Lidocaine versus Mepivacaine in Sedated Pediatric Dental Patients: Randomized, Prospective Clinical Study
Bibliographic record
Abstract
UNLABELLED: Dental anxiety is usually seen in the pediatric patients. specially in the case of minor oral surgical procedures and exodontia, cooperation of the patients and their families with the dentist will lead to superior treatment outcomes. Pain control is important in dentistry. The aim of this randomized prospective clinical study is to compare the local anaesthetic and haemodynamic effects of 2% lidocaine (Group 1) and 3% mepivacaine (Group 2) in sedated pediatric patients undergoing primary tooth extraction. STUDY DESIGN: 60 pediatric patients undergoing sedation for elective primary tooth extraction was prospectively included in the study in a randomized fashion. Inclusion and exclusion criteria were assigned. Patients were given premedication via oral route. Local anesthesia was achieved before extraction(s). RESULTS: There were no significant differences between the groups in patient demographics, number of teeth extracted, duration of the operation and time from the end of the procedure to discharge (p ≥ 0.05). FLACC pain scale scores were not statistically significant between the groups, except at 20 minutes post-operatively when the score is significantly lower in Group 2 (p=0.029). CONCLUSION: Prevention of pain during dental procedures can nurture the relationship of the patient and dentist. Tooth extraction under sedation in pediatric patients could be safe with both local anesthetics.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".