Antifungal resistance in dermatophytes – review of the epidemiology, diagnostic challenges and treatment strategies for managing <i>Trichophyton indotineae</i> infections
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction There is an increasing number of reports of Trichophyton indotineae infections. This species is usually poorly responsive to terbinafine.Areas covered A literature search was conducted in May 2024. T.indotineae infections detected outside the Indian subcontinent are generally associated with international travel. Reports of local spread are mounting.As a newly identified dermatophyte species closely related to the T. mentagrophytes complex with limited genetic and phenotypic differences, there is an unmet need to develop molecular diagnosis for T. indotineae. Terbinafine has become less effective as a first-line agent attributed to mutations in the squalene epoxidase gene (Leu393Phe, Phe397Leu). Alternative therapies include itraconazole for a longer time-period or a higher dose (200 mg/day or higher). Generally, fluconazole and griseofulvin are not effective. In some cases, especially when the area of involvement is relatively small, topical non-allylamine antifungals may be an option either as monotherapy or in combination with oral therapy. In instances when the patient relapses after apparent clinical cure then itraconazole may be considered. Good antifungal stewardship should be considered at all times.Expert Opinion When both terbinafine and itraconazole are ineffective, options include off-label triazoles (voriconazole and posaconazole). We present four patients responding to these newer triazoles.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it