Feasibility of a tapering opioids prescription program for trauma patients at high risk of chronic consumption (TOPP-trauma): protocol for a pilot randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Opioid use disorder (OUD) and deaths related to the chronic use of opioids have increased significantly over the last two decades. Chronic consumption of opioids has been documented in many patients with traumatic injuries. Preliminary research findings have shown that interventions using cognitive-behavioral strategies were a promising adjunct in decreasing the burden associated with opioid consumption. Accordingly, the Tapering Opioids Prescription Program in Trauma (TOPP-Trauma) was developed. PURPOSE: To assess the feasibility of the TOPP-Trauma intervention and its research methods; and explore the potential efficacy of TOPP-Trauma in reducing opioid consumption. METHODS: A 2-arm pilot randomized controlled trial (RCT) will be conducted in patients presenting a high risk for chronic opioid consumption. Fifty participants at high risk for chronic consumption of opioid will receive either TOPP-Trauma or an educational pamphlet. The feasibility assessment of TOPP-Trauma will be based on the ability to provide its components as initially planned. Several parameters will be evaluated to determine the feasibility of the research methods, including the adequacy of the sampling pool, the dropout rate, and the ease of data collection. The morphine equivalent dose (MED) per day between both groups will be measured at 6 and 12 weeks. Pain intensity and pain interference with activities will also be evaluated at the same time points. DISCUSSION: This study will provide evidence on the feasibility of a preventive program aimed at reducing chronic opioid use in high risk trauma patients. Information will also be gathered on the methods that should be used to test the efficacy of such programs. TRIAL REGISTRATION: International Standard Randomized Controlled Trial Number (ISRCTN): 40263056. Registered 26 May 2018.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.039 | 0.032 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.012 | 0.005 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.056 | 0.010 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".