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Record W2415414355 · doi:10.2310/7750.2012.12060

Laser Therapy for Onychomycosis

2013· review· en· W2415414355 on OpenAlexaff
Aditya K. Gupta, Fiona C. Simpson

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2013
Typereview
Languageen
FieldMedicine
TopicNail Diseases and Treatments
Canadian institutionsMediprobe Research (Canada)University of Toronto
Fundersnot available
KeywordsMedicineClinical trialFood and drug administrationClinical researchLaser therapyClinical study designMEDLINERandomized controlled trialLaser treatmentDermatologySurgeryInternal medicineLaserPharmacology

Abstract

fetched live from OpenAlex

BACKGROUND: Laser therapy is a rapidly expanding new treatment modality for onychomycosis. OBJECTIVE: To review current and prospective laser systems for the treatment of onychomycosis. METHOD: We searched the PubMed database, the Food and Drug Administration 510(k) database, ClinicalTrials.gov, and Google Scholar for in vitro studies, peer-reviewed clinical trials, manufacturers' white papers, and registered clinical trials of laser systems indicated for the treatment of onychomycosis. All published clinical trials were assessed on a 20-point methodological quality scale. RESULTS: We identified three basic science articles, five peer-reviewed articles, three white papers, and four pending clinical trials, as well as numerous gray literature documents. The overall methodological score for the clinical trials was 9.1 ± 1.1, with peer-reviewed studies showing a higher score (9.8 ± 1.5) than white papers (7.5 ± 0.7). We also identified 11 commercial laser device systems of varying global availability. CONCLUSION: Laser therapy has been tested and approved as a cosmetic treatment only for onychomycosis. It cannot be recommended as a therapeutic intervention to eradicate fungal infection at this time as more rigorous randomized, controlled trials are required to determine if laser therapy is efficacious on par with oral and topical interventions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.896
Threshold uncertainty score0.791

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.107
GPT teacher head0.375
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations25
Published2013
Admission routes1
Has abstractyes

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