Venous Thrombosis

Machine learning based approaches for structure activity relationship analysis of heparanase inhibitors.

Human Heparanase (HPSE), the only mammalian endo-β-D-glucuronidase, plays an important role in extracellular matrix remodeling and the release of heparin-bound growth factors. Its overexpression is strongly correlated with increased tumor growth, angiogenesis, metastasis, and inflammation, highlighting HPSE as a compelling therapeutic target for oncology and inflammatory diseases. This study aimed...

Predictors of warfarin therapeutic dose across thromboembolic indications: an exploratory early clinical evaluation study using machine learning-integrated explainable artificial intelligence and Bayesian models.

BACKGROUND: Warfarin dosing varies widely due to genetic, demographic, and clinical factors, but it is unknown whether the importance, equilibrium and prediction uncertainty of established pharmacogenetic predictors (VKORC1 and CYP2C9) differ between arterial (AF/stroke) and venous (DVT/PE) thromboembolic indications. RESEARCH DESIGN AND METHODS: This exploratory study (early clinical evaluation) ...

Impact of Unfractionated Heparin Use on Maternal Bone Mineral Density During Pregnancy: A Retrospective Study Using AI-Assisted Radiographic Analysis.

PURPOSE: This study aimed to evaluate the impact of unfractionated heparin (UFH) use during pregnancy on maternal bone mineral density (BMD) by assess...

Advancing stroke prevention in atrial fibrillation: a systematic review of machine learning-based risk prediction models.

BACKGROUND: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and confers a four to fivefold increase in ischemic stroke risk, ...

[Position paper of the German Society of Cardiology-quality criteria for performing catheter ablation of atrial fibrillation: executive summary].

The updated German Society of Cardiology (DGK) position paper on catheter ablation of atrial fibrillation (AF) [1] presents the current evidence, tech...

Integrated Diagnosis of Submassive Pulmonary Embolism Using Computed Tomography Angiography, Echocardiography, and Artificial Intelligence.

OBJECTIVES: Early intervention in submassive pulmonary embolism (SMPE) has been shown to improve long-term cardiopulmonary outcomes compared to antico...

Development of Models for Predicting the 7-Month Risk of Venous Thromboembolism and Clinically Relevant Bleeding in Ambulatory Patients with Cancer: Analysis from the AVERT Trial.

BACKGROUND: Patients with cancer are at elevated risk of venous thromboembolism (VTE). While primary thromboprophylaxis reduces VTE incidence, it also...

Consistency analysis of AI cell recognition results between non anticoagulant and anticoagulant marrow smear after Wright's staining.

The integration of artificial intelligence with bone marrow cytology represents a significant trend in the application of AI image recognition technol...

Thrombosis at the crossroads of inflammation, coagulation, and vascular biology: Recent advances and emerging therapeutic strategies.

Thrombosis is a multifaceted pathological process involving intravascular clot formation that drives a range of cardiovascular and cerebrovascular dis...

Machine learning in bleeding risk assessment for low-molecular-weight heparin or fondaparinux: a predictive model study.

BACKGROUD:  No universally accepted model exists for predicting bleeding risk in patients receiving low-molecular-weight heparin or fondaparinux. OBJE...

Performance of large language models and clinical decision support in perioperative management of oral anticoagulants.

BACKGROUND: Perioperative anticoagulant management is critical because of the competing risks of ischemia and bleeding. Large language models (LLMs) a...

Evaluation of an AI-Driven Risk Stratification System for Clinical Deterioration in Geriatric Hip Fracture Patients.

OBJECTIVES: To determine whether an artificial-intelligence-driven Clinical Deterioration Index (CDI) could identify geriatric hip-fracture patients a...

AI in Point-of-Care Imaging for Clinical Decision Support: Systematic Review of Diagnostic Accuracy, Task-Shifting, and Explainability.

BACKGROUND: Artificial intelligence (AI) integrated with point-of-care imaging is a promising approach to expand access in settings with limited speci...

A Deep Neural Network for Interpreting Wearable Electrocardiogram Data in Atrial Fibrillation: Prospective Observational Diagnostic Accuracy Study.

BACKGROUND: Atrial fibrillation (AF) and atrial flutter (AFL) are common arrhythmias associated with the risk of ischemic stroke, which can be reduced...

Decoding perioperative anesthesia-associated signature in Kawasaki disease patients with deep vein thrombosis; evidence from machine-learning driven multi-omics.

UNLABELLED: Inappropriate perioperative anesthesia (PA) drug management may lead to the detrimental clinical outcomes of Kawasaki disease (KD) patient...

Indispensable tools of critical care management: blood gas analyzers.

Blood gas analysis remains one of the most indispensable diagnostic tools in critical care, yet increasing automation often obscures its analytical fo...

Neutrophil CD14 is a driver and a therapeutic target for deep vein thrombosis.

Neutrophil-mediated persistent inflammation and neutrophil extracellular trap formation (NETosis) are critical in the pathogenesis of deep vein thromb...

AI-based autism identification from hyperspectral imaging detection of oxidative stress in pediatric red blood cells.

BACKGROUND: Oxidative stress (OS) plays a key role in many pathologies, yet the non-invasive, label-free, and cost-effective detection remains a chall...

Thrombosis after surgical splenectomy - why, in whom and can we prevent it?

Splenectomy remains a common operation performed in the setting of trauma, haematological disease, malignancy and diagnostic purposes. Contemporary ev...

A novel predictive model for evaluating thrombus regression in postpartum venous thromboembolism patients.

INTRODUCTION: Antithrombotic evaluation of postpartum venous thromboembolism (VTE) after anticoagulant therapy is challenging because of the lack of h...