Metabolic Syndrome

Association of blood urea nitrogen to high-density lipoprotein ratio with all-cause and cardiovascular mortality in individuals with mildly reduced eGFR.

BACKGROUND: Patients with mild-to-moderate renal impairment face elevated cardiovascular risk, yet early detection tools remain limited. The Cardiovascular-Kidney-Metabolism (CKM) interplay underscores the need for integrated biomarkers. The Blood Urea Nitrogen (BUN) to High-Density Lipoprotein (HDL) cholesterol ratio (BUN/HDL) was therefore evaluated for early risk stratification. METHODS: This c...

Metabolic convergence of diabetes and prostate cancer: from dysglycemia to tumor microenvironment reprogramming.

The relationship between diabetes mellitus and prostate cancer (PC) represents one of the most intriguing paradoxes in cancer epidemiology, with diabetic individuals exhibiting a reduced incidence of PC yet poorer prognosis following diagnosis. This apparent contradiction underscores the need for an integrated understanding of how systemic metabolic dysfunction influences prostate carcinogenesis a...

Long-PVSUNet: A Longitudinal Deep Learning Framework for Count-Oriented Perivascular Space Segmentation in Brain MRI.

Enlarged perivascular spaces (ePVS) are small, sparse MRI-visible markers of cerebral small vessel disease and brain ageing. Their size, low contrast,...

Predicting Incomplete Occlusion Following Endovascular Treatment of Intracranial Aneurysms: Development and Validation of a Multidimensional Machine Learning Model.

RATIONALE AND OBJECTIVES: Incomplete occlusion after endovascular treatment (EVT) of intracranial aneurysms (IAs) increases the risks of re-rupture an...

Machine Learning-Based Subtype Classification of Sepsis-Associated Acute Kidney Injury and Differential Responses to Renal Replacement Therapy.

BackgroundSepsis-associated acute kidney injury (SA-AKI) is highly heterogeneous with controversial optimal renal replacement therapy (RRT) strategies...

Unsupervised machine learning with Cluster Analysis in patients with rheumatoid arthritis: insights in CV risk phenotypes from a multicentre Italian cohort.

Rheumatoid arthritis (RA) patients face increased cardiovascular (CV) risk, yet existing 10-year estimation tools often underperform. This study evalu...

Combined predictive value of TyG index and PLR for mental health in Chinese adults: A machine learning approach.

OBJECTIVE: To investigate the independent and combined associations of the triglyceride-glucose (TyG) index and platelet-to-lymphocyte ratio (PLR) wit...

Integrated multi-omics analyses identify an RAS-SLC11A2-associated molecular framework linking iron metabolism with PCOS-related cardiometabolic risk.

INTRODUCTION: PCOS is a common endocrine disorder with elevated cardiometabolic risk, yet the role of the renin-angiotensin system (RAS)-iron metaboli...

New Evidence in Heart Failure: 2026 Update.

Heart failure (HF) remains a major cause of morbidity, mortality, impaired quality of life and healthcare expenditure worldwide. The global burden of ...

Lipoprotein(a) and the C-reactive protein-triglyceride-glucose index in relation to coronary lesion burden in patients with acute coronary syndrome.

BACKGROUND: Lipoprotein(a) [Lp(a)] reflects inherited atherothrombotic risk, whereas the C-reactive protein-triglyceride-glucose index (CTI) integrate...

Machine learning models for early detection of urinary tract infections in kidney transplant patients.

BACKGROUND: Renal transplantation is the preferred treatment for end-stage chronic kidney disease but requires lifelong immunosuppression, increasing ...

Development of Insulin Bolus Calculators in Type 1 Diabetes Using a Framework Based on Real-World Data, Digital Twins and Machine Learning.

OBJECTIVE: Precise mealtime insulin bolus (MIB) dosing is essential in type 1 diabetes (T1D) to minimize glucose excursions from carbohydrate intake. ...

Development of a Prognostic Survival Risk Score for Lung Cancer Patients With Type 2 Diabetes Mellitus: A Territory-Wide Retrospective Cohort Study.

BACKGROUND: Lung cancer is a leading cause of cancer-related mortality, and its prognosis is often affected by comorbidities such as type 2 diabetes m...

Identification of comorbidity-based clusters and mortality risk in hospitalised patients with diabetes mellitus in Karachi, Pakistan: a machine learning analysis.

BACKGROUND: Diabetes has reached epidemic proportions in Pakistan. This study applied machine learning (ML) techniques to identify comorbidity-based a...

Clinical and Metabolomic Panel for Noninvasive Screening of Biopsy-Confirmed MASH in Children and Adolescents.

BACKGROUND & AIMS: Noninvasive tests to identify pediatric metabolic dysfunction-associated steatohepatitis (MASH) remain a critical need. We aimed to...

Myocardial Fibrosis in Pediatric Heart Disease: Mechanisms, Imaging Biomarkers, Clinical Consequences, and Emerging Antifibrotic Therapies.

Myocardial fibrosis is increasingly recognized as a central determinant of adverse cardiac remodeling and long-term cardiovascular outcomes in childre...

Risks of Major Adverse Kidney Events in Non-Hispanic Black Patients with Diabetes or Hypertension: A real-world cohort study.

INTRODUCTION: Chronic kidney disease (CKD) disproportionately burdens non-Hispanic Black (NHB) patients who experience a three- to four-fold higher ri...

Performance and label efficiency of traditional deep-learning models and a retina-specific foundation model for ocular and systemic disease detection: a retrospective comparative study.

BACKGROUND: RETFound, a self-supervised retina-specific foundation model, has shown potential in downstream tasks, but its performance in comparison w...

Machine learning-based prediction model for predicting the impact of insulin resistance on the risk of ischemic cardiomyopathy.

BACKGROUND: The triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C) ratio and triglyceride glucose-body mass (TyG-BMI) index are reliable ...

The metabolic-inflammatory axis in chronic heart failure: integrating the NLR and TyG index for recent-onset atrial fibrillation prediction via machine learning and mediation analysis.

INTRODUCTION: Recent-onset atrial fibrillation (AF) is a common complication of chronic heart failure (CHF), potentially involving both inflammatory a...