Efinaconazole 10% solution: a comprehensive review of its use in the treatment of onychomycosis
Bibliographic record
Abstract
INTRODUCTION: Onychomycosis is an infection of the nail bed and the nail plate. While oral antifungals are first-line for moderate-to-severe onychomycosis, topical efinaconazole 10% solution (JUBLIA®; Clenafin®) is effective and safe for mild-to-moderate severity onychomycosis. It is FDA-approved for patients aged 6 years and above. AREAS COVERED: This literature review includes pharmacokinetics, microbiology, efficacy, safety, and post-marketing surveillance. It demonstrates consistent safety and efficacy across diverse patient demographics and comorbidities, including pediatric, diabetic and the elderly populations, without systemic side effects or drug interactions. EXPERT OPINION: Efinaconazole 10% solution is an important addition to the armamentarium of therapies available to treat onychomycosis. Certain subgroups respond particularly well: females versus males, children versus adults, early onset onychomycosis (<1-year disease), those with mild onychomycosis (≤25% nail involvement), absence of tinea pedis, and thin nail plates at baseline (<1 mm thickness). Efinaconazole 10% solution is effective in diabetics and has demonstrated efficacy against dermatophytomas. Efinaconazole may be a consideration when terbinafine resistance is a concern, due to its different target of action.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".