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Record W4200573515 · doi:10.1111/ijd.15999

Review of the alternative therapies for onychomycosis and superficial fungal infections: posaconazole, fosravuconazole, voriconazole, oteseconazole

2021· review· en· W4200573515 on OpenAlexaff
Aditya K. Gupta, Mesbah Talukder, M. Venkataraman

Bibliographic record

VenueInternational Journal of Dermatology · 2021
Typereview
Languageen
FieldMedicine
TopicNail Diseases and Treatments
Canadian institutionsMediprobe Research (Canada)University of Toronto
Fundersnot available
KeywordsPosaconazoleTerbinafineMedicineVoriconazoleItraconazoleDermatologyDosingDermatophytePharmacologyAntifungal

Abstract

fetched live from OpenAlex

Terbinafine and itraconazole are the most commonly used oral antifungals to treat onychomycosis and superficial dermatomycoses. Recently, poor response to oral terbinafine has been reported. We have summarized the most appropriate dosing regimens of posaconazole, fosravuconazole, voriconazole, and oteseconazole (VT-1161) to treat onychomycosis and superficial fungal infections. A structured search on PubMed and Google Scholar was conducted. Additionally, the bibliographies of selected articles were searched to identify relevant records. The number of records identified from the searches was 463, with 50 articles meeting the inclusion criteria for review. None of the new azoles are US FDA approved for onychomycosis treatment; however, an increasing number of studies have evaluated these agents. The efficacies (complete cure and mycologic cure) of the antifungal agents for dermatophyte great toenail onychomycosis treatment are terbinafine 250 mg/day × 12 weeks (Phase III trial) (38%, 70%), itraconazole 200 mg/day × 12 weeks (Phase III trial) (14%, 54%), posaconazole 200 mg/day × 24 weeks (Phase IIB) (54.1%, 70.3%), fosravuconazole 100 mg/day ravuconazole equivalent × 12 weeks (Phase III) (59.4%, 82.0%), and oteseconazole 300 mg/day loading dose × 2 weeks (Phase II), followed by 300 mg/week × 10 weeks (maintenance dose) (45%, 70%). Guidelines for monitoring are also presented.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.919
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
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 head0.037
GPT teacher head0.384
Teacher spread0.348 · 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 designOther design
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

Citations30
Published2021
Admission routes1
Has abstractyes

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