Treating Onychomycosis with Efinaconazole: Considerations for Diverse Patient Groups
Bibliographic record
Abstract
Onychomycosis is a common nail disease that manifests with varying severity and frequency in specific patient populations, warranting a personalized treatment approach. Novel topical antifungals, such as efinaconazole 10% approved for use in North America and Japan, offer a safe treatment option for many of these patients, though real-world use requires special considerations. In this scoping review, a literature search was conducted in October 2025 using PubMed, Embase (Ovid), the Cochrane Central Register of Controlled Trials (CENTRAL), and Web of Science (Core Collection). In children and adolescents (≥6 years), efinaconazole 10% has shown higher efficacy rates than in adults, possibly attributed to less nail trauma, thinner nail plates, and faster nail growth. In the elderly, a mycological response can precede visual nail improvements, which may require extending treatment beyond the standard 48-week regimen, along with intermittent maintenance therapies. Although antifungal resistance is a concern, dermatophytes-including terbinafine-resistant strains-have generally shown high susceptibility to efinaconazole. In diabetic individuals, onychomycosis should be treated promptly to prevent secondary complications. Efinaconazole 10% showed similar efficacy in this population, regardless of glycemic control. In historically underserved populations, efinaconazole 10% showed no significant difference in efficacy for Latino/Hispanic patients, though further research is needed. Overall, efinaconazole 10% solution was well-tolerated across patient groups, with application-site reactions occurring without systemic sequalae. Healthcare providers are advised to check for concomitant tinea pedis, which increases the risk of relapse or re-infection, and advise patients on nail polish use, which may degrade after topical antifungal application. A shared decision-making framework can help improve treatment compliance and patient satisfaction.
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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 | 0.014 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".