Venous Thrombosis

Two-Stage Machine Learning Based Prediction of Thrombophilia Management

Thrombophilia diagnosis and management rely on the nuanced interpretation of clinical history, risk factors, and laboratory data, yet significant variability exists in clinical practice due to subjective assessment, institutional differences, and limited consensus guidelines. In this retrospective study, we evaluated the use of a two-stage machine learning (ML) approach to predict thrombophilia di...

Machine learning model predicts new-onset lower extremity deep vein thrombosis after pelvic fracture surgery and targeted diagnosis

Postoperative new-onset deep vein thrombosis (PNO-DVT) of the lower extremities represents a prevalent and serious clinical complication following pelvic fractures, which substantially impedes patient rehabilitation and diminishes quality of life. Conventional risk assessment methodologies exhibit inherent limitations, rendering them inadequate for precise prediction and individualized management ...

Association of early enoxaparin prophylactic anticoagulation with ICU mortality in critically ill patients with chronic obstructive pulmonary disease: a machine learning-based retrospective cohort study.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a major contributor to global morbidity and mortality, particularly during acute exacerbat...

Applying Machine Learning for Prescriptive Support: A Use Case with Unfractionated Heparin in Intensive Care Units.

Continuous unfractionated heparin is widely used in intensive care, yet its complex pharmacokinetic properties complicate the determination of appropr...

Improving VTE Identification through Language Models from Radiology Reports: A Comparative Study of Mamba, Phi-3 Mini, and BERT

Venous thromboembolism (VTE) is a critical cardiovascular condition, encompassing deep vein thrombosis (DVT) and pulmonary embolism (PE). Accurate a...

Innovative approaches to atrial fibrillation prediction: should polygenic scores and machine learning be implemented in clinical practice?

Atrial fibrillation (AF) prediction and screening are of important clinical interest because of the potential to prevent serious adverse events. Devic...

Dynamic Online Recommendation for Two-Sided Market with Bayesian Incentive Compatibility

Recommender systems play a crucial role in internet economies by connecting users with relevant products or services. However, designing effective r...

[Construction of a back propagation neural network model for predicting urosepsis after flexible ureteroscopic lithotripsy].

OBJECTIVES: To analyze the association of serum heparin-binding protein (HBP) and C-reactive protein (CRP) levels with urosepsis following flexible ur...

Efficacy of Intraoperative Cell Salvage on Perioperative Blood Transfusion in Pelvic and Acetabular Surgery: A Matched Cohort Analysis.

BACKGROUND: Pelvic fractures often result in traumatic and intraoperative blood loss. Cell salvage (CS) is a tool where autologous blood lost during s...

Skin Changes in Suspected Lyme Disease.

Dear Editor, Ticks carry many diseases, bacteria, and viruses and represent a very important healthcare issue both in Croatia and globally. Although m...

Critical Appraisal on the Role of Warfarin in the Current Era.

Warfarin has been the most extensively used oral anticoagulant (OAC) in medical settings for over 60 years. Its uses, potential adverse effects, and m...

Predictors of bleeding event among elderly patients with mechanical valve replacement using random forest model: A retrospective study.

Available classification tools and risk factors predicting bleeding events in elderly patients after mechanical valve replacement may not be suitable ...

A Machine Learning Approach to Predict Deep Venous Thrombosis Among Hospitalized Patients.

Deep venous thrombosis (DVT) is associated with significant morbidity, mortality, and increased healthcare costs. Standard scoring systems for DVT ris...

Natural Language Processing Performance for the Identification of Venous Thromboembolism in an Integrated Healthcare System.

Real-time identification of venous thromboembolism (VTE), defined as deep vein thrombosis (DVT) and pulmonary embolism (PE), can inform a healthcare o...

Cost-Effective Machine Learning Based Clinical Pre-Test Probability Strategy for DVT Diagnosis in Neurological Intensive Care Unit.

In order to overcome the shortage of the current costly DVT diagnosis and reduce the waste of valuable healthcare resources, we proposed a new diagnos...

[Determination of sulfation degree of heparin and low molecular weight heparins by capillary electrophoresis].

Heparin is composed of a highly sulfated linear saccharide and is widely used as an anticoagulant. Low molecular weight heparins (LMWHs) are derived f...

[Severe influenza A (H1N1) in late pregnancy: a case report].

Pregnancy has increased susceptibility to H1N1 influenza virus infection. Maternal influenza infection is associated with increased risk of morbidity ...

Anticoagulant treatment in elderly patients with atrial fibrillation: a position paper.

Atrial fibrillation (AF) is common in the elderly. The treatment of this condition is based on anticoagulation to prevent stroke and systemic arterial...

Clinical observation of the efficacy of low-molecular-weight heparin calcium in prophylaxis of the deep venous thrombosis following the gynecological tumor surgery.

Present study is conducted to investigate the efficacy and safety of application of low-molecular-weight heparin calcium in the prophylaxis of deep ve...

Development of a Computer-Aided Dosage and Telemonitoring System for Patients Under Oral Anticoagulation Therapy.

In this paper, we present a system that allows patients who require anticoagulation medicine an opportunity to independently manage their dosage conce...