha...
Triglycerides Middle Aged Risk Assessment Blood Glucose Insulin Resistance Female Nutrition Surveys Risk Factors Aged United States Adult Hypertension Cross-Sectional Studies Obesity Male Predictive Value of Tests Humans Cause of Death Machine Learning Waist Circumference Biomarkers Prognosis
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Exploring the triglyceride-glucose index's role in depression and cognitive dysfunction: Evidence from NHANES with machine learning support.

Journal of affective disorders Jan 11, 2025
BACKGROUND: Depression and cognitive impairments are prevalent among older adults, with evidence suggesting potential links to obesity and lipid metabolism disturbances. This study investigates the relationships between the triglyceride-glucose (TyG)...
Male Middle Aged Depression Cognitive Dysfunction Blood Glucose Nutrition Surveys Humans Machine Learning Female Aged Body Mass Index Obesity Mendelian Randomization Analysis Triglycerides
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Machine learning-based analyses of contributing factors for the development of hypertension: a comparative study.

Clinical and experimental hypertension (New York, N.Y. : 1993) Jan 8, 2025
OBJECTIVES: Sufficient attention has not been given to machine learning (ML) models using longitudinal data for investigating important predictors of new onset of hypertension. We investigated the predictive ability of several ML models for the devel...
Female Risk Factors Aged Adult Male Middle Aged Humans Machine Learning Waist Circumference ROC Curve gamma-Glutamyltransferase Hypertension Triglycerides Body Mass Index Blood Pressure Japan
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Exploring the prognostic impact of triglyceride-glucose index in critically ill patients with first-ever stroke: insights from traditional methods and machine learning-based mortality prediction.

Cardiovascular diabetology Dec 18, 2024
BACKGROUND: The incidence and mortality of first-ever strokes have risen sharply, especially in the intensive care unit (ICU). Emerging surrogate for insulin resistance, triglyceride-glucose index (TyG), has been linked to stroke prognosis. We aims t...
Humans Machine Learning Databases, Factual Biomarkers Prognosis Retrospective Studies Triglycerides Critical Illness Intensive Care Units Female Reproducibility of Results Risk Factors Aged Blood Glucose Male Time Factors Middle Aged Hospital Mortality Risk Assessment Predictive Value of Tests China Cause of Death Length of Stay Stroke
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Identification and optimization of relevant factors for chronic kidney disease in abdominal obesity patients by machine learning methods: insights from NHANES 2005-2018.

Lipids in health and disease Nov 26, 2024
BACKGROUND: The intake of dietary antioxidants and glycolipid metabolism are closely related to chronic kidney disease (CKD), particularly among individuals with abdominal obesity. Nevertheless, the cumulative effect of multiple comorbid risk factors...
Middle Aged Antioxidants Nutrition Surveys Humans Renal Insufficiency, Chronic Aged Glycolipids Machine Learning Obesity, Abdominal Aged, 80 and over Triglycerides Female Waist Circumference Young Adult Risk Factors Adult Male
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Predicting stroke severity of patients using interpretable machine learning algorithms.

European journal of medical research Nov 14, 2024
BACKGROUND: Stroke is a significant global health concern, ranking as the second leading cause of death and placing a substantial financial burden on healthcare systems, particularly in low- and middle-income countries. Timely evaluation of stroke se...
Area Under Curve Registries Severity of Illness Index Stroke Risk Factors Humans Length of Stay Iran Aged Adolescent Datasets as Topic Machine Learning Young Adult Age Factors Triglycerides Retrospective Studies Adult Predictive Value of Tests Female Male Middle Aged
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