Metabolic Syndrome

Synergistic impact of insulin resistance and hepatic fibrosis on cardiovascular events in patients with coronary artery disease: A machine learning subtyping and interaction analysis.

BACKGROUND AND AIMS: Insulin resistance (IR) and hepatic fibrosis are significant yet underexplored synergistic risk factors for cardiovascular events in coronary artery disease (CAD). We investigated the interaction between the triglyceride-glucose (TyG) index and liver fibrosis scores (FIB-4, BARD) for risk prediction. METHODS AND RESULTS: Within a prospective cohort of 14,660 CAD patients, we p...

Clinical Phenotypes in Hypertension: A Data-Driven Approach to Risk Stratification.

BACKGROUND: Hypertension is a major contributor to cardiovascular morbidity and mortality. Its heterogeneity complicates risk stratification. Unsupervised machine learning can uncover risk profiles and refine preventative strategies. This study applied a data-driven approach to identify clinical phenotypes of hypertension, examine their associations with cardiovascular imaging characteristics and ...

Value of Multiomics Over Clinical Risk Factors in Hypertension Prediction.

BACKGROUND: Several omics methods have been successfully used in hypertension prediction. However, the predictive ability of various multiomics data h...

Machine learning-based binary classification of elevated HbA1c (≥6.5 %) for risk assessment.

OBJECTIVE: One of the most important biomarkers for evaluating long-term glycemic management and estimating the risk of diabetes is glycated hemoglobi...

Predictors of glycemic control with imeglimin for type 2 diabetes: Results of machine learning analyses using clinical trial data.

INTRODUCTION: Identifying patient characteristics predictive of treatment response is crucial for optimizing type 2 diabetes outcomes. Using data from...

Comparative performance of machine learning vs classical formulas for LDL-cholesterol calculation.

INTRODUCTION: Low-density lipoprotein cholesterol (LDL-C) is a significant cardiovascular risk factor, as direct measurement is expensive and often un...

Enlarged Perivascular Spaces and Modifiable Vascular Risk Factors: Cross-Sectional and Longitudinal Analysis in the UK Biobank Cohort.

OBJECTIVE: To examine cross-sectional and longitudinal associations between vascular risk factors, APOE genotype, and perivascular spaces (PVS), with ...

Statin-Induced Decade-Long Stabilization of Noncalcified Coronary Plaque Despite a Zero Calcium Score.

BACKGROUND: A 48-year-old man with a coronary artery calcium (CAC) score of 0 underwent serial artificial intelligence (AI)-assisted coronary computed...

Gut microbiome profiles and associated functional pathways are linked to Mediterranean diet adherence and blood glucose control in adults with type 1 diabetes mellitus.

BACKGROUND AND AIMS: The Mediterranean diet (MD) has been associated with better glycaemic control in children with type 1 diabetes mellitus (T1DM) an...

Diabetes-linked metabolic dysfunction relates with distinct tau phosphorylation patterns, neuroinflammation and cognitive impairment in mouse models of Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by amyloid-β plaques and tau neurofibrillary tangles, with tau path...

Building and validating a machine learning model to predict coronary heart disease risk based on non-invasive indicators.

BACKGROUND: Coronary heart disease (CHD) remains a leading global cause of death. Early identification of high-risk individuals and timely interventio...

Personalized adrenal gland volume reference ranges and development of a fully automated deep learning screening tool.

OBJECTIVE: This study aims to develop a low-dose CT-based, fully automated deep learning tool for screening adrenal gland volume abnormalities and est...

Machine Learning-Based Prediction of Postoperative Vasoplegia After Cardiac Surgery.

OBJECTIVE: To develop and internally validate a machine-learning model for the early prediction of postoperative vasoplegia after cardiac surgery. DES...

Development and validation of a machine learning model to predict 30-day mortality in ischemic stroke patients with consciousness impairment: Insights from MIMIC-IV database and multicenter ICU data in China.

BACKGROUND: Patients with ischemic stroke complicated by consciousness disorders remain associated with high mortality risks. This study aims to devel...

GCLM as a novel biomarker for preeclampsia: Integrating bioinformatics and mechanistic validation.

INTRODUCTION: Preeclampsia (PE) is a pregnancy-specific disorder associated with hypertension and multi-organ dysfunction, posing serious risks to mat...

Drug Repurposing in Oncology: A Strategic Pathway to Unlocking New Therapeutic Potential.

The growing number of cancer cases and deaths highlights the urgent need for innovative treatment approaches. One technique that has lately been recog...

A machine learning-based discriminative framework for mild cognitive impairment risk in middle-aged and elderly Chinese patients with depression: evidence from CHARLS and CLHLS.

OBJECTIVE: This study aimed to evaluate the application value of machine learning (ML) techniques in the discrimination of mild cognitive impairment (...

Manipulating starch crystalline structure for controlled digestibility and glycemic response.

Postprandial hyperglycemia is a key driver in the development of type 2 diabetes, and dietary starch is a major modulator of glycemic response. The cr...

Effects of Real-Time Notification of AI-Detected Incidental Coronary Artery Calcium on Statin Prescription: The NOTIFY-PICTURE Trial.

Artificial intelligence in nephrology: predicting CKD progression and personalizing treatment.

Chronic kidney disease (CKD) represents a major and expanding global health challenge, with prevalence rising due to aging populations, diabetes, hype...