Utility of polymerase chain reaction for assessment of onychomycosis during topical therapy
Bibliographic record
Abstract
BACKGROUND: Increased detection of fungi including non-dermatophyte molds (NDMs) using polymerase chain reaction (PCR) methods is well-established. However, the use of PCR to evaluate ongoing onychomycosis treatment outcome has not been investigated. METHODS: Nail samples from 28 patients receiving topical efinaconazole were evaluated by both KOH/culture and PCR methods across the study period. Detection of microorganisms by PCR was compared to the culture at baseline and end of study at month 24 (M24). Fungal detection by both methods was evaluated with respect to clinical cure observed as 100% visual clearance of the target toenail. RESULTS: By culture, all 28 subjects were dermatophyte-positive at pre-treatment; only 4/28 also exhibited an NDM microorganism. According to PCR, 24/28 subjects were dermatophyte-positive pre-treatment, with 25/28 also exhibiting NDMs. At M24, 18/28 (64.3%) participants had negative KOH/culture results, in contrast to 4/28 (14.3%) negative PCR results. PCR showed higher rates of NDM detection than the culture at baseline as well as M24. Calculations to compare the diagnostic utility of KOH/culture versus PCR found that positive tests with both methods reliably indicate the presence of onychomycosis, but negative PCR correlated better with onychomycosis cure than did KOH/culture. DISCUSSION: PCR confirmed a high presence of NDMs pre-treatment, and continued presence of NDMs to M24, with unknown significance requiring further investigation. Though both KOH/culture and PCR have diagnostic limitations, PCR showed better overall utility than culture in predicting onychomycosis topical treatment outcome and should be more strongly considered for evaluation of topical therapies.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".