The effect of Apotel and Diclofenac suppository on pain relief after cesarean section among primiparous women: A randomized double-blind clinical trial study
Bibliographic record
Abstract
Introduction: Inadequate pain control after caesarean can have adverse effects on various body systems, cause the mother not pay attention to the baby and problems in the breastfeeding process. Therefore, the present study was performed with aim to compare Apotel and diclofenac suppository on pain relief after cesarean section. Methods: This double-blind clinical trial study was performed in 2018 on 120 qualified primiparous women referred to Imam Reza and Pastor Hospitals in Mashhad. The subjects were randomly divided into two groups A and B (Apotel and diclofenac suppository). After cesarean delivery, if the mother requested for pain medication, group A received Apotel and group B diclofenac suppository. The severity of pain was assessed by McGill Pain Questionnaire before intervention, 6, 12 and 24 hours after cesarean section. Data were analyzed by SPSS software (version 16), and Mann-Whitney, t-test, Chi-square and Fisher exact tests. P<0.05 was considered statistically significant. Results: The two groups had no significant difference in the cesarean pain score before intervention (p=0.214), 6 hours (p=0.318), 12 hours (p=0.305) and 24 hours (p=0.117) after cesarean section. The mean of diclofenac suppository used in group A was 3.21±1.06 and the mean of Apotel used in group B was 1.02±1.22; the two groups were significantly different in the number of Apotel and Diclofenac used (p=0.048). Conclusion: Although there was no significant difference in the pain scores of the mothers in the Apotel and diclofenac suppository groups, the mean number of diclofenac suppository used was 3 times of Apotel used. Therefore, due to the longer effectiveness of intravenous acetaminophen and its safety compared to diclofenac, Apotel is recommended for cesarean section pain relief.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| 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) | 0.006 | 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".