The Effect of Vitagnus on Cyclic Breast Pain in Women of Reproductive Age
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: One of the most common complaints in women is breast pain associated with reduced women quality of life and a lot of problems and costs. This study aimed to investigate the effect of vitagnus on severity of cyclic mastalgia in women of reproductive age. METHODS: This study is a triple blind controlled clinical trial performed on 67 women with cyclic mastalgia. Women randomly entered to an intervention group (34 patients) or a placebo (n=33) groups and training and proper nutrition were done. Vitagnus daily was given for three months in the intervention group (8 ml) and eatable paraffin (1 ml) mixed with water and honey (a total of 10 ml) was given to the placebo group. The pain from two months before to three months after treatment with VAS and McGill measuring instruments were compared. FINDINGS: The mean score of McGill in Vitagnus group decreased from 16.94±3.94 before the intervention to 9.50±5.32 in fifth month and in the placebo group decreased from 15.08±3.62 before the intervention to 13.08±4.29 in fifth month (p<0.0001). Mean VAS score in Vitagnus Group decreased from 6.59±3.35 before the intervention to 3.27±2.20 in fifth month and in the placebo group from 5.94±1.32 before the intervention to 4.94±1.81 in the fifth month (p<0.0001). CONCLUSION: The results showed that Vitagnus can be used as an effective and low-cost treatment in 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".