Detection of <i>Candida</i> species by PCR in self‐collected vaginal swabs of women after taking antibiotics
Bibliographic record
Abstract
Women undergoing antibiotic treatment can develop vulvovaginal candidiasis. This study evaluated polymerase chain reaction (PCR) for the detection of Candida species in comparison with the conventional laboratory culture methods in samples from women with and without symptoms of postantibiotic candidiasis. The self-collected vaginal swabs from 90 women, with no recent symptoms of vulvovaginal candidiasis (VVC), who were prescribed antibiotics for non-genital infection were evaluated 8 days after completion of antibiotics and/or at the time of developing symptoms of VVC. Broad-spectrum fungal PCR was performed on extracted DNA from each sample. Overall PCR detected four additional Canidida albicans, three Candida parapsilosis and one Candida tropicalis when compared with culture. All but one case additionally detected by PCR were found in patients with no VVC symptoms. PCR, although more sensitive than conventional culture methods, in this small number of cases, has not been able to detect Candida species in significantly more patients with symptoms suggestive of candidiasis. The results of this study may indicate that other agents including other yeast species may be responsible for symptoms of postantibiotic vulvovaginitis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".