Evaluation of an App Based on Artificial Intelligence for Pain Assessment in Pediatric Department

NCT ID: NCT05527600

Last Updated: 2024-01-12

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 2500 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2023-03-07
• Study Completion Date: 2023-09-12

Brief Summary

Accurate assessment of pain in Pediatric Department is challenging. However, recent publications highlight that children do not receive optimal pain management, particularly in Emergency Departments.

An Artificial Intelligence-based tool could help physicians to optimize analgesia use.

Detailed Description

Acute pain is the reason that the majority of patients present to the Emergency Department. Multiple studies conducted over many years have demonstrated that pain is poorly managed in the Emergency Department. This phenomenon has been referred to in the Medical Literature as "Oligoanalgesia.". Morever, untreated pain can have short and long term effects in Pediatric population, including sensitisation to pain episodes in later life and can affects the Neurodevelopment of the child.

The generally accepted standard for pain assessment is self-reported; however, in preverbal children who cannot communicate their pain, age-appropriate behavioural or observational pain assessment tools are recommended. Because children are not always able to voice their feelings, they completely depend on their caregiving team for the interpretation and management of their pain and discomfort. Thus, accurately validated scales to assess pain levels are crucial. In France, the EVENDOL is the most used widely scale. The EVENDOL scale (from the French Evaluation Enfant Douleur) is used to evaluate pain in children in any situation covering a wider age group than other pain scales (birth up to seven years). Despite a large number of scales with a variety of Psychometric properties having been published in the last decades, to date, there is no criterion standard when considering the assessment of pain. As a result, children continue to be suffered pain without adequate pain management. International guidelines incorporate the need for prompt recognition of pain.

Artificial Intelligence (AI) in Medicine is booming and has already proven its worth in terms of prevention, monitoring and diagnosis. AI in this field can be used to support clinician decision making, allow curiosity-driven care, remove the need to complete mundane tasks, improve communication, and facilitate collaboration. Evaluation of the face is central to all observational pain assessment tools, as the face is highly accessible and facial expressions are considered the most encodable feature of pain Therefore.the investigators aim to develop, validate and asses a system based on Digital Face Recognitation for pain assessment in the Children's Department.

Conditions

C23.888.592.612.081

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

assessment of pain in Pediatric Department

2000 children patients admitted in emmergency department

intensity of acute pain evaluation

Intervention Type: DIAGNOSTIC_TEST

the facial expression of each patient will be collected from a short video of 10 seconds, follow by with the evaluation of the pain intensity.

Interventions

intensity of acute pain evaluation

the facial expression of each patient will be collected from a short video of 10 seconds, follow by with the evaluation of the pain intensity.

Intervention Type: DIAGNOSTIC_TEST

Eligibility Criteria

Inclusion Criteria

• Child under 18
• Informed and written consent of a parent or guardian (only 1 accompanying person allowed).

Exclusion Criteria

• Language barrier.
• Refusal to participate by parents/children
• Sign of collapsus, or in serious clinical condition (stage I or II) requiring absolute emergency care,
• Delayed mental or staturo-ponderal development
• Facial injury or wound, presence of a bandage on the face, pre-existing facial deformity

• Minimum Eligible Age: 0 Days
• Maximum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Centre Hospitalier Universitaire de Nice

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

CHU de Nice

Nice, CHU de NICE, France

Hopital pédiatrique Fondation Lenval

Nice, , France

Countries

France

Other Identifiers

2021-A02726-35

Identifier Type: OTHER

Identifier Source: secondary_id

21-PP-16

Identifier Type: -

Identifier Source: org_study_id