The effect of Nigella Sativa syrup on the relief of cyclic mastalgia: A triple-blind randomized clinical trial
Bibliographic record
Abstract
Background & Aim: Mastalgia is one of the most common complaints of women and its cyclic type constitutes two-thirds of the cases. This study aimed to determine the effect of Nigella Sativa syrup on cyclic mastalgia. Methods & Materials: This study is a triple-blind randomized clinical trial (IRCT201104304785N3). The study samples included 65 women with cyclic mastalgia referred to the Breast Cancer Research Center (BCRC), Academic Center for Education, Culture and Research (ACECR) in Tehran in 2014-2015. The samples were randomly divided into two groups: intervention group (Nigella Sativa=36) and placebo group (oral paraffin=36). The pain was measured by the VAS and McGill Short Form questionnaire two months before and three months after the intervention. Data were analyzed using statistical tests on the SPSS software version 18. Results: The results of the VAS and McGill pain score changes showed a significant difference between the two groups. Considering that the interaction between time and group was significant, the two groups were compared at each stage using independent t-test and the Bonferroni correction test. Thus, there was no significant difference between the two groups of Nigella Sativa and placebo on the basis of the McGill instrument but a significant difference was observed between the two groups on the basis of the VAS (P=0.002). Conclusion: According to the results, Nigella Sativa reduces pain more than placebo. Therefore, it can be used along with other medications for the treatment of mastalgia.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 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".