Review of Treatment for Onychomycosis: Consideration for Special Populations
Bibliographic record
Abstract
This article provides a brief discussion of onychomycosis treatment in special populations such as children, the elderly, and patients with diabetes, human immunodeficiency virus (HIV), or Down syndrome. These subjects are generally not included in clinical trials, and few data on antifungal therapy are available in the literature. Issues with onychomycosis infection and treatment affecting each group are discussed, and where treatment reports exist, efficacy and safety data are presented. The discussion is restricted to agents approved for use in onychomycosis in Canada: oral terbinafine, oral itraconazole, and ciclopirox 8% nail lacquer. Although sparse, the literature demonstrates that onychomycosis therapies can be used safely and effectively in these special populations, although it is likely that the appropriateness of such treatment would have to be assessed on a case-by-case basis. Typically, oral medications are used reluctantly in these groups as the potential for adverse liver or kidney effects and medication interactions may be significant. Ciclopirox nail lacquer has recently become available for use and may offer an alternative to oral therapy in the future for mild to moderate cases of onychomycosis; however, the efficacy in these patients has not typically been reported. It remains to be seen what impact this medication will have for special populations. More knowledge of treatment in special populations must be accumulated in the literature before more formal treatment guidelines may be formulated.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".