Comparison the Effect of Mefenamic Acid and Matricaria Chamomilla on Primary Dysmenorrhea in Kashan Medical University Students
Bibliographic record
Abstract
Background & Objectives: Regarding to high incidence of dysmenorrhea and influence on daily activities and fewer side effects of herbal medicines than chemical drugs, the aim of this study was to compare the effect of mefenamic acid and matricaria chamomilla (MC) on primary dysmenorrhea. Methods: This triple-blind randomized clinical trial study was done on 90 female students residents in dormitories of Kashan University of Medical Sciences in 2012. The subjects were categorized into two groups randomly. Mefenamic acid capsules (250 mg, every 8 hours) were given to the first group from 48 hours before menstruation until 24 hours after it. The second group received MC capsules made in Barij Essence Factory of Kashan (250 mg, every 8 hours). Severity of dysmenorrhea was measured by McGill ruler. Finally, the data were analyzed by SPSS. The chi-squire, fisher and paired t-test were used. The p-value of less than 0.05 was considered as statistically significant difference. Results: The result of this study indicated that both chamomilla and mefenamic acid can reduce the severity of pain and hemorrhage (p<0.05) but there was no significant difference between two groups (p>0.05). Conclusion: This study showed that matricaria chamomilla is effective in decreasing the severity of primary dysmenorrhea and reducing hemorrhage as well as mefenamic acid.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".