CO<sub>2</sub> Laser-Assisted Nail Sampling for Mycological Testing in Onychomycosis
Bibliographic record
Abstract
Introduction: Onychomycosis is the most common nail infection, predominantly caused by Trichophyton spp., and is divided into four main types. Confirmatory testing is crucial, but obtaining an adequate sample may be challenging. We suggest the use of carbon dioxide (CO2) laser for painlessly detaching the nail plate during mycological examination and ensuring a sufficient specimen. Methods: We retrospectively enrolled 25 patients with distolateral onychomycosis, treated according to the following protocol: (1) multiple passes of CO2 laser at 10 W in continuous mode along the proximal border of the affected nail plate; (2) the nail plate was gently cut; (3) the nail bed was curetted; (4) subungual debris and plate fragments were collected for KOH test and culture. Results: The mean visual analog score (VAS) for pain experienced during the procedure was 0.7 (SD: 2.1), indicating that the sampling was relatively painless for the majority of patients. There were no permanent changes observed in the nail unit of any patients during the follow-up visits as a result of using the CO2 laser. Conclusion: We firmly believe that the use of lasers offers numerous advantages, including ease of use, reduced pain perception, and the ability to target the proximal margin of fungal infections where viable hyphae are significantly represented.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".