PCI

Chronic Total Occlusion Recanalization in a 14-Year-Old Girl With Pseudoxanthoma Elasticum: IVUS-Guided Stentless Strategy.

BACKGROUND: Pseudoxanthoma elasticum (PXE) is a hereditary disorder causing progressive arterial mineralization that may cause premature coronary disease in children. CASE SUMMARY: A 14-year-old girl with exertional angina since age 8 was diagnosed with PXE after her mother used an artificial intelligence tool to identify skin lesions. Coronary imaging revealed mid-left anterior descending artery ...

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 IDDVT after total knee arthroplasty (TKA), established a prediction model for the occurrence of IDDVT after arthroplasty. METHOD: We collected data on 590 patients who underwent TKA from September 2021 to June 2023 from the hospital's electronic system...

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...

A Multidimensional Integrated Strategy for Identifying Anti-thrombotic Quality Markers(Q-Markers) in Taohong Siwu Decoction through Combined Analysis of Chemical Profiling, Bioactivity, and Pharmacodynamic Efficacy.

ETHNOPHARMACOLOGICAL RELEVANCE: Taohong Siwu Decoction (TSD), originating from the Qing Dynasty medical text Gynecology Ice Mirror, is a representativ...

Latent biochemical phenotypes delineate divergent health trajectories in older adults.

Ageing heterogeneity hampers prevention and care. We used routine biochemical panels and unsupervised learning to identify latent phenotypes in commun...

Idiopathic Intracranial Hypertension Is Characterized by a Distinct Proteomic Profile.

OBJECTIVES: The pathophysiology of idiopathic intracranial hypertension (IIH) is poorly understood and disease-specific biomarkers are lacking. We aim...

Prediction of cancer-associated thrombosis by machine learning: results from the Vienna Cancer and Thrombosis Study.

BACKGROUND: Improved risk prediction of cancer-associated venous thromboembolism (VTE) remains an unmet clinical need. We aimed to apply machine learn...

Personalised thrombo-embolic risk prediction after endometrial cancer surgery: an explainable AI approach using SHAP.

To address the clinical challenge of postoperative lower extremity deep vein thrombosis (LEDVT) in endometrial cancer care, this study establishes an ...

Predicting intracranial angioplasty failure using vessel wall MRI habitat radiomics and deep learning: a multicenter study.

BACKGROUND: Primary balloon angioplasty (PBA) is a promising strategy for symptomatic intracranial atherosclerotic stenosis but carries the risk of pr...