Which treatments for fungal nail infections work better, those taken by mouth work or those applied to the nail?
Bibliographic record
Abstract
Onychomycosis is a fungal infection of the nail and is more likely to occur in toenails. In Europe and North America, approximately 4.3% of people have this infection. The infection accounts for approximately 50% of all nail‐related disease. To treat toenail infection, oral (taken by mouth) and topical (applied to the skin) medications are available. Topical treatments have lower success rates than oral treatments, but oral treatments may produce side effects or affect how other medications work. Published studies of clinical trials do not directly compare oral and topical treatments. This study, from Canadian researchers, aimed to use a statistical analysis called network meta‐analysis in order to estimate how oral and topical treatments compare to each other in terms of mycological cure (eradicating the fungal infection) and in adverse events (side effects). The authors found 26 published studies to include in their analysis. The authors wanted to include device‐based treatments (e.g. laser) and combination treatments, but there were not enough randomised controlled trials on these treatments. The results showed that daily use of the oral treatments of terbinafine 250 mg and itraconazole 200 mg were significantly more likely to eradicate the fungal infection compared to topical treatments. Other oral treatments and regimens were similar to topical treatments in producing mycological cure and every treatment was better than controls. In terms of side effects, there was no difference between oral and topical medications, and this may be because reports of side effects with oral medications arose after these clinical studies were completed. This current review suggests that patients have safe oral and topical medication options for toenail fungal infection. This summary relates to the study: Monotherapy for toenail onychomycosis: a systematic review and network meta‐analysis
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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 | 0.020 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.011 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".