Adolescent Outcomes of Post-operative Opioid EXposure — APEX  

Pain, Chronic Clinical Trial

Official title: Adolescent Outcomes of Post-operative Opioid EXposure

Status Not yet recruiting

Clinical Trial Summary

The goal of this observational study is to examine the factors associated with the transition from medical exposure to opioids with "signposts" of future opioid use disorder among adolescent surgical patients. The main question aims to identify factors (moderators, mediators, and covariates) associated with risk factors for opioid use disorder (ROUD) in the 12 months following major surgery with opioid exposure among adolescents aged 12-17. Participants will be asked to complete electronic surveys pre- and post-operatively and approve the collection of peri-operative data from the Electronic Medical Record to assess correlations.

Clinical Trial Description

This project will collect data from a diverse sample of 10,000 dyads, including adolescent (aged 12-17 years, inclusive) patients undergoing major surgery with planned post-operative opioid analgesic use. and a parent (Total N=20,000) to identify ROUD that may occur within the 12 months after surgery. The resulting data repository will allow clinician scientists and physicians to develop research-informed pain management protocols for adolescent surgical patients to reduce the risk of OUD in this vulnerable population. Using a novel combination of data sources (electronic medical records (EMR), patient-reported outcomes, and parent-reported outcomes), this study investigates the twin problems of postoperative pain and ROUD in adolescent surgical patients. Using real-world evidence to evaluate longitudinal behaviors and outcomes. This project will provide insights into the associations between post-operative pain management and ROUD in adolescents. Findings could yield information about potential risks, which may inform future studies and ultimately lead to new screening tools to assess risk before opioid prescribing, updated protocols for managing pain intra-operatively and post-operatively in high-risk populations, updated patient and family education materials to reduce risks for those undergoing painful procedures, and revised recommendations for monitoring for patients being treated for pain. Furthermore, the project enables the establishment of an infrastructure among pediatric surgical centers that can be used for future projects to evaluate the best postoperative outcomes for youth. Aim 1: Machine learning models will be used to develop and validate screening algorithms to detect "early warning signs" or Risk factors for Opioid Use Disorder (ROUD). The features in these models will include the pre-, intra-, and post-operative EMR-derived data elements and the survey data. Models will fit against the primary outcome described above. Model evaluation will be done via cross-validation, where the models will be fit on a randomly selected training set of patients and evaluated on the remaining held-out subset of the patients to be used exclusively for testing the performance of the final models. Aim 2: Develop and validate a prediction model designed to predict a clinical trajectory of post-surgical opioid use and pain. The model will use clustering to identify typical patient trajectories of opioid use and will use similar prediction and validation techniques as in Aim 1. ;

Related Conditions & MeSH terms

• Chronic Pain
• Opioid Use Disorder
• Opioid-Related Disorders
• Pain, Chronic

• NCT number: NCT06350409
• Study type: Observational
• Source: Boston Children's Hospital
• Contact: Sharon Levy, MD, MPH
• Phone: 857-218-4308
• Email: sharon.levy@childrens.harvard.edu
• Status: Not yet recruiting
• Start date: August 10, 2024
• Completion date: October 10, 2026