Using machine learning to quickly detect deep vein thrombosis
Evaluating a New Diagnostic Strategy for Suspected DVT Consisting of Point of Care D-dimer, AI-based Prediction Model and Compression Ultrasound
NA · Ostfold Hospital Trust · NCT06842446
This study is testing if a new machine learning tool can help doctors quickly rule out deep vein thrombosis in patients without needing an ultrasound every time.
Quick facts
| Phase | NA |
|---|---|
| Study type | Interventional |
| Enrollment | 1000 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Ostfold Hospital Trust (other) |
| Locations | 1 site (Sarpsborg) |
| Trial ID | NCT06842446 on ClinicalTrials.gov |
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.
Who should consider this trial
Good fit: Ideal candidates for this study are adults aged 18 and older who are referred to the emergency department with suspected deep vein thrombosis.
Not a fit: Patients currently on anticoagulation therapy for more than 72 hours or with a life expectancy of less than three months may not benefit from this study.
Why it matters
Potential benefit: If successful, this approach could lead to faster and more accurate diagnosis of deep vein thrombosis, reducing unnecessary procedures and improving patient care.
How similar studies have performed: While the use of machine learning in medical diagnostics is a growing field, this specific approach to DVT detection is relatively novel and has not been extensively tested in prior studies.
Eligibility criteria
Show full inclusion / exclusion criteria
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 this trial is running
Sarpsborg
- Østfold Hospital Trust — Sarpsborg, Norway (RECRUITING)
Study contacts
- Study coordinator: Waleed Ghanima, Professor
- Email: waleed.ghanima@so-hf.no
- Phone: 69860000
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions: Deep Vein Thrombosis, Machine Learning, POC D-dimer, POC Ultrasound