Efficacy and safety of compound glycyrrhizin in the patients with vitiligo: a systematic review and meta-analysis
Bibliographic record
Abstract
Compound glycyrrhizin (CG) is widely used to treat vitiligo in China, and the efficacy and adverse events (AEs) of CG for vitiligo need further analysis. This study aimed to systematically reevaluate the efficacy and safety of CG in the patients with vitiligo. Eight literature databases were searched up to 31 December 2022, and randomized controlled trials which compared CG plus conventional treatments with conventional treatments alone were included. 17 studies with 1492 patients were included. The pooled results showed that the combination of CG and conventional treatments was superior to conventional treatments alone in the total efficacy rate (risk ratio (RR) = 1.54, 95% confidence interval (CI) = 1.40 to 1.69, P < 0.00001), cure rate (RR = 1.62, 95%CI = 1.32 to 1.99, P < 0.00001), the levels of serum IL-6, TNF-α, IL-17, and TGF-ß, and the ratio of CD4+/CD8+ T cell in blood. Moreover, few patients suffered from the mild and tolerable AEs of CG. CG plus conventional treatments is an effective treatment for vitiligo with mild and tolerable AEs. More high-quality and large-sample studies are required in the future to provide more evidence of CG for vitiligo. CRD42023401166
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.028 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".