Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Venous Thrombosis I: Introduction01:30

Venous Thrombosis I: Introduction

216
Venous thrombosis, the most common disorder of the veins, involves the formation of a thrombus or blood clot associated with vein inflammation. It can be classified as either superficial vein thrombosis or deep vein thrombosis.Superficial Vein Thrombosis: This involves the formation of a thrombus in a superficial vein, usually the greater or lesser saphenous vein. Though less severe than deep vein thrombosis (DVT), SVT can lead to complications if untreated.Deep Vein Thrombosis (DVT): This...
216
Venous Thrombosis II: Clinical Manifestations and Diagnostic Studies01:20

Venous Thrombosis II: Clinical Manifestations and Diagnostic Studies

244
The key difference between Superficial Vein Thrombosis (SVT) and Deep Vein Thrombosis (DVT) lies in their location and severity.Clinical ManifestationsSVT typically presents with localized pain, tenderness, and redness along the course of a superficial vein, often accompanied by a palpable, cord-like structure under the skin. This condition is usually less dangerous than DVT but can be uncomfortable and may lead to complications such as cellulitis or, rarely, a clot extension into the deep...
244
Venous Thrombosis III: Interprofessional Care01:29

Venous Thrombosis III: Interprofessional Care

239
Venous thrombosis requires effective prevention and treatment strategies to improve patient outcomes and reduce potential complications.Prevention StrategiesHealthcare providers must prioritize preventing venous thromboembolism (VTE) for all adult patients upon admission. Interventions depend on bleeding and thrombosis risk, medical history, current medications, diagnoses, planned procedures, and patient preferences. Patients on bed rest should change positions every two hours and, if not...
239
Venous Return01:04

Venous Return

11.4K
The circulatory system plays a crucial role in ensuring the optimal functioning of the human body. One of its critical components is venous return - the process that completes the blood circulation cycle. This article will delve into the concept of venous return, how it works, and its significance to our health.
What is Venous Return?
Venous return refers to the rate at which blood flows back to the heart from the body's peripheral veins. It's an integral part of the circulatory system...
11.4K
Venous Thrombosis IV: Nursing Management01:30

Venous Thrombosis IV: Nursing Management

163
Nursing management begins with a thorough assessment of the patient's health history. Key factors include trauma to veins, peripherally inserted central catheters, varicose veins, recent pregnancy or childbirth, surgery, bacteremia, prolonged bed rest, atrial fibrillation, COPD, heart failure, cancer, coagulation disorders, myocardial infarction, spinal cord injury, stroke, prolonged travel, recent bone fractures, and dehydration. Review medication intake, particularly oral contraceptives,...
163
Pulmonary Embolism II: Diagnostic Studies and Interprofessional Care01:29

Pulmonary Embolism II: Diagnostic Studies and Interprofessional Care

242
Diagnosing Pulmonary EmbolismDiagnosing pulmonary embolism (PE) involves clinical assessment and advanced imaging tests. The preferred diagnostic tool is the spiral (helical) CT scan or CT angiography (CTA), which uses intravenous contrast media to visualize the pulmonary vasculature and identify emboli.A ventilation-perfusion (V/Q) scan is an alternative for patients unable to receive contrast media. This scan includes both perfusion and ventilation scanning. Perfusion scanning involves...
242

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

External validation of established clinical risk scores for cancer-associated venous thromboembolism in a Brazilian registry.

Journal of thrombosis and thrombolysis·2026
Same author

Artificial intelligence in computational modeling of thrombosis: Bridging mechanistic insights and clinical translation.

Journal of thrombosis and thrombolysis·2025
Same author

Evaluation of the podoplanin/C-type lectin-like receptor-2 (CLEC-2) pathway as a mediator of platelet and coagulation activation in sickle cell disease.

Research and practice in thrombosis and haemostasis·2025
Same author

Determination of Patient-Specific Blood Coagulation Kinetic Parameters via Neural Networks: Toward Thrombosis Prediction in Personalized Medicine.

