Using machine learning to quickly detect deep vein thrombosis

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This clinical trial aims to evaluate the effectiveness of a machine learning algorithm combined with point-of-care D-dimer testing and ultrasound in excluding deep vein thrombosis (DVT) in patients suspected of having the condition. Participants will undergo standard diagnostic procedures, including clinical assessment, D-dimer analysis, and ultrasound, while also receiving additional tests with POC D-dimer and ultrasound performed by emergency department physicians. The study will assess whether the machine learning model can accurately predict DVT exclusion without the need for ultrasound in some cases. The goal is to improve diagnostic efficiency and patient outcomes in DVT management.

Why it matters

Who can join: the full rules

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.

Where it's running

• Østfold Hospital Trust
  Sarpsborg, Norway Recruiting

Study contacts

• Study coordinator: Waleed Ghanima, Professor
• Email: waleed.ghanima@so-hf.no
• Phone: 69860000

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How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.