Deep Vein ThrombosisDOACTNCT07290608
DOACT Algorithm Versus AI-Based Decision Models in Oral Anticoagulant Therapy for Vascular Patients
A study testing DOACT algorithm, No algorithm and LLM-based tools in people with Deep Vein Thrombosis and Superficial Thrombophlebitis, run by ITALO EUGENIO SOUZA GADELHA DE ABREU at 1 site in Brazil.
Trial summary
Study using a decision algorithm for the application of an oral anticoagulant calculator in vascular diseases, aimed at validating a clinical decision-support tool for conditions such as deep vein thrombosis, superficial thrombophlebitis, and pulmonary thromboembolism. Read more about this study
- Who is it for?
- Ages 18 to 89 yearsHealthy volunteers can take part
- Conditions the study is for
- Deep Vein Thrombosis, Superficial Thrombophlebitis, Pulmonary Thromboembolisms
- What is being tested?
- DOACT algorithm, No algorithm and LLM-based tools
- Type of treatment
- Pill or oral medicine
- Could I receive a placebo?
- Yes, some participants may receive a placebo
- How many people
- 59 participants
- Where
- 1 siteBrazil
- Study dates
- 20 Jan 2025to 10 Oct 2025
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 89 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Physicians with residency training in Vascular Surgery or official Board Certification in Vascular Surgery.
- Currently practicing clinical and/or surgical vascular care in Brazil.
- Completed the informed consent process (TCLE) and voluntarily agreed to participate.
- Free-access LLMs available to the public at the time of data collection.
- All responses generated using the same standardized prompt.
- Capable of producing complete, text-based clinical answers relevant to vascular surgery decision-making.
Who cannot join
- Physicians without formal Vascular Surgery residency and without Board Certification.
- Physicians not performing vascular clinical or surgical care (e.g., exclusively administrative, academic, or non-assistance roles).
- Less than 1 year of professional experience after medical school graduation.
- Did not sign or did not fully complete the TCLE.
- Large Language Models (LLMs)
- Paid or subscription-based LLMs.
- LLMs requiring institutional licenses, restricted access, or proprietary tokens.
- Models unable to generate full responses to the standardized prompt.
Trial locations and contacts
1 site in 1 country.
Brazil1 site
Irmandade da Santa Casa de Misericórdia de São Paulo
São Paulo, São Paulo, 01.223-001
About this study
Official title: Clinical Performance of the DOACT Algorithm Versus AI-Based Decision Models in Oral Anticoagulant Therapy for Vascular Patients
Study using a decision algorithm for the application of an oral anticoagulant calculator in vascular diseases, aimed at validating a clinical decision-support tool for conditions such as deep vein thrombosis, superficial thrombophlebitis, and pulmonary thromboembolism.
Read the detailed description
Cross-sectional, three-arm comparative validation study evaluating the accuracy and clinical utility of the DOACT algorithm versus standard clinical decision-making and large language model (LLM)-based decision tools.
- Conditions
- Deep Vein Thrombosis, Superficial Thrombophlebitis, Pulmonary Thromboembolisms, Clinical Decision Support Systems, Artificial Intelligence
- Being tested
- DOACT algorithm, No algorithm, LLM-based tools
- Keywords
- anticoagulant, algorithm, thrombosis
- Medical subject headings
- Venous Thrombosis, Pulmonary Embolism, Thrombosis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
DOACT algorithmOther
Vascular and non-vascular physicians using DOACT (Dose-Oriented Anticoagulant Calculator for Evidence-Based Decision Tool) to recommend appropriate oral anticoagulant regimens-dose selection and duration responding 15 standardized clinical case vignettes representing patients with vascular diseases such as deep vein thrombosis (DVT), superficial thrombophlebitis, and pulmonary thromboembolism (PTE).
No algorithmOther
Vascular and non-vascular physicians using standard clinical decision-making (no use of algorithm) to recommend appropriate oral anticoagulant regimens-dose selection and duration responding 15 standardized clinical case vignettes representing patients with vascular diseases such as deep vein thrombosis (DVT), superficial thrombophlebitis, and pulmonary thromboembolism (PTE).
