Combatting antifungal resistance: Paradigm shift in the diagnosis and management of onychomycosis and dermatomycosis
Bibliographic record
Abstract
Antifungal resistance has become prevalent worldwide. Understanding the factors involved in spread of resistance allows the formulation of strategies to slow resistance development and likewise identify solutions for the treatment of highly recalcitrant fungal infections. To investigate the recent explosion of resistant strains, a literature review was performed focusing on four main areas: mechanisms of resistance to antifungal agents, diagnosis of superficial fungal infections, management, and stewardship. The use of traditional diagnostic tools such as culture, KOH analysis and minimum inhibitory concentration values on treatment were investigated and compared to the newer techniques such as molecular methods including whole genome sequencing, and polymerase chain reaction. The management of terbinafine-resistant strains is discussed. We have emphasized the need for antifungal stewardship including increasing surveillance for resistant infection.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| 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".