The emergence of <i>Trichophyton indotineae</i>: Implications for clinical practice
Bibliographic record
Abstract
Emergence and increase of terbinafine-resistant dermatophytosis led to the identification of Trichophyton mentagrophytes internal transcriber space (ITS) genotype VIII in 2017, later renamed as Trichophyton indotineae and classified as a separate species in 2020. With its suspected origin in South Asia, this novel strain has emerged in Bahrain, Canada, Denmark, Finland, France, Germany, India, Iran, Japan, Russia, and Switzerland, with its spread attributed primarily to travel and migration. Diagnosis using routine mycology laboratory techniques is unable to distinguish T. indotineae from T. mentagrophytes and T. interdigitale; specific identification requires genomic sequencing to identify unique, specific markers. One speculated reason for this recent outbreak is the unrestricted use of topical steroid creams and antifungal agents. Patients with extensive tinea corporis and cruris due to T. indotineae present with inflammatory red plaques in multiple body sites. The majority of these infections prove to be resistant to conventional antifungals, including allylamines and azoles (itraconazole and fluconazole), thus emphasizing the need for antifungal susceptibility testing before treatment initiation and for reassessing in nonresponsive patients. Molecular studies have identified several point mutations in the ERG1 (terbinafine resistance) and ERG11 (azole resistance) genes, which need to be analyzed further. Use of relatively new agents, such as voriconazole and luliconazole, as well as device modalities and combination therapy, could be investigated for recalcitrant T. indotineae infections.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".