Treatment of Onychomycosis: Pros and Cons of Antifungal Agents
Bibliographic record
Abstract
BACKGROUND: Antifungal agents are beneficial in the treatment of onychomycosis in the general population, as well as in children, the elderly, and immunocompromised individuals. Special patient populations can be more difficult to treat due to such factors as drug interactions with concomitant medications, adverse events, and poor compliance. In addition, there is limited information about the use of antifungal agents in special populations, e.g., children. OBJECTIVE: The pros and cons of oral and topical antifungal agents are discussed, with focus on special patient populations. METHODS: We searched MedLine (1966 to April 2003) for clinical studies evaluating the efficacy of oral and topical antifungal agents to treat onychomycosis. The key words used in conjunction with "onychomycosis" include: "terbinafine," "itraconazole," "fluconazole," "amorolfine nail lacquer," "ciclopirox nail lacquer," "HIV," "transplant patients," "diabetes," "children," and "elderly." Studies were excluded if published in a language other than English. RESULTS: Studies have shown that antifungal agents can be of benefit in treating the elderly, children, and immunocompromised individuals (e.g., transplant patients, Down's patients, HIV patients, and diabetics) with onychomycosis. CONCLUSION: The treatment modality of onychomycosis in special patient populations should take into account the clinical presentation of the onychomycosis, the causative organism, patient and physician preference, the concomitant medications that the patient is on, and the potential for adverse events for that patient if antifungal therapy is undertaken.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".