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Record W2810048344 · doi:10.1111/pde.13561

Onychomycosis in children: Safety and efficacy of antifungal agents

2018· review· en· W2810048344 on OpenAlexaff
Aditya K. Gupta, Rachel Mays, Sarah G. Versteeg, Neil H. Shear, Sheila Fallon Friedlander

Bibliographic record

VenuePediatric Dermatology · 2018
Typereview
Languageen
FieldMedicine
TopicNail Diseases and Treatments
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreMediprobe Research (Canada)University of Toronto
Fundersnot available
KeywordsMedicineAdverse effectDosingAntifungalCochrane LibraryRandomized controlled trialIncidence (geometry)Intensive care medicineClinical trialPediatricsDermatologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

Onychomycosis is an uncommon condition in childhood, but prevalence in children is increasing worldwide.The objective was to review the efficacy and safety of systemic and topical antifungal agents to treat onychomycosis in children. Databases (Pubmed, OVID, Scopus, clinicaltrials.gov, Cochrane Library) were searched. Seven studies were selected for inclusion. Only one was a randomized controlled trial. In total, 208 children were administered antifungal agents for the treatment of onychomycosis. Four reports of mild adverse events were documented (1.9% of treated children), one of which discontinued treatment (0.5%). Limitations of this review are the lack of randomized controlled trials available in pediatric onychomycosis. These findings suggest that antifungal therapies used to treat onychomycosis in children are associated with a low incidence of adverse events. Current dosing regimens for antifungal drugs are effective and appear safe to use in children, notwithstanding that the Food and Drug Administration has not approved any of these agents for the treatment of onychomycosis in children. To our knowledge, this review is the most up-to-date, comprehensive summary of pediatric onychomycosis treatment.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.023
GPT teacher head0.332
Teacher spread0.309 · 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 source (direct Gemma or distilled Codex), 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

Citations36
Published2018
Admission routes1
Has abstractyes

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