NCT05474274
PAIN (Pain AI iNtervention) Platform for Patients at Home
Enrolling by Invitation
Not specifiedAges 18+ObservationalMayo ClinicInvestigator-initiated
~70 participants
Updated 2025-12-22 on ClinicalTrials.gov
What's tested:Machine learning algorithms
At a glance
Recruiting sites
0 of 1 listed site is recruiting right now
RecruitingSuspended, closed, or not yet open
What they're measuring
Using machine Learning for Postoperative Pain Pain Prediction
Measured over 8 months
Conditions
Where it's being run
1 sites across 1 statesFlorida1
Study leadership
- Antonio Forte, MD, PhD · PRINCIPAL_INVESTIGATOR · Mayo Clinic
Who to contact
This trial hasn't published a contact. View it on ClinicalTrials.gov
Do you actually qualify for this trial?
Add a private profile and we'll compare every criterion below against your situation — and tell you which ones are met, uncertain, or excluding.
Eligibility criteria
Inclusion
Patients undergoing low-risk outpatient plastic surgery procedures with expected pain intensities ranging from mild to severe.
Exclusion
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.
What this trial measures
- Using machine Learning for Postoperative Pain Pain Prediction8 months
The primary outcome will be the accuracy of machine learning algorithms for postoperative pain prediction using root mean square errors.