A Pilot Study of Inhaled Low-dose Methoxyflurane to Support Cunningham Reduction of Anterior Shoulder Dislocation
Bibliographic record
Abstract
Aim: The Cunningham method allows for the reduction of anterior shoulder dislocations (ASD) without procedural sedation and analgesia (PSA) in some patients.This pilot study evaluates the feasibility of investigating whether the administration of inhaled methoxyflurane (I-MEOF) increases the success rate of Cunningham reduction of ASD. Materials and Methods:Twenty patients with uncomplicated ASD underwent reduction attempts using the Cunningham method supported by I-MEOF analgesia (Cunningham/I-MEOF).Outcomes included the success rate without the requirement for PSA, emergency department length of stay (LOS), and operator and patient satisfaction.Results: Of the patients enrolled.80% were male, median age was 38.6 years (range 18-71) and 55% were the first dislocations.35% (8/20 patients) were successfully reduced using Cunningham/I-MEOF.The remainder of patients proceeded to successful closed reduction under PSA.60% of operators reported good to excellent satisfaction with the process.Operators identified the primary cause of failed initial reduction attempts as inadequate muscle relaxation.80% of patients reported good to excellent satisfaction.Patients whose initial reduction attempt with Cunningham/I-MEOF was successful had an average LOS of 149 min, compared with 216 min for those who proceeded to reduction under PSA.Conclusion: Success with ASD reduction by the Cunningham technique was marginally increased with the use of I-MEOF, although 65% of patients still required PSA to facilitate reduction.Both providers and patients found the process generally satisfactory, suggesting that early administration of analgesia is appreciated.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".