Reducing the flavour of oral lidocaine: randomized controlled trial assessing the efficacy of mint-flavoured mouthwash.
Bibliographic record
Abstract
OBJECTIVE: To test the hypothesis that using an alcohol-based, mint-flavoured oral mouthwash prior to applying oral lidocaine spray will result in an improvement in the unpleasant taste of the lidocaine. DESIGN: A double-blind, randomized, controlled trial using a crossover design. SETTING: A tertiary care hospital. METHODS: Fifteen able-bodied volunteers rinsed for 30 seconds with either a mint-flavoured, alcohol-based mouthwash (treatment) or plain water (placebo) prior to the administration of topical lidocaine spray. All subjects received both the treatment and the placebo; however, the order of exposure was randomized. OUTCOME MEASURES: Subjects completed two 100 mm visual analogue scales (VASs). The first assessed the overall satisfaction with the taste of the lidocaine. This consisted of a 100 mm VAS with 0 defined as the "most unpleasant taste" and 100 mm defined as the "most pleasant taste," whereas 50 mm was defined as neutral or no taste. The second VAS assessed subjective analgesia after lidocaine administration. RESULTS: There was a statistically significant improvement in the taste of oral lidocaine after administering the treatment intervention (p = .003). There was a reduction in subjective analgesia, which did not reach statistical significance (p = .03). Use of the oral mouthwash reduced the perception of the negative flavour of the lidocaine from 20.77 (13.2) mm to 50.2 (12.84) mm as assessed by the VAS. CONCLUSIONS: A brief rinse with a mint-flavoured, alcohol-based mouthwash prior to administration of topical lidocaine resulted in a significant improvement in the perceived flavour of topical lidocaine with a minimal reduction in subjective analgesia.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".