Strokes

Beyond the Coronaries: Utility of Extra-Coronary Calcification for Cardiovascular Risk Assessment in Women.

PURPOSE OF REVIEW: Globally, cardiovascular disease (CVD) is the leading cause of mortality in women. Traditional risk calculators underestimate atherosclerotic cardiovascular disease risk (ASCVD), particularly in women classified as low or intermediate risk. While coronary artery calcium scoring improves risk stratification, it remains underutilized in practice. Extra-coronary calcification (ECC)...

Echocardiography-Based Machine Learning Model for Atrial Fibrillation Risk Assessment in Hypertension.

BACKGROUND: Early identification of atrial fibrillation (AF) allows for timely interventions to reduce cardiovascular complications. Risk scores including C2HEST and CHA2DS2-VASc have limitations in capturing cardiovascular remodeling. Given the association between hypertension, cardiovascular remodeling, and AF, integrating echocardiographic and demographic parameters may improve AF risk assessme...

Multi-Omics and Machine Learning Integration Identifies Key Endothelial Modules in Carotid Artery Stenosis.

BACKGROUND: Carotid artery stenosis (CAS) is a major cause of ischemic stroke, yet reliable molecular biomarkers for early identification remain limit...

DSA-NRP: No-Reflow Prediction from Angiographic Perfusion Dynamics in Stroke EVT.

Following successful large-vessel recanalization via endovascular thrombectomy (EVT) for acute ischemic stroke (AIS), some patients experience a compl...

Diagnostic value of machine-learning using conventional magnetic resonance imaging markers for pediatric idiopathic intracranial hypertension: a retrospective study.

BACKGROUND: Pediatric idiopathic intracranial hypertension can be challenging to diagnose; magnetic resonance imaging (MRI) signs are considered suppo...

Integrative multi-omics and machine learning reveal glycolysis-related biomarkers driving vascular remodeling in pulmonary arterial hypertension.

Metabolic reprogramming toward aerobic glycolysis, a phenomenon analogous to the Warburg effect, is increasingly recognized as a hallmark of pulmonary...

The role of nitrogen dioxide in the prevalence of adverse cardiovascular and cerebrovascular diseases in China: a national multi-pollutant geospatial analysis.

INTRODUCTION: Cardiovascular and cerebrovascular diseases (CCVDs) pose a severe global health threat, particularly among middle-aged and elderly popul...

Advancing stroke prevention in atrial fibrillation: a systematic review of machine learning-based risk prediction models.

BACKGROUND: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and confers a four to fivefold increase in ischemic stroke risk, ...

An Explainable Machine Learning Model Integrating Transcranial Doppler and Clinical Data to Predict Outcomes After Endovascular Thrombectomy in Acute Ischemic Stroke.

BACKGROUND: Endovascular thrombectomy (EVT) has improved outcomes in patients with acute ischemic stroke due to large vessel occlusion (AIS-LVO); howe...

Combined effects of cumulative triglyceride-glucose and blood pressure on stroke in middle-aged and older Chinese adults: a longitudinal analysis.

BACKGROUND: The triglyceride-glucose (TyG) index has increasingly been recognised an indicator for stroke risk. We aimed to explore the relationship b...

AI-driven multimodal retinal imaging for early detection and risk stratification of vascular and neurodegenerative diseases.

Systemic vascular and neurodegenerative disorders are important causes of disability and death worldwide, mainly because of the late stage of diagnosi...

Prediction and diagnosis of post-stroke epilepsy using artificial intelligence approaches: a systematic review and meta-analysis.

INTRODUCTION: Post-stroke epilepsy (PSE) is a common complication following a stroke and is a major cause of epilepsy in the elderly. Artificial intel...

Machine learning based hepatic safety score predicts decompensation in hepatocellular carcinoma systemic therapy.

Hepatocellular carcinoma (HCC) frequently coexists with portal hypertension, significantly increasing the risk of hepatic decompensation (HD) and vari...

Integrative transcriptomic analysis identifies immune-associated candidate genes and altered immune cell infiltration in pulmonary arterial hypertension.

BACKGROUND: Pulmonary arterial hypertension (PAH) is a progressive vascular disease characterized by immune dysregulation and pulmonary vascular remod...

Prediction of Early Functional Outcome After Acute Ischemic Stroke Using Real-World Clinical Data in Vietnam and Indonesia: Retrospective Cohort Study.

Accurate prediction of early functional outcome after acute ischemic stroke is critical for clinical decision-making. This retrospective cohort study ...

Machine Learning Applications Within the Earlier Medicine Framework for Stroke: A Scoping Review.

This scoping review explores how machine learning (ML) has been applied to stroke research within the Earlier Medicine framework, which promotes proac...

AI-Enhanced Nanophotonic Heterochain Sensor Enables Multiplexed Biomarker Detection across Serum, Urine, and Saliva for Stroke Differentiation.

Background: Rapid and accurate identification of stroke subtype is critical for timely intervention, yet current diagnostic assays are limited by long...

Current Artificial Intelligence Large Language Models Exhibit Sycophantic Behavior in Orthopaedic Contexts.

BACKGROUND: The use of large language models (LLMs) is increasingly common. However, LLMs may exhibit sycophancy, echoing users' beliefs while avoidin...

NATURal history of coronary PlaquE on cardiac computed tomography in individuals without MACE or lipid-lowering therapy: NATURE-CTstudy.

BACKGROUND: Coronary artery disease (CAD) progression has been examined mainly in cohorts enriched for major adverse cardiovascular events (MACE), a h...

Optimization of artificial intelligence models for prediction of new-onset cardiovascular disease in patients with arterial hypertension.

Advanced preventive strategies are needed to decrease the burden of cardiovascular disease (CVD). We aimed to develop a predictive tool to identify in...