A retrospective chart review of the clinical efficacy of Nd:YAG 1064-nm laser for toenail onychomycosis
Bibliographic record
Abstract
Cosmetic improvement in nail appearance is a great concern to patients with onychomycosis. Although oral and topical treatments for onychomycosis can potentially eradicate the infection, unsightly nails may remain despite negative mycology. Laser-based devices have been approved for the temporary clearance of nails with onychomycosis, thus providing a means of improving the aesthetic appearance of the nails. A retrospective chart review of patients treated with a Nd:YAG 1064-nm laser and debridement for onychomycosis, and terbinafine 1% cream for associated tinea pedis, between July 2012 and February 2014 was performed to ascertain the proportion of patients who achieved clinical outcomes. A temporary improvement in the appearance of the target nail was observed in 78% of patients and the affected area of the nail plate was reduced by at least 50% from baseline in 46% of patients. It appears that patients whose great toenails are potentially infected with non-dermatophyte molds may particularly benefit from laser therapy. Higher clinical outcome rates were observed with administration of four or more treatments, but additional observations and/or studies are needed to optimize the regimen of laser therapy to improve the cosmetic appearance of infected nails.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".