LLM-based toolsOther
Vascular and non-vascular physicians using large language model (LLM)-based tools to recommend appropriate oral anticoagulant regimens-dose selection and duration responding 15 standardized clinical case vignettes representing patients with vascular diseases such as deep vein thrombosis (DVT), superficial thrombophlebitis, and pulmonary thromboembolism (PTE).
| Study group | Role | What they receive |
|---|---|---|
| DOACT algorithm | Experimental | Use of DOACT algorithm (Dose-Oriented Anticoagulant Calculator for Evidence-Based Decision Tool) to recommend appropriate oral anticoagulant regimens. Receives: Other: DOACT algorithm |
| No algorithm | Placebo comparator | Standard clinical decision-making to recommend appropriate oral anticoagulant regimens. Receives: Other: No algorithm |
| LLM-based tools | Active comparator | Use of large language model (LLM)-based tools to recommend appropriate oral anticoagulant regimens. Receives: Other: LLM-based tools |
What is being measured
The primary outcome is the main question the study is designed to answer.
Accuracy of the DOACT Algorithm in Guiding Oral Anticoagulant Therapy
Accuracy of anticoagulation recommendations
Description: Proportion of correct responses generated by the four evaluated LLMs, vascular surgeons, and non-vascular physicians, with and without access to the DOACT algorithm, using standardized clinical vignettes.
Measured: Day 1
Accuracy of anticoagulation recommendations
Proportion of correct responses generated by LLMs, vascular surgeons, and non-vascular physicians with and without access to the DOACT algorithm. All LLM outputs will be generated using the same standardized prompt, following methodological guidance recommended by IBM for evaluating large language models.
Measured: Day 1
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted18 Dec 2025
- Study start20 Jan 2025
- Primary completion10 Oct 2025
- Study completion10 Oct 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (4)Papers the sponsor has linked to this study.
- Other trials for Deep Vein ThrombosisStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- Three-arm comparative validation study evaluating the accuracy and clinical utility of the DOACT algorithm versus standard clinical decision-making and large language model (LLM)-based decision tools.
- Masking
- Single blind
- Who is masked
- Investigator
- Enrolment
- 59 participants (actual)
Sponsor and investigators
- Lead sponsor
- ITALO EUGENIO SOUZA GADELHA DE ABREU
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, ITALO EUGENIO SOUZA GADELHA DE ABREU, Science Valley Research Institute
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07290608
- Sponsor's protocol ID
- DOACT-AI-VASC Study
- Acronym
- DOACT
- Status last verified
- Dec 2025
- First submitted
- 24 Nov 2025
- Last updated
- 18 Dec 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Gee E. The National VTE Exemplar Centres Network response to implementation of updated NICE guidance: venous thromboembolism in over 16s: reducing the risk of hospital-acquired deep vein thrombosis or pulmonary embolism (NG89). Br J Haematol. 2019 Sep;186(5):792-793. doi: 10.1111/bjh.16010. Epub 2019 Jun 5. No abstract available.
PubMed 31168834Vinogradova Y, Coupland C, Hill T, Hippisley-Cox J. Risks and benefits of direct oral anticoagulants versus warfarin in a real world setting: cohort study in primary care. BMJ. 2018 Jul 4;362:k2505. doi: 10.1136/bmj.k2505.
PubMed 29973392Nielsen PB, Lundbye-Christensen S, Rasmussen LH, Larsen TB. Improvement of anticoagulant treatment using a dynamic decision support algorithm: a Danish Cohort study. Thromb Res. 2014 Mar;133(3):375-9. doi: 10.1016/j.thromres.2013.12.042. Epub 2014 Jan 7.
