PCI

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 tools. We aimed to evaluate whether integrating gut microbiome profiles with routine clinical data could enhance the classification performance for identifying DVT in a case-control cohort. Stool samples were collected from individuals with DVT (n =...

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 management remain limited. In this review, we discuss how recent advances in microfluidic thrombosis models, mechanobiology, and microrobotic technologies may enable the development of clinically actionable and personalized thrombosis platforms. RECE...

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...

Construction of a prediction model for isolated distal deep vein thrombosis after total knee arthroplasty based on machine learning.

BACKGROUND: Isolated distal deep vein thrombosis (IDDVT) is a common complication after arthroplasty. In this study, we calculated the incidence of ID...

Machine learning models to predict the recurrence of common bile duct stones after ERCP.

OBJECTIVE: To construct predictive models for the recurrence of common bile duct stones (CBDS) following endoscopic retrograde cholangiopancreatograph...

Combinations of single gene predictors with AI-driven polygenic precision therapies in cardiovascular diseases.

Pharmacogenomics (PGx) is transforming how we treat cardiovascular disease (CVD) by enabling us to select and dose drugs based on our genetic profiles...

Postpartum ovarian vein thrombosis: plain CT with clinical indicators-diagnostic performance and clinical application.

BACKGROUND: Postpartum ovarian vein thrombosis (POVT) is a rare but serious condition, often presenting with nonspecific symptoms and potentially lead...

Deep learning-based biliary stent classification and transfer learning adaptation to an additional stent type.

OBJECTIVE: Accurate classification of previously deployed biliary stents is crucial for planning reintervention, yet conventional image interpretation...

No-reflow phenomenon during percutaneous coronary intervention: Contemporary insights into mechanisms, prediction, and management.

No-reflow phenomenon remains a common and prognostically adverse complication of percutaneous coronary intervention (PCI), characterized by impaired m...

End to End Proximal Anastomosis is the Sole Modifiable Variable in Risk Score for Loss of Patency of Aortobifemoral Artery Bypass After Index Operative Hospitalization.

OBJECTIVE: The purpose of this study was to create a risk score for loss of aorto-bifemoral artery bypass (ABF) patency utilizing preoperative, periop...

Development, internal testing, and external validation of an interpretable machine-learning model for predicting imaging-confirmed in-hospital postoperative deep vein thrombosis in older patients with patellar fractures.

BACKGROUND: Older patients with patellar fractures may be at increased risk of postoperative deep vein thrombosis (DVT) because of trauma, perioperati...

A novel deep learning network for small bowel ulcerative lesion detection and differential diagnosis on double-balloon endoscopy images.

Differentiating small bowel ulcerative diseases (SBUDs) on double-balloon endoscopy (DBE) is challenging. We aimed to develop an artificial intelligen...

Plasma signals of lung tumor promotion for molecular cancer prevention.

Predicting lung cancer risk would enhance prevention trials. Although the Canakinumab Anti-inflammatory Thrombosis Outcome Study (CANTOS) trial demons...

Making Machine Learning Clinically Useful in Thrombosis and Hemostasis: A Roadmap for Diagnostic Translation.

Artificial intelligence (AI), most often in the form of machine learning (ML), attracts high expectations across medicine and is often discussed as a ...

Designing the Future of Hemostasis.

Bleeding disorders arising from dysfunctional platelet-protein interactions pose a significant clinical challenge due to their heterogeneity and compl...

Machine learning prediction of PICC-associated thrombotic complications in critically ill patients.

BACKGROUND: Peripherally inserted central catheters (PICCs) are widely used vascular access devices in intensive care, yet thrombotic complications re...