Probiotics used as adjuvants to conventional antifungal drugs vs conventional antifungal drugs: Clinical cure
Probiotics used as adjuvants to conventional antifungal drugs may leads to higher clinical cure rate (short‐term) compared with conventional antifungal drugs (low certainty).
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Probiotics used as adjuvants to conventional antifungal drugs vs conventional antifungal drugs Clinical cure rate (short‐term) · non‐pregnant women with vulvovaginal candidiasis Probiotics used as adjuvants to conventional antifungal drugs may leads to higher clinical cure rate (short‐term) compared with conventional antifungal drugs (low certainty). Probiotics for vulvovaginal candidiasis in non‐pregnant women (2017) · Cochrane Headline outcomes only | RR 1.14 [1.05, 1.24] | 5 studies · 695 participants | Low |
Probiotics used as adjuvants to conventional antifungal drugs vs conventional antifungal drugs Clinical cure rate (long‐term) · non‐pregnant women with vulvovaginal candidiasis It is very uncertain whether probiotics used as adjuvants to conventional antifungal drugs changes clinical cure rate (long‐term) compared with conventional antifungal drugs (very low certainty). Probiotics for vulvovaginal candidiasis in non‐pregnant women (2017) · Cochrane Headline outcomes only | RR 1.07 [0.86, 1.33] | 1 study · 172 participants | Very low |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Probiotics for vulvovaginal candidiasis in non‐pregnant women 2017 · Cochrane Headline outcomes only | Not reported | list not extracted yet | Not assessed |
Studies behind the findings
None of these reviews ties its included studies to this outcome in the data here. Cochrane reviews and reviews with headline outcomes only do not list their studies yet.
How reviews are matched to this question
Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.