Nondermatophyte mould onychomycosis
Bibliographic record
Abstract
Nondermatophyte moulds (NDMs) onychomycosis is often difficult to diagnose as NDMs have been considered contaminants of nails. There are several diagnostic methods used to identify NDMs, however, repeated laboratory isolation is recommended to validate pathogenicity. With NDM and mixed infection (dermatophytes plus NDM) onychomycosis on the rise, accurate clinical diagnosis along with mycological tests is recommended. Systemic antifungal agents such as itraconazole and terbinafine (e.g. pulse regimen: 1 pulse = every day for one week, followed by no treatment for three weeks) have shown efficacy in treating onychomycosis caused by various NDMs such as Aspergillus spp., Fusarium spp., Scopulariopsis brevicaulis, and Onychocola canadensis. Studies investigating topical therapy and devices for NDM onychomycosis are limited. The emergence of antifungal resistance necessitates the incorporation of antifungal susceptibility testing into diagnosis when possible, for the management of recalcitrant infections. Case studies documented in the literature show newer azoles such as posaconazole and voriconazole as sometimes effective in treating resistant NDM onychomycosis. Treatment with broad-spectrum antifungal agents (e.g. itraconazole and efinaconazole) and other combination therapy (oral + oral and/or oral + topical) may be considerations in the management of NDM onychomycosis.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".