Perioperative Wearable Device Features are associated with Moderate-to-Severe Chronic Pain after Surgery in the "All of Us" Research Program
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View abstract on PubMed
Summary
This summary is machine-generated.Consumer wearable devices can predict chronic postoperative pain. Sleep patterns and activity levels before surgery are key indicators for developing long-term pain after surgical procedures.
Area Of Science
- Biomedical Engineering
- Digital Health
- Pain Medicine
Background
- Chronic pain affects millions, with surgery being a risk factor for developing persistent pain.
- Current methods for predicting or managing postoperative pain lack reliable biomarkers.
- Digital health technologies offer new avenues for identifying digital biomarkers.
Purpose Of The Study
- To investigate the potential of digital biomarkers from wearable devices for predicting chronic pain after surgery.
- To leverage data from the "All of Us" Research Program, linking Electronic Health Records (EHR) with Fitbit data.
Main Methods
- Utilized EHR and Fitbit data from 302 surgical patients, including preoperative and postoperative activity and sleep metrics.
- Developed predictive models for moderate-to-severe pain 3 months to 5 years post-surgery.
- Analyzed sleep features, activity levels, and demographic data for predictive accuracy.
Main Results
- Sleep features demonstrated the strongest predictive performance for chronic postoperative pain (AUC of .722).
- Lower preoperative step variability and higher preoperative REM sleep variability were associated with increased pain risk.
- Younger age also correlated with a higher risk of developing chronic pain post-surgery.
Conclusions
- Digital biomarkers derived from consumer wearables show promise in predicting chronic postoperative pain.
- Integrating wearable data with EHRs can enhance the understanding and management of postsurgical pain.
- Further research into digital biomarkers could revolutionize pain prevention and treatment strategies.
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