Annals of biomedical engineering·2025
Same author

Integrating biomarkers for hemostatic disorders into computational models of blood clot formation: A systematic review.

Mathematical biosciences and engineering : MBE·2025
Same author

Mapping Thrombosis Serum Markers by <sup>1</sup>H-NMR Allied with Machine Learning Tools.

Molecules (Basel, Switzerland)·2025

Related Experiment Video

Updated: Jan 1, 2026

A Multicenter MRI Protocol for the Evaluation and Quantification of Deep Vein Thrombosis
10:26

A Multicenter MRI Protocol for the Evaluation and Quantification of Deep Vein Thrombosis

Published on: June 2, 2015

17.8K

Principal Component Analysis on Recurrent Venous Thromboembolism.

Tiago D Martins1,2, Joyce M Annichino-Bizzacchi3, Anna V C Romano3

  • 1School of Chemical Engineering, University of Campinas, Campinas, Brazil.

Clinical and Applied Thrombosis/Hemostasis : Official Journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
|December 21, 2019
PubMed
Summary

Identifying predictors for recurrent venous thromboembolism (RVTE) is crucial. This study found that simple clinical factors, like blood counts and age, can effectively predict RVTE risk.

Keywords:
embolism and thrombosismultivariate analysisprincipal component analysisrecurrencestatistics

More Related Videos

Point-Of-Care Ultrasound Screening for Proximal Lower Extremity Deep Venous Thrombosis
06:45

Point-Of-Care Ultrasound Screening for Proximal Lower Extremity Deep Venous Thrombosis

Published on: February 10, 2023

15.6K
Electrolytic Inferior Vena Cava Model EIM of Venous Thrombosis
06:03

Electrolytic Inferior Vena Cava Model EIM of Venous Thrombosis

Published on: July 12, 2011

17.6K

Related Experiment Videos

Last Updated: Jan 1, 2026

A Multicenter MRI Protocol for the Evaluation and Quantification of Deep Vein Thrombosis
10:26

A Multicenter MRI Protocol for the Evaluation and Quantification of Deep Vein Thrombosis

Published on: June 2, 2015

17.8K
Point-Of-Care Ultrasound Screening for Proximal Lower Extremity Deep Venous Thrombosis
06:45

Point-Of-Care Ultrasound Screening for Proximal Lower Extremity Deep Venous Thrombosis

Published on: February 10, 2023

15.6K
Electrolytic Inferior Vena Cava Model EIM of Venous Thrombosis
06:03

Electrolytic Inferior Vena Cava Model EIM of Venous Thrombosis

Published on: July 12, 2011

17.6K

Area of Science:

  • Cardiology
  • Hematology
  • Medical Statistics

Background:

  • Recurrent venous thromboembolism (RVTE) rates vary significantly, with underlying causes requiring further investigation.
  • Multivariate statistical methods are essential for identifying disease predictors and refining risk assessment tools.

Purpose of the Study:

  • To apply principal component analysis (PCA) to clinical data of patients with prior venous thromboembolism (VTE).
  • To identify key factors predicting recurrent thrombosis (RVTE).

Main Methods:

  • Collected data on 39 factors from 235 patients, including blood/lipid parameters, thrombophilia, antiphospholipid syndrome, VTE history, treatment, and Doppler ultrasound.
  • Utilized principal component analysis (PCA) to analyze the dataset and extract significant predictive factors for RVTE.

Main Results:

  • 13 principal components were associated with RVTE.
  • 18 of the 39 analyzed factors were identified as important predictors of RVTE.
  • Key predictive factors include red blood cell count, white blood cell count, hematocrit, red cell distribution width, glucose, lipids, natural anticoagulants, creatinine, age, and initial deep vein thrombosis (DVT) characteristics (e.g., location, d-dimer levels, anticoagulation duration).

Conclusions:

  • Simple, easily obtainable clinical parameters can predict RVTE rates.
  • These findings can inform the development of novel clinical decision support systems for predicting RVTE risk.