بررسی مقایسهای واکنش کودکان 12-9 ساله نسبت به تزریق انفیلتراسیون کامی با استفاده از Mucoadhesive patch
Bibliographic record
Abstract
Introduction: Decreasing injection pain will make the patient more comfortable during dental procedures, giving a positive feeling towards dentistry. The most recently developed product for topical anesthesia is Denti Patch. The aim of this study was to evaluate the effectiveness of Denti Patch as a topical anesthetic agent before palatal infiltration injection. Materials and Methods: For this randomized double-blind clinical trial, fifty-four 9-12 year-old subjects, (23 boys and 31 girls) were selected. Before the study, Visual Analogue Scale (VAS) was explained to the participants. The injection area was dried by air spray for 5 seconds; then both patches, the placebo and lidocaine, were placed 5-10 mm from the free gingival margin of the palate on the injection site for 12 minutes. A total of 0.2 mL of 2% lidocaine was injected. After 1-2 minutes the second injection was made on the contra-lateral side. Data was analyzed by paired t-test and Willcoxon test comparing VAS and CPS scales (α = 0.05). Results: Means from Childrens hospital of eastern Ontario Pain Scale (CPS) test in the non-anxious children for placebo and Denti Patch were 8.5 and 8.4, respectively, with no significant differences (p value = 0.88). The results from VAS test in non-anxious children for placebo and Denti Patch were 75.2 and the 70.2, respectively, demonstrating a statistically significant difference (p value = 0.006). Conclusion: According to this study, Denti Patch is effective in reducing the pain of palatal infiltration injection. The differences between CPS and VAS test results might be attributed to the cooperation of subjects, their friendly relationship with the dentist, and their abstinence from exhibiting false alarm reactions in the CPS test. Key words: Anesthesia, Denti Patch, Pain, Palate.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".