Canadian Paramedic Experience with Intramuscular Ketamine for Extreme Agitation: A Quality Improvement Initiative
Bibliographic record
Abstract
Background There are no published reports in Canada examining paramedic use of ketamine for highly agitated patients or excited delirium syndrome. We employed a Plan, Do, Study, Act (PDSA) quality improvement approach to evaluate the safety and effectiveness of advanced care paramedic administered intramuscular (IM) ketamine for patients with extreme agitation in the out-of-hospital setting. Methods Data were prospectively collected from July 2018 to January 2019 when advanced care paramedics with specific training administered IM ketamine as an alternative to midazolam. Paramedics used a clinical audit form to document the ketamine dose, patient response on the Richmond Agitation Sedation Scale (RASS) at time intervals, adverse effects, and any airway management interventions they performed. Results Thirty-three patients received either 4 mg/kg or 5 mg/kg of ketamine. Combining data for both doses, the median change in RASS score at 5 minutes post-ketamine was 3 (range 0 to 8) and statistically significant for each dose. There were seven cases (21%) with reported adverse effects including SpO 2 <90% (3/7), hypersalivation (3/7), trismus or teeth grinding (2/7), muscular rigidity (1/7) and laryngospasm (1/7). Statistical analysis confirmed that the incidence of adverse events was not dose dependent. Basic airway management was performed in one-third of all cases. Conclusion We piloted the implementation of ketamine for sedation in our paramedic system by employing a PDSA cycle. Ketamine 5 mg/kg IM provided effective control of acutely agitated patients with adequate sedation at 5 minutes post-delivery. Any adverse events that occurred as a result of IM ketamine were readily managed with basic airway management interventions.
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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 | 0.016 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".