Navigating fungal infections and antifungal stewardship: drug resistance, susceptibility testing, therapeutic drug monitoring and future directions
Bibliographic record
Abstract
Antifungal stewardship refers to the rational use of antifungal agents. Historically, in some instances, the misuse or overuse of antifungal agents has predisposed patients to an elevated risk of systemic side-effects and treatment resistance, as well as increased healthcare costs. Superficial mycoses, such as onychomycosis, are sometimes treated without any diagnostic testing and is associated with a high likelihood of self-diagnosis and self-treatment, potentially leading to the emergence of resistance against commonly used antifungals like terbinafine. Practitioners need to ensure that a proper clinical diagnosis is backed up by appropriate testing. This may include the traditional light microscopy and culture; additionally, molecular techniques (such as polymerase chain reaction, terbinafine gene mutational analysis) and antifungal susceptibility testing are considerations as appropriate. The choice of antifungal agent should be guided by what is the standard of care in the location where the clinician practices as well as more broadly state and national prescription patterns. Recently, reports of treatment resistance concerning both superficial and deep fungal infections have added another layer of difficulty to clinical practice. This review aims to explore the phenomenon of antifungal drug resistance, and highlights the importance of adopting antifungal stewardship programs. We provide an overview of treatment resistance and mechanisms of resistance reported thus far in dermatophytes. Challenges of performing antifungal susceptibility testing and therapeutic drug monitoring are discussed, as well as principles, recommendations and future directions of antifungal stewardship programs.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".