NCT07290608

DOACT Algorithm Versus AI-Based Decision Models in Oral Anticoagulant Therapy for Vascular Patients

Clinical Performance of the DOACT Algorithm Versus AI-Based Decision Models in Oral Anticoagulant Therapy for Vascular Patients

• Status: Completed
• Phase: N/A
• Study type: Interventional
• Enrollment: 59 (actual)
• Sponsor: ITALO EUGENIO SOUZA GADELHA DE ABREU · Academic / Other
• Sex: All
• Age: 18 Years – 89 Years
• Healthy volunteers: Accepted

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.

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

Interventions

Type	Name	Description
OTHER	DOACT algorithm	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).
OTHER	No algorithm	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).
OTHER	LLM-based tools	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).

Timeline

• Start date: 2025-01-20
• Primary completion: 2025-10-10
• Completion: 2025-10-10
• First posted: 2025-12-18
• Last updated: 2025-12-18

Locations

1 site across 1 country: Brazil