Peripheral Artery Disease

Improving 10-year cardiovascular disease risk prediction using automated machine learning.

AIMS: To develop a cardiovascular disease (CVD) risk prediction model with improved accuracy and interpretability by integrating diverse risk factors and applying Automated Machine Learning (AutoML), thereby enhancing clinical utility over conventional models. METHODS: This is a prospective cohort study. Data were obtained from the Multi-Ethnic Study of Atherosclerosis (MESA), including baseline a...

Artificial Intelligence-Enhanced Risk Stratification in Non-ST-Segment Elevation Myocardial Infarction: The Incremental Prognostic Value of the Modified Glasgow Prognostic Score in Predicting 36-Month Mortality.

OBJECTIVE: Current clinical guidelines for non-ST-segment elevation myocardial infarction (NSTEMI) emphasize the duration of dual antiplatelet therapy (DAPT) based on scores such as the Predicting Bleeding Complications in Patients Undergoing Stent Implantation and Subsequent Dual Antiplatelet Therapy (PRECISE-DAPT) score and the Dual Antiplatelet Therapy (DAPT) score. However, these anatomical an...

Post-traumatic Psychopathology and Cardiovascular Risk: A Danish Case-Control Study of Sex-Specific Associations.

BACKGROUND: There is increasing recognition that trauma exposure and related psychiatric consequences predict cardiovascular disease risk. However, mo...

[Artificial intelligence in cardiovascular prevention: a strategic opportunity for risk prediction and early diagnosis].

Cardiovascular diseases remain the leading cause of mortality and morbidity worldwide, with substantial impact in Italy. Cardiovascular prevention is ...

[Breast arterial calcifications and cardiovascular risk in women].

Cardiovascular (CV) diseases remain the leading cause of mortality in women and often present as the first clinical manifestation, highlighting the li...

Takotsubo syndrome diagnosis: the biomarker-based BioTAK score.

BACKGROUND AND AIMS: Takotsubo syndrome (TTS) closely mimics acute coronary syndrome (ACS). Early differentiation remains challenging because diagnosi...

Advancements in Pediatric Moyamoya Disease: A Critical Review of Surgical Decision-Making, Outcomes, and Future Directions.

Pediatric moyamoya disease (MMD) is a progressive steno-occlusive arteriopathy that carries a high risk of recurrent ischemic stroke and neurocognitiv...

Ligustilide and tectoridin from Danggui Buxue Decoction synergistically attenuate atherosclerosis by targeting the CD36/TRPM2 axis and TNF-α/NF-κB pathway.

BACKGROUND: Atherosclerosis (AS) is a common chronic disease and the primary pathological basis for myocardial infarction, stroke, and other disabling...

Non-calcified plaque volume assessed by coronary computed tomographic angiography: prognostic significance, reproducibility, and temporal progression.

AIMS: Coronary artery disease remains the leading cause of cardiovascular mortality worldwide, with a substantial proportion of acute coronary events ...

Trends and hotspots in artificial intelligence applications for atherosclerosis research: A bibliometric analysis.

BACKGROUND: Atherosclerosis (AS) is a complex systemic, immune-inflammatory vascular disease, and there is an urgent need to innovate its diagnostic a...

Artificial intelligence for risk prediction in atherosclerotic cardiovascular disease: A narrative review of advances, validation challenges, and clinical translation (2020-2026).

Since 2020, artificial intelligence (AI) has been increasingly applied to atherosclerotic cardiovascular disease (ASCVD) risk prediction. This structu...

Predictive, preventive, and personalized medicine in statin-treated patients with NSTE-ACS, HFpEF, and type 2 diabetes: a data-driven model for long-term residual risk assessment.

BACKGROUND: Despite significant advances in guideline-directed medical therapy (GDMT), statin-treated patients with non-ST-elevation acute coronary sy...

A Simplified Metric to Streamline Between-Group Fairness Assessment for Predictive Models: Algorithm Development and Evaluation Study.

BACKGROUND: Fairness evaluation is essential for trustworthy clinical risk prediction. However, existing fairness-oriented discrimination metrics eith...

Development and Independent Validation of a Machine Learning-Based Non-Invasive Venous Waveform Analysis for Heart Failure (NIVAHF) Device to Estimate Pulmonary Capillary Wedge Pressure.

BACKGROUND: Hemodynamic-guided management improves outcomes in heart failure (HF), but implantable pulmonary artery pressure monitoring is limited by ...

Computed Tomographic Angiography-Based Radiomics Predicted Stroke Recurrence in Patients With Symptomatic Intracranial Atherosclerotic Stenosis.

BACKGROUND: The aim of the current study was to investigate the predictive values of computed tomographic angiography-derived radiomics features (RFs)...

Opportunistic Screening of Carotid Atherosclerosis and Cardiovascular Mortality Risk Using Chest Radiographs: A Comparative Study of Foundation Models.

BACKGROUND: Cardiovascular disease (CVD) remains a leading cause of death, but population-level screening for atherosclerosis often depends on special...

Artificial Intelligence-Driven Angiographic Quantification of Fractional Flow Reserve: Proof-of-Concept Validation Study.

BACKGROUND: Angiography-based fractional flow reserve (FFR) techniques offer wire-free alternatives but often require manual segmentation and 3-dimens...

Abdominal vascular calcification at CT: opportunistic quantification and imaging-based risk stratification.

Abdominal vascular calcification is increasingly recognized as a clinically relevant marker of systemic atherosclerotic burden and regional vascular d...

Multicenter External Validation of an AI-Based Funduscopic Carotid Atherosclerosis Score and Assessment of Its Association With Coronary Artery Calcification: External Validation Study.

BACKGROUND: Screening for atherosclerosis is essential for early intervention, but conventional screening methods are often invasive and resource-inte...

Molecular clustering in osteoarthritis primary tissues identifies shared inflammatory and tissue-specific pathway profiles.

OBJECTIVES: To disentangle the molecular heterogeneity of knee osteoarthritis (OA) through the classification and characterization of transcriptomic c...