Clinical Development of a Tool for Optimized Self- and Hetero-diagnosis of Stroke Using Artificial Intelligence: Stage1- Collection of Video-clinical Data in a Pragmatic Situation. (PREDISTROKE)

Centre Hospitalier Universitaire de Nīmes

Status

Enrolling

Conditions

Stroke, Cerebrovascular

Treatments

Other: AI-STROKE application

Study type

Interventional

Funder types

Other

Identifiers

NCT05959746

CIVI/2022/ET-01

Details and patient eligibility

About

The study authors aim to form a collection of video-clinical data in a pragmatic situation to enable the development of relevant AI algorithms (for both hetero- and self-diagnosis modes). The aim is to optimize management through early diagnosis (self- and hetero-diagnosis) and thus to reduce sequelae disability.

The study authors hypothesize that some stroke patients will be able to successfully perform a self-test consisting of a few exercises dictated by an application on a smartphone or tablet and recorded on video.

Enrollment

300 estimated patients

Sex

All

Ages

18+ years old

Volunteers

No Healthy Volunteers

Inclusion criteria

Patients treated in the emergency department or hospitalized in the NICU at the CHU de Nîmes for suspected stroke or transient ischemic attack in the acute phase (<72h), with or without motor deficit
Patient to be seen again in consultation within 4 months
Patient has given free and informed consent and signed the consent form. If the patient is not in a position to give consent, it must be obtained, prior to filming the first video, from the designated trusted support person or relatives present. In this case, data will not be used until the patient is able to sign the consent (CNIL).
Patient affiliated or beneficiary of a health insurance scheme

Exclusion criteria