Evaluation of an App Based on Artificial Intelligence for Pain Assessment in Pediatric Department (DEF II)

Development and Validation of a System Based on Digital Face Recognitation for Pain Assessment in Children's Emergency

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.

Study Overview

• Status: Completed
• Conditions: C23.888.592.612.081
• Intervention / Treatment: Diagnostic test: intensity of acute pain evaluation

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.

• Study Type: Observational
• Enrollment (Actual): 2500

Contacts and Locations

Study Locations

• France
  • Nice, France, 06000
    • Hopital pédiatrique Fondation Lenval
    • Principal Investigator: Antoine TRAN
  • Chu de Nice
    • Nice, Chu de Nice, France, 06003
      • CHU de Nice

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 1 second to 18 years (Child, Adult)
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

2000 patients under 18 year old admitted in Emergency Department

Description

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

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
assessment of pain in Pediatric Department; 2000 children patients admitted in emmergency department	Diagnostic test: 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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
assessment of The intensity of acute pain with the EVENDOL Scale	The intensity of acute pain will be assessed by the current reference French methods for evaluating pain in children with the EVENDOL Scale (reference between 0 and 7 years).	day 0
assessment of The intensity of acute pain with the VAS Scale	The intensity of acute pain will be assessed by the current reference French methods for evaluating pain in children with the VAS Scale (Age > 7 years)	day 0
the facial expression captured by short video	a short 10-second video is collected to assess facial expression of pain in children	day 0

Collaborators and Investigators

• Sponsor: Centre Hospitalier Universitaire de Nice

Study record dates

Study Major Dates

• Study Start (Actual): March 7, 2023
• Primary Completion (Actual): March 7, 2023
• Study Completion (Actual): September 12, 2023

Study Registration Dates

• First Submitted: August 30, 2022
• First Submitted That Met QC Criteria: September 1, 2022
• First Posted (Actual): September 2, 2022

Study Record Updates

• Last Update Posted (Actual): January 12, 2024
• Last Update Submitted That Met QC Criteria: January 11, 2024
• Last Verified: January 1, 2024

More Information

Terms related to this study

• Other Study ID Numbers: 21-PP-16; 2021-A02726-35 (Other Identifier: ANSM)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No