PCI

Artificial Intelligence in Vascular Surgery: Translating Innovation into Clinical Practice: A Narrative Review.

Artificial intelligence (AI) is rapidly reshaping modern medicine, with expanding applications in vascular surgery ranging from diagnostic imaging and risk prediction to intraoperative guidance and postoperative surveillance. Despite the growing volume of research in this field, real-world clinical implementation remains limited, highlighting the need to critically evaluate current evidence, ident...

Personalized antiplatelet therapy: are we ready for a precision medicine approach.

Dual antiplatelet therapy (DAPT), combining aspirin with a P2Y12 inhibitor, remains central to secondary prevention after acute coronary syndrome and percutaneous coronary intervention. However, substantial interindividual variability in antiplatelet response, particularly clopidogrel resistance associated with CYP2C19 polymorphisms, has challenged the conventional "one-size-fits-all" approach and...

Precision Imaging Evaluation and Clinical Application Progress of Vascular Calcification in Lower Extremity Peripheral Artery Disease.

Lower extremity peripheral artery disease (PAD) affects a large and growing population worldwide and imposes a substantial clinical burden, particular...

Approaches to transcatheter aortic valve replacement failure: is more focus on prevention required?

INTRODUCTION: Transcatheter aortic valve replacement (TAVR) has transformed the management of severe aortic stenosis across all surgical risk strata. ...

Deep learning models based on post-procedural angiography for predicting the future risk of in-stent restenosis.

In-stent restenosis (ISR) remains a significant complication after percutaneous coronary intervention. Identifying patients at high risk for ISR from ...

Secondary prevention of recurrent ischemic stroke: from guidelines to precision medicine.

Recurrent ischemic stroke remains a major global health challenge, accounting for substantial disability and mortality despite advances in acute manag...

Bioactive Natural Products in Cardiovascular Disease: Focus on Thrombotic Events.

Bioactive compounds derived from natural products (NPs) continue to attract considerable scientific interest due to their wide range of beneficial bio...

Predictive Model for Thrombosis in Mature Autologous Arteriovenous Fistula.

OBJECTIVE: Based on the "high-risk stenosis-thrombosis" theory, this study developed a risk prediction model for thrombosis in mature autogenous arter...

Automated CT Quantification of Iliofemoral Venous Arc Length Demonstrates Left-Sided Predominance and Sex-Specific Variation.

OBJECTIVE: In treatment planning for iliac venous obstruction, iliofemoral venous anatomy is central to procedural planning, but population-level refe...

Prediction of hypertension and restenosis under guideline-directed management in aortic coarctation: development and validation of machine-learning models.

BACKGROUND: Aortic coarctation (CoA) is a major cause of arterial hypertension in young individuals, with recurrence occurring in up to one-third of p...

Review Article: Advances in the Diagnosis of Dysplasia in Barrett's Oesophagus.

BACKGROUND: Barrett's oesophagus (BE), the precursor to oesophageal adenocarcinoma, progresses through a stepwise dysplastic sequence. Accurate dyspla...

Artificial intelligence in the diagnosis of deep vein thrombosis: A scoping review.

Deep vein thrombosis (DVT) is the formation of thrombi in the deep venous system, most often in the lower extremities. Although usually not life-threa...

Identifying Patients at Elevated Risk of Stroke After.

BACKGROUND: Transcarotid artery revascularization (TCAR) has assumed a significant role in the surgical treatment of extracranial carotid occlusive di...

Gut microbiome signatures discriminate deep vein thrombosis through machine learning and metabolic analysis.

Deep vein thrombosis (DVT) remains difficult to distinguish because of its often silent presentation and the limited specificity of current diagnostic...

From biomimicry to clinical actionability: rethinking high-shear thrombosis as a mechanobiological system.

PURPOSE OF REVIEW: Arterial thrombosis remains a leading cause of morbidity and mortality worldwide, while its mechanistic understanding and clinical ...

High-throughput signal detection of hepatotoxic drug-drug interactions in hospitalized elderly patients: an NLP-driven pharmacovigilance study.

BACKGROUND: Elderly patients are highly susceptible to drug-drug interaction (DDI)-induced liver injury, yet comprehensive real-world evidence remains...

Applying machine learning to pharmacovigilance data: A proof-of-concept study.

AIM: Machine learning (ML) applications in pharmacovigilance remain limited and underexplored. Using data from the French National pharmacovigilance d...

Plasma proteomics improves thrombosis prediction in patients with cancer and identifies targetable IL-17-driven endothelial activation.

Thrombosis remains a major cause of morbidity and mortality in patients with cancer. Existing risk models fail to reliably predict venous thromboembol...

Multimodal Deep Learning for Predicting Deep Vein Thrombosis Risk After Total Knee Arthroplasty: A Clinical Study.

BACKGROUND: Deep vein thrombosis (DVT) following total knee arthroplasty (TKA) remains a major postoperative complication. Conventional risk assessmen...

Proteomics as a Theranostic Compass in BCR::ABL1-Negative Myeloproliferative Neoplasms: Integrating Biomarker Discovery with Therapeutic Stratification.

Classic BCR::ABL1-negative myeloproliferative neoplasms (MPNs)-polycythaemia vera, essential thrombocythaemia, and primary myelofibrosis-are clonal ha...