PAIN (Pain AI iNtervention) Platform for Patients at Home

NCT05474274 | Enrolling By Invitation

• 1 other identifier: 21-013443
• Study Type: observational
• Target: 70
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Pain

Keywords

Physiological markers for pain intensity; AI to objectively measure pain intensity; Medication over-use

Outcome Measures

Primary Outcomes (1)

• 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 Outcomes (2)

• Physiologic variable %Δ defining the physiologic biomarker's change in measurements after pain medication

  8 months

• Physiologic variable absolute Δ defining the physiologic biomarker's change in measurements after pain medication

  8 months

Study Arms (1)

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

Interventions

Machine learning algorithms OTHER

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

Also known as: Artificial Intelligence (AI) enabled system

Post-Surgery data collection system

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Age Groups: Adult (18-64), Older Adult (65+)
• 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.

You may qualify if:

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

You may not qualify if:

• 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.

Sponsors & Collaborators

• Mayo Clinic: lead

Study Sites (1)

Mayo Clinic Florida

Jacksonville, Florida, 32224, United States

Location

Related Links

• Mayo Clinic Clinical Trials

MeSH Terms

Conditions

Pain

Interventions

Machine Learning Algorithms; Artificial Intelligence

Condition Hierarchy (Ancestors)

Neurologic Manifestations; Signs and Symptoms; Pathological Conditions, Signs and Symptoms

Intervention Hierarchy (Ancestors)

Algorithms; Mathematical Concepts

Study Officials

• Antonio Forte, MD, PhD

  Mayo Clinic

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: July 22, 2022
• First Posted: July 26, 2022
• Study Start: November 23, 2022
• Primary Completion (Estimated): November 1, 2026
• Study Completion (Estimated): November 1, 2027
• Last Updated: December 22, 2025

Record last verified: 2025-12

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)