Systematic Machine Learning Algorithm for Rapid Thrombosis Detection

Recruiting now · Not applicable

Conditions studied: Deep Vein Thrombosis

In brief

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.

Key facts

Study ID

NCT06842446

Run by

Ostfold Hospital Trust

People needed

1000

Starts

2025-01-06

Expected to finish

2029-01-05

Last updated by the study team

2025-02-26

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• Patients referred to the ED due to suspicion of DVT
• Age ≥ 18 years
• Able to give informed consent

You may not qualify if…

• Ongoing use of anticoagulation for more than 72 hours
• Previous participation in the study
• Life expectancy of less than three months.

Where it is running

• Østfold Hospital Trust — Sarpsborg, Norway (enrolling)

Full record on ClinicalTrials.gov

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