DOACTDOACT Algorithm vs. AI-Based Models in Oral Anticoagulant Therapy Accuracy
This study aims to compare the accuracy of the DOACT Algorithm and AI-Based Models in managing oral anticoagulant therapy, to provide better supportive care.
DOACT algorithm
+ No algorithm
+ LLM-based tools
Cardiovascular Diseases+6
+ Embolism
+ Lung Diseases
Supportive Care Study
Summary
Study start date: January 20, 2025
Actual date on which the first participant was enrolled.This study focuses on comparing the performance of the DOACT algorithm to other decision-making tools in managing oral anticoagulant therapy for vascular patients. The DOACT algorithm is a new method designed to help doctors make decisions about blood-thinning medications. This research involves a broad analysis, looking at how well the DOACT algorithm stacks up against traditional clinical decision-making and large language model-based decision tools. The ultimate goal is to improve supportive care for patients with vascular conditions who require oral anticoagulant therapy. In this study, participants' data will be evaluated using three different methods: the DOACT algorithm, standard clinical decision-making, and large language model-based decision tools. The study aims to measure the accuracy and clinical utility of each method. This means researchers will assess how well each approach predicts the best treatment decisions and how useful these predictions are in a real-world clinical setting. The study does not mention any specific risks or benefits associated with participation.
Protocol
This section provides details of the study plan, including how the study is designed and what the study is measuring.59 patients to be enrolled
Total number of participants that the clinical trial aims to recruit.Supportive Care Study
Eligibility
Researchers look for people who fit a certain description, called eligibility criteria: person's general health condition or prior treatments.Any sex
Biological sex of participants that are eligible to enroll.From 18 to 89 Years
Range of ages for which participants are eligible to join.Healthy volunteers allowed
If individuals who are healthy and do not have the condition being studied can participate.Conditions
Pathology
Criteria
Inclusion Criteria * 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. Exclusion Criteria * 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) * Inclusion Criteria * 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. Exclusion Criteria * Paid or subscription-based LLMs. * LLMs requiring institutional licenses, restricted access, or proprietary tokens. * Models unable to generate full responses to the standardized prompt.
Study Plan
Find out more about all the medication administered in this study, their detailed description and what they involve.3 intervention groups are designated in this study
33.333% chance of being blinded to the placebo group
Treatment Groups
Group I
ExperimentalGroup II
PlaceboGroup III
Active ComparatorStudy Centers
These are the hospitals, clinics, or research facilities where the trial is being conducted. You can find the location closest to you and its status.This study has 1 location
Irmandade da Santa Casa de Misericórdia de São Paulo
São Paulo, BrazilOpen Irmandade da Santa Casa de Misericórdia de São Paulo in Google Maps