Clinical trial NCT06334796: Artificial Intelligence-powered Virtual Assistant for Emergency Triage in Neurology
Official title: Phase 1 Trial of the Implementation of an Artificial Intelligence-powered Virtual Assistant for Emergency Triage in Neurology
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: EARLY_PHASE1
Conditions: Stroke
Guillain-Barre Syndrome
Facial Palsy
Migraine
Status Epilepticus
Vertigo Benign Positional
Delirium
Trigeminal Neuralgia
Meningitis
Subarachnoid Hemorrhage
Lead sponsor: Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia
Sponsor class: OTHER
Collaborators: name: Entelai
First posted: 2024-03-28
Enrollment: 10
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NON_RANDOMIZED
Intervention model: SINGLE_GROUP
Intervention model description: The model of this Phase 1 interventional study involves evaluating the diagnostic accuracy and utility of an AI-powered virtual assistant in the triage of emergency neurological conditions. Patients and healthcare professionals interacted with the assistant, providing real-world clinical scenarios to assess its effectiveness. The study's design aimed to demonstrate the assistant's potential to enhance emergency neurological care by comparing its performance with established diagnostic tools and patient outcomes.
Primary purpose: DIAGNOSTIC

Brief summary: This study examines the use of an AI-powered virtual assistant for quickly identifying and handling neurological emergencies, particularly in places with limited medical resources. The research aimed to check if this AI tool is safe and accurate enough to move on to more advanced testing stages. In a first-of-its-kind trial, the virtual assistant was tested with patients having urgent neurological issues. Neurologists first reviewed the AI's recommendations using clinical records and then assessed its performance directly with patients. The findings were as follows: neurologists agreed with the AI's decisions nearly all the time, and the AI outperformed earlier versions of Chat GPT in every tested aspect. Patients and doctors found the AI to be highly effective, rating it as excellent or very good in most cases. This suggests the AI could significantly enhance how quickly and accurately neurological emergencies are dealt with, although further trials are needed before it can be widely used.

Detailed description: Background and Objectives: Neurological emergencies pose significant challenges in medical care, especially in resource-limited countries. Artificial Intelligence (AI), particularly health chatbots, offers a promising solution. However, rigorous validation is required to ensure safety and accuracy. The objective of our work is to evaluate the diagnostic accuracy and resolution effectiveness of an AI-powered virtual assistant designed for the triage of emergency neurological pathologies, to ensure the minimum standard of safety that allows for the progression to successive validation tests.

Methods: This Phase 1 trial evaluates the performance of an AI-powered virtual assistant for emergency neurological triage. Ten patients over 18 years old with urgent neurological pathologies were selected. In the first stage, nine neurologists assessed the safety of the virtual assistant using their clinical records. In the second part, the assistant's accuracy when used by patients was evaluated. Finally, its performance was compared with Chat GPT 3.5 and 4.

Eligibility criteria: Inclusion Criteria:

* Patients over 18 years old consulting in the ER due to a neurological emergency

Exclusion Criteria:

* Pregnancy

Primary outcomes:
measure: Diagnostic performance
timeFrame: The first interaction between participants and the virtual assistant occurred within less than a year after the event. Outcome measures were evaluated immediately after the interaction between patients and the virtual assistant.
Secondary outcomes:
measure: Appropriate medical conduct or recommendation
timeFrame: The first interaction between participants and the virtual assistant occurred within less than a year after the event. Outcome measures were evaluated immediately after the interaction between patients and the virtual assistant.
measure: Assessment of Usability and Satisfaction
timeFrame: The first interaction between participants and the virtual assistant occurred within less than a year after the event. Outcome measures were evaluated immediately after the interaction between patients and the virtual assistant.
Other outcomes:
Locations:
city: Buenos Aires
country: Argentina
facility: Fleni
Study officials:
affiliation: Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia
name: Mauricio F Farez, MD MPH
role: PRINCIPAL_INVESTIGATOR
References:
citation: Haug CJ, Drazen JM. Artificial Intelligence and Machine Learning in Clinical Medicine, 2023. N Engl J Med. 2023 Mar 30;388(13):1201-1208. doi: 10.1056/NEJMra2302038. No abstract available.
citation: Au Yeung J, Wang YY, Kraljevic Z, Teo JTH. Artificial intelligence (AI) for neurologists: do digital neurones dream of electric sheep? Pract Neurol. 2023 Nov 23;23(6):476-488. doi: 10.1136/pn-2023-003757.
citation: Patel UK, Anwar A, Saleem S, Malik P, Rasul B, Patel K, Yao R, Seshadri A, Yousufuddin M, Arumaithurai K. Artificial intelligence as an emerging technology in the current care of neurological disorders. J Neurol. 2021 May;268(5):1623-1642. doi: 10.1007/s00415-019-09518-3. Epub 2019 Aug 26.