Systematic Machine Learning Algorithm for Rapid Thrombosis Detection

Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18+
SponsorOstfold Hospital Trust

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.

Eligibility criteria

Qualifiers

Patients referred to the ED due to suspicion of DVT

Age ≥ 18 years

Able to give informed consent

Disqualifiers

Ongoing use of anticoagulation for more than 72 hours

Previous participation in the study

Life expectancy of less than three months.

Trial design

Treatments tested in this trial

  • POC D-dimer
  • POC ultrasound
  • Machine learning model

Treatment groups

1,000 Participants
are divided into 1 treatment group

Sponsors and collaborators

Ostfold Hospital Trust

Lead sponsor

Sahlgrenska University Hospital

Collaborator