Prevention of pain from propofol injection
Bibliographic record
Abstract
Adequately studied, but inadequately managed P Marazzi/SPL Propofol is a sedative-hypnotic drug used to provide sedation or anaesthesia in operating rooms, critical care units, and emergency departments. Its popularity is not surprising. It has a rapid onset, is easily titrated, allows a smooth emergence from anaesthesia,1 and has other benefits such as preventing nausea or vomiting⇑.2 Propofol has serious side effects including hypotension and respiratory depression.1 However, these risks are well understood and readily mitigated when it is administered by experienced clinicians in appropriate environments. Pain after intravenous injection is one of the most common adverse effects but is much less well understood and poorly managed. In the linked systematic review and meta-analysis (doi:10.1136/bmj.d1110), Jalota and colleagues compared the effects of different interventions for the prevention of pain after propofol injection.3 Pain occurs in 70% of untreated patients,4 and it has been ranked by expert anaesthesiologists as the third most common avoidable adverse event related to anaesthesia.5 A previous systematic review found that a modified Bier’s block was the most effective intervention for preventing …
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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 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".