Improved treatment of vulvovaginal candidiasis with fluconazole plus probiotic<i>Lactobacillus rhamnosus</i>GR-1 and<i>Lactobacillus reuteri</i>RC-14
Bibliographic record
Abstract
AIMS: To determine the ability of probiotic lactobacilli to improve the treatment of vulvovaginal candidiasis (VVC) using a randomized, double-blind and placebo-controlled trial. METHODS AND RESULTS: Fifty-five women diagnosed with VVC by vaginal discharge positive for Candida spp. (according to culture method) associated with at least one of the symptoms (itching and burning vaginal feeling, dyspareunia and dysuria), were treated with single dose of fluconazole (150 mg) supplemented every morning for the following 4 weeks with two placebo or two probiotic capsules (containing Lactobacillus rhamnosus GR-1 and Lactobacillus reuteri RC-14). At 4 weeks, the probiotic treated group showed significantly less vaginal discharge associated with any of the above mentioned symptoms (10.3%vs 34.6%; P = 0.03) and lower presence of yeast detected by culture (10.3%vs 38.5%; P = 0.014). CONCLUSION: This study has shown that probiotic lactobacilli can increase the effectiveness of an anti-fungal pharmaceutical agent in curing disease. SIGNIFICANCE AND IMPACT OF THE STUDY: This novel finding of probiotic lactobacilli augmenting the cure rate of yeast vaginitis, not only offers an alternative approach to a highly prevalent condition that adversely affects the quality of life of women around the world, but also raises the question of how this combination works.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".