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RECRUITINGINTERVENTIONAL

Systematic Machine Learning Algorithm for Rapid Thrombosis Detection

Evaluating a New Diagnostic Strategy for Suspected DVT Consisting of Point of Care D-dimer, AI-based Prediction Model and Compression Ultrasound

Important: This information is not medical advice. Talk to your doctor about whether a clinical trial is right for you.

About This Trial

The goal of this clinical trial is to compare the use of a machine learning-based algorithm and point-of-care D-dimer to laboratory D-dimer and compression ultrasound to exclude deep vein thrombosis in the under extremities in patients referred to a medical department suspected of having deep vein thrombosis. The main aim is to answer are if a machine learning algorithm and point of care D-dimer can exclude deep vein thrombosis in more patients than clinical assessment and D-dimer alone.

Who May Be Eligible (Plain English)

Who May Qualify: - Patients referred to the ED due to suspicion of DVT - Age ≥ 18 years - Able to give willing to sign a consent form Who Should NOT Join This Trial: - Ongoing use of anticoagulation for more than 72 hours - Previous participation in the study - Life expectancy of less than three months. Always talk to your doctor about whether this trial is right for you.

Original Eligibility Criteria

View original clinical language
Inclusion Criteria: * Patients referred to the ED due to suspicion of DVT * Age ≥ 18 years * Able to give informed consent Exclusion Criteria: * Ongoing use of anticoagulation for more than 72 hours * Previous participation in the study * Life expectancy of less than three months.

Treatments Being Tested

DIAGNOSTIC_TEST

POC D-dimer

POC D-dimer will be compared to laboratory D-dimer in hospital setting and used in a machine learning model

DIAGNOSTIC_TEST

POC ultrasound

Point of care (POC) ultrasound performed by ED physicians compared to ultrasound performed by radiologist. POC ultrasound 3 point examination performed by ED physician will be compared with POC ultrasound full leg examination performed by ED physician.

DIAGNOSTIC_TEST

Machine learning model

The DSS will be compared to the usual strategy. It will also be estimated how many participants where DVT could have been excluded without ultrasound.

Locations (1)

Østfold Hospital Trust
Sarpsborg, Norway