Bacteriostatic Saline Containing Benzyl Alcohol Decreases the Pain Associated with the Injection of Propofol
Bibliographic record
Abstract
In Brief Bacteriostatic saline is a physiological saline solution containing the bacteriostatic agent benzyl alcohol as a 0.9% solution. It is used mostly for diluting and dissolving drugs for IV injection and as a flush for intravascular catheters. It also has local anesthetic properties. We studied its efficacy in decreasing the pain associated with IV administration of propofol and compared it with mixing lidocaine with propofol. One-hundred-twenty patients were randomly allocated into three groups. All patients received propofol 50 mg. The benzyl alcohol group received bacteriostatic saline as a preinjection, and the lidocaine group received propofol containing lidocaine. The placebo group did not receive bacteriostatic saline or lidocaine. Fifteen of 39 patients (38%) in the benzyl alcohol group complained of pain on injection compared to 33 of 39 (84%) in the placebo group and 22 of 42 (52%) in the lidocaine group. Differences were significant between the benzyl alcohol and placebo groups (P < 0.01) and the lidocaine and placebo groups (P < 0.01). Preinjection with bacteriostatic saline decreases the incidence of pain associated with IV administration of propofol and is comparable to that of mixing lidocaine with propofol. IMPLICATIONS: We studied the effect of preinjection with bacteriostatic saline, an agent with known anesthetic properties, on the incidence of pain associated with the IV injection of propofol. We found that it decreases the incidence and severity of pain, and the decrease is comparable to that of mixing lidocaine with propofol.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".