A systematic review and meta-analysis on the prevalence of vulvovaginal candidiasis in Southeast Asian countries
Bibliographic record
Abstract
Vulvovaginal candidiasis (VVC) is a disease caused by pathogenic Candida species. This disease typically affects women of reproductive age with high sexual activity (i.e., sex workers), poor educational attainment and economic status, and infrequent hygiene practices. VVC remains a major public health concern. VVC prevalence across Southeast Asian countries remains poorly understood. To address this concern, the current study estimated the current prevalence of VVC infections among women in Southeast Asian countries by conducting a systematic review and meta-analyses. All studies reporting the prevalence of VVC in Southeast Asia were obtained from Ovid Medline, Scopus, and CINAHL. A review of titles and abstracts was done independently by three reviewers. The quality of the studies was assessed using the Newcastle-Ottawa scale. Meta-analysis was performed in R v.4.1,1 using the ‘meta’ package (version 4.19-0). Based on the results of the current study, the pooled estimated prevalence of VVC among Southeast Asian women is 23.0% (95% CI: 18.0% to 28.0%). Across countries, Laos had the highest estimated prevalence at 33.0% (95% CI: 22.0% to 46.0%). Subgroup analysis based on pregnancy status and occupation revealed a higher estimated prevalence among non-pregnant women (32.0%, 95% CI: 25.0% to 40.0%) and non-sex workers (33.0%, 95% CI: 20.0% to 48.0%). Based on the diagnostic method, the prevalence was higher for the combinatorial approach using microscopy, a culture-based approach, and molecular techniques (51.0%) and lowest when solely based on clinical diagnosis (9.0%, 95% CI: 1.0% to 22.0%) or an exclusively culture-based approach (11%, 95% CI: 6.0% to 18.0%). Overall, further study is necessary to accurately characterize the current distribution of VVC across Southeast Asian countries. Developing more effective diagnostic and management strategies is to improve the health of affected women.
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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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.037 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".