Peripheral Artery Disease

Unsupervised Agglomerative Cluster Phenotyping of Young Patients With Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention.

BACKGROUND: Young patients with acute coronary syndrome (ACS) exhibit diverse demographic, clinical and angiographic characteristics. We hypothesized that unsupervised machine learning (ML) can identify phenotypic clusters and predict the prognosis among young patients with ACS who undergo percutaneous coronary intervention (PCI). METHODS: We used the Houston Methodist Young-ACS PCI registry (2010...

Prevalence of Lipoprotein(a) Testing in Patients With Atherosclerotic Cardiovascular Disease Within a Large Australian Cardiology Network.

BACKGROUND: Increased lipoprotein(a) (Lp[a]) is a genetically determined causal risk factor for atherosclerotic cardiovascular disease (ASCVD). Historically, Lp(a) testing has been uncommon in Australia. This study aims to assess the prevalence and trends in Lp(a) testing in Australia, and the associated patient characteristics. METHOD: This retrospective cross-sectional study examined over 1.1 mi...

Deep learning-based early prediction of carotid plaque response to lipid-lowering therapy using longitudinal multimodal ultrasound imaging.

OBJECTIVE: This study aimed to develop and validate a deep learning prediction model using longitudinal multimodal ultrasound imaging for early identi...

Risk prediction models for incident heart failure: a systematic review and meta-analysis.

BACKGROUND: Early identification of patients at risk of heart failure (HF) provides opportunities for preventative management. Though models have been...

Development of Novel and Interpretable Automated Models for Predicting Total Knee Replacement in Knee Osteoarthritis: An International Multicenter Study.

RATIONALE AND OBJECTIVES: Subtle changes in the infrapatellar fat pad (IPFP) enable prediction and quantification of knee osteoarthritis (KOA). This s...

Comorbidity Burden and Length of Stay After Myocardial Infarction: A Retrospective Study Using Large Language Model-Assisted Chart Abstraction in a Tertiary Cardiac Hospital.

Patients' length of stay (LOS) during admission for myocardial infarction (MI) represents a closely tracked outcome metric for Cardiology services, wh...

Multimodal imaging in left main and bifurcation revascularization: contemporary evidence and comparative modalities review.

Left main (LM) and bifurcation coronary artery disease (CAD) are anatomically complex lesions which require detailed planning and precise execution fo...

Targeted use of large language models for EHR-based computable phenotyping.

OBJECTIVE: Computable phenotypes derived from electronic health records (EHRs) are central to clinical research and quality reporting. Although large ...

Prevalent vertebral fracture (PVFx) and abdominal aortic calcification (AAC) independently predict incident atherosclerotic cardiovascular disease (ASCVD) events in older men.

PURPOSE: To estimate the associations of prevalent vertebral fracture (PVFx) and abdominal aortic calcification (AAC) with incident ASCVD (myocardial ...

Artificial Intelligence-Empowered Image Fusion of Coronary Computed Tomography Angiography and Invasive Angiography for Guiding Chronic Total Occlusion Percutaneous Coronary Intervention.

Coronary computed tomography angiography (CCTA) provides qualitative and quantitative characteristics of atherosclerotic plaques, quantified percentag...

Deep-learning-based diagnostic models for transcutaneous oxygen pressure-defined peripheral arterial disease and lower extremity wound healing in patients with diabetic foot.

BACKGROUND: Few studies have evaluated peripheral artery disease (PAD) and wound healing in patients with lower extremity wounds using a convolutional...

Machine learning integrated clinical-proteomics data identifies a 6-protein panel signature for atherosclerotic severity and enhanced patient stratification.

Atherosclerosis, a major cause of adverse cardiovascular events and mortality rates worldwide, stems from sustained lipid accumulation and subsequent ...

Self-enhancement-based perfusion mapping with contrast-enhanced magnetic resonance imaging for PAD assessment.

We developed an automatic self-enhancement-based perfusion mapping (SEPM) method to relatively map the microvascular perfusion level in contrast-enhan...

Vessel Wall Imaging at 7T: State of the Art.

Intracranial vessel wall imaging (VWI) has emerged as a critical tool in neurovascular diagnostics, enabling direct assessment of the vessel wall, whi...

Enabling ankle-brachial index prediction from doppler sounds using deep learning.

The ability to perform accurate point-of-care assessment of limb perfusion is critical for safe clinical decision-making. A formal ankle-brachial inde...

Ischaemia in tuberculous meningitis: update on pathophysiology, clinical predictors and management.

PURPOSE OF REVIEW: Tuberculous meningitis (TBM) is a severe manifestation of Mycobacterium tuberculosis infection, associated with high mortality and ...

AI-Derived LA Volume Index, LA/RA and LA/LV Volume Ratios From Coronary Artery Calcium Scans Predict Long-Term Atrial Fibrillation and Stroke.

BACKGROUND: The AI-CVD initiative aims to extract actionable insights from coronary artery calcium (CAC) scans beyond the traditional CAC score. Altho...

Elucidating the role of SF3B3 in coronary atherosclerosis: integrating bioinformatics and machine learning for advanced insights.

Utilizing Deep Learning-based Computed Tomography Fractional Flow Reserve on Coronary Artery Disease Diagnosis and Treatment: 1-year Clinical Application From a Chinese Major Hospital.

PURPOSE: Machine learning-based coronary computed tomography fractional flow reserve (CT-FFR) holds great potential for assessing coronary ischemic st...

Magnetically controlled capsule endoscopy: Innovations, standardized practice, and emerging clinical roles.

Capsule endoscopy has transformed small bowel evaluation but remains limited for gastric examination because of passive, peristalsis dependent movemen...