Efficacy and safety of Lutai Danshen Baishao granules for treating female melasma: A randomized, double-blind, placebo-controlled trial
Bibliographic record
Abstract
Objective: To investigate the potential efficacy and safety of Lutai Danshen Baishao granules (LDBG) for treating female melasma associated with kidney deficiency and blood stasis patterns. Methods: A randomized, double-blind, placebo-controlled trial was conducted at the Third Central Hospital of Tianjin, China from March to December 2023. A total of 110 female patients with melasma linked to kidney deficiency and blood stasis were enrolled and treated with either LDBG or a placebo twice daily for 60 days. Efficacy was assessed through measures such as the total melasma area, reduced melasma area, reduction rate of melasma area, melasma color score, Melasma Area and Severity Index (MASI) score, and traditional Chinese medicine (TCM) symptom score scale. Safety assessments included routine blood and biochemical tests. Results: Participants in both groups were aged 52–63 years, with no significant differences. After the 2-month intervention, the total melasma area decreased in both groups; however, a greater reduction was observed in the test group [462.50 mm2 (12.81%) vs. 100.00 mm2 (3.11%), P < .001]. Moreover, LDBG treatment significantly reduced the MASI and melasma color scores in the test group (P < .05). The total TCM symptom evaluation score significantly decreased (test group: 6.00 vs. placebo group: 7.00, P = .001), with significant relief in symptoms such as improvement in dark lips, nails, and waist soreness in the test group, compared with that in the placebo group (P < .05). Within-group comparisons revealed that TCM syndrome was significantly alleviated in the test group (P < .05). Conclusion: LDBG intervention shows promising effectiveness in reducing female melasma and alleviating TCM syndromes.
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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) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".