PAIN (Pain AI iNtervention) Platform for Patients at Home

Development of the PAIN (Pain AI iNtervention) Platform for Patients at Home

The purpose of this research is to identify physiological markers to determine pain intensity and build an Artificial Intelligence (AI) enabled system to objectively measure pain intensity. Researchers hope to personalize pain medication regimens to help prevent medication over-use.

Study Overview

• Status: Enrolling by invitation
• Conditions: Pain
• Intervention / Treatment: Other: Machine learning algorithms

• Study Type: Observational
• Enrollment (Estimated): 70

Contacts and Locations

Study Locations

• United States
  • Florida
    • Jacksonville, Florida, United States, 32224
      • Mayo Clinic Florida

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 16 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: N/A

• Sampling Method: Non-Probability Sample

Study Population

Patients aged 18 or older undergoing low-risk outpatient plastic surgery procedures with expected pain intensities ranging from mild to severe will be included in the study.

Description

Inclusion Criteria:

• Patients undergoing low-risk outpatient plastic surgery procedures with expected pain intensities ranging from mild to severe.

Exclusion Criteria:

• Patients with treated or untreated cardiopulmonary syndromes.
• Patients with treated or untreated ophthalmologic pathologies.
• Patients with skin pathologies that prevent us from using the TENS device.
• Patients with pathologies or conditions preventing them from appropriately using their voice.
• Patients with barriers to effective communication.
• Patients with poor digital literacy.
• Patients incapable of taking oral medication.
• Patients who are currently taking medical therapy for chronic pain.
• Patients with a previous diagnosis of severe anxiety disorders.
• Patients who are immobile at baseline.

Study Plan

How is the study designed?

Design Details

• Observational Models: Cohort
• Time Perspectives: Prospective

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Post-Surgery data collection system; Subjects undergoing standard of care low-risk plastic surgery be provided with wearable sensors to take home and start recording heart rate, body temperature and body movements	Other: Machine learning algorithms; Machine learning techniques to rank order physiologic variables obtained via the wearable and handheld devices as well as remove low-importance and redundant variables to accurately determine postoperative pain intensity in outpatients; Other Names: Artificial Intelligence (AI) enabled system

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Using machine Learning for Postoperative Pain Pain Prediction	The primary outcome will be the accuracy of machine learning algorithms for postoperative pain prediction using root mean square errors.	8 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Physiologic variable %Δ defining the physiologic biomarker's change in measurements after pain medication	The secondary outcome will be the physiologic variable's use to define the physiologic biomarker's change in measurements after pain medication (%Δ in signal's respective units).	8 months
Physiologic variable absolute Δ defining the physiologic biomarker's change in measurements after pain medication	The secondary outcome will be the physiologic variable's use to define the physiologic biomarker's change in measurements after pain medication (absolute Δ in signal's respective units).	8 months

Collaborators and Investigators

• Sponsor: Mayo Clinic
• Investigators: Principal Investigator: Antonio Forte, MD, PhD, Mayo Clinic

Publications and helpful links

Helpful Links

• Mayo Clinic Clinical Trials

Study record dates

Study Major Dates

• Study Start (Actual): November 23, 2022
• Primary Completion (Estimated): November 1, 2024
• Study Completion (Estimated): November 1, 2025

Study Registration Dates

• First Submitted: July 22, 2022
• First Submitted That Met QC Criteria: July 25, 2022
• First Posted (Actual): July 26, 2022

Study Record Updates

• Last Update Posted (Actual): November 8, 2023
• Last Update Submitted That Met QC Criteria: November 6, 2023
• Last Verified: November 1, 2023

More Information

Terms related to this study

• Keywords: Physiological markers for pain intensity; AI to objectively measure pain intensity; Medication over-use
• Other Study ID Numbers: 21-013443

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