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Clinical Trial Details — Status: Completed

Administrative data

NCT number NCT05659836
Other study ID # ABT-CIP-10408
Secondary ID
Status Completed
Phase
First received
Last updated
Start date May 27, 2021
Est. completion date June 15, 2023

Study information

Verified date December 2022
Source Abbott Medical Devices
Contact n/a
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

Spinal Cord Stimulation Trial to Permanent Prediction is a prospective, longitudinal, multi-center, non-randomized, multi-arm, open-label, clinical feasibility study designed to investigate whether objective data collected from chronic pain patients is predictive of subjective patient-reported outcomes and of adjustments to patient programming parameters.


Description:

The study will enroll up to 60 subjects at 10 sites in the United States. Follow-up will continue for a period of 6 months post-trial for subjects who choose not to receive a permanently-implanted system as well as 6 months post implant for subjects receiving a permanent implant.


Recruitment information / eligibility

Status Completed
Enrollment 28
Est. completion date June 15, 2023
Est. primary completion date June 15, 2023
Accepts healthy volunteers No
Gender All
Age group 18 Years and older
Eligibility Inclusion Criteria: 1. Subject must provide written informed consent prior to any clinical investigation-related procedure. 2. Subject is at least 18 years of age or older at the time of enrollment. 3. Subject is scheduled to undergo trial of an Abbott neuromodulation system for chronic intractable pain at least 7 days after enrollment and commencement of the baseline data collection period. 4. Subject's scheduled trial duration for the Abbott neuromodulation system is at least 3 days. 5. Subject has a baseline (with no stimulation) pain NRS of = 6. 6. Subject is willing to cooperate with the study requirements including completion of all office visits. 7. Subject agrees to wear the wearable sensing devices (Anne™ patch, Anne™ limb unit, Apple watch®, and Oura™ Ring). 8. Subject agrees to answer questionnaires regularly for the duration of the study. Exclusion Criteria: 1. Subject is enrolled, or intends to participate, in a competing or confounding clinical study, as determined by Abbott. 2. Pregnant or nursing subjects and those who plan pregnancy during the clinical investigation follow-up period. 3. Subject is part of a vulnerable population. 4. Presence of other anatomic or comorbid conditions, or other medical, social, or psychological conditions that, in the investigator's opinion, could limit the subject's ability to participate in the clinical investigation or to comply with follow-up requirements of the clinical investigation results. 5. Subject has a current diagnosis of a coagulation disorder, bleeding diathesis, progressive peripheral vascular disease, post-herpetic neuralgia or uncontrolled diabetes mellitus. 6. Subject has, or is scheduled to receive, implantation of another neuromodulation system (e.g. DRG or SCS system or intrathecal pump) to address their chronic pain. 7. Subject has already participated in a SCS trial period before enrolling in the study. 8. Subject engages in a profession or other activity that could be damaging to the wearable sensors, as determined by the investigator. 9. Subject has a skin condition that could be exacerbated by use of the adhesive Anne™ sensor or the other wearables (e.g. skin allergy to adhesives, metals, plastics, hydrogels), as determined by the investigator. 10. Subject has a physical condition that makes it difficult to wear the wearable sensors, as determined by the investigator. 11. Subject has tremors (e.g. Parkinson's disease or Familial tremors). 12. Subject has sleep/wake schedule that would present a challenge in completing all clinical site visits or in use of the wearable devices and engagement in the surveys via the mobile device. 13. Subject is bedridden. 14. Subject has evidence of an active disruptive psychological or psychiatric disorder or social condition as determined by the investigator. 15. Subject has a current diagnosis of a progressive neurological disease as determined by the Investigator. 16. Subject is immunocompromised. 17. Subject has history of cancer requiring active treatment in the last 12 months. 18. Subject has a documented history of substance abuse (narcotics, alcohol, etc.) or substance dependency in the 6 months prior to baseline data collection. 19. Subject has life expectancy of less than 6 months. 20. Subject is involved in an injury claim under current litigation.

Study Design


Related Conditions & MeSH terms


Intervention

Device:
Abbott SCS Systems
Patients will be implanted with Abbott spinal cord stimulation (SCS) systems (both trial and permanently-implanted systems) and provided with wearable sensors, and software applications presented on a mobile device.

Locations

Country Name City State
United States iSpine Clinics Burnsville Minnesota
United States Coastal Pain & Spinal Diagnostics Carlsbad California
United States Goodman Campbell Brain & Spine Carmel Indiana
United States St. Louis Pain Consultants Chesterfield Missouri
United States The Orthopedic Institute Gainesville Florida
United States Expert Pain Houston Texas
United States Pacific Research Institute Santa Rosa California

Sponsors (1)

Lead Sponsor Collaborator
Abbott Medical Devices

Country where clinical trial is conducted

United States, 

Outcome

Type Measure Description Time frame Safety issue
Primary Correlation between app-based pain scores and physiological data from wearable biosensors Ability to use a machine learning algorithm to predict daily pain Numeric Rating Scale (NRS) or weekly average pain NRS by monitoring physiological data from the Apple Watch, Oura ring, and Sibel Anne wearable sensors:
Pain NRS scores will be collected multiple days per week throughout the study duration via a mobile application. The Apple Watch, Oura ring, and Sibel Anne wearable biosensors will also be used by participants multiple days per week. The primary endpoint is the ability to successfully predict either daily pain NRS scores or classes of NRS pain scores (e.g., mild, moderate, or severe) or weekly average pain NRS scores or classes of NRS scores with a machine learning algorithm that processes historic information from the bio-wearables. Success is defined as a 60% or higher accuracy in classifying pain via a multi-fold cross-validation routine.
6 months
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