PubMed 24444650Kakkos SK, Gohel M, Baekgaard N, Bauersachs R, Bellmunt-Montoya S, Black SA, Ten Cate-Hoek AJ, Elalamy I, Enzmann FK, Geroulakos G, Gottsater A, Hunt BJ, Mansilha A, Nicolaides AN, Sandset PM, Stansby G, Esvs Guidelines Committee, de Borst GJ, Bastos Goncalves F, Chakfe N, Hinchliffe R, Kolh P, Koncar I, Lindholt JS, Tulamo R, Twine CP, Vermassen F, Wanhainen A, Document Reviewers, De Maeseneer MG, Comerota AJ, Gloviczki P, Kruip MJHA, Monreal M, Prandoni P, Vega de Ceniga M. Editor's Choice - European Society for Vascular Surgery (ESVS) 2021 Clinical Practice Guidelines on the Management of Venous Thrombosis. Eur J Vasc Endovasc Surg. 2021 Jan;61(1):9-82. doi: 10.1016/j.ejvs.2020.09.023. Epub 2020 Dec 15. No abstract available.
PubMed 33334670
Study at a glance
From the registry record, last updated by the sponsor on 18 Dec 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Clinical Performance of the DOACT Algorithm Versus AI-Based Decision Models in Oral Anticoagulant Therapy for Vascular Patients
- ClinicalTrials.gov ID
- NCT07290608
- Acronym / sponsor ID
- DOACT / DOACT-AI-VASC Study
- Conditions
- Deep Vein Thrombosis, Superficial Thrombophlebitis, Pulmonary Thromboembolisms, Clinical Decision Support Systems, Artificial Intelligence
- Keywords
- anticoagulant, algorithm, thrombosis
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 59 participants (actual)
- Lead sponsor
- ITALO EUGENIO SOUZA GADELHA DE ABREUUniversity, hospital or other
- Study start
- 20 Jan 2025 (actual)
- Primary completion
- 10 Oct 2025 (actual)
- Study completion
- 10 Oct 2025 (actual)
- First posted
- 18 Dec 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Study using a decision algorithm for the application of an oral anticoagulant calculator in vascular diseases, aimed at validating a clinical decision-support tool for conditions such as deep vein thrombosis, superficial thrombophlebitis, and pulmonary thromboembolism.
Detailed description
Cross-sectional, three-arm comparative validation study evaluating the accuracy and clinical utility of the DOACT algorithm versus standard clinical decision-making and large language model (LLM)-based decision tools.
Study design
- Primary purpose
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (investigator)
- Number of arms
- 3
- Model description
- Three-arm comparative validation study evaluating the accuracy and clinical utility of the DOACT algorithm versus standard clinical decision-making and large language model (LLM)-based decision tools.
| Arm | Type | Receives |
|---|---|---|
| DOACT algorithm | Experimental | Other: DOACT algorithmUse of DOACT algorithm (Dose-Oriented Anticoagulant Calculator for Evidence-Based Decision Tool) to recommend appropriate oral anticoagulant regimens. |
| No algorithm | Placebo comparator | Other: No algorithmStandard clinical decision-making to recommend appropriate oral anticoagulant regimens. |
| LLM-based tools | Active comparator | Other: LLM-based toolsUse of large language model (LLM)-based tools to recommend appropriate oral anticoagulant regimens. |
Who may qualify
- Ages
- 18 to 89 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (6 listed)
- Physicians with residency training in Vascular Surgery or official Board Certification in Vascular Surgery.
- Currently practicing clinical and/or surgical vascular care in Brazil.
- Completed the informed consent process (TCLE) and voluntarily agreed to participate.
- Free-access LLMs available to the public at the time of data collection.
- All responses generated using the same standardized prompt.
Key exclusion criteria (8 listed)
- Physicians without formal Vascular Surgery residency and without Board Certification.
- Physicians not performing vascular clinical or surgical care (e.g., exclusively administrative, academic, or non-assistance roles).
- Less than 1 year of professional experience after medical school graduation.
- Did not sign or did not fully complete the TCLE.
- Large Language Models (LLMs)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| DOACT algorithmVascular and non-vascular physicians using DOACT (Dose-Oriented Anticoagulant Calculator for Evidence-Based Decision Tool) to recommend appropriate oral anticoagulant regimens-dose selection and duration responding 15 standardized clinical case vignettes representing patients with vascular diseases such as deep vein thrombosis (DVT), superficial thrombophlebitis, and pulmonary thromboembolism (PTE). | Other | DOACT algorithm |
| No algorithmVascular and non-vascular physicians using standard clinical decision-making (no use of algorithm) to recommend appropriate oral anticoagulant regimens-dose selection and duration responding 15 standardized clinical case vignettes representing patients with vascular diseases such as deep vein thrombosis (DVT), superficial thrombophlebitis, and pulmonary thromboembolism (PTE). | Other | No algorithm |
| LLM-based toolsVascular and non-vascular physicians using large language model (LLM)-based tools to recommend appropriate oral anticoagulant regimens-dose selection and duration responding 15 standardized clinical case vignettes representing patients with vascular diseases such as deep vein thrombosis (DVT), superficial thrombophlebitis, and pulmonary thromboembolism (PTE). | Other | LLM-based tools |
Primary outcome
Accuracy of the DOACT Algorithm in Guiding Oral Anticoagulant Therapy
Time frame: Day 1
Accuracy of anticoagulation recommendations Description: Proportion of correct responses generated by the four evaluated LLMs, vascular surgeons, and non-vascular physicians, with and without access to the DOACT algorithm, using standardized clinical vignettes.
Accuracy of anticoagulation recommendations
Time frame: Day 1
Proportion of correct responses generated by LLMs, vascular surgeons, and non-vascular physicians with and without access to the DOACT algorithm. All LLM outputs will be generated using the same standardized prompt, following methodological guidance recommended by IBM for evaluating large language models.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 18 Dec 2025.
- Background: PubMed 31168834Gee E. The National VTE Exemplar Centres Network response to implementation of updated NICE guidance: venous thromboembolism in over 16s: reducing the risk of hospital-acquired deep vein thrombosis or pulmonary embolism (NG89). Br J Haematol. 2019 Sep;186(5):792-793. doi: 10.1111/bjh.16010. Epub 2019 Jun 5. No abstract available.
- Background: PubMed 29973392Vinogradova Y, Coupland C, Hill T, Hippisley-Cox J. Risks and benefits of direct oral anticoagulants versus warfarin in a real world setting: cohort study in primary care. BMJ. 2018 Jul 4;362:k2505. doi: 10.1136/bmj.k2505.
- Background: PubMed 24444650Nielsen PB, Lundbye-Christensen S, Rasmussen LH, Larsen TB. Improvement of anticoagulant treatment using a dynamic decision support algorithm: a Danish Cohort study. Thromb Res. 2014 Mar;133(3):375-9. doi: 10.1016/j.thromres.2013.12.042. Epub 2014 Jan 7.
- Background: PubMed 33334670Kakkos SK, Gohel M, Baekgaard N, Bauersachs R, Bellmunt-Montoya S, Black SA, Ten Cate-Hoek AJ, Elalamy I, Enzmann FK, Geroulakos G, Gottsater A, Hunt BJ, Mansilha A, Nicolaides AN, Sandset PM, Stansby G, Esvs Guidelines Committee, de Borst GJ, Bastos Goncalves F, Chakfe N, Hinchliffe R, Kolh P, Koncar I, Lindholt JS, Tulamo R, Twine CP, Vermassen F, Wanhainen A, Document Reviewers, De Maeseneer MG, Comerota AJ, Gloviczki P, Kruip MJHA, Monreal M, Prandoni P, Vega de Ceniga M. Editor's Choice - European Society for Vascular Surgery (ESVS) 2021 Clinical Practice Guidelines on the Management of Venous Thrombosis. Eur J Vasc Endovasc Surg. 2021 Jan;61(1):9-82. doi: 10.1016/j.ejvs.2020.09.023. Epub 2020 Dec 15. No abstract available.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing DOACT algorithm, No algorithm and LLM-based tools in people with Deep Vein Thrombosis and Superficial Thrombophlebitis, run by ITALO EUGENIO SOUZA GADELHA DE ABREU at 1 site in Brazil.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 8 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 18 Dec 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Brazil. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. Some participants in this study may receive a placebo. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accuracy of the DOACT Algorithm in Guiding Oral Anticoagulant Therapy (time frame: Day 1). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07290608, which also lists 4 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 18 Dec 2025.