A Comparison of Amethocaine and Liposomal Lidocaine Cream as a Pain Reliever Before Venipuncture in Children
Bibliographic record
Abstract
OBJECTIVE: Although the use of anesthetic creams before intravenous (IV) insertion has been shown to be both safe and effective in decreasing pain during IV cannulation, the use of any single agent based on efficacy is not yet considered the standard of care in children. We sought to compare a commonly used preparation, 4% liposomal lidocaine (Maxilene), with 4% amethocaine (Ametop), a newer agent with reportedly good efficacy and an intrinsic vasodilatory effect. METHODS: A total of 60 children aged 5 to 12 years were randomized to receive topically either 4% amethocaine or 4% liposomal lidocaine before IV cannulation. The primary outcome variable was the child's rating of pain using the Faces Pain Scale - Revised. Secondary outcomes included success rate on first IV cannulation attempt, cannulation difficulty ratings by the nurses, and adverse skin reactions. RESULTS: We found no statistically significant differences in self-reported scores in the Faces Pain Scale-Revised with the use of 4% amethocaine versus 4% lidocaine before IV cannulation. There was a trend toward fewer IV cannulation attempts in the 4% amethocaine group. Adverse skin reactions were uncommon, and there were no statistically significant differences between groups. DISCUSSION: This study demonstrates that there is no difference between 4% amethocaine and 4% liposomal lidocaine in reducing pain associated with IV cannulation in children. Amethocaine confers no advantage in improving IV cannulation success rate over lidocaine. Both agents are associated with few local adverse skin reactions.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".