Emergency department procedural sedation for primary electrical cardioversion — a comparison with procedural sedations for other reasons
Bibliographic record
Abstract
BACKGROUND: Atrial fibrillation (AF) is the most common arrhythmia treated in the emergency department (ED), with primary electrical cardioversion (PEC) the preferred method of rhythm control. Anecdotally, patients undergoing ED procedural sedation (EDPS) for PEC differ from those requiring EDPS for other procedures: they are at higher risk of adverse events, and require fewer drugs and lower doses. We attempt to verify this using an EDPS registry at a Canadian, tertiary care teaching hospital. METHODS: This is a retrospective review of patients that underwent EDPS for the period of June 2006 to September 2014. We compared demographics, medication use and intra-procedural adverse events between those receiving EDPS for PEC for AF compared to that for other indications. We report the asssociation between AEs and predictors using logistic regression. RESULTS: A total of 4 867 patients were included, 714 for PEC for AF and 4 153 for other indications. PEC patients were more likely male (58.5% vs. 47.1%), older (59.5 years vs. 48.1 years), and less likely to be ASA I (46.6% vs. 69.0%). PEC patients received smaller doses of propofol and less likely to receive adjuvant analgesic therapy (11.5% vs. 78.2%). PEC patients were more likely to experience hypotension (27.6% vs. 16.5%) but respiratory AEs (apnea, hypoxia and airway intervention) were not different. CONCLUSION: EDPS for PEC differs from that conducted for other purposes: patients tend to be less healthy, receive smaller doses of medication and more likely to suffer hypotension without an increase in respiratory AEs. These factors should be considered when performing EDPS.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".