Ketamine‐Propofol Versus Propofol Alone for Procedural Sedation in the Emergency Department: A Systematic Review and Meta‐analysis
Bibliographic record
Abstract
OBJECTIVES: Propofol is an agent commonly used for procedural sedation and analgesia (PSA) in the emergency department (ED), but it can cause respiratory depression and hypotension. The combination of ketamine-propofol (K-P) is an alternative that theoretically provides a reduction in adverse events compared to propofol. The primary objective of this review was to determine if K-P has a lower frequency of adverse respiratory events in patients undergoing PSA in the ED than propofol alone. Secondary objectives were to compare the proportion of overall adverse events, sedation time, procedure time, and recovery time between K-P and propofol. METHODS: Electronic searches of Medline, EMBASE, Cochrane Central Register of Controlled Trials, and CINAHL were conducted and reference lists were hand-searched. Randomized controlled trials (RCTs) published in English comparing the use of K-P to propofol alone for PSA in the ED were included. RESULTS: Six RCTs were included with a combined total of 932 patients (K-P = 520, propofol = 412). Five RCTs reported the proportion of adverse respiratory events; the pooled estimate revealed fewer adverse respiratory events with K-P compared to propofol (29.0% vs. 35.4%; risk ratio [RR] = 0.82; 95% confidence interval [CI] = 0.68 to 0.99). There was no significant difference with respect to the proportion of overall adverse events (38.8% vs. 42.5%; RR = 0.88; 95% CI = 0.75 to 1.04). Procedure time was similar when the groups were compared. CONCLUSIONS: The premise of combining ketamine with propofol is based on the many synergies that theoretically exist between these two agents. In this study, K-P had a lower frequency of adverse respiratory events in patients undergoing PSA in the ED compared to propofol alone.
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.031 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".