Metabolic Syndrome

Transcranial Doppler ultrasonography in geriatric anesthesia: moving toward personalized brain protection strategies.

The increasing volume of geriatric surgical procedures presents a critical challenge: protecting the aging brain from perioperative complications such as postoperative delirium and postoperative cognitive dysfunction. Conventional anesthetic management, which relies primarily on systemic parameters like blood pressure, often overlooks age-related vulnerabilities, including impaired cerebral autore...

Retinal image-based cardiovascular risk prediction using AI-CRS: a multi-modal deep learning framework.

This study presents AI-CRS, an AI-driven deep learning framework for cardiovascular risk assessment using retinal images. By combining convolutional neural networks (CNNs), attention mechanisms, and vasculature segmentation, AI-CRS overcomes the limitations of traditional methods, such as reliance on handcrafted features and single-modality data. The model integrates multi-modal information, fusin...

Development and validation of a nomogram for predicting advanced chronic kidney disease.

The objective of this study was to develop and validate a nomogram for predicting advanced chronic kidney disease (CKD) through the utilization of rou...

Prediction model for frailty risk in ischemic stroke patients: Application and validation of support vector machines and nomograms.

This study aimed to develop a prediction model based on nomograms and support vector machines (SVM) to assess frailty risk in ischemic stroke patients...

EHR-derived cognitive load is associated with guideline-concordant statin initiation in primary care.

INTRODUCTION: Linking electronic health record (EHR) use to care quality may offer insights into potential interventions improving guideline adherence...

SELFormer-guided discovery of xanthohumol and cirsilineol as multi-target natural therapeutics for type 2 diabetes: computational prediction and experimental validation.

Type 2 diabetes mellitus (T2DM) requires multi-target therapeutic approaches addressing both insulin resistance and insulin secretion deficits. Althou...

Retinal vascular phenotyping for early detection of coronary artery disease: quantitative assessment and diagnostic modelling.

OBJECTIVES: To investigate the association between quantitative retinal vascular parameters and coronary artery disease (CAD) and to evaluate the effi...

The Role of Machine Learning and Artificial Intelligence in Drug Discovery and Clinical Care of Pulmonary Hypertension.

Pulmonary hypertension (PH) is a severe and oftentimes fatal disease with a high degree of clinical variability. Its complexity necessitates a multifa...

Arterial pulse harmonic alterations: a novel biomarker linking vascular dysfunction to prefrailty.

BACKGROUND AND AIMS: The identification of prefrailty, a reversible state of vulnerability in older adults, remains a clinical challenge. Arterial sti...

Interpretable deep learning with pharmacogenomics predicts myocardial infarction in angiotensin receptor blocker treated hypertension.

OBJECTIVE: A significant residual risk of myocardial infarction (MI) persists in hypertensive patients treated with angiotensin receptor blockers (ARB...

Echocardiographic Evaluation of Global Cardiac Function in Systemic Sclerosis-Associated Pulmonary Arterial Hypertension: An Integrated Review of Parameters and Techniques.

Systemic sclerosis (SSc) is a connective tissue disease frequently complicated by pulmonary arterial hypertension (PAH), a leading cause of morbidity ...

Multi-Omics and Machine Learning-Driven Discovery of ABCC8 (SUR1) for Diabetes Mellitus: Integrating Molecular Insights on Nigella sativa Bioactives and Sulfonylurea.

Diabetes mellitus is a chronic metabolic disorder characterized by hyperglycemia and pancreatic β-cell dysfunction. The ATP-sensitive potassium KATP c...

Machine Learning-driven Prioritisation of Lipoprotein(a) Testing: Model Development and Validation.

AIMS: Elevated lipoprotein(a) [Lp(a)] is a common risk factor for cardiovascular disease (CVD) affecting ∼1.4 billion people globally, with novel trea...

Radiomics-Based Classification of Pathological Patterns in Common Carotid Artery Wall.

OBJECTIVES: Abnormal echogenic patterns such as the triple signal pattern can be identified in the common carotid artery (CCA) using ultrasound. These...

Using machine learning algorithms to predict MACE in peritoneal dialysis patients.

The study aimed to predict the risks of Major adverse cardiac events (MACE) in patients undergoing peritoneal dialysis (PD) with machine learning (ML)...

Association between triglyceride-glucose index and related indicators with heart failure-related mortality in individuals with early-stage cardiovascular-kidney-metabolic syndrome.

BACKGROUND: Insulin resistance is a central pathophysiological feature of cardiovascular-kidney-metabolic (CKM) syndrome and has been implicated in ad...

Personalized mapping of body homeostasis using whole-body PET connectomics and routine FDG PET imaging.

BACKGROUND: Immuno-inflammation and systemic alterations are key features of chronic diseases. While PET molecular imaging is widely used in precision...

High-density lipoprotein-related inflammatory ratios and coronary heart disease: A cross-sectional machine learning analysis of NHANES 2009 to 2020.

High-density lipoprotein (HDL)-related inflammatory ratios (monocyte-to-HDL cholesterol ratio [MHR], lymphocyte-to-HDL cholesterol ratio, neutrophil-t...

Reappraising cardiac function with myocardial contraction fraction: normal values, disease detection, and prognostication.

AIMS: Assessing cardiac function is critical for managing cardiovascular disease, guiding treatment, monitoring progression, and risk stratification. ...

Exploring the association between Frailty Index and Knee osteoarthritis in middle-aged and older Chinese adults: A cross-sectional analysis of data from the China Health and Retirement Longitudinal Study.

OBJECTIVE: To explore the relationship between Frailty Index (FI) and Knee osteoarthritis (KOA) in Chinese people aged 45 and above. METHODS: Data on ...