Addressing the Opioid Epidemic: A Review of the Role of Plastic Surgery
Bibliographic record
Abstract
The opioid epidemic has been a growing public health threat in the United States and Canada for the past 30 years, with alarming and steadily increasing opioid-related mortality rates. Originating with well-intentioned efforts by physicians to relieve pain and suffering in their patients, the source of the opioid epidemic and much of its ammunition continues to be the sales of legally produced pharmaceutical opioids. Although surgeons are increasingly recognizing the important role they can play in mitigating this crisis, the recognition and evaluation of the opioid epidemic in plastic surgery has been lacking. The authors identified several aspects of plastic surgery that make judicious prescription of opioids in this field uniquely complex, including high variability of cases managed, large volume of ambulatory procedures, and frequent involvement in collaborative care with other surgical specialties. Additional research in plastic surgery is needed to both increase current knowledge of opioid prescribing practices and provide evidence for recommendations that can successfully combat the opioid epidemic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".