The safety of oral antifungals for the treatment of onychomycosis
Bibliographic record
Abstract
INTRODUCTION: Oral antifungals are used for the treatment of moderate-severe onychomycosis. Terbinafine and itraconazole are approved for onychomycosis treatment in North America; additionally, fluconazole is indicated for onychomycosis in Europe. Other oral antifungals such as ketoconazole and griseofulvin are no longer used for the treatment of onychomycosis due to safety concerns and relatively lower efficacy. SEARCH STRATEGY: On 7 March 2023, we conducted a comprehensive search in PubMed and Google Scholar, while also manually examining selected article bibliographies and package inserts. AREAS COVERED: Terbinafine, itraconazole, and fluconazole have several interactions with cytochrome-p450, and either alone, or when co-administered with other drugs these interactions can facilitate a multitude of adverse events. This article identifies possible hepatic, renal, cutaneous, cardiovascular, neurological, hemopoietic, and obstetric adverse events. We have also compared the rates of hepatotoxicity, clinically apparent liver injury, and alanine transaminase elevations between oral antifungals, and recommendations for hepatic monitoring. EXPERT OPINION: We recommend laboratory testing of liver function tests prior to the administration of any oral antifungals, especially when clinically indicated. In the event of a first treatment failure, the diagnosis of onychomycosis must be confirmed, and consideration given to antifungal susceptibility testing. Antifungal stewardship will help reduce the incidence of antifungal resistance.
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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 | 0.005 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".