Postoperative Yanghe decoction regimen improves outcomes for idiopathic granulomatous mastitis
Bibliographic record
Abstract
The etiology of idiopathic granulomatous mastitis (IGM), a rare inflammatory breast disease, is not understood. There is no consensus regarding the treatment of IGM. The purpose of this study was to determine the efficacy of surgery combined with traditional Chinese medicine for the treatment of IGM.We retrospectively analyzed 53 patients of IGM who were treated with surgical excision at our hospital. Group A (n = 25) included patients treated with only surgery, and Group B included patients treated with surgery combined with postoperative Yanghe decoction. The clinical data were compared between the 2 groups, including demographics, clinical characteristics, and outcomes.All patients were female with a mean age of 34.6 ± 5.9 years. There were no significant differences between the groups regarding preoperative demographics or clinical characteristics. The follow-up time was comparable between the groups (13.2 ± 10.0 vs 12.0 ± 10.2 months). Patients in Group B had shorter complete remission (CR) times than patients in Group A (76.1 ± 15.2 vs 84.0 ± 12.2 days; P < .05). The CR rate was higher in Group B than in Group A (96.4% vs 76.0%; P < .05), and the recurrence rate was lower in Group B than in Group A (0% vs 16.0%; P < .05).The postoperative Yanghe decoction regimen was associated with more rapid recovery after IGM surgery. Surgical management combined with postoperative oral Yanghe decoction treatment yielded a higher CR rate and lower recurrence rate than surgery alone. The effect of traditional Chinese medicine in IGM treatment requires further study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".