What is the Effect of Lidocaine Compared to Lidocaine and Clove Oil on Episiotomy Site Anesthesia: Results from a Randomized Clinical Trial
Bibliographic record
Abstract
Background: Episiotomy is a commonly performed obstetric procedure that often results in perineal pain for women. Objectives: This study aimed to compare the effects of lidocaine alone and lidocaine combined with clove oil on pain at the episiotomy site. Methods: This randomized clinical trial was conducted at Baharloo Hospital in Tehran, involving 65 nulliparous women who underwent episiotomy. Perineal pain was assessed using the Visual Pain Intensity Scale (VAS) and the McGill Questionnaire. The control group received a 2% lidocaine injection, while the intervention group received a combination of 0.8% clove oil and 2% lidocaine to alleviate pain before the episiotomy. The clove oil was applied topically to the episiotomy site 10 minutes prior to the lidocaine injection. During the episiotomy repair stage, both groups received a 2% lidocaine injection. Pain intensity was measured using the aforementioned tools at 1, 6, and 12 hours after episiotomy repair. Results: There was no statistically significant difference in average pain intensity between the two groups before and 12 hours after the intervention (P > 0.05). However, at 1 and 6 hours after the intervention, the combination of clove oil and lidocaine resulted in significantly lower pain compared to the lidocaine-only group (P < 0.05). Conclusions: Considering the greater effectiveness of lidocaine combined with clove oil in reducing episiotomy site pain intensity and the absence of side effects, this method can be recommended as an adjuvant therapy to reduce pain at the episiotomy site.
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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 | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".