Treatment and diagnostic challenges associated with the novel and rapidly emerging antifungal-resistant dermatophyte, <i>Trichophyton indotineae</i>
Bibliographic record
Abstract
ABSTRACT Trichophyton indotineae is a recently discovered dermatophyte species that causes recalcitrant dermatophytosis. It was first reported from India and has quickly spread across the globe. The exact prevalence of T. indotineae remains unknown due to limited surveillance. It has reached epidemic proportions in the Indian subcontinent. In India, this new species has largely replaced other previously common dermatophytes. Reports from Western countries suggest most cases are imported, with some reports of local transmission. A recent report from the United Kingdom indicates that T. indotineae now accounts for 38% of dermatophyte isolates tested in their national referral laboratory. T. indotineae causes widespread, inflammatory dermatophytosis affecting large areas of the body. Dermatophytosis caused by T. indotineae is difficult to manage due to the limited availability of mycology laboratories capable of reliably identifying and performing antifungal susceptibility testing, and because of its resistance to commonly used antifungals. Culture and physiological characteristics cannot confirm identification to the species level, requiring species-level confirmation by molecular methods like internal transcribed spacer sequencing. It is important for clinicians and mycology laboratories to be aware of and consider the possibility of T. indotineae infection in patients with relevant demographic, clinical, and travel history. This would decrease delay in diagnosis, prevent inappropriate use of medications like steroids and ineffective antifungal agents, and provide opportunities to make recommendations for good hygiene practices to prevent transmission. In this mini review, we describe the emergence of T. indotineae , its diagnostic and treatment challenges, and the current state, and provide recommendations for future direction.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".