Metabolic Syndrome

Smart insulin dosage software based on trend arrows: an effective method for controlling hyperglycemia in hospitalized diabetic patients in non-endocrine departments (a randomized controlled trial).

Epidemiological Trajectories and Quality of Care Disparities of MASLD in Asia, 1990-2023.

BACKGROUND: To characterize temporal and geographic patterns of metabolic dysfunction-associated steatotic liver disease (MASLD) across Asia from 1990 to 2023, assess disparities in disease burden and care quality, and identify key demographic and metabolic determinants shaping its trajectory. METHODS: We analyzed Global Burden of Disease (GBD) 2023 data for 47 Asian countries (1990-2023). Age-sta...

Machine learning-predicted insulin resistance is a risk factor for 12 types of cancer.

Insulin resistance is suggested to be a risk factor for cancer; however, large-scale epidemiological evidence linking insulin resistance to cancer rem...

Detection and prognostic stratification of left ventricular systolic dysfunction in left bundle branch block using an artificial intelligence-enabled electrocardiography.

BACKGROUND: Left bundle branch block (LBBB) significantly increases the risk of left ventricular systolic dysfunction (LVSD) due to cardiac dyssynchro...

Proactive haemodynamic management using the hypotension prediction index during caesarean section: a randomised controlled study.

INTRODUCTION: Intra-operative hypotension is common during caesarean section and may result in adverse maternal effects, such as nausea and vomiting. ...

Association of cardiovascular-kidney-metabolic syndrome stages with MASLD prevalence and liver fibrosis severity: evidence from traditional and machine learning approaches.

INTRODUCTION: Cardiovascular-Kidney-Metabolic (CKM) syndrome reflects the convergence of cardiovascular, renal, and metabolic disorders. Metabolic dys...

Disease-specific crosstalk of Alistipes with lipoprotein profiles in overweight individuals at high cardiometabolic risk.

Metabolic syndrome (MS) and systemic lupus erythematosus (SLE) represent two pathophysiologically distinct chronic conditions associated with elevated...

Diagnosis of Cardiac Amyloidosis on Echocardiography Using Artificial Intelligence.

BACKGROUND: Diagnosing cardiac amyloidosis (CA) on echocardiography can be challenging due to the imaging overlap between CA and more prevalent causes...

Explainable machine learning model based on clinical and radiological features for predicting hematoma expansion or rebleeding after decompressive craniectomy in traumatic brain injury: a bicentric cohort study.

BACKGROUND: Hematoma expansion or rebleeding after decompressive craniectomy (DC) is a critical determinant of poor prognosis in traumatic brain injur...

Leveraging natural language processing and machine learning to identify chronic conditions from primary care electronic medical records.

Primary care electronic medical records (EMRs) contain rich data that can support proactive identification of chronic health conditions. However, leve...

Predicting risk of ascending thoracic aortic aneurysm in asymptomatic adults using machine learning.

Most patients with ascending thoracic aortic aneurysms (ATAA) remain asymptomatic until they develop fatal complications, including aortic dissection ...

DNA Methylation Markers for Pregnancy Hypertension via Machine Learning Methods.

BACKGROUND: This study aims to develop a prediction model to identify individuals at risk of hypertensive disorders of pregnancy (HDPs), including ges...

Detection of esophageal varices and prediction of hepatic decompensation in unresectable hepatocellular carcinoma using AI.

BACKGROUND & AIMS: In hepatocellular carcinoma (HCC) with cirrhosis, portal hypertension worsens outcomes. Esophagogastroduodenoscopy (EGD), the curre...

Data-driven subgroups for 3-year risk stratification of incident diabetes and complications in diabetes-free Chinese adults.

BACKGROUND: Substantial metabolic heterogeneity exists prior to the development of diabetes, creating opportunities for earlier and more precise inter...

A Cross-Sectional Study Based on Deep Learning to Explore the Effect of Triglyceride/Glucose Index on Periodontitis: An Analysis Based on the Large NHANES Database.

PURPOSE: Periodontitis is a common chronic inflammatory disease closely associated with metabolic syndrome. The triglyceride-glucose (TyG) index is a ...

Health-oriented sleep states: making sleep states reflect health conditions.

STUDY OBJECTIVES: The rich information in sleep offers insights into brain function and overall health. The current guidelines for sleep staging by th...

Machine-learning-derived phenotypes of hypertensive patients using multidimensional clinical and echocardiographic data including strain imaging.

AIMS: We applied unsupervised machine learning clustering to a large cohort of hypertensive patients undergoing echocardiography with strain imaging t...

Effects of Lactiplantibacillus plantarum on moderate dyslipidemia before medication involving gut microbiota and host genetics.

In this 12-week trial, 136 participants with moderately dyslipidemia were randomly assigned to receive Lactiplantibacillus plantarum (LP) or placebo. ...

Factors Associated with Machine Learning-Based Predictions of Retinal Aging Using Teleretinal Screening Images from Patients with Diabetes.

PURPOSE: To identify factors associated with accelerated retinal aging based on machine learning predictions of age using fundus images from teleretin...

Simultaneous Segmentation of Geographic Atrophy in Longitudinally Acquired Fundus Autofluorescence Images.

PURPOSE: Accurately measuring geographic atrophy (GA) progression in clinical trials is challenging, owing to its slow and variable nature. This study...