Developing a Wearable Sensor-Based Digital Biomarker of Opioid Dependence.

ABSTRACT:

Background

Repeated opioid exposure leads to a variety of physiologic adaptations that develop at different rates and may foreshadow risk of opioid-use disorder (OUD), including dependence and withdrawal. Digital pharmacovigilance strategies that use noninvasive sensors to identify physiologic adaptations to opioid use represent a novel strategy to facilitate safer opioid prescribing. This study aims to identify wearable sensor-derived features associated with opioid dependence by comparing opioid-naïve individuals to chronic opioid users with acute pain and developing a machine-learning model to distinguish between the 2 groups.

Methods

Using a longitudinal observational study design, continuous physiologic data were collected on participants with acute pain receiving opioi

SUBMITTER: Carreiro S 

PROVIDER: S-EPMC12000379 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature