Clinical Guidelines and Policies: Can they Improve Emergency Department Pain Management?
Bibliographic record
Abstract
The prevalence of pain in patients presenting to Emergency Departments (ED) has been well documented by both Cordell and Johnston. Equally well documented has been the apparent failure to adequately control that pain. In 1990 Selbst found that patients with long bone fractures received little analgesia in the ED, and Ngai, et al., showed that the under-treatment of pain continued after discharge. In a prospective study, Ducharme and Barber found that up to one third of patients presented with severe pain and were often unrelieved at discharge. Even though specific patient subgroups appear to be at greater risk, all patients are potential victims of oligoanalgesia - the under-treatment of pain. Despite an ever increasing volume of research about pain in emergency medicine, dissemination of relevant information with widespread change in practice patterns has not been witnessed. Recent studies continue to affirm that pain management in the ED is suboptimal.
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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 | 0.124 | 0.435 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.014 | 0.017 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.018 | 0.013 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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".