Metabolic Syndrome

Development of an explainable machine learning model for predicting depression in adults with type 2 diabetes mellitus: A cross-sectional SHAP-based analysis of NHANES 2009-2023.

Depression (DEP) is a common yet underdiagnosed comorbidity in adults with type 2 diabetes mellitus (T2DM), worsening glycemic control and increasing complication risk. Practical, interpretable risk tools using routine patient data are limited. We conducted a cross-sectional analysis using data from adults with T2DM enrolled in the National Health and Nutrition Examination Survey between 2009 and ...

Prediction of Fontan failure and correlates of Fontan-associated liver disease severity using machine learning and radiomic features from multi-parametric abdominal MRI.

BACKGROUND: Fontan-associated liver disease (FALD) is associated with morbidity and mortality in patients with palliated single ventricle congenital heart disease. OBJECTIVE: To develop machine learning models using radiomic features from T1-weighted, T2-weighted, and diffusion-weighted MRI with pertinent clinical variables to predict Fontan failure and correlates of FALD severity in patients who ...

Prediction of recurrent ischemic stroke using machine learning from real-world data.

BACKGROUND: Recurrent ischemic stroke (RIS) is a significant challenge in Malaysia, affecting approximately 33% of patients. However, studies using ar...

AI-Guided Design of pH- and Redox-Responsive Lignin@GO@ZIF-8 Nanocarriers for Targeted Co-Delivery of 5-Fluorouracil and Metformin in Prostate Cancer Therapy.

Prostate cancer therapy is limited by systemic toxicity and inefficient tumor-selective delivery. Here we report a multi-stimuli-responsive nanocompos...

Development of an interpretable machine learning model for predicting 4-year chronic kidney disease risk in elderly hypertensive patients.

INTRODUCTION: Age and hypertension are key drivers of renal impairment, predisposing older hypertensive adults to faster kidney function decline and h...

Exploring the intricate interplay between metabolic abnormalities and multidimensional cognitive impairment in stable schizophrenia patients.

Cognitive deficits across multiple domains are prevalent in patients with schizophrenia (PWS), and metabolic syndrome (MetS) may significantly contrib...

Stress hyperglycemia ratio and mortality risk in cardiometabolic multimorbidity: a multicenter retrospective study.

Monocyte-to-HDL ratio (MHR) is associated with overall and renal mortality in community-dwelling older individuals with chronic kidney disease (CKD).

From non-specific biomarker to targeted action: transdiagnostic and sex-specific drivers of high-CRP status in severe mental illness across the FondaMental Advanced Centers of Expertise (FACE) cohorts.

BACKGROUND AND OBJECTIVES: Low-grade systemic inflammation contributes to the pathophysiology of severe mental illness (SMI) in a substantial subset o...

Constructing a comprehensive nursing risk assessment model for older adults inpatients with multiple chronic conditions: A multicenter cross-sectional study.

AIM: To build a comprehensive nursing risk model for older adults inpatients with multiple chronic conditions to identify nursing risks. METHOD: This ...

Machine learning-driven identification of shared and disease-specific mitochondria-related genes in COPD, NSCLC, and NSCLC with COPD.

Chronic obstructive pulmonary disease (COPD) and non-small-cell lung cancer (NSCLC) often coexist; here, the shared mitochondrial drivers were investi...

First-Trimester Machine Learning to Predict Preeclampsia in Normotensive Pregnancies by American Heart Association Guidelines.

This study aimed to determine whether unsupervised machine learning can identify phenotypically distinct subgroups at increased risk for preeclampsia ...

A systematic review of the scope and impact of rural primary healthcare innovations using digital health technology.

OBJECTIVES: Digital technology in primary healthcare service delivery can enhance accessibility, service delivery and health outcomes in rural populat...

Optimizing Early Detection of Diabetic Kidney Disease through Synergistic Biomarkers and Serum Metabolites in Human.

BACKGROUND: Diabetic kidney disease (DKD) progresses to end-stage renal disease more rapidly than chronic kidney disease due to persistent hyperglycem...

Digital hypertension in 2024-2025: emerging evidence and future directions.

Recent advances in digital technology are remarkable, and they are driving profound transformations in healthcare and medical research. Within this co...

Metabolic Syndrome and a Broken Heart: Trust Your Gut or Risk Your Heart.

Gut dysbiosis is increasingly recognized as a contributor to heart failure; however, its specific role in the development of metabolic syndrome-induce...

Prognostic value of the triglyceride-glucose index combined with atherogenic index of plasma for all-cause mortality in critically ill patients with chronic heart failure: a machine learning-driven retrospective cohort study.

BACKGROUND: The triglyceride-glucose index (TyG) and atherogenic index of plasma (AIP) are emerging metabolic biomarkers associated with cardiovascula...

Machine learning-based LASSO-Cox model for dementia prediction: the role of midlife cardiometabolic, inflammatory, and genetic risk factors in a US cohort.

PURPOSE: We aimed to identify key midlife dementia predictors and develop a novel machine learning (ML) -enabled risk prediction model. METHODS: Using...

Endocrine and metabolic determinants of cardiometabolic risk in mild autonomous cortisol secretion.

BACKGROUND: Benign adrenal tumours, found in 1-7% of adults, can be non-functioning (NFAT) or show mild autonomous cortisol secretion (MACS), i.e., bi...

Association of cardiometabolic index with spondyloarthritis and its impact on health-related quality of life: findings from NHANES 2009-2010.

BACKGROUND: Cardiometabolic index (CMI) is a novel marker reflecting metabolic and cardiovascular health, but its role in spondyloarthritis (SpA) rema...