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.

Centre Hospitalier Universitaire de Nīmes300 enrolled

Overview

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.

Study Type

INTERVENTIONAL

Allocation

Purpose

DIAGNOSTIC

Masking

NONE

Enrollment

300

Conditions

Stroke, Cerebrovascular

Interventions

AI-STROKE application

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

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: * Patients who do not speak or read French. * Patient in a period of exclusion determined by another study. * Patient under court protection, guardianship or curatorship. * Pregnant, parturient or breast-feeding patients.

Outcomes

Primary Outcomes

Usable video recording made by the patient

Recording using AI-STROKE application

Time frame: Day 0

Usable video recording made by the hospital worker

Recording using AI-STROKE application

Time frame: Day 0

Secondary Outcomes

Usable video recording made by the patient

Recording using AI-STROKE application

Time frame: Month 3

Usable video recording made by the hospital worker

Recording using AI-STROKE application

Time frame: Month 3

Feasibility of patient self-recording

Patient able to record without assistance: yes/no

Time frame: Day 0

Feasibility of patient self-recording

Patient able to record without assistance: yes/no

Time frame: Month 3

Acceptability of self-recording by patients

Patient accepting to self-record: Yes/no

Time frame: Month 3

Patient-reported ease of self-recording

Visual numerical scale 0-10

Time frame: Day 0

Patient-reported ease of self-recording

Visual numerical scale 0-10

Time frame: Month 3

Stroke severity

NIHSS (National Institute of Health Stroke Scale) score assessed by neurologist

Time frame: Day 0

Stroke severity

NIHSS (National Institute of Health Stroke Scale) score assessed by neurologist

Time frame: Month 3

Degree of disability following stroke

mRS (modified Rankin Scale) score, range 0 (no symptoms) to 5 (severe handicap) administered by the neurologist

Time frame: Day 0

Degree of disability following stroke

mRS (modified Rankin Scale) score, range 0 (no symptoms) to 5 (severe handicap) administered by the neurologist

Time frame: Month 3

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.

Overview

Conditions

Interventions

Eligibility

Locations (1)

Outcomes

Primary Outcomes

Secondary Outcomes

Central Contacts