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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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| DOACT algorithm | Experimental | Use of DOACT algorithm (Dose-Oriented Anticoagulant Calculator for Evidence-Based Decision Tool) to recommend appropriate oral anticoagulant regimens. |
|
| No algorithm | Placebo Comparator | Standard clinical decision-making to recommend appropriate oral anticoagulant regimens. |
|
| LLM-based tools | Active Comparator | Use of large language model (LLM)-based tools to recommend appropriate oral anticoagulant regimens. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| DOACT algorithm | Other | 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). |
| Measure | Description | Time Frame |
|---|---|---|
| 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. | 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. | Day 1 |
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| Measure | Description | Time Frame |
|---|---|---|
| 1. Identification of key clinical elements 2.Response time | Correct reporting of dosing adjustments, renal criteria, bleeding risks, reversal agents, and contraindications. Description: Time (seconds) from prompt submission to full answer generation for LLMs, and time to completion for physicians. | Day 1 |
Inclusion Criteria
Exclusion Criteria
Large Language Models (LLMs)
Exclusion Criteria
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Irmandade da Santa Casa de Misericórdia de São Paulo | São Paulo | São Paulo | 01.223-001 | Brazil |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 31168834 | Background | 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. | |
| 29973392 |
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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.
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Single-blind. Investigator was blinded to the intervention assignment.
|
| No algorithm | Other | 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 tools | Other | 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). |
|
| Vinogradova 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. |
| 24444650 | Background | Nielsen 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. |
| 33334670 | Background | Kakkos 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. |
| ID | Term |
|---|---|
| D020246 | Venous Thrombosis |
| D011655 | Pulmonary Embolism |
| D013927 | Thrombosis |
| ID | Term |
|---|---|
| D016769 | Embolism and Thrombosis |
| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |
| D004617 | Embolism |
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