[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"trial:NCT05474274":3,"trial-entities:NCT05474274":89,"trial-summary:NCT05474274":92},{"id":4,"nct_id":4,"org_study_id":5,"brief_title":6,"official_title":7,"overall_status":8,"completion_date":9,"status_verified_date":10,"last_update_date":11,"start_date":12,"sponsor_name":13,"lead_sponsor_class":14,"has_dmc":15,"brief_summary":16,"detailed_description":17,"conditions":18,"keywords":20,"study_type":24,"primary_purpose":17,"phases":25,"enrollment_info":26,"interventions":29,"primary_outcomes":37,"secondary_outcomes":42,"sex":49,"minimum_age":50,"maximum_age":17,"healthy_volunteers":17,"eligibility_criteria":51,"std_ages":66,"locations":69,"central_contacts":79,"overall_officials":80,"references":84,"see_also_links":85},"NCT05474274","21-013443","PAIN (Pain AI iNtervention) Platform for Patients at Home","Development of the PAIN (Pain AI iNtervention) Platform for Patients at Home","ENROLLING_BY_INVITATION","2027-11","2025-12","2025-12-22","2022-11-23","Mayo Clinic","OTHER",false,"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.",null,[19],"Pain",[21,22,23],"Physiological markers for pain intensity","AI to objectively measure pain intensity","Medication over-use","OBSERVATIONAL",[],{"count":27,"type":28},70,"ESTIMATED",[30],{"type":14,"name":31,"description":32,"armGroupLabels":33,"otherNames":35},"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",[34],"Post-Surgery data collection system",[36],"Artificial Intelligence (AI) enabled system",[38],{"measure":39,"description":40,"timeFrame":41},"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",[43,46],{"measure":44,"description":45,"timeFrame":41},"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).",{"measure":47,"description":48,"timeFrame":41},"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).","ALL","18 Years",{"inclusion":52,"exclusion":54,"raw_text":65},[53],"Patients undergoing low-risk outpatient plastic surgery procedures with expected pain intensities ranging from mild to severe.",[55,56,57,58,59,60,61,62,63,64],"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.","Inclusion Criteria:\n\n* Patients undergoing low-risk outpatient plastic surgery procedures with expected pain intensities ranging from mild to severe.\n\nExclusion Criteria:\n\n* Patients with treated or untreated cardiopulmonary syndromes.\n* Patients with treated or untreated ophthalmologic pathologies.\n* Patients with skin pathologies that prevent us from using the TENS device.\n* Patients with pathologies or conditions preventing them from appropriately using their voice.\n* Patients with barriers to effective communication.\n* Patients with poor digital literacy.\n* Patients incapable of taking oral medication.\n* Patients who are currently taking medical therapy for chronic pain.\n* Patients with a previous diagnosis of severe anxiety disorders.\n* Patients who are immobile at baseline.",[67,68],"ADULT","OLDER_ADULT",[70],{"facility":71,"city":72,"state":73,"zip":74,"country":75,"geoPoint":76},"Mayo Clinic Florida","Jacksonville","Florida","32224","United States",{"lat":77,"lon":78},30.33218,-81.65565,[],[81],{"name":82,"affiliation":13,"role":83},"Antonio Forte, MD, PhD","PRINCIPAL_INVESTIGATOR",[],[86],{"label":87,"url":88},"Mayo Clinic Clinical Trials","https:\u002F\u002Fwww.mayo.edu\u002Fresearch\u002Fclinical-trials",{"nct_id":4,"conditions":90,"biomarkers":91},[19],[],{"nct_id":4,"found":15,"summary":17,"prompt_version":17}]