Effect of Time on Clinical Efficacy of Topical Anesthesia
Bibliographic record
Abstract
The objective of this study was to determine the effect of time on the clinical efficacy of topical anesthetic in reducing pain from needle insertion alone as well as injection of anesthetic. This was a randomized, double-blind, placebo-controlled, split-mouth, clinical trial which enrolled 90 subjects, equally divided into 3 groups based upon time (2, 5, or 10 minutes) of topical anesthetic (5% lidocaine) application. Each group was further subdivided into 2: needle insertion only in the palate or needle insertion with deposition of anesthetic (0.5 mL 3% mepivacaine plain). Each subject received drug on one side and placebo on the other. Subjects recorded pain on a 100-mm visual analog scale (VAS). The results showed that for needle insertion only, 5% lidocaine reduced pain as determined by a significant difference in mean VAS after 2 minutes (20.1 mm, P < .002), 5 minutes (15.7 mm, P < .022), and 10 minutes (13.7 mm, P < .04), as analyzed by paired t tests. For needle insertion plus injection of local anesthetic, a significant difference in mean VAS was noted only after 10 minutes (14.9 mm, P < .031), yet pain scores for both topical anesthetic and placebo were elevated at this time point resulting in no reduction in actual pain. Time of application did not result in a significant difference in effect for either needle insertion only or needle insertion plus injection of local anesthetic, as analyzed by 1-way analysis of variance (ANOVA). In conclusion, topical anesthetic reduces pain of needle insertion if left on palatal mucosa for 2, 5, or 10 minutes, but has no clinical pain relief for anesthetic injection.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".