ArticleBMJ open2025
Identifying bio-behavioural signatures of persistent opioid use risk in trauma injury patients: a protocol for a prospective cohort study.
Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Review of Risk Factors for Opioid Misuse and Addiction Following Traumatic Injury.Healthcare (Basel, Switzerland) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
introductionExposure to prescription opioids following traumatic injury can increase the risk of developing tolerance, persistent opioid use and opioid use disorder. The mechanisms underlying opioid tolerance or dependence are not well understood, and no biomarkers predict risk. Opioid exposure causes epigenetic modifications, including alterations in microRNA (miRNA) expression. Several miRNAs, which regulate synaptic plasticity, are hypothesised to underlie substance use disorders and influence µ-opioid receptor levels, modulating opioid tolerance. This project aims to develop a bio-behavioural signature to predict persistent opioid use and chronic pain up to 6 months post-discharge. METHODS AND ANALYSIS: The study will use a prospective cohort design, enrolling 180 adult patients at a Level I Trauma Center who are prescribed opioids at discharge. Prospective data will be collected in the hospital and at 7 days and 1, 3 and 6 months post-discharge. Biological data (genotyping and miRNA levels) and clinical measures of opioid use, pain, pain sensitivity (EEG) and psychosocial functioning will be collected at each time point. Bayesian regression methods will be used to identify baseline clinical, genetic, epigenetic and psychosocial predictors of opioid use and pain outcomes at 6 months post-discharge. Growth mixture modelling will identify distinct subgroups with varying trajectories, followed by Bayesian hierarchical modelling to predict trajectory classification based on predictor variables. ETHICS AND DISSEMINATION PLAN: Ethics approval for this study was obtained from the University of Texas Health Science Center at Houston Committee for the Protection of Human Subjects (HSC-MS-24-0314). Findings will be disseminated in peer-reviewed scientific journals and at national and international conferences.
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Registered trials
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