ANALGESIC EFFECT OF INTRAVENOUS ASCORBIC ACID VERSUS ACELCOFENAC POST-TRANSALVEOLAR EXTRACTION: A CASE–CONTROL STUDY
Bibliographic record
Abstract
One of the most important aspects of postsurgical care is finding an efficient way for the management of pain. Third molar extractions/surgical impaction is one of the most frequent surgical procedures in dental hospitals, and it is most often associated with postoperative complications like severe pain, oedema and reduced mouth opening. This study was aimed to evaluate the efficacy of 2 g intravenous (IV) vitamin C compared to 100 mg aceclofenac on postsurgical pain, swelling and trismus after the surgical removal of third molars. A total of 101 patients were recruited for the study, and theywere divided into two treatment groups; group A (n = 51) received 2 g IV vitamin C and group B (n = 50) received 100 mg aceclofenac. Pain intensity, facial swelling and mouth opening were assessed till day 3 post-surgically. Statistical analysis of pain intensity revealed that IV vitamin C performed slightly better but not significantly different (p>0.05) from aceclofenac group at the end of day 3. No significant difference for facial swelling and mouth opening between the two treatment protocols was seen (p>0.05). Our results concluded that both treatment groups were overall similar in analgesic efficacy, postoperative oedema and reduction in mouth opening. It was also determined that the method devised administering 2 g IV vitamin C intravenously was well suited to the treatment of postoperative pain, swelling and trismus following the surgical extraction of impacted third molars